Investigating and applying free solution capillary electrophoresis with direct UV detection to bioethanol research

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1 Investigating and applying free solution capillary electrophoresis with direct UV detection to bioethanol research By James D. Oliver BSc (Gene Science) BSc (Honours) Class I Principle Supervisor: Dr Patrice Castignolles Co-supervisors: Dr Michael Phillips Julie Markham Prof. Paul Peiris Submitted for the completion of a Doctor of Philosophy degree at the University of Western Sydney July 2014

2 This thesis is dedicated to my loving and supportive family and to my love Amy.

3 Statement of Authentication The work presented in this thesis is, to the best of my knowledge and belief, original except as acknowledged in the text. I hereby declare that I have not submitted this material, either in full or in part, for a degree at this or any other institution.. James Oliver Date James Oliver CE for bioethanol research i

4 Abstract Bioethanol fermentation is an important process that is reducing the global demand on fossil fuels and remains a field of research for the foreseeable future. Carbohydrates are sourced from crops and hydrolyzed into simpler sugars then fermented into ethanol. Fermentation of sugars sourced from food crops presents a sustainability issue with a growing population. Fermentation of lignocellulosic material is more sustainable since it is sourced from non-food crops or wastes. It is comprised of a variety of both pentose and hexose sugars. The composition and ratio of these varies depending on the source of the material. Accurate analysis of the material is essential for both the monitoring of the hydrolysis and its fermentation to valuable end-products such as ethanol. Although there have been major advances in novel fermentation processes and the discovery and construction of novel microorganisms, development of methods for analysis of these complex substrates and their fermentation to ethanol has not advanced as rapidly. High Performance Liquid Chromatography (HPLC) is one of the most common techniques for the analysis of these complex substrates. The resolution of popular HPLC modes was compared and no mode was found to have complete separation of common fiber sugars. Free solution Capillary Electrophoresis / capillary zone electrophoresis (CE) is used and recognized in both research and industry as a viable technique for the separation of carbohydrates. Recent studies on the use of direct UV detection for determination of underivatized carbohydrates have shown great promise and, in this work, the technique was applied to lignocellulosic plant fiber analysis as well as monitoring its fermentation to ethanol and sugar alcohols. All resolution values with CE were higher than 0.5, in contrast to any HPLC mode investigated. The running cost of HPLC, for this application, is also much higher than CE. Determination of carbohydrates from lignocellulosic fiber by both HPLC on a cation exchange resin and by CE resulted in values % higher with CE than HPLC. The influence of the counter-ion in the BackGround Electrolyte (BGE) was found to affect the resolution and time of the separation. 130 mm K was shown to be effective for a fast separation of simple mixtures and a mixture of 65 mm Na and 65 mm Li achieved a better resolution with more complex carbohydrate mixtures than the other BGE s studied. In a quantitative study on fermentation samples, CE, HPLC and High Performance Anion Exchange Chromatography (HPAEC) closely agreed within experimental error (less than 7 % difference from the average total detected amount). James Oliver CE for bioethanol research ii

5 The most significant drawback to the CE method was the limited understanding of the mechanism behind the direct UV detection. Carbohydrates are readily observed at 270 nm with this method, although they were commonly deemed as not possessing any chromophores. An investigation of the mechanism of detection showed that a photo-oxidation reaction was responsible for the detection and not enediolate formation as previously theorized. The photooxidation reaction produces an intermediate species that absorbs at 270 nm. This resolved the controversy between two competing theories. The reaction pathway was found to be similar to a free radical pathway previously investigated by Electron Spin Resonance (ESR) by Bruce Gilbert et al., (1982) where semidiones were identified as intermediates. The reaction pathway was investigated with quantum mechanical calculations of the theoretical UV spectra of the semidiones as well as by 13 C NMR (Nuclear Magnetic Resonance) spectroscopy of the photo-oxidation end products. Some of the end-products were found to be carboxylates and not aldehydes as previously theorized. The sensitivity of the detection of carbohydrates was increased by 42 % with the use of a stable radical photo-initiator. A weakness of this method was the inability to monitor ethanol. When investigating a potential method, it was found that methanol, ethanol, isopropanol and triethylamine had a negative effect on the sensitivity of the detection hence they could be detected by interference of the photo-oxidation reaction. In the case of ethanol, it is assumed to have a hydrogen abstracted by the oxygen centered radicals produced by the photo-oxidation of a carbohydrate, thereby interfering in the pathway (Scheme A-1). Ethanol quantification was achieved though the detection of photo-oxidation interference. Scheme A-1: Summarized scheme of glucose photo-oxidation to UV-absorbing intermediates (circled red) and its interference by ethanol. James Oliver CE for bioethanol research iii

6 Ethanol was quantified in a vodka sample and a simple fermentation sample with good recovery (100 and 110% respectively). The robustness of ethanol determination was successfully tested with a sample from ethanol fermentation of lignocellulosic plant fiber. A limitation of this method, is that ethanol and carbohydrates require two subsequent injections on the same CE instrument. Future work can focus on single injection in order to improve the method for online monitoring of ethanol fermentation of lignocellulose. James Oliver CE for bioethanol research iv

7 Acknowledgements I wish to acknowledge the contribution that made this project possible. First and foremost, my principal supervisor Dr Patrice Castignolles for his continued guidance in the field of analytical chemistry, his infinite patience and dedication to our work. My supervisors Dr Michael Philips, Prof Paul Peiris and Julie Markham who helped form the basis of this project and encouraged me to pursue the field of analytical chemistry to meet our goals. My collaborator Dr Marion Gaborieau for her guidance and training on NMR, her continued support and supply of high quality coffee. My collaborator Prof Emily Hilder (UTas) who, despite her high demanding role, made time for her thoughts on the work, access to the facilities of ACROSS UTas, support for funding applications and the opportunity to give a talk at ACROSS UTas that yielded many ideas that have come out in the publications. My collaborators Dr Christopher Fellows (UNE), Dr Yohann Guillaneuf and Dr Jean-Louis Clement (Aix-Marseille) for their insight to radical chemistry. Dr Naama Karu (UTas) for her training on IC, Dr Mark Williams for his training on the HPLC in my first year and introducing me to the field of analytical chemistry and Patrice. Carol Adkins, Jenny Nelson Julie Svanberg and Adam Hale for ensuring everything I needed was available and Prof Barry McGlasson for his guidance on the plant science aspect of this work. To my fellow students Emily Groison, Fiona Loudon, Adam Sutton, Ashleigh Van Oosterum, Alison Maniego, David Fania, Tim Murphy, Elizabeth Whitty, Michelle Toutounji, Danielle Taylor, Joel Thevarajah and Kristina Eriksson-Scott, thank you for your support over my candidature. To my family for their continued support and most importantly to my partner Amy for her support, patience and faith in me. James Oliver CE for bioethanol research v

8 Preface The project started with a focus of using non-food plants, adaptable to Australian marginal lands, for bioethanol production. We first attempted to determine the carbohydrate composition of these plants however the use of the well-established High Performance Liquid Chromatography (HPLC) methods were unsuccessful. Free solution Capillary Electrophoresis (CE) with direct UV detection was a new application of a well-researched separation technique. We compared the separation of fiber sugars by common HPLC modes to that of CE. We then analyzed the carbohydrate content of acid treated fiber by CE in comparison to the most robust HPLC column. One limitation at this point was that the mechanism of the direct detection in CE was not well understood. There were, at the time, 2 different proposed pathways by different authors. We investigated the detection with a combination of novel CE experiments as well as 1 H Nuclear Magnetic Resonance (NMR) spectroscopy, and we were able to determine which of the 2 pathways was correct. We then used our new understanding of this mechanism for the detection and quantification of ethanol. We then finally brought this PhD project back to the foundation of fermentation science by developing CE as a tool for monitoring both carbohydrates and ethanol in both simple and complex fermentation broths. A quantitative comparison between CE and the most common separation techniques of HPLC and High Performance Anion Exchange Chromatography (HPAEC) was also carried out. The aim of this PhD project was to provide the field of biotechnology a robust, yet simple and cost effective means of analyzing prospective fermentation feedstocks, as well as an understanding of the separation and detection mechanisms that make it possible. This thesis by publication is formatted in United States English as to conform to the publications. References that are noted in the publications can be found at the end of the corresponding section and are in each Journal s individual style. All other references can be found in section 7. Published versions of the publications can be found in the appendix. James Oliver CE for bioethanol research vi

9 Publications Oliver, J. D.; Gaborieau, M.; Hilder, E. F.; Castignolles, P., Simple and robust determination of monosaccharides in plant fibers in complex mixtures by capillary electrophoresis and high performance liquid chromatography Journal of Chromatography A (IF 4.6, top 10 % of Analytical Chemistry) 2013, 1291, Oliver, J. D.; Rosser, A. A.; Fellows, C. M.; Guillaneuf, Y.; Clement, J.-L.; Gaborieau, M.; Castignolles, P., Understanding and improving direct UV detection of monosaccharides and disaccharides in free solution capillary electrophoresis Analytica Chimica Acta (IF 4.4, top 10 % of Analytical Chemistry) 2014, 809, Oliver, J. D.; Gaborieau, M.; Castignolles, P., "Ethanol determination using pressure mobilization and free solution capillary electrophoresis by photo-oxidation assisted ultraviolet detection." Journal of Chromatography A (IF 4.6, top 10 % of Analytical Chemistry) 2014, 1348, Invited contribution Oliver, J. D.; Sutton, A.; Karu, N.; Phillips, M.; Markham, J.; Peiris, P.; Hilder, E. F.; Castignolles, P., Simple and robust monitoring of ethanol fermentations by capillary electrophoresis Biotechnology and Applied Biochemistry (IF 1.348) Manuscript ID: BAB R1, Accepted 06/07/2014 James Oliver CE for bioethanol research vii

10 Conference and seminar presentations Conferences: 33 rd Australasian Polymer Symposium (33 APS, Oral presentation Determination of Monosaccharides from Chemically Hydrolysed Polysaccharides for the Biofuel Industry James D. Oliver, Mark Williams, Patrice Castignolles. Published as 33rd Australasian Polymer Symposium proceedings. ISBN number: th International Symposium on the Separation and Characterization of Natural and Synthetic Macromolecules (SCM-6, Oral presentation Simple and robust separation of hydrolysed pectin and hemicellulose by capillary electrophoresis and high performance liquid chromatography James D. Oliver, Marianne Gaborieau, Emily F. Hilder, Patrice Castignolles Poster presentation Fermentation of complex polysaccharide mixes to ethanol and other valued products James D. Oliver, Naama Karu, Adam Sutton, Emily F. Hilder, Michael Phillips, Julie Markham, Paul Peiris, Patrice Castignolles James Oliver CE for bioethanol research viii

11 Seminar Presentations: 2014 School of Science and Health post-graduate forum presentation Monitoring carbohydrates and ethanol in complex fermentations James D. Oliver, Adam T. Sutton, Prof. Emily F. Hilder, Dr Michael Phillips, Julie Markham, Prof. Paul Peiris, Dr Marion Gaborieau, Dr Patrice Castignolles (June 2014) ACROSS Seminar at the University of Tasmania (UTas) invited by Prof Emily Hilder Optimising Analysis of Carbohydrates in Plant Material for the Biofuel Industry James D. Oliver and Patrice Castignolles (Feb 2012) School of Science and Health Research Seminar at the University of Western Sydney (UWS) Simple and robust separation of monosaccharides in complex mixtures by capillary electrophoresis and high performance liquid chromatography James D. Oliver, Marianne Gaborieau, Emily F. Hilder, Michael Phillips, Julie Markham, Paul Peiris and Patrice Castignolles (Sept 2012) 2012 School of Science and Health forum presentation Industrial ethanol from novel substrates James D. Oliver, Michael Phillips, Julie Markham, Paul Peiris and Patrice Castignolles (June 2012) School of Natural Sciences Research Seminar at the University of Western Sydney (UWS) Bioethanol from Novel Substrates James D. Oliver, Paul Peiris, Julie Markham and Michael Phillips (July 2011) 2011 School of Natural Sciences forum presentation Bioethanol from novel substrates James D. Oliver, Paul Peiris, Julie Markham and Michael Phillips (June 2011) 2010 School of Natural Sciences forum presentation Bioethanol from novel substrates James D. Oliver, Paul Peiris, Julie Markham and Michael Phillips (June 2010) James Oliver CE for bioethanol research ix

12 Table of Contents Statement of Authentication... i Abstract... ii Acknowledgements... v Preface... vi Publications... vii Conference and seminar presentations... viii Table of Contents... x List of figures... xii List of schemes... xvi List of tables... xvii List of equations... xx List of abbreviations... xxi 1. Introduction Background The structure, hydrolysis and fermentation of lignocellulosic material The structure of lignocellulosic plant fiber Hydrolysis of lignocellulosic material Microbial ethanol fermentation Determination of carbohydrates in complex matrices Chemical assays Separation methods Determination of carbohydrates in complex matrices summary Determination of ethanol PhD project aim and objectives Publication Simple and robust determination of monosaccharides in plant fibers in complex mixtures by capillary electrophoresis and high performance liquid chromatography Contribution to PhD work, field, and candidates personal and professional development Advantages and limitations of CE with direct UV detection and HPLC for carbohydrate determination in lignocellulosic plant fiber Theory of NMR spectroscopy Investigation of the direct UV detection Contribution to my personal development Publication Publication supporting information Publication Understanding and improving direct UV detection of monosaccharides and disaccharides in free solution capillary electrophoresis Contribution to PhD work, field, and candidates personal and professional development Investigation of the photo-oxidation reaction James Oliver CE for bioethanol research x

13 3.1.2 Theory of radical chemistry in relation to carbohydrate photo-oxidation Contribution to my personal development Publication Publication supporting information Publication Ethanol determination using pressure mobilization and free solution capillary electrophoresis by photo-oxidation assisted ultraviolet detection Contribution to PhD work, field, and candidates personal and professional development Ethanol determination with CE Contribution to my personal development Publication Publication supporting information Publication Simple and robust monitoring of ethanol fermentations by capillary electrophoresis Contribution to PhD work, field, and candidates personal and professional development Fermentation monitoring by CE Contribution to my personal development Publication Publication supporting information Conclusion and future directions Conclusion Future directions Improving sensitivity and throughput Fermentation monitoring Application to polysaccharide characterization Application to nutrition and health Conclusion of future work References Appendix James Oliver CE for bioethanol research xi

14 List of figures Figure 1.2-1: (A) Glucose with numbered carbons and (B) cellulose polymer with a DP of 2n+2 adapted from [14] Figure 1.2-2: The three structural units of lignin polymers (adapted from [21]) Figure 1.2-3: Hemicellulose polymer (adapted from [25]) Figure 1.2-4: Structure of pectin polysaccharide rhamnogalacturonan II (adapted from [29]) Figure 1.2-5: Summary flowchart of substrate hydrolysis Figure 1.2-6: Action of cellulose enzymes [38] Figure 1.3-1: (A) Isomerization of glucose between open chain form and cyclic form (D- Glucopyranose) and (B) reaction of D-Glucose in open form and 3,5-dinitrosalicylic acid to gluconic acid (2,3,4,5,6-pentahydroxyhexanoic acid) and 3-amino-5-nitrosalicylic acid Figure 1.3-2: Derivatization of glucose to its alditol acetate by acetic anhydride adapted from [89]. 16 Figure 1.3-3: Movement of sodium hydroxide and glucose along the pellicular anion exchange resin (adapted from [101, 102]) Figure 1.3-4: Counter-EOF separation in free solution capillary electrophoresis Figure 1.3-7: Possible mechanism for direct UV detection of carbohydrates in CE by UV initiated photo-oxidation (adapted from [111]) Figure 2.1-1: Ranges of 1 H chemical shifts for different functional groups, adapted from [138] Figure 2.1-2: Ranges of 13 C chemical shifts for different functional groups, adapted from [139] Figure 2.2-1: Separation of a fiber sample (A) and mixture of standard (B) and using HPX-87H column 1: cellobiose, 2: glucose, 3: galactose, 4: xylose, 5: rhamnose, 6: arabinose, 7: void volume, 8: galacturonic acid, 9: unknown Figure 2.2-2: Fiber standard 250 m gl -1 (A) and sample (B) plotted with electrophoretic mobility and migration time (C-i). Separation by CE via Rovio et al. s method [33]. 1: Cellobiose, 3: galactose, 2: glucose, 5: rhamnose, 4: arabinose, 6: xylose and corresponding UV absorption spectra (C-ii) for glucose (dashed line), xylose (solid line) and arabinose (dotted line) Figure 2.2-3: Migration of 1 g L -1 of glucose into 130 mmol Na electrolyte by 16 kv electric field (solid line) and with voltage for 2 min followed by 42 mbar pressure (dashed line) Figure 2.2-4: Degradation of glucose in 130 mmol Na monitored by migration with voltage. The arrows indicate the evolution with increasing time (0 h: bold solid line, 1.5 h: bold dashed line, 4 h: solid line, 7 h: dotted line, 27 h: dashed line, 46 h: bold dotted line) Figure 2.2-5: 1 H NMR of glucose (1 g L -1 with 130 mmol Na in D 2O) before (A) and after irradiation with CE deuterium lamp for 5 min (B), 30 min (C) and 60 min (D). The arrows indicate the region in which new signals appear Figure 2.2-6: Detection of glucose (1 g L -1 ) in 130 mm Na with 16 kv separation. Each peak represents a pass of the sugar though the lamp, after which the voltage was inverted Figure 2.3-1: HPLC Separation of sugars on HPX-87C with water mobile phase (A), HPX-87P with water mobile phase (B) and LC-NH2 with 75:25 ACN:water mobile phase (C). Sol: Solvent peak. 1: Cellobiose, 2: Glucose 3: Galactose 4: Xylose 5: Rhamnose 6: Arabinose 7: Mannose James Oliver CE for bioethanol research xii

15 Figure 2.3-2: Calibration curve of response with RID for the sugars in our fiber standard on the HPX- 87H column Figure 2.3-3: Comparison of electrophoretic mobility of DMSO (1) and methanol (2) in 130 mmol Na and 36 mmol Na 2HPO 4, detected at 200 nm Figure 2.3-4: Calibration curves with standards, showing R 2 values (capillary of 60 cm total length). Equations are given in Table Figure 2.3-5: Evolution of the area of the glucose peak monitored by CE for a solution of glucose 1 g.l-1 in 130 mm Na Figure 2.3-6: Degradation of glucose in 130 mmol Na monitored by migration with pressure. The arrows indicate the evolution with increasing time (0 h: bold solid line, 1.5 h: bold dashed line, 4 h: solid line, 7 h: dotted line, 27 h: dashed line, 46 h: bold dotted line) Figure 2.3-7: Photo-oxidation of glucose in CE. Adapted from Gilbert et al. (1982) [5] Figure 2.3-8: Separation and detection of glucose (1 g L-1) in 130 mmol Na in water (dotted line) and in D2O (solid line) Figure 2.3-9: 1H NMR of 1 g L -1 glucose (A) in 130 mmol of Na after 2 hours (A-I) and 5 days (A-II) and of sucrose (B) in water (B-I), 130 mmol Na after 2 hours (B-II) and after 5 days (B-III) Figure 3.2-1: Proposed sequence of events leading to UV-absorbing intermediates and carboxylated end-products Figure 3.2-2: 13 C NMR spectrum of 1 g L C-labelled glucose continuously and hydrodynamically injected into CE, after subtraction of the spectrum of the control glucose. Both original spectra are shown in supporting information (Figure 3.3-4). Corresponding molecules taken from [40] where R refers to a saturated alkyl group Figure 3.2-3: effect of hydrogen peroxide in BGE on peak area of 1 g L -1 sucrose in 130 mm Na. The Increase in peak area is relative to 1 g L -1 sucrose injected with 130 mm Na BGE (no hydrogen peroxide). The error bar in this graph indicates the highest and lowest value (n=2) for a given run, while the different points indicate different runs. Runs were carried out on the HP3D instrument (n=2) as well as the Agilent Figure 3.2-4: The effect of Irgacure 2959 in BGE on peak area of 1 g L -1 sucrose. (A) The increase in peak area is shown relative to 1 g L -1 sucrose injected with 130 mm Na BGE. Separations were carried out in a conventional capillary (solid line) and a high sensitivity capillary (dotted line). Error bar indicates relative standard deviation (n=5) (B) Overlay of sucrose peak in a conventional capillary without Irgacure 2959 (dash line) and with M Irgacure 2959 (solid line), in a high sensitivity capillary without Irgacure 2959 (dotted line) and with M Irgacure 2959 (dash dotted line) Figure 3.3-3: 1 HNMR spectra of 1 g L C glucose in 130 mm Na before (black) and after (red) continuous and hydrodynamic injection into CE Figure 3.3-4: 13 CNMR spectra of 1 g L Cglucose in 130 mm Na before (black) and after (red) continuous hydrodynamic injection into a capillary Figure 3.3-5: Experimental 13 C NMR spectrum for malondialdehyde tetrabutylammonium salt in the same conditions as Figure (A) and predicted 13 C NMR chemical shifts for dihydroxyacetone (B) (predictions performed with ChemNMR at neutral ph) Figure 3.3-6: 13 C NMR spectrum (black) and DEPT-135 NMR spectrum (red) of 1 g L C glucose in 130 mm Na after continuous hydrodynamic injection into a capillary. A DEPT-135 NMR spectrum exhibits positive CH and CH 3 signals, negative CH 2 signals, and no signal for other carbons James Oliver CE for bioethanol research xiii

16 Figure 3.3-7: 1 H NMR spectra of A. glycerol (solid black), B. sodium oxalate (solid red), C.sodium glycolate (dotted black), D. sodium gluconate (dotted red), E. sodium methanoate (dashed black) and F. gluconolactone (dashed red). The chemical shifts predicted with ChemNMR are shown on the molecules on the left Figure 3.3-8: 13 C NMR spectra of A. glycerol (solid black), B. sodium oxalate (solid red), C. sodium glycolate (dotted black), D. sodium gluconate (dotted red), E. sodium methanoate (dashed black) and F. gluconolactone (dashed red). The chemical shifts predicted with ChemNMR are shown on the molecules on the left Figure 3.3-9: First step in photolysis of Irgacure 2959 adapted from [8]. Products react further to form a variety of radicals Figure : UV absorption spectra of Irgacure 2959 at M (red) and M (black) in 130 mm Na, obtained using pressure mobilization in the 7100 CE instrument using a high sensitivity capillary and pressure mobilization Figure : Separation of oligoacrylate in a high sensitivity capillary (black) and normal fuse silica capillary (red). The initiated monomer (AA1) peak [9] is identified with the blue box. Separation conditions: 30 kv, 25 C, 75 mm sodium borate buffer Figure 4.2-1: Pressure mobilization at 50 mbar: (A) of 2 g L -1 sucrose in 130 mm Na not spiked (solid line) or spiked with ethanol at 250 mg L -1 (dotted line), 1 g L -1 (dashed line) and 2 g L -1 (dotteddashed line), with Na 130 mm as the mobile phase. (B) of 2 g L -1 sucrose in 130 mm Na (with 130 mm Na as the mobile phase, dotted line) and of 1 g L -1 ethanol in 2 g L -1 sucrose and 130 mm Na (with 130 mm Na with 2 g L -1 sucrose as the mobile phase, solid line). Performed on MDQ instrument (n=5) Figure 4.2-2: Hydrogen abstraction from ethanol by a free radical R. Adapted from [18] Figure 4.2-3: Interference of alcohols and triethylamine at 5 mm (white) and 44 mm (striped) with the photo-oxidation of 2 g L -1 sucrose during pressure mobilization. Relative difference in peak height (PH RD) is calculated as PPPPRD = PPPPS PPPPEtPPPPS where PH S is the height of the sucrose peak, PH Et is the height of the peak of sucrose spiked with ethanol. 10 cm effective length, 50 mbar pressure mobilization (n=3), performed on MDQ instrument Figure 4.2-4: Possible reaction scheme for the interference of ethanol with glucose photo-oxidation Figure 4.2-5: Peak heights in the pressure mobilization of 2 g L -1 sucrose (black square), 2 g L -1 sucrose and 250 mg L -1 ethanol (circle) and 2 g L -1 sucrose and 1 g L -1 ethanol (cross) in 130 mm Na passing the detection window multiple times (A) and the relative difference in their peak height (B). Initial pressure was 50 mbar (outlet to inlet) for 6 min then reversed (inlet to outlet) for 3 min and reversed every 3 min for a total of 28 passes. Error bars show standard deviation (n=3). Peak overlay can be seen in Figure Performed on MDQ instrument Figure 4.2-6: 1 H NMR of 2 g L -1 ethanol in the presence of 1 g L -1 fully labelled 13 C glucose continuously and hydrodynamically injected into a 7100 CE instrument (solid line) with nonirradiated control of the same age (dotted line) as well as freshly prepared control (dashed line).the spectra were normalized by the number of scans (20480, 2400 and 800 respectively) and the dilution factor (the controls were undiluted, sample was diluted 1/4.46 as described in section 2.2.1) Figure 4.2-7: 13 C NMR of 1 g L -1 fully labelled 13C glucose in the presence of 2 g L -1 ethanol continuously and hydrodynamically injected into a 7100 CE instrument (solid line, top) and control (dotted line, bottom). The rectangles indicate the ethanol signals James Oliver CE for bioethanol research xiv

17 Figure 4.2-8: Sucrose peak height (solid line), sucrose spiked with 1 g L -1 ethanol peak height (dotted line) and difference between sucrose peak heights with and without ethanol (dashed) after pressure mobilization at 50 mbar in a 90 cm (10 cm effective length) capillary (n = 5). Error bars on peak height difference are ± sum of the standard deviations of both peaks (n=5). Performed on MDQ instrument Figure 4.2-9: Detection of ethanol and carbohydrates via CE (A) and detection of varying concentrations of ethanol by interference with the photo-oxidation (B). BGE in outlet and inlet was 130 mm Na, BGE in capillary was 130 mm Na + 2 g L -1 of sucrose. Migration was by electric field (24 kv) for 12 min followed by pressure mobilization at 50 mbar. Assignment of ethanol concentrations for (B): 2 g L -1 (solid line), 1 g L -1 (short dotted line), 500 mg L -1 (short dashed line), 250 mg L -1 (dotted line), 125 mg L -1 (dashed line) and 0 mg L -1 (dashed-dotted line). Current was 147 µa. Performed on 7100 CE instrument Figure 4.3-1: Relationship between the multiplication of the analyte Refractive Index (RI) by the concentration of the analyte and the relative peak difference. The analytes are methanol (square), ethanol (triangle), isopropanol (star), tert-butanol (pentagon) and triethylamine (circle). RI values are 20 C [1] Figure 4.3-2: Blank of injection 130 mm Na (green), 1 g L -1 Ethanol in 130 mm Na (blue), 2 g L -1 sucrose in 130 mm Na (black) and 1 g L -1 Ethanol in 2 g L -1 sucrose in 130 mm Na (red) Figure 4.3-5: 1 H NMR of 1 g L -1 fully labelled 13 C glucose in the presence of 2 g L -1 ethanol continuously and hydrodynamically injected into a 7100CE instrument for 94.5 h (black), control with no UV exposure for the same length of time (blue) and prepared fresh (red) Figure 4.3-6: 13 C NMR of 1 g L -1 fully labelled 13 C glucose in the presence of 2 g L -1 ethanol continuously and hydrodynamically injected into a 7100CE instrument for 94.5 h (black), control with no UV exposure for the same length of time (blue) and freshly prepared control (red) Figure 4.3-7: Oxidation of ethanol radical to acetic acid (a-d) adapted from [5] and to butan-2,3-diol (e). G-H represents glucose and G represents glucose derived radical as shown in Figure Figure 4.3-8: Possible but unobserved products of glucose photo-oxidation in the presence of ethanol. Unobserved chemical shifts are in brackets Figure 4.3-9: Possible interference of water derived radicals by ethanol Figure : Peak areas of sucrose (solid line) and sucrose spiked with 1 g L -1 ethanol (dotted line), as well as difference between sucrose peak areas with and without ethanol (dashed) after pressure mobilization at 50 mbar in a 90 cm (10 cm effective length) capillary (n = 5). Error bars on peak area difference are ± sum of the standard deviations of both peaks (n=5). Performed on MDQ instrument Figure : Sucrose peak at 500 mg L -1 (black solid), 1000 mg L -1 (black dotted), 2000 mg L -1 (red solid) 4000 mg L -1 (red dotted) and 8000 mg L -1 (blue solid) without ethanol (A) with 1000 mg L -1 ethanol (B). Performed on MDQ instrument Figure : Effect of sucrose concentration on the signal to noise ratio (S/N) Figure : Standard curve obtained from MDQ (red) obtained from 4 separated days spaced over a month, 7100 (black) and a combination of the 2 (blue) Figure : Calibration curve of ethanol concentration against difference in peak height for sucrose (black circles) and xylitol (red triangles) (n=5) Figure : Pressure mobilization of 5.8 mm sucrose (black) and xylitol (red) in the presence of 1 g L -1 ethanol. Performed on MDQ instrument James Oliver CE for bioethanol research xv

18 Figure : Comparison of the signal to noise ratio of a sucrose peak (2 g L -1 ) between the 7100 CE and the MDQ instruments (n=5) Figure : CE of ethanol when the electric field (24 kv) was applied for the entire separation. Performed on 7100 CE instrument Figure : Detection of 1 g L -1 ethanol via CE by interference with the photo-oxidation of sucrose. Indirect ethanol peak is shown in the dashed boxes. BGE in outlet and inlet was 130 mm Na, BGE in capillary was 130 mm Na + 2 g L -1 of sucrose (black, S/N = 37) and 130 mm Na g L -1 of sucrose (red, S/N = 36). Migration was by electric field (24 kv) for 12 min followed by pressure mobilization at 50 mbar. Current was 160 µa. Performed on 7100 CE instrument Figure 5.2-3: Quantitative comparison of glucose (A), arabinose (B) and arabitol (C) in a complex fermentation sample by HPLC ( ) and CE ( ). Error bars represent ± STD (n=3) Figure 5.2-4: Fermentation of hydrolyzed plant fiber to ethanol. Samples taken at 0 hours (A), 6 hours (B) and 24 hours (C). Peak assignments: (1) lactose (internal standard), (2) galactose, (3) glucose, (4) mannose, (5) fructose, (6) arabinose, (7) xylose, (8) arabitol, (9) unknown (for migration plot see Figure 5.3-8). Ethanol peak in sequential injection given as inverted peak for 0 h ( ), 6 h ( ) and 24 h ( ) Figure 5.3-2: Contour plot of the varying K and Li proportion in 130 mm total alkaline concentration (when relevant the third component is Na). Contour shows the distribution of inverse difference in electrophoretic mobility of glucose and mannose where the lowest value is shown by the darkest region. The labels (stars) display the relative position of rhamnose to glucose and mannose defined as (mmmm mmgg)(mmmm mmmm) Figure 5.3-4: Graphical determination of peak widths and retention times taken as an example and extracted from Figure 5.2-1A glucose and galactose peaks Figure 5.3-6: Separation of glucose (a) and fructose (b) (equal concentration) in 130 mm K with a fixed concentration of 500 mg L -1 lactose (c) internal standard. Glucose and fructose at (A) 1000 mg L -1 (B) 500 mg L -1 (C) 250 mg L -1 (D) 125 mg L -1 (E) 62.5 mg L -1 each Figure 5.3-9: Separation of ethanol and carbohydrates in a 25 mg L -1 standard (black) and fermentation sample (red) with HPAEC-PAD. Peak assignment: 1. Void peak, 2. Ethanol, 3. Elevated baseline indicating other analytes, 4. Media components, 5. Arabinose, 6. Glucose, 7. Fructose. PA1 column with a 30mM Na mobile phase at 1 ml min-1 operating at room temp List of schemes Scheme 2.3-1: Set-up of CE photo-oxidation experiment Scheme 3.2-2: Formation of semidione B from β-d-glucose adapted (and corrected to place missing radical in 1 st and 2 nd molecule), from Gilbert et al. [29]. It is noted that between the 4 th and 5 th stage, protonation followed by de-protonation of the alcohol on the 4 th carbon is not necessary Scheme 3.3-1: List of potential UV absorbing intermediates based on Gilbert et al.[2] and the assignments Scheme 3.3-2: A second possibility for the oxidation of glucose in the presence of oxygen leading to sodium methanoate and sodium glycolate as well as sodium glycerate James Oliver CE for bioethanol research xvi

19 List of tables Table 1.3-1: The structure and pk a of some monosaccharides, disaccharides and sugar alcohols Table 2.2-1: Experimental conditions used in HPLC for the different columns Table 2.2-2: Resolution values for consecutive peaks on each column and in CE Table 2.2-3: Electrophoretic mobility (µ ep) with its relative standard deviation (RSD) and calibration of response at 270 nm with its correlation coefficient R 2, for the sugars in our fiber standard (capillary of 66 cm total length) Table 2.2-4: Comparison of the determined sugar concentration C (g L -1 ), with their relative standard deviation RSD (%), by CE (capillary of 66 cm total length) and HPLC with HPX-87H column Table 2.3-1: Calibration of response with RID with its relative standard deviation (RSD) of response at 270 nm with its correlation coefficient R2, for the sugars in our fiber standard on the HPX-87H column Table 2.3-2: Electrophoretic mobility (10-8 m 2 V -1 s -1 ) of common fiber sugars determined in this study (35 injections), before and after correction using lactose as the internal standard. RSD is the relative standard deviation (%). The values are compared with published values Table 2.3-3: Estimate of the cost of the typical CE and HPLC separations ($ is for Australian dollar and prices are as for 2012) Table 2.3-4: Comparison of the determined sugar concentration C (g L-1), with their relative standard deviation RSD (%), by CE (capillary of 66 cm total length) and HPLC with HPX-87H column. Compared to Table 4, these separations have been fully reproduced with fresh solution and new capillaries Table 2.3-5: Fraction experiments to determine the loss in HPLC in comparison to CE: comparison of the concentrations of glucose injected in HPLC, C inj, eluted from HPLC according to RID detection, C RID, and as determined from CE, C CE Table 2.3-6: Peak areas of glucose degrading in 130 mm sodium hydroxide, separated by CE with 16 kv Table 3.2-2: Simulated spectral properties of possible UV absorbing intermediates Table 3.2-3: Possible identification of some products from photo-oxidation of 13 C glucose according to their 13C and 1H NMR chemical shifts δ. The individual 1 H and 13 C NMR spectra are shown in supporting information. All compounds listed except sodium oxalate, malondialdehyde and sodium gluconolactone are potentially present in the sample Table 3.2-4: Comparison of limit of detection (LOD) between different analytical separation and detection methods. CE separation with direct UV detection (this study) was at 24 kv in 90 cm (81.5 cm effective length) high sensitivity capillary in 130 mm Na with M Irgacure Table 3.3-1: Results of TD-B3LYP/6-31++G(2d, 2p) Calculations. Electronic energies (E), zero point energies (E ZPE), thermal energies (U), enthalpies (H) and Gibbs Free Energies (G) in hartrees and entropies (S) in cal mol 1 K Table 3.3-2: Principal Features of Predicted Spectra Table 4.2-2: Linearity of ethanol quantification, LOD, LOQ and recovery in pressure mobilization and CE with sucrose and xylitol as background carbohydrates. n=5 for all standards and samples James Oliver CE for bioethanol research xvii

20 Table 4.3-4: Estimate of the minimal concentration (E) of end products that, resulting from decomposition of ethanol, could be detected by 13 C NMR Table 4.3-5: Predicted 13 C shifts of potential end products of carbohydrate photo-oxidation in the presence of oxygen. Prediction done with ChemDraw Ultra 12. Bold, underlined chemical shifts are not observed in the 13 C NMR spectrum (Figure 4.2-4) Table 4.3-6: Predicted 13 C shifts of potential UV absorbing intermediates from carbohydrate photooxidation as studied by [4]. Prediction done with ChemDraw Ultra 12. Bold, underlined chemical shifts are not observed in the 13 C NMR spectrum (Figure 4.2-4) Table 5.2-1: Electrophoretic mobility (µ ep) of carbohydrates and related fermentation end products (0.5 g L -1 each) in different BGE (a more extensive version is given as Table 5.3-1). Conditions: Voltage 24 kv, temperature 15 C, current of 160 ± 6 µa. The values are an average of three sequential injections Table 5.2-2: Resolution (expressed as orthogonal valley to peak ratio expressed as 100 x V s/p) of the mixture of carbohydrates (the lowest value is given in bold). Separation conditions: 24 kv, 90 cm capillary (81.5 cm effective length). Mixture contains 0.5 g L -1 xylitol, arabitol, lactose, galactose, glucose, rhamnose, mannose, arabinose and xylose. n=3. The lowest values are indicated in bold. 167 Table 5.2-3: List of current/potential fermentation substrates and the recommended BGE to monitor the fermentation using CE Table 5.3-1: Comparison of various Background Electrolytes (BGE) and their effect on electrophoretic mobility and electro-osmotic flow (EOF). Electrophoretic mobility was calculated using Equation Table 5.3-2: Electrophoretic mobility of carbohydrates and related fermentation end products (0.5 g L -1 each) in Li with varying concentration. Conditions: Voltage 24 kv, temperature 15 C Table 5.3-4: Values for a, b, d, e, and f for exploration viscosity by Equation Table 5.3-5: Calculation of the ratio of ionic charge to hydrodynamic radius calculated by Equation Table 5.3-8: Time to achieve a given resolution, T res, based on R ovp, for a mixture of carbohydrates. Separation conditions: 24 kv, 90 cm capillary (81.5 cm effective length). Mixture contains 0.5 g L -1 xylitol, arabitol, lactose, galactose, glucose, rhamnose, mannose, arabinose and xylose. Lowest T res is in bold Table 5.3-9: T res based on R vp (Table for the equivalent values based on R ovp) for a mixture of carbohydrates. Separation conditions: 24 kv, 90 cm capillary (81.5 cm effective length). Mixture contains 0.5 g L -1 xylitol, arabitol, lactose, galactose, glucose, rhamnose, mannose, arabinose and xylose. Lowest T res is in bold Table : T Res in BGE: 52 mm K 52 mm Na 26 mm Li (M5), capillary length 112 cm (103.5 cm effective length), 29.8 kv electric field. The lowest values are given in bold Table : Repeatability of HPAEC injections of 2 fermentation samples in terms of determined concentration and retention time (n=5). BDL= below detectable limit. PA1 column with a 30mM Na mobile phase at 1 ml min -1 operating at room temp Table : Repeatability of HPLC injections of 5 fermentation samples in terms of determined concentration and retention time (n=5). HPX-87H hydrogen form cation exchange resin with a mobile phase 5 mm H 2SO 4 at 0.60 ml min -1 operating at 60 C Table : Analysis of results displayed in Figure James Oliver CE for bioethanol research xviii

21 Table : Calibration curves for quantification of carbohydrates in fiber fermentation samples by CE Table 6.1-1: Comparison of HPLC, HPAEC and CE on various fermentation samples James Oliver CE for bioethanol research xix

22 List of equations Equation 1.2-1: Aerobic respiration of glucose [44] Equation 1.2-2: Anaerobic respiration of glucose by an ethanologen [44] Equation 1.2-3: Microaerobic respiration of xylose by Pichia stipitis [49] Equation 1.3-1: Relationship between apparent velocity (v app), electroosmotic velocity (v eof) and electrophoretic velocity (v ep) Equation 1.3-2: Calculation of the velocity of the EOF (v eof) and an analytes apparent velocity (v app), where v stands for either v app or v eof. Where L d is the length to the detection window (or effective length) and t is the time the analyte or EOF marker is detected Equation 1.3-3: Relationship between an analytes electrophoretic mobility µ ep, its ionic velocity v and the electric field E Equation 1.3-4: Calculation of the electric field strength where L t is the total length of the capillary and V is the voltage Equation 1.3-5: Formula used to calculate electrophoretic mobility µ ep of an analyte Equation 1.3-6: Stokes law governing electrophoretic mobility Equation 3.1-1: Formation of oxygen biradicals Equation Equation Equation Equation Equation Equation Equation Equation Equation Equation 6.3-1: relationship between apparent velocity (v app), electroosmotic velocity (v eof) and electrophoretic velocity (v ep) Equation 6.3-2: Formula used to calculate the experimental electrophoretic mobility values Equation 5.3-3: Expression of electro-osmotic flow (6) Equation 5.3-4: Stokes law governing electrophoretic mobility (6) Equation 5.3-5: Calculation of viscosity of K, Na and Li. (5) Equation 5.3-6: Calculation for resolution of symmetric peaks Equation 5.3-7: Formula used to calculate the experimental electrophoretic mobility values with an internal standard James Oliver CE for bioethanol research xx

23 List of abbreviations C Degree Celsius δ Chemical shift η Viscosity of the solution µl Microliter µm Micrometre (v/v) Volume to volume (w/v) Weight to volume 13 C NMR 13 C nuclear magnetic resonance 1 H NMR 1 H (proton) NMR ACROSS Australian centre of research on separation science AFEX Ammonia fiber explosion ACN Acetonitrile BGE Background electrolyte C 4 D or CCD Contactless conductivity detection CE Capillary electrophoresis (refers to free solution capillary electrophoresis or capillary zone electrophoresis in this thesis) DAD Diode array detector DMSO Dimethylsulfoxide DSS 4,4-dimethyl-4-silapentane-1-sulfonic acid DP Degree of polymerization E Electric field EOF Electroosmotic flow ESR Electron spin resonance Et Ethanol FID Flame ionization detection g Gram GC Gas chromatography GLC Gas-Liquid Chromatography GMO Genetically modified organism GRAS Generally recognized as safe h Hour HILIC Hydrophilic interaction liquid chromatography HMF hydroxymethyl furfural HPAEC High performance anion exchange chromatography HPLC High performance liquid chromatography Hz Hertz i.d. Internal diameter IF Impact factor L Litre L d Length of capillary to the detector/effective length L t Total capillary length LOD Limit of detection LOQ Limit of quantification M Mole per litre m Meter m app Apparent mobility m eof Electroosmotic mobility µ ep Electrophoretic mobility James Oliver CE for bioethanol research xxi

24 mbar mg min ml mm mm mol MS MW nm NMR o.d PAD ph pk a ppm PPP q r rf RP-HPLC RSD s SD SDS SNR SPE t t eof t m UNE UTas UV UWS V v v eof v app v ep Millibar Milligram Minute Millilitre Millimole per litre Millimetre Mole Mass spectrometry Molecular weight Nanometre Nuclear magnetic resonance Outer diameter Pulsed amperometric detection Potential hydrogen Negative log of acidity constant K a Parts per million Pentose phosphate pathway Effective charge Ionic radius Radio frequency Reverse phase high performance liquid chromatography Relative standard deviation Second Standard deviation sodium dodecyl sulfate Signal-to-noise ratio Solid phase extraction Time Migration time of the neutral species Migration time of the analyte University of New England University of Tasmania Ultraviolet University of Western Sydney Voltage Velocity Velocity of the neutral species Apparent velocity Electrophoretic velocity James Oliver CE for bioethanol research xxii

25 1. Introduction 1.1 Background Liquid biofuels have the potential to provide a carbon neutral liquid energy source. Since the realization of a limited coal and oil supply, alternative sources of renewable energy have been investigated worldwide. It is believed that fossil fuels will be depleted at some point over the next century. They could last for the next 20 to 100 years if they were progressively replaced by alternative fuels [1]. Biofuels are an attractive alternative for transport fuels as they require minimal change to infrastructure and also have the potential to be carbon neutral. In Brazil between 1975 and 2005, ethanol fuel substituted for 240 billion liters of gasoline, saving $56 billion in direct importation costs over the 30 year period [2]. Both the sucrose from sugar cane and starch from corn are easy to release and ferment to ethanol. Although there are clear benefits of the use of biofuels, especially in Brazil, there have been a number of studies that have continually reviewed its economic and environmental sustainability [1, 3]. First generation biofuels (or conventional biofuels) are prepared from food crops, including sugar cane from Brazil and corn from the USA and Mexico. In Australia, high grain prices in 2007 forced plans for a number of bioethanol production plants to be cancelled [4]. A major shortfall of this approach is that supply is limited by food demand, which increases with a growing population. Second generation biofuels (or advanced biofuels) are prepared from lignocellulosic materials. These are sourced from non-food crops, such as switch grass [5] and various woods [6, 7], or food crop wastes, such as sugar cane bagasse [8], agave bagasse [9] and corn stover [10]. They are considered to be more sustainable (in relation to food security) as they can be obtained from any plant material not only food crops. A drawback to these sources is that the carbohydrates of these plants are more difficult to access, requiring more complex treatment to release the carbohydrates which makes economic sustainability an issue. Unlike first generation fuels, lignocellulosic materials also contain other hexose sugars, such as galactose, rhamnose and mannose, and pentose sugars, such as arabinose and xylose (discussed later in 1.2.1). These complex mixtures of carbohydrates require innovative fermentation strategies to ferment the larger variety of sugars (discussed later in 1.2.3) and analysis techniques (discussed later in 1.3) to monitor the process. James Oliver CE for bioethanol research 1

26 As the field moves further into second generation biofuels, the performance of the methods to analyze these substrates are not improving accordingly. These samples have complex matrices (large variation of molecules in the sample) therefore a robust separation is required to obtain accurate results. As there is no IUPAC definition [11] robust in this study is to mean a method that can be applied to analytes in a wide variety of matrices [12]. 1.2 The structure, hydrolysis and fermentation of lignocellulosic material The hydrolysis and fermentation of lignocellulose substrates is more complex than that of first generation substrates. Lignocellulose contains a variety of sugars bound by lignin, which makes its breakdown and subsequent analysis more difficult The structure of lignocellulosic plant fiber Lignocellulosic plant fiber is comprised of cellulose microfibrils, a variety of hemicellulose and pectin polysaccharides, as well as the chemical compound lignin. Together these polymers make up the primary and secondary cell wall that account for the majority of dry mass of the plant as well as its fermentable carbohydrates. The ratio and composition of each will vary greatly depending on the plant Cellulose Cellulose ([C 6H 10O 5] n) is the most abundant naturally occurring compound. It is a reproducible organic polysaccharide, comprising at least a third of advanced plants [13]. Cellulose is a polymer of glucose (C 6H 12O 6) units joined by β(1 4) bonds [14]. The β(1 4) of cellulose differs from the glucose α(1 4) of starch in that every second β(1 4) force the glucose unit to bend back 180 on itself creating tightly bound subunits. The intermolecular hydrogen bonds formed between glucose subunits by this bend (Figure 1.2-1), produces a strong secondary ribbon structure [15]. The length of the polymer chain varies greatly with the type of plant and is measured as Degrees of Polymerization (DP) that is the number of glucose units in a chain. The chains of cellulose are bound with each other by hydrogen bonds to form a water impermeable crystalline microfibril structure, stronger than starch, which makes the sugars more difficult to hydrolyze [16, 17]. James Oliver CE for bioethanol research 2

27 Figure 1.2-1: (A) Glucose with numbered carbons and (B) cellulose polymer with a DP of 2n+2 adapted from [14] Lignin Lignin ([C 9H 10O 2] n [C 10H 12O 3] n [C 11H 14O 4] n) is the second most abundant terrestrial polymer and accounts for 30 % of organic carbon in the biosphere [18]. This complex phenolic polymer gives plants structure and strength by cross-linking with cellulose in the secondary cell wall [19, 20]. It is comprised of three structural units (Figure 1.2-2) that vary in ratio depending on the plant [21]. Figure 1.2-2: The three structural units of lignin polymers (adapted from [21]). The hydrolysis of lignin is needed to access the cellulose polymers, however the products may inhibit the carbohydrate fermentation to ethanol [22] and increase difficulty in analysis (see ) of both the hydrolysis plant fiber and subsequent fermentation. James Oliver CE for bioethanol research 3

28 Hemicellulose and pectin Hemicelluloses are a family of polysaccharides that link to cellulose microfibrils by hydrogen bonds in the primary cell wall [21] and have other functions throughout the plant [23]. The structure and composition of hemicellulose varies greatly with plant type. Hemicellulose consists of varying amounts and concentrations of xyloglucans (β(1 4)-linked glucose backbone with α(1 6)-linked single D-xylose unit side chains; Figure 1.2-3). Some D-xylose units have β(1 2)-linked D-galactose or D-fucose units or L-arabinose residues (Figure 1.2-3). Arabinose may also be directly linked to the glucose backbone (C-2) [19, 24, 25] (Figure 1.2-3). Figure 1.2-3: Hemicellulose polymer (adapted from [25]). Pectin is present in both the primary cell wall and the spaces between cells (middle lamella). Pectin is a group of polysaccharides that contain a significant amount of galacturonic acid and some smaller amounts of arabinose, galactose and rhamnose. Galacturonic acids are bound together by α(1 4) bonds [26] (Figure 1.2-4). Like hemicellulose, its structure varies greatly with plant type. In addition, the distributions of composition for pectin varies between plants, as well as within one plant [27, 28]. Pectin contributes structure to the cell wall by forming intermolecular bonds with free carboxyl groups. James Oliver CE for bioethanol research 4

29 Figure 1.2-4: Structure of pectin polysaccharide rhamnogalacturonan II (adapted from [29]). The determination of carbohydrates during hydrolysis and fermentation of lignocellulose (discussed in and 1.2.3) requires a method capable of determining not only the amount of glucose from cellulose but the variety of sugars found in hemicellulose and pectin resisting interference of other compounds, such as lignin monomers Structure of lignocellulose summary The structure of lignocellulose is complex which leads to difficulty in its hydrolysis (discussed in 1.2.2), fermentation (discussed in 1.2.3) as well as its analysis (discussed in 1.3) Hydrolysis of lignocellulosic material Due to intermolecular bonding between lignin, pectin, cellulose and hemicellulose within cell walls, the plant material must be pre-treated and hydrolyzed into fermentable monosaccharides and disaccharides before their fermentation into ethanol. There are two primary methods of pre-treatment; acid or alkaline hydrolysis and steam explosion (Figure 1.2-5). When pre-treating lignocellulose, the aims are to hydrolyze the hemicelluloses completely to monomers without degradation, to remove the lignin and to reduce the size of the cellulose semi-crystalline structure for enzyme hydrolysis [30, 31]. According to Kumur et al. (2009) the pre-treatment must improve the release of sugars or the ability to subsequently release sugars by hydrolysis, avoid the degradation or loss of carbohydrate, avoid the formation of by-products that are inhibitory to the subsequent hydrolysis and fermentation processes and be costeffective. After pre-treatment, the cellulose polymers are exposed for enzymatic hydrolysis (Figure 1.2-5). Alternatively acid hydrolysis or pyrolysis maybe used (Figure 1.2-5). James Oliver CE for bioethanol research 5

30 Figure 1.2-5: Summary flowchart of substrate hydrolysis Physical pre-treatment (milling) The substrates are milled to a smaller particle size for hydrolysis via chipping and milling. It has been shown, in relation to woody plant species, that the particle size has a direct impact on the efficacy of the pre-treatment step [32]. Woody substrates are generally chipped down to a size of mm and/or milled down to a size of mm [33]. The overall effect of milling is that cellulose loses some of its semi-crystalline structure Physicochemical pre-treatment Physicochemical pre-treatment uses a combination of physical pre-treatment such as mild pyrolysis, which exploits the molecular alteration and decomposition of biomass under heat, with chemical decomposition. The three primary types are: Steam Explosion: chipped biomass is exposed to high pressure steam between C followed by a swift pressure reduction, which forces the biomass to undergo explosive decompression [33]. Ammonia Fiber Explosion (AFEX): biomass is exposed to liquid ammonia at high-pressure and temperature followed by a swift pressure reduction. This pre-treatment does not significantly solubilize the hemicelluloses compared to steam explosion, acid catalyzed steam explosion and acid pre-treatment in studied substrates [33]. James Oliver CE for bioethanol research 6

31 CO 2 Explosion: CO 2 explosion is similar to steam and ammonia fiber explosion wherein the biomass is treated under high pressure and temperature with CO 2. This is followed by a rapid lowering in pressure. Theoretically, CO 2 forms carbonic acid which then speeds up hydrolysis [33]. For recycled paper mix and bagasse, CO 2 explosion is found to be more cost effective than ammonia explosion and, unlike steam explosion, does not form inhibitory compounds [34]. However, this method with alfalfa only yielded 75% of the theoretical glucose in the following hydrolysis, which is a lower yield compared to steam and ammonia explosions [35] Chemical pre-treatment The popular chemical pre-treatments, an alternative to physicochemical pre-treatment, usually involve hydrolytic techniques with acids, alkalis and to a small extent, oxidizing agents. Acids such as sulfuric, hydrochloric, nitric or phosphoric acid are used individually or in combination with a physicochemical pre-treatment such as steam explosion to break down hemicelluloses. Peroxides or alkalis such as sodium hydroxide, ammonia and calcium hydroxide are used for delignification (removal of lignin; see ) and hemicellulose removal. Solvents such as methanol, ethanol and acetone are also used for delignification [1] by extraction Enzymatic hydrolysis Three major hydrolysis processes are typically used in ethanol production: dilute acid, concentrated acid (both discussed next) and enzymatic hydrolysis [31]. Enzymatic hydrolysis has 3 main advantages. Firstly, production of by-products can be controlled and thereby increase yield efficiency. Secondly, they require milder conditions (e.g. ph, temperature and pressure) and thirdly they require low energy inputs [36]. There are two distinct disadvantages of enzymatic hydrolysis. First, the production of enzymes adds to the cost of the overall process. Second, the sample requires neutralization (to reach the enzymes optimum ph range) after acid/alkaline pretreatments which can produce inhibitory salts or add to the sample preparation time (if an ion exchange resin is used) before analysis and fermentation. Enzymes are commercially available for cellulose, hemicellulose and pectin polymers. A class of enzymes called cellulases breaks down cellulose into glucose (Figure 1.2-6). The three main cellulases are [37]: James Oliver CE for bioethanol research 7

32 endoglucanase, which binds to, and cleaves the most accessible glycosidic bonds of the cellulose polymer chain to create smaller cellulose chains (oligomers) and thus increase the amount of binding ends of points for the other cellulase enzymes (Figure 1.2-6). exoglucanase, which binds to the chain ends and breaks off the disaccharide cellobiose (Figure 1.2-6). β-glucosidase, which breaks the cellobiose into glucose monosaccharides (Figure 1.2-6). Figure 1.2-6: Action of cellulose enzymes [38] Acid hydrolysis Acid hydrolysis, which predates enzymatic hydrolysis, has the advantage of not requiring feedstock to produce enzymes [1] and is simple and relatively inexpensive to carry out on a small scale. High strength acids (30-70 %) are used close to room temperature, while much lower concentrations ( 1 %) can be used when combined with high temperatures (190 C-220 C). The distinct disadvantage is that microbial inhibitors, such as furfural and hydroxymethyl furfural (HMF), are formed. Ions from certain acids, such as sulfates from sulfuric acid, are also inhibitory to the fermentation [33, 39]. Microbial inhibitors need to be removed before the fermentation process. Pyrolysis is another form of physical treatment in which biomass is thermally decomposed in the absence of oxygen to yield solid, liquid and gas by-products [40]. James Oliver CE for bioethanol research 8

33 Hydrolysis summary Hydrolysis is able to liberate monosaccharides and disaccharides out of the fibers but with difficulty and thus combining different methods is advised. Each hydrolysis technique has the ability to increase the complexity of the sample matrix. The acid pre-treatment is simple to carry out on a small scale and it is typically used in combination with enzymatic hydrolysis to maximize the carbohydrate available for fermentation. The presence of by-products formed by the acid pre-treatment as well as the presence of enzymes increases difficulty in analysis and thus a robust analysis technique is required Microbial ethanol fermentation Once the polysaccharides are broken down into monosaccharides and disaccharides, fermentation can take place. The biochemical pathways of microorganisms produce many different end products that are desirable to industries. These include pharmaceutical active ingredients, antibiotics, flavors and enzymes [41]. The aim of the fermentation is to gain accumulation of the end product (in this case ethanol) which is achieved by altering growth conditions and/or available substrates. Fermentation of carbohydrates into ethanol is achieved through ethanol producing microorganisms called ethanologens. The biochemical pathway used to produce ethanol varies depending on the organism and influences the growth requirements and speed of ethanol production. For the fermentation of glucose to ethanol, the yeast Saccharomyces cerevisiae uses the Embden-Meyerhof-Parnas pathway, [42] whereas the bacterium Zymomonas mobilis uses the Entner-Doudoroff pathway [43] Theory of ethanol fermentation For most microorganisms, the initial catabolism of glucose in the presence of oxygen is shown in Equation C 6H 12O 6 + 6O 2 6CO 2 + 6H 2O Equation 1.2-1: Aerobic respiration of glucose [44]. The equation for anaerobic respiration of glucose by an ethanologen, such as the bacterium Zymomonas mobilis, can be summarized by Equation C 6H 12O 6 2CO 2 + 2C 2H 5 Equation 1.2-2: Anaerobic respiration of glucose by an ethanologen [44]. James Oliver CE for bioethanol research 9

34 Every 1 mol of glucose metabolized by the organism produces 2 mol of ethanol, so for every 100 g of glucose metabolized, 51 g of ethanol is accumulated as a by-product giving a 51 % theoretical maximum (g ethanol/g glucose). The theoretical maximum would only be reached if all of the carbon source was utilized for ATP production and if there was no utilization of carbon for cell replication [45]. In a practical fermentation situation, glucose represents not only the energy source to drive the cellular endothermic reactions, but also the carbon source that is converted to the cells organic materials for cellular division and growth. Therefore, the more cellular division occurs, the further from theoretical maximum of conversion the end products fall [46]. For production of ethanol from a microorganism, the fermentation is flooded with an excessive amount of substrate, in this case glucose, that forces the organism to exceed its maximum uptake of oxygen required for the oxidative process and thereby producing an overflow of other metabolites, such as ethanol, from other biochemical pathways that do not require oxygen [1]. Therefore, once the growth rate of an ethanologen is minimal, glucose is channeled to ethanol production and not cell growth. When growth rate is significant, or other metabolic side products are formed, the theoretical maximum of ethanol yield cannot be achieved [44]. Pichia stipitis is an ethanologen that has shown great promise, as it has the ability to ferment hexose sugars as well as the pentose sugars found in hemicellulose (see ) of lignocellulosic materials [47, 48]. Xylose, one of the most predominate pentose sugars in hemicellulose, can be fermented microaerobically into ethanol. The microaerobic fermentation of xylose by Pichia stipitis is summarized by Equation C 5H 10O 5 + O 2 4CO 2 + 3C 2H 5 + H 2O Equation 1.2-3: Microaerobic respiration of xylose by Pichia stipitis [49]. Only 1.5 mol of ethanol is produced per mol of xylose (compared to 2 mol of ethanol per mol of glucose) with the theoretical mass conversion of 0.46 g of ethanol per g of xylose [50], although experimentally this has been as high as 0.48 g of ethanol per g of xylose [51]. Organisms that use microaerobic fermentation, such as Pichia stipitis [52] are theoretically less efficient for the fermentation of xylose to ethanol by the Pentose Phosphate Pathway (PPP) in comparison to anaerobic fermentation of xylose which yields 1.67 mol of ethanol per mol of xylose. This gives a theoretical maximum of 0.51 g of ethanol per g of xylose. This highlights the influence of the type of substrate on the selection of ethanologen needed to ferment all sugars and the resulting yields. James Oliver CE for bioethanol research 10

35 Ethanologens Many ethanol producing microorganisms have been discovered and these have been reviewed by numerous authors [1, 53, 54]. The yeast Saccharomyces cerevisiae is the microorganism of choice for industrial use [55]. The bacterium Zymomonas mobilis has been researched in great depth but is yet to be used industrially [53]. The yeast Pichia stipitis (previously mentioned) has the ability to ferment pentose sugars found in hemicellulose [47, 48]. Clostridium acetobutylicum is another ethanologen that ferments carbohydrates to butanol and acetate as well as ethanol [56] Saccharomyces cerevisiae Currently yeasts are the major industrial ethanol-producing microorganisms [55]. Fermentation is achieved via the Embden-Meyerhof-Parnas pathway. When fermenting biomass, the yeast S. cerevisiae has many distinct advantages over most organisms hence its application in the last few decades. It ferments glucose to ethanol with virtually no other by-products, other than CO 2 and has a high ethanol tolerance (ability to withstand the solvent effects of ethanol) in comparison to other yeasts [44]. Like most other yeasts, S. cerevisiae is host to a dual metabolism for the utilization of glucose. If an adequate supply of oxygen (O 2) is present then it can completely metabolize glucose into CO 2 and H 2O via aerobic respiration (Equation 1.2-1). When submerged in a flask with a limited supply of oxygen, S. cerevisiae accumulates ethanol as the end product as well as CO 2 [57] (Equation 1.2-2). The other distinct advantages are rapid fermentation rates that can be achieved under acidic conditions and its resistance to acetic acid found in some lignocellulosic hydrolysates. It can rapidly metabolize glucose, fructose, sucrose, galactose, mannose and maltose, and more gradually metabolize trehalose, isomaltose, raffinose, maltotriose, ribose and glucuronic acid [1]. However, the most distinctive disadvantage of Saccharomyces is the narrow substrate range in comparison to other yeasts. It cannot directly ferment xylose, which is one of the main sugars in lignocellulosic substrate sources [44]. Other disadvantages include low ethanol tolerance and high biomass production in comparison to Zymomonas mobilis [58]. James Oliver CE for bioethanol research 11

36 Zymomonas mobilis Z. mobilis is a bacterium that achieves fermentation through the Entner-Doudoroff pathway and produces one mol of ATP per mol of glucose in comparison to yeasts which produce two mol of ATP per mol glucose [59]. Z. mobilis has many advantages over yeasts including growth at glucose concentrations above 25 % (w/v) and the ability to produce and tolerate ethanol up to 13 % (v/v) [60]. In addition, ethanol yields close to the theoretical maximum have been reported from glucose [53]. The increased yield of ethanol from glucose is due to less biomass being produced in comparison to yeast [44]. Similar to most yeasts, Zymomonas sp. cannot utilize pentose sugars for ethanol production. Z. mobilis has many desirable characteristics of an ethanol producer including being classified as a GRAS organism (Generally Recognized As Safe), the ability to produce 5-10 % higher ethanol yield per unit of glucose, 2.5 fold higher specific productivity than S. cerevisiae [61], the absence of the Pasteur effect (presence of oxygen does not inhibit the fermentation) on the glucose consumption rate [62] and the ability to channel more glucose to ethanol production than to growth of the organism [61]. The use of Z. mobilis as an industrial ethanologen does have some disadvantages, the most significant being that its substrate range for ethanol fermentation is limited to three sugars: glucose, fructose, and sucrose [63, 64]. Also, during the fermentation of ethanol, a less acidic medium is produced by Z. mobilis than by the yeast S. cerevisiae [65]. The more acidic medium aids in minimizing contamination and the need for sterilization [65]. The expression of the desirable traits is the cause for extensive research into genetic manipulation of Z. mobilis in order to increase the substrate utilization. It has been reported that Z. mobilis can be engineered to utilize pentose sugars by transferring genes from other organisms [64]. The pentose sugars xylose and arabinose are the main components of hemicellulose material which is derived from plant waste Pichia stipitis Pichia stipitis is a strain of yeast that is in the same family as Saccharomyces, however it ferments alcohol from xylose utilizing the PPP followed by the glycolytic pathway. It has been successfully used in the fermentation of a number of hydrolysates from eucalyptus wood [6], red oak wood [66], wheat straw [47] and sugar bagasse [67]. However limitations of Pichia stipitis prevent it from being used as an industrial ethanologen. In the presence of hexoses, the metabolism of xylose is repressed and its ethanol tolerance is much lower than that of Z. mobilis and S. cerevisiae. James Oliver CE for bioethanol research 12

37 Constructed ethanologens Genetic modification opened the door to the possibility of constructing ethanologens with all of the desired traits with minimal drawbacks. The most successful approach to creating these genetically modified organisms (GMOs) was by modifying Z. mobilis and S. cerevisiae to ferment pentose sugars. One of the first successful recombinants of Z. mobilis was produced [68] after previous attempts of insertion of single genes failed to produce stable mutations without selection pressure and low levels of gene expression [53]. Insertion of gene sequences to express enzymes for the PPP and xylose assimilation produced a Z. mobilis capable of utilizing xylose for ethanol production [68]. S. cerevisiae has also been successfully genetically modified for xylose fermentation after numerous failed attempts [69]. This was achieved by inserting genes for the PPP from P. stipitis. Although in the case of yeast, modification can occur by breeding, it was shown that these strains accumulated a large amount of xylitol and low amount of ethanol in comparison to laboratory strains [70]. E. coli has a large substrate range which was also genetically modified for ethanol production by the insertion of genes from Z. mobilis. Although successful it still had the disadvantage, shared by some other bacterial ethanologens, of generating acid by-products[71] Microbial fermentation summary There are a number of different ethanologens that could ferment the lignocellulosic substrates. In this work, Zymomonas mobilis was chosen for simple fermentations due to its higher ethanol yield and specific productivity. Due to the complexity of the fiber substrates Pichia stipitis was also chosen. Previous work on the fermentation of complex mixtures to ethanol with these organisms has been successful [48, 72]. 1.3 Determination of carbohydrates in complex matrices Analysis of carbohydrates is essential for determining the substrate composition and monitoring of the fermentation to ethanol and other end-products. Monitoring of individual carbohydrates during fermentation also provides an understanding of the bioconversion process, e.g. when an ethanologen has switched carbohydrates. Analysis of carbohydrates can either be by chemical analysis or by separation and detection. James Oliver CE for bioethanol research 13

38 1.3.1 Chemical assays Chemical methods have the advantage of being fast and inexpensive methods of carbohydrate analysis Dinitrosalicylic acid (DNS) assay The DNS assay detects reducing sugars by oxidizing the aldehyde carbohydrate to a carboxylic acid with 3,5-dinitrosalicylic acid which in turn is reduced to 3-amino-5-nitrosalicylic acid. Figure 1.3-1: (A) Isomerization of glucose between open chain form and cyclic form (D- Glucopyranose) and (B) reaction of D-Glucose in open form and 3,5-dinitrosalicylic acid to gluconic acid (2,3,4,5,6-pentahydroxyhexanoic acid) and 3-amino-5-nitrosalicylic acid. The carbohydrate concentration is determined by the concentration of 3-amino-5- nitrosalicylic acid which is detected spectrophotometrically at a absorption of 640 nm [73]. The reducing power of different carbohydrates vary [74] and a non-reducing carbohydrate such as sucrose cannot be detected by this method. As the reducing power of each saccharide varies, a different color intensity is observed between both pure solution and mixtures of different carbohydrates [74, 75]. Additionally any unhydrolyzed hemicellulose may also cause a discrepancy [76]. The Fehling method also detects carbohydrates based on the aldehyde functional group [77] Phenol-sulfuric assay The phenol-sulfuric assay was developed to determine the end-group of polysaccharides [78] or to be used in conjunction with paper chromatography to study the composition of polysaccharides [79]. The method uses a reaction of sulfuric acid to dehydrate the carbohydrate to its furfural derivative (furfural for pentoses, hydroxymethylfurfural for hexoses) which forms a James Oliver CE for bioethanol research 14

39 colored complex with phenol [80]. The absorption of the complex varies for each sugar between 460 and 490 nm [79, 81] which creates an error of up to 25 % even if no pentose or hexuronic acids are present [82] Chemical assays summary Although chemical assays are inexpensive and simple, they cannot distinguish between individual types of carbohydrates. As highlighted in , the composition of the lignocellulosic fiber is required to select the appropriate ethanologen and conditions. Thus, these methods were not appropriate for this PhD work. A method that can identify and quantify at least the different hexoses and pentoses, which were previously mentioned (section 1.2.1), was required Separation methods Separation coupled to detection provides more accuracy for carbohydrate analysis than the traditional chemical methods. Carbohydrates can be separated by a variety of methods either in their natural state or after derivatization or complexation. Chromatography is the most common type of separation technique for mixtures. In chromatography, the sample is immersed in the mobile phase which brings it through a stationary phase and analytes are generally separated by their interaction with the stationary phase. The detection of carbohydrates is much more challenging than the chemical methods as carbohydrates do not naturally absorb UV light above 190 nm. A detection that is selective (only detecting analytes of interest) for carbohydrates is desirable. The repeatability (precision, ability to yield a consistent value on one system) and reproducibility (precision, the ability to yield a consistent value between systems or operators [83]) depend on the separation method Gas Chromatography (GC) GC separates analytes by the interaction with a stationary phase, or with a liquid phase on an inert solid support (the latter also called Gas-Liquid Chromatography or GLC) [84]. The analytes are carried by a gaseous mobile phase (or carrier gas). GC requires analytes to be volatile, which is ideal for ethanol quantification. However carbohydrates need to be derivatized to more volatile forms such as their alditol acetate derivatives [60, 85, 86], trifluroacetate derivatives [87], or others [88, 89]. The goal of derivatization is to reduce the boiling point by reducing intermolecular hydrogen bonding. Once derivatized, carbohydrates can be vaporized without degradation. One example, the derivatization of glucose to its alditol derivative has 3 main steps [90]. First, the open form of glucose is reduced to its alditol (sorbitol) by sodium James Oliver CE for bioethanol research 15

40 borohydride. Second, the resulting borate is then removed to avoid interference with the derivatization and third, the alditol is acetylated with acetic anhydride to the alditol acetate derivative. This reduces hydrogen bonding thus decreasing the boiling point and interactions with other components of the sample [90]. After separation the analytes are detected by Flame Ionization Detection (FID) or mass spectrometry (MS). Figure 1.3-2: Derivatization of glucose to its alditol acetate by acetic anhydride adapted from [90] High Performance Liquid Chromatography (HPLC) HPLC is one of the most popular techniques for the analysis of carbohydrates. Unlike GC, HPLC can separate carbohydrates without derivatization (no need to volatilize the sugar). Reverse Phase (RP-HPLC) is one of the most common HPLC methods as it separates analytes based on their hydrophobicity. The stationary phase is non-polar and inert, commonly an octadecyl carbon chain (C18) bound to silica. The mobile phase is a polar organic solvent or buffer with water. RP- HPLC requires derivatization for both the separation and selective detection [91] of carbohydrates, as they are hydrophilic and thus do not interact with the hydrophobic stationary phase. Underivatized carbohydrates can be separated by a number of modes other than RP-HPLC [92], however these modes require a universal detector such as a refractive index (RI) detector that will also detect other compounds such as those from the hydrolysis of lignin or other byproducts. Hydrophilic Interaction Liquid Chromatography (HILIC) separates carbohydrates by their interaction with an amino-abundant stationary phase [93]. A hydrophobic mobile phase, such as acetonitrile, promotes interaction with the stationary phase. Smaller carbohydrates, such as pentoses, have less interaction with the stationary phase and thus elute first, followed by hexoses, disaccharides and oligosaccharides, with the retention time increasing with the degree of polymerization. Samples require dilution in the polar organic mobile phase which can cause precipitation of polysaccharides and proteins in the sample before injection. Sample pretreatment, such as Solid Phase Extraction (SPE), increases recovery and resolution on this column [94]. HILIC and the DNS assay were compared on different lignocellulosic hydrolysates [76]. The results showed a discrepancy between the two methods with the amount of sugars quantified by James Oliver CE for bioethanol research 16

41 HILIC up to 73 % lower than the one quantified with the DNS assay. The authors suggested that oligomers of 2 to 3 units, which were separated and detected by HPLC (and not originally counted), may have caused the over-estimation with the DNS assay. The difference in reducing power of different sugars was not considered. Calcium and lead form resins can separate carbohydrates by ligand exchange with a contribution of size exclusion [95-97]. The saccharide forms a complex with the metal in the stationary phase slowing down its migration. The separation can be improved by altering the metal, however this also influences the pore size, the size and strength of the metal-saccharide complex as well as the mutarotation of the saccharide. The benefit of these columns is that water is the mobile phase. The sample preparation however, requires some clean up to remove compounds (such as salts produced by the neutralization before enzymatic hydrolysis; see ) that can interact and alter the stationary phase resulting in the loss of separation. Samples of non-starch polysaccharides were analyzed by GC after their derivatization to alditol acetates as well as HPLC with a lead based ligand exchange column [98]. Although the determination of individual sugars was significantly different between techniques, with arabinose being higher on HPLC, the determination of total sugars was not. Hydrogen form resin can also separate carbohydrates as well as organic acids and alcohols [99] without any sample pre-treatment. The mobile phase of sulfuric acid ensures the stationary phase is replenished during analysis. The drawback of this column is that, contrary to separation on the lead form resins, the common fiber sugars, galactose and xylose, are not resolved [100]. There have been studies on sample recovery with this column, with one study claiming recovery as low as 80.3 %, 85.7 % and 90.1 % for lactose, galactose and glucose respectively [101] High Performance Anion Exchange Chromatography (HPAEC) HPAEC is a mode of ion chromatography that separates negatively charged analytes based on their affinity with the positively charged stationary phase. Carbohydrates are negatively charged by a basic mobile phase such as a solution of sodium hydroxide and thus compete with hydroxide for the positively charged binding sites on the stationary phase (Figure 1.3-3). The carbohydrate s affinity for the stationary phase increases with the charge which is determined by the pk a of the carbohydrate: the lower the pk a the longer the retention time. Weakly charged carbohydrates (high pk a) such as sugar alcohols, elute first while the most acidic carbohydrates (low pk a) such as mannose elute later. Between separations, the column is cleared of all residual James Oliver CE for bioethanol research 17

42 compounds from the matrix by increasing the hydroxide concentration. The excess hydroxide increases competition with the residual compounds for the cationic sites of the stationary phase. Residual compounds may be peptides, oligosaccharides and polysaccharides, which may are present in lignocellulosic fiber samples. Figure 1.3-3: Movement of sodium hydroxide and glucose along the pellicular anion exchange resin (adapted from [102, 103]). The detection commonly used for the determination of carbohydrates with HPAEC is Pulsed Amperometric Detection (PAD). It employs an oxidation reaction between an electrode, usually of gold (Au), and the oxidizing groups of the carbohydrate in alkaline media [104]. PAD is considered to be superior to RI detection as it has an increased sensitivity and selectivity. Sensitivity is increased as only electron-donor functional groups at the set voltage are detected (carbohydrates have numerous electron-donor functional groups) [105]. Detection selectivity is increased as neutral and cationic species are not detected [105]. A drawback for complex samples is that amino acids, peptides and organic acids all give a positive reading, therefore the detection of carbohydrates with PAD is not selective of amino acids, peptides and organic acids also present in lignocellulosic fiber samples [106]. HPAEC, after SPE, and GC have been compared for the analysis of acid hydrolyzed lignocellulose from wood and the methods were considered to be in excellent agreement [107]. James Oliver CE for bioethanol research 18

43 Capillary Electrophoresis (CE) of carbohydrates Theory of CE Electrophoresis is a method of separating charged analytes based on their movement though a solution under the influence of an electric field [108, 109]. The analyte can be passed through a gel immersed in an electrolyte (gel electrophoresis) or passed through a free solution in a tube. Capillary Electrophoresis (CE) is carried out in a capillary (typically with a µm internal diameter) with either gel (capillary gel electrophoresis) or free solution (free solution capillary electrophoresis/capillary zone electrophoresis). Working with a smaller volume increases the efficacy of cooling thus limiting Joule heating (or the Joule effect) in CE. The solution moves with the flow of ions (explained in the next paragraph) and analytes are separated and identified based on the difference of migration though the solution. Additionally the separation can occur in the presence of micelles (Micellar Electrokinetic Chromatography/MEKC). Typically, fused-silica capillaries are used in free solution capillary electrophoresis. The surface of the fused silica capillary is typically negatively charged (conditioned) by flushing with a strong alkaline solution such as 1 M sodium hydroxide. This also aids in the cleaning of the capillary. The capillary is filled with a BackGround Electrolyte (BGE). Due to the negative charge of the capillary surface, the cations adsorb along its surface. For example, if the BGE was Na then the hydrated sodium ions would adsorb along the capillary surface. When the electric field is applied, the cations migrate along the capillary wall towards the cathode. The flow of water hydrating the ions creates an electro-osmotic flow (EOF) (also known as the electro-osmotic velocity), marked by any uncharged molecule. The velocity of the analyte (know as it electrophoretic velocity) is affected by the analytes charge and the strength of that charge. The analyte migrates faster than the EOF if the charge is the opposite to the charge of the capillary surface and slower than the EOF if the charge is the same. The latter is named a counter-eof separation. The sum of the EOF and the analytes electrophoretic velocity give its apparent velocity. James Oliver CE for bioethanol research 19

44 Figure 1.3-4: Counter-EOF separation in free solution capillary electrophoresis. In Figure 1.3-4, the analyte (glucose) has an electrophoretic velocity towards the anode, opposite to the EOF, giving a counter-eof separation. The difference between the EOF and the electrophoretic velocity of glucose gives an apparent velocity slower than the EOF (Equation 1.3-1). v ep = v app v eof Equation 1.3-1: Relationship between apparent velocity (v app), electroosmotic velocity (v eof) and electrophoretic velocity (v ep). The analytes apparent velocity and the velocity of the EOF are calculated by Equation v = LL d tt Equation 1.3-2: Calculation of the velocity of the EOF (v eof) and an analytes apparent velocity (v app), where v stands for either v app or v eof. Where L d is the length to the detection window (or effective length) and t is the time the analyte or EOF marker is detected. The electrophoretic mobility, the fundamental parameter of capillary electrophoresis, is the proportionality constant between electric field and velocity (Equation 1.3-3). µ ep m2 V s = v ep (m/s) EE (V/m) Equation 1.3-3: Relationship between an analytes electrophoretic mobility µ ep, its ionic velocity v and the electric field E. James Oliver CE for bioethanol research 20

45 The field strength is proportional to the length of the capillary and the voltage (Equation 1.3-4), if either is altered, the field strength alters. EE = VV LL t Equation 1.3-4: Calculation of the electric field strength where L t is the total length of the capillary and V is the voltage. In Equation 1.3-3, substituting the value for E by Equation and the value for v ep by Equation with the values for v app and v eof by Equation 1.3-2, the following is obtained [110]: µ ep = LL d LL t VV 1 tt m 1 tt eo Equation 1.3-5: Formula used to calculate electrophoretic mobility µ ep of an analyte. In this equation, t m is the migration time of the analyte and t eo is the migration time of the EOF marker. The electrophoretic mobility is proportional to the charge-to-friction ratio; the friction is assumed to be hydrodynamic (Equation 1.3-6) in the case of small molecules and therefore the separation is based on charge-to-size ratio. Thus electrophoretic mobility is governed by Stokes law where q is the effective charge, r is the ionic radius and η represents the viscosity of the solution [111]. mm ep = qq 6πηηηη Equation 1.3-6: Stokes law governing electrophoretic mobility Application of CE to carbohydrate analysis The analyte must be charged for separation to take place. The simplest way to charge a carbohydrate is to use a BGE with a ph above the pk a of the carbohydrates. The pk a of the most common carbohydrates and sugar alcohols is 12 to 12.5 and 13 to 14 respectively [ ] (Table 1.3-1). Thus the most commonly used BGE have a ph of [ ]. The least charged carbohydrates (sugar alcohols) migrate just after the EOF due to the weaker charge, followed by disaccharides, then monosaccharides. Hexoses migrate faster than pentoses [113]. Carboxylates can also be separated from samples in this high ph BGE, however due to the relatively low pk a compared to the carbohydrates, their migration is much slower [115]. CE has James Oliver CE for bioethanol research 21

46 also shown to be useful for the separation of polysaccharides such as gellan gums [118], chitosan [119] and pectin [28]. Table 1.3-1: The structure and pk a of some monosaccharides, disaccharides and sugar alcohols. Molecule Structure pk a (25 C) Galactose HO O [120] Molecule Structure pk a Sucrose HO O O O (25 C) HO [120] Glucose HO O [120] Xylitol HO 13.7 [112] Rhamnose CH 3 O NA Arabitol HO NA Mannose HO Lactose HO O [120] HO O O O [120] Fructose O [120] Xylose O [120] Arabinose O [120] James Oliver CE for bioethanol research 22

47 Separation of carbohydrates can also be achieved via complexation with a metal compound such as borate leading to separation and quantification with good repeatability and recovery [121]. The sugar-borate complex has a much lower pk a and can be charged in a BGE with a ph of 9.2 [122, 123]. The electrophoretic mobility of each complex varies based on the isomer and the position of the vicinal hydroxyl groups. Unlike the separation of native carbohydrates, the complex has an UV absorption around 195 nm [122]. The Limit of Detection (LOD) for carbohydrate-borate complexes, to our knowledge, has not been published, however it is considered to suffer from poor sensitivity [112]. LOD is improved by derivatization of the carbohydrates before separation of their borate complexes (Table 1.3-2). MEKC is a modification of the classical CE method, where the analytes are separated by their interaction with micelles (pseudo-stationary phase). Micelles migrate much slower than the EOF. Analytes that do not interact with the micelles migrate with the EOF, followed by the analytes that have some interaction. Analytes that strongly interact and any analytes that completely interact with the micelles migrate at the same time as the micelles. As the separation is based on interaction with micelles instead of size-to-charge ratio, the ph of the buffer is close to neutral. MEKC of carbohydrates after derivatization can be achieved in less than 6 min [124]. The drawback for MEKC is that it requires the use of surfactants such as sodium dodecyl sulfate (SDS) which interact with proteins and lipids present in complex matrices. The detection of underivatized or complexed carbohydrates can be achieved by a number of different methods. Indirect UV detection of carbohydrates (without derivatization or complexation) is achieved by the addition of a UV absorbing molecule to the background, such as sorbate (sorbic acid) [115] or 2,6-pyridinedicarboxylic acid [114]. The UV absorbing molecule takes on the role of the co-ion in the BGE and is displaced in the presence of the analyte [125] (Figure 1.3-5A). The displacement is detected as a negative peak (1.3-4B). Indirect detection is considered to be one of the least sensitive detection methods for carbohydrates (Table 1.3-2). James Oliver CE for bioethanol research 23

48 Figure 1.3-5: The theory of indirect detection represented in the capillary (A) where lowering of the concentration of a UV-absorbing co-ion (Black circle) by the analyte (Purple circle) leads to a negative peak (B). PAD can be hyphenated to CE, [126] although this is not commercially available. As mentioned in , PAD is considered to be sensitive and selective. More recently, contactless conductivity detection (C 4 D or CCD) was also developed for carbohydrate analysis. The detector measures the conductivity of the BGE with and without the presence of the analyte. A BGE with an ion that has a large difference in charge to the analyte is desired to give the best sensitivity [127]. Although C 4 D has one of the lowest published LOD values in the case of carbohydrates (Table 1.3-2), the use of the C 4 D detector limits the concentration of the BGE [128]. Only a maximum Na concentration of 100 mm can be used, when much higher concentrations are considered to be optimal for separation [113, 116]. Recently, direct UV absorption of carbohydrates at 270 nm has been reported [113]. This novel detection method, although not well understood, requires no derivatization or complexation. The method is not as sensitive as the derivatization methods or than PAD or C 4 D, however detection is achieved with a commercially available diode array detector (DAD). James Oliver CE for bioethanol research 24

49 Table 1.3-2: Comparison of various detection methods for carbohydrates in CE. Separation Method Derivatization Detection LOD of glucose Reference (mg L -1 ) MEKC 4-aminobenzonitrile UV-284 nm [124] Borate complexation 1-phenyl-3-methyl-5- UV-245 nm 0.14 [121] pyrazolone [129] (Mannose)* Borate complexation None UV-200 nm NA** [122, 123] High ph None Contactless conductivity [128] [127] High ph None Indirect 13 [114] High ph None PAD 0.36 [130] High ph Sodium None Direct UV 3.6 [131] phosphate buffer High ph Sodium None Direct UV 7.2 [112] hydroxide * LOD of glucose not given **not stated to the best of our knowledge but suffers from poor sensitivity [112]. The direct UV detection was originally theorized to be the result of enediolate formation [113] (Figure 1.3-6). It was later noted that such as a reaction scheme would not be possible with the non-reducing carbohydrate sucrose and that a photo-oxidation reaction that takes place in the detection window [112] (Figure 1.3-7) was more likely. Figure 1.3-6: Possible mechanism for direct UV detection of carbohydrates in CE by enediolate formation (adapted from [113]). James Oliver CE for bioethanol research 25

50 Figure 1.3-7: Possible mechanism for direct UV detection of carbohydrates in CE by UV initiated photo-oxidation (adapted from [112]). CE with direct UV detection has been applied to the analysis of wood hydrolysates [132] as well as forensic, pharmaceutical and beverage samples [133]. CE with direct UV detection was compared to HPAEC for the analysis of wood hydrolysates [132]. Although the values for different hydrolysates were in good agreement between the two methods, the precision of quantification was much lower with CE. Similar results were found in a comparison between CE and ligand exchange chromatography on similar samples [131]. It is worth noting that neither CE methods included an internal standard. The potential of direct UV detection as a simple alternative for determination of carbohydrates at non-trace concentrations is yet to be fully realized Determination of carbohydrates in complex matrices summary Methods based on separation are more suited to analysis of carbohydrates in complex samples than chemical methods. Determination of individual carbohydrates in a mixture provides more detail of lignocellulose carbohydrate composition than chemical methods. This detail is required to determine the optimum ethanologen (see ). From the separation methods reviewed, free solution CE has the ability to separate all the carbohydrates of interest with a simple detection technique. CE with direct UV detection has the advantage of neither requiring derivatization unlike GC and RP-HPLC nor sample clean-up or filtration unlike HPAEC and HPLC- RID. Thus it has potential to efficiently analyze lignocellulosic fibers and their fermentation. The drawback to this method was the lack of understanding of the direct UV detection of carbohydrates. For continued development and application of this detection, an adequate level of understanding must be reached. James Oliver CE for bioethanol research 26

51 1.4 Determination of ethanol Determination of ethanol as well as carbohydrates by the same method would be advantageous. Ethanol can be determined by a number of the separation methods already listed above. The typical method for the determination of volatile compounds such as ethanol is GC-FID [134]. However the analysis of carbohydrates by GC requires derivatization (see ). HPLC on a hydrogen form resin can separate carbohydrates without derivatization and alcohols [99] hence it is a popular choice among fermentation scientists. However this column does not resolve galactose and xylose which are both present in lignocellulosic fiber. HPAEC can determine ethanol and carbohydrates in standards with a Microbead TM pellicular resin [135, 136] however other compounds present in the matrix of the fermentation sample co-elute with the ethanol. Determination of ethanol is possible with some modes of CE. Ethanol as well as other solvents have been determined by MEKC with indirect detection [137] however it requires the use of the surfactant SDS that may interact with proteins and lipids that are present in lignocellulosic fermentations. CE with PAD [126] or indirect UV detection [138] can also detect ethanol however no quantification was carried out in this study. No single method can determine all the fiber sugars of interest as well as ethanol. This is an area that was explored further in this PhD. 1.5 PhD project aim and objectives Based on the literature review, the field of bioethanol research lacked simple and robust analytical methods for carbohydrate and ethanol analysis in lignocellulosic fiber and fermentation samples. A method was required that was able to separate the various saccharides found in lignocellulose as well as robust enough to not be affected by the various by-products of the lignocellulosic hydrolysis and fermentation media. There were two aims of this PhD work, each with their own research questions: 1) To determine the potential of free solution capillary electrophoresis with direct UV detection to analyze samples with complex matrices (lignocellulosic hydrolysates and bioethanol fermentation products) o Is CE with direct UV detection an adequate method for fiber analysis in comparison to HPLC methods? This was investigated by comparing the separation (by resolution) of common fiber sugars with CE to popular HPLC modes and by comparing the quantification of an acid treated fiber sample between CE and HPLC with a hydrogen form resin. James Oliver CE for bioethanol research 27

52 o Can CE be used for monitoring of lignocellulosic fermentations? This was investigated by analyzing the influence of the BGE on the separation (by electrophoretic mobility, resolution and time of separation) and by comparing the quantification of carbohydrates in fermentation samples to HPAEC and HPLC. 2) To improve the understanding of the direct UV detection. o o o Is the underlying cause of the direct UV detection enediolate formation or a photo-oxidation reaction? This was investigated by studying the detection with novel 1 H NMR and CE experiments. What is the reaction pathway that makes the photo-oxidation detection possible? This was investigated by studying the mechanism by quantum mechanics calculations and the end products by novel 13 C NMR experiments. Can the photo-oxidation detection be used to quantify ethanol in fermentation samples? This was investigated by novel CE experiments with pressure mobilization and 13 C NMR experiments with samples of vodka and fermentation broth. The long term goal was to provide the field with a method that is simple to implement, with sufficient sensitivity (not trace analysis) and robust with a range of complex lignocellulosic samples after hydrolysis and during fermentation. This method was sought to facilitate future research into the use of non-food based plants for the production of bioethanol. James Oliver CE for bioethanol research 28

53 2. Publication Simple and robust determination of monosaccharides in plant fibers in complex mixtures by capillary electrophoresis and high performance liquid chromatography Contribution to PhD work, field, and candidates personal and professional development Advantages and limitations of CE with direct UV detection and HPLC for carbohydrate determination in lignocellulosic plant fiber This work initially began with an investigation of the carbohydrate content of non-food plants, adaptable to Australian marginal lands, for bioethanol production. These included Atriplex nummularia, Aloe vera, Agave attenuate and Opuntia ficus-indica. The plants were chosen due to their low lignin content and ability to grow in harsh environments. The lignocellulosic fiber of these plants was acid hydrolyzed before carbohydrate determination. The acid treatment was used as it was simple to carry out on a small scale. The presence of by-products formed by the acid treatment increases difficulty in analysis and thus a robust analysis technique is required. Chemical assays are fast and inexpensive for carbohydrate analysis. The phenol-sulfuric assay was attempted for the analysis of carbohydrates (not published). The assay could detect but not accurately quantify (Section ) the carbohydrates. Following the research trends, HPLC was attempted. Two key issues arose after utilizing HPLC to analyze complex hydrolysis samples: inadequate resolution and/or robustness. Alternative methods were reviewed in the literature (as discussed in 1.3) and CE with direct UV detection seemed a viable analysis technique. CE has many benefits over HPLC for the analysis of carbohydrates in plant fiber including being more robust, and based on previous work [132], resolving all main fiber monosaccharides. The 1 st publication compared the separation of underivatized carbohydrates in CE to the common HPLC modes. When the CE separation was found to be superior, a quantitative study was undertaken. CE gave consistently higher quantification values than HPLC leading to an investigation of the mechanism of detection. The lower quantification values of individual sugars may indicate a recovery or accuracy issue on the hydrogen form HPLC column. This has only once, to the best of our knowledge, been noted in the literature [101]. While it is established that carbohydrates do not absorb UV above 200 nm, carbohydrates were unexpectedly observed by direct UV detection at 270 nm. The main limitation of the CE separation method in this PhD project was the minimal understanding of the detection technique. At the time of this publication there were two competing theories by Rovio et al. (2007) [113] and Sarazin et al. (2011) [112] (as discussed in James Oliver CE for bioethanol research 29

54 ) explaining the mechanism of the detection. To determine which theory was correct, 1 H NMR (Nuclear Magnetic Resonance) and CE experiments were designed and carried out. 1 H NMR was used to identify the changes in chemical structures in a solution of glucose in 130 mm Na D 2O Theory of NMR spectroscopy NMR spectroscopy is a type of absorption spectroscopy where an atom s nucleus absorbs electromagnetic radiation in the radio frequency (rf) range under appropriate conditions in a magnetic field [139]. NMR can be used for either investigating molecular dynamics or for structure elucidation. It is used in this work for the latter. For 1 H NMR (proton NMR) spectroscopy signals are observed at chemical shifts (δ) between 0 and 10 ppm. The signal frequencies are acquired in Hz and then the chemical shifts are calculated as their relative difference to the Larmor frequency of the investigated nucleus in the main magnetic field. The values for the chemical shifts are independent from the magnetic field. The chemical shift relates to the hydrogen position in the molecule relative to carbon, oxygen, hydrogen and other atoms (Figure 2.1-1). The chemical shift is also influenced by the solvent, hence in this study chemical shifts of standard compounds were experimentally measured in the presence of Na. The intensity of the observed peak is proportional to the concentration of the hydrogen of the corresponding functional group in the sample, provided the delay between scans is sufficient to ensure complete relaxation (complete return to the equilibrium state). Several scans are accumulated in order to average out noise and acquire enough signal with a sufficient signal-to-noise ratio. Figure 2.1-1: Ranges of 1 H chemical shifts for different functional groups, adapted from [139]. James Oliver CE for bioethanol research 30

55 13 C NMR spectroscopy is similar to 1 H NMR spectroscopy except the isotope 13 C is measured [140]. Since the 13 C isotope represents only 1.1 % of all carbons in natural abundance, the sensitivity of 13 C NMR spectroscopy is limited. By using fully labeled 13 C glucose (as done in the 2 nd and 3 rd publication) sensitivity can be increased by a factor of 91. Signals are observed at chemical shifts (δ) between 0 and 200 ppm in 13 C NMR spectroscopy (Figure 2.1-2) resulting in a higher resolution than in 1 H NMR spectroscopy. The higher resolution allows for easier structure elucidation. For example, chemical shifts of carboxylates are in the ppm range whereas chemical shifts of aldehydes are in the ppm range (Figure 2.1-1). As with 1 H NMR spectroscopy, chemical shift relates to the carbon s position with respect to other atoms in the molecule and is affected by the solvent. The intensity of the observed signal is proportional to the concentration of the corresponding functional groups, provided the delay between scans is sufficient to ensure complete relaxation. A sequence of different electromagnetic radiation pulses can manipulate the magnetization to change the signal output. In this study a 135 DEPT (Distortionless Enhancement by Polarization Transfer) sequence was used where primary and tertiary carbons have positive signals, secondary carbons have negative signals and quaternary carbons are not observed [140]. Electron Spin Resonance (ESR) spectroscopy is a technique very similar to NMR spectroscopy however unpaired electrons are observed, rather than nuclei [141]. The main limitation being that only radicals can be observed by ESR. Figure 2.1-2: Ranges of 13 C chemical shifts for different functional groups, adapted from [140]. James Oliver CE for bioethanol research 31

56 2.1.3 Investigation of the direct UV detection 1 H NMR was used to investigate the chemical structure of end products from glucose in 130 mm Na after UV irradiation due to NMR s sensitivity and resolution. Consistent with Sarazin et al. [112], an in-situ photo-oxidation reaction was the reason behind the UV absorption of carbohydrates observed at 270 nm. This led to an investigation of the reaction pathway causing this detection. After an in-depth literature search, the pathway could be linked to past ESR spectroscopy experiments performed by Gilbert et al. [142, 143] on a radical initiated oxidation pathway. The studies were performed in similar conditions (ph >9.0) as in the CE. The 2 nd publication looked at the potential UV absorbing intermediates by comparing each carbohydrate s experimental wavelength and absorption intensity to their calculated ones. It strongly indicated a link between the absorption seen in CE and the free radical pathway suggested by Gilbert et al. [143]. Due to the success of the 1 H NMR spectroscopy experiments in analyzing end products, NMR spectroscopy was used in the 2 nd publication. The end products of the reaction pathway were investigated by 13 C NMR spectroscopy. A sample was generated by continuously injecting a 13 C glucose in D 2O with Na for 95 hours. It was discovered that the end products contain carboxylates contrary to the theory of Sarazin et al. [112] which predicted aldehydes. The successful use of the 13 C NMR spectroscopy experiments resulted in its repeated use in the 3 rd publication. Based on this new understanding, sensitivity of the detection was improved by the use of radical photo-initiators. The 2 research questions of the 1 st publication were: Is CE with direct UV detection an adequate method for fiber analysis in comparison to HPLC methods? and Is the underlying cause of the direct UV detection enediolate formation or a photo-oxidation reaction? Contribution to my personal development This publication contributed to my personal development in a number of ways. Aside from being my first publication in a peer reviewed journal, this work gave me the opportunity to give an oral presentation at an international conference, the 33 rd Australasian Polymer Symposium (33APS, see Conference and seminar presentations ). Also I was provided training on the important analytical techniques of HPLC, CE and 1 H NMR (solution state). Professional development was achieved through my collaboration with Professor Emily Hilder from the Australian Center for Research On Separation Science (ACROSS) at the University of Tasmania, Australia (UTas). A part of this collaboration included an invited seminar at ACROSS (see James Oliver CE for bioethanol research 32

57 Conference and seminar presentations ) chaired by Professor Paul Haddad, fellow of both the Australian Academy of Science and the Academy of Technological Sciences and Engineering. This publication had 3 co-authors. The last author, Dr Patrice Castignolles provided the direction of the publication as well as training and understanding of CE. He also assisted in forming the collaboration with UTas via the ACROSS network. Dr Marianne Gaborieau provided assistance with performing 1 H NMR as well as discussion to understand the results of the 1 H NMR experiments. Prof. Emily Hilder provided the idea and equipment for irradiating a sample of glucose external to the CE and analyzing by 1 H NMR. In addition Prof. Emily Hilder also organized the invited seminar at ACROSS in UTas. I performed all background research, experiments, data acquisition and analysis as well as writing the first draft of the publication. Initially I had the idea to use HPLC to characterize the various fiber samples due to its use popularity in the field. However it proved to be inadequate for the complex fiber sample I was working with. After a literature search and a discussion of different possibilities, I proposed CE with direct UV detection as potentially the most robust separation with a simple yet selective detection. I proposed comparing the separations HPLC mode and CE as well as comparing the quantification. I also developed the experiments in this publication that determined that enediolate formation was not the cause of the detection mechanism and that the electric field played a role in enhancing the detection. I selected the plant Opuntia ficus-indica as it flourishes in Australian semi-arid climates. James Oliver CE for bioethanol research 33

58 2.2 Publication Simple and robust determination of monosaccharides in plant fibers in complex mixtures by capillary electrophoresis and high performance liquid chromatography James D. Oliver a, Marianne Gaborieau b, Emily F. Hilder c, Patrice Castignolles a, * 1 University of Western Sydney (UWS), Australian Centre for Research on Separation Science (ACROSS), School of Science and Health, Locked Bag 1797, Penrith NSW 2751, Australia, james.oliver@uws.edu.au, p.castignolles@uws.edu.au 2 University of Western Sydney (UWS), School of Science and Health, Nanoscale Organisation and Dynamics group, Locked Bag 1797, Penrith NSW 2751, Australia, m.gaborieau@uws.edu.au 3 Australian Centre for Research on Separation Science (ACROSS), School of Chemistry, University of Tasmania, Hobart TAS 7001, Australia, emily.hilder@utas.edu.au * Corresponding author: p.castignolles@uws.edu.au Abstract: Carbohydrates partially liberated by acid hydrolysis of plant fiber can be separated by Hydrophilic Interaction Liquid Chromatography (HILIC), ligand-exchange liquid chromatography or other forms of LC with ion-exchange columns. However, the robust hydrogen-exchange columns show co-elution of galactose, xylose and mannose. Free solution capillary electrophoresis (CE) can be used without derivatization at ph 12.6 and was found to provide a higher resolution of galactose and xylose than common LC with no sample pre-treatment required, other than dilution, within 26 min. CE was able to provide resolution higher than 0.79 for all separated carbohydrates, and the RSDs of determined concentrations lower than 10% for concentrations above 1.3 g L -1. A quantitative comparison between CE and HPLC revealed that up to 22% more carbohydrates are quantified with CE. Direct UV detection in CE of mono- and disaccharides is unexpectedly possible at 270 nm. NMR analysis shows that alkaline degradation is too slow to explain this detection. This CE detection sensitivity is increased by the electric field and our CE and NMR analyses are consistent with a photo-oxidation process. Keywords: Monosaccharide, Plant fiber, Capillary electrophoresis, Ion-exchange chromatography, Photo-oxidation James Oliver CE for bioethanol research 34

59 1. Introduction Carbohydrates make up most of the living world around us. Their identification and quantification is generally sought after in many fields such as food and beverage analysis, plant analysis, fermentation studies and metabolism studies. Different separation techniques for mono- and disaccharides have been previously compared, mainly on model samples or diluted samples such as fruit juices or wine. However there is a need for a separation technique that can characterize complex samples with little sample preparation. These complex samples have a significant variation of carbohydrate type and concentration as well as significant levels of acids, bases, salts, amino acids and other cell debris. Dilute acid treatment of fiber is routinely used in biotechnology to break down hemicellulose fiber and exposes cellulose to enzymatic breakdown [1-7]. The characterization of these important samples is the focus of this manuscript. Preparation of these samples for analysis, i.e. matrix removal, is tedious and lowers the accuracy. Carbohydrates can be separated by high performance liquid chromatography (HPLC) using a number of modes [8]. Ion exchange resins in the calcium or lead form were first shown to separate carbohydrates without clear mention of the separation mechanism [9,10] which was later proven to be ligand exchange with a contribution of size exclusion [11]. Separation with ligand-exchange on ion exchange resins containing cations such as lead or calcium provide the same order of separation; however, in the case of lead, an improved resolution is observed for the common fiber sugars xylose and galactose. Separation on a cation-exchange resin in the hydrogen form with a sulfuric acid mobile phase elutes disaccharides first, followed by hexoses, pentoses then alcohols. The mechanism of separation for carbohydrates on this column has been shown by several groups but has not been definitively proven [12]. Separation with amino columns, as hydrophilic interaction liquid chromatography (HILIC), utilizes hydrophilic interactions between the sample and the amino-rich resin with pentoses eluting first, followed by hexoses, disaccharides then oligosaccharides in order of increasing oligomer units. HILIC is better adapted to small oligomers than monosaccharides [13]. HPLC can also be used in reverse phase mode (RP-HPLC) after multistep derivatization [14]. Each method has its own issues relating to co-elution, tedious sample preparation, salt intolerance or acid intolerance leading to incomplete separation and short column life [15]. Gas chromatography (GC) is also commonly used; however, it requires multistep derivatization of the carbohydrates [16-18]. RP-HPLC and GC were recently compared for plant fiber analysis [19], and although the determination of a number of monosaccharides was accurate within 10 %, rhamnose and galactose were not resolved via HPLC. James Oliver CE for bioethanol research 35

60 CE is used and recognized in both research and industry as a viable technique for the separation of carbohydrates [20-22]. GC and CE were recently compared for the separation of hydrolyzed wood samples [23]. Although these methods required derivatization, both carbohydrates and uronic acids could be determined in the same run with CE. HILIC and CE were also compared for fruit juice samples for the detection of sucrose, glucose and fructose [24]. Both methods were not significantly different and showed good repeatability. Pre-column derivatization is avoided in this work to keep the method simple and robust and ensure no sidereaction occurs with proteins and lipids of complex samples (we follow as definition of a robust method a method that can be applied to analytes in a wide variety of matrices [25]). GC of carbohydrates is not possible without derivatization and this may be why it is not currently a common method to analyze plant fiber degradation products [16-18]. Without derivatization or complex formation CE cannot separate carbohydrates below ph 9, as expected. Monosaccharides can be charged, separated and detected in borate buffer since they complex the borate [26,27]. The detection suffers however from a poor sensitivity of the borate complex. Separation can also be achieved at ph 7.5 with micellar electrokinetic chromatography (MEKC) [27]; however, the method requires the addition of sodium dodecyl sulfate (SDS) surfactant that also interacts with proteins and lipids present in complex mixtures. Separation of underivatized sugars in CE is possible using an electrolyte with a ph above the pk a of the sugars, which is generally above ph 12. On this basis earlier methods demonstrated separations in strongly alkaline electrolytes with indirect or pulsed amperometric detection [28-31]. CE with indirect UV detection was shown to be a rapid, repeatable and sensitive method for carbohydrates, and has also shown quantitative recovery of carbohydrates in similar samples [30,32]. However, the limitations and possible artifacts of indirect detection or pre-derivatization for complex samples containing complex carbohydrate mixtures in conjunction with other compounds have never been investigated. More recently CE has been shown to separate up to 12 different mono-, disaccharides and sugar alcohols in direct detection without derivatization using a high ph buffer of sodium hydroxide and sodium phosphate. The direct detection was found to be unexpectedly possible through UV absorption at 270 nm by Rovio et al. [33] and the method was applied to plant fiber samples with a maximum concentration of 400 mg L -1 for single sugars [34]. An adapted version of the method has been applied to forensic, pharmaceutical and beverage samples) [35,36]. While maximizing the detection sensitivity is an objective for some applications, plant degradation leads to complex mixtures but with relatively large quantities of monosaccharides, thus detection does not require the highest sensitivity. Rather for this application we have focused on the development and critical comparison of approaches to achieve the most robust and simple separation of James Oliver CE for bioethanol research 36

61 carbohydrate mixtures from complex plant samples. The specific objectives were to adapt the separation of Rovio et al. to achieve high resolution separations at higher concentrations and to compare the optimized CE method to existing HPLC methods, specifically in terms of quantification. 2. Materials and methods 2.1. Materials Water was of MilliQ quality (Millipore, Bedford, MA, USA). Fused-silica capillaries (50 µm i.d., 360 µm o.d.) were obtained from Polymicro (Phoenix, AZ, USA). Xylose 99% was obtained from Alfa Asear (Ward Hill, MA, USA). Dimethyl sulfoxide (DMSO), D+glucose 99.5%, D+galactose 99%, L-rhamnose monohydrate 99%, L-arabinose 99% and D+cellobiose 99% and acetonitrile (ACN) were obtained from Sigma-Aldrich (Castle Hill, NSW, Australia). Sodium hydroxide pellets (Na), disodium hydrogen phosphate powder (Na 2HPO 4), lactose, glacial acetic acid and sulfuric acid were obtained from Univar (Ingleburn, NSW, Australia) Plant sample and standard preparation Three cladodes (flattened paddle shaped stems) of the plant of Opuntia fiscus-indicia were obtained from the wild in Richmond, NSW, Australia in November They were immediately homogenized with water and then centrifuged at 3000 rpm for 30 min to isolate the fiber. The insoluble fraction was then dried to a constant weight at 75 C and milled to fit through a 1 mm sieve and stored in an airtight container until sample preparation. A 5 ml solution of 0 to 4 % (v/v) sulfuric acid was loaded with 5 % (w/v) of dried fiber in a sealed glass tube and heated to 134 C for 1 h as done in [1]. The sample was then filtered through a nylon 0.45 µm filter before analysis. The fiber standard was prepared by measuring 200 mg of each sugar (glucose, galactose, rhamnose, arabinose, mannose, xylose and cellobiose) in a 200 ml volumetric flask then filling to the mark with MilliQ water High performance liquid chromatography All separations were performed on a Shimadzu 10A Series System with a RID-10A refractive index detector and SPD-M10Avp PDA detector (Shimadzu Scientific Instruments, Rydalmere, NSW, Australia). The injector was equipped with a 20 µl injection loop and rinsed with 200 µl of samples before injection. The different column sets were purchased from Bio-Rad (HPX-87H, HPX-87P and HPX-87C) (Hercules, California, USA) and Supelco (LC-NH 2) (Sigma-Aldrich James Oliver CE for bioethanol research 37

62 Castle Hill, NSW, Australia). Experimental conditions are given in Table Each mobile phase was vacuum filtered through a 0.45 µm filter before use. Results were integrated via VP class 5.0 software from Shimadzu. Table 2.2-1: Experimental conditions used in HPLC for the different columns. Column Resin form Mobile phase Temperature Flow rate Column RID HPX-87P Lead Water 80 C 60 C 0.6 ml min -1 HPX-87C Calcium Water 80 C 60 C 0.6 ml min -1 HPX-87H Hydrogen M H 2SO 4 60 C 60 C 0.6 ml min -1 LC-NH 2 Amino 75:25 ACN:water 25 C 40 C 1.0 ml min Capillary electrophoresis Separations were performed on Agilent 7100 or 3D Capillary Electrophoresis systems (Agilent Technologies, Santa Clara, CA, USA) with a Diode Array Detector monitoring at 200 nm and 270 nm with a 10 nm bandwidth. The buffer preparation and separation was carried out as described by Rovio et al. [33]. Typically a capillary with a 60 cm total length (51.5 cm effective length), was filled with 130 mmol Na and 36 mmol of Na 2HPO 4 and a voltage of 16 kv ramped up over 2 min. The capillary was pre-treated prior to use by flushing with 1 M Na, 0.1 M Na and water for 20 min each. The sample was injected hydrodynamically by applying 34 mbar of pressure for 4 s ( 55.6 nl according to the Poiseuille law) followed by buffer in the same manner. Between each run, the capillary was flushed with 10 % (v/v) acetic acid for 5 min followed by water and then running buffer. After the last injection, the capillary was flushed 1 min with Na 1M, 10 min with water and 10 min with air. Dimethyl sulfoxide (DMSO, 1 µl/500 µl) was added to each sample to mark the electro-osmotic flow (EOF) and 1 g L -1 of lactose was added as an internal standard. The EOF was determined at 200 nm. Calibration curves (Figure 2.3-4) were calculated from 5 concentrations between g L -1 and 1 g L -1 ; each concentration level was determined from an average of 5 injections with lactose used as an internal standard. All electropherograms were corrected for the EOF by plotting the intensity against the electrophoretic mobility (µ ep) (Equation 2.3-1). Integration was performed on signals at 270 nm with Origin Pro 8.5 (Northampton, MA, USA). James Oliver CE for bioethanol research 38

63 2.5. NMR spectroscopy 1 H nuclear magnetic resonance (NMR) spectra of 1 g L -1 glucose and sucrose in water with 130 mmol L -1 Na were recorded at 25 C on a Bruker Avance 400 spectrometer (Bruker, Alexandria, NSW, Australia) operating at 400 MHz for 1 H, with a BBO probe, using WATERGATE water suppression. A 14 µs 90 pulse was used for the first 1 H irradiation and 18 µs 180 pulses were used for WATERGATE; 16 scans were recorded with a 5 s relaxation delay. The chemical shift scale was externally calibrated with the resonance of 4,4-dimethyl-4-silapentane-1-sulfonic acid (DSS) at 0 ppm. 1 H NMR spectra of glucose samples (1 g L -1 with 130 mmol Na in D 2O) irradiated with a HP 3D CE deuterium lamp (Agilent Technologies, Part number: ) were recorded at room temperature on a Varian Mercury 2000 spectrometer (Palo Alto, CA, USA) operating at a 1 H Larmor frequency of 300 MHz. A 11 µs 90 pulse was used for 1 H irradiation; a 4 s repetition delay was used and 2 to 64 scans were recorded. The chemical shift scale was externally calibrated with the resonance of 4,4-dimethyl-4-silapentane-1-sulfonic acid (DSS) at 0 ppm. 3. Results and discussion Plant fiber was partially hydrolyzed and the composition was determined for the first time by both common liquid chromatography methods as well as free solution capillary electrophoresis with direct UV detection Comparison of common HPLC separations of monosaccharides and application to fiber analysis HPLC is the dominant method for carbohydrate identification and quantification owing to its relatively high throughput (separation in typically min) and ease of use. Ligand exchange with lead and calcium form resins, LC with hydrogen exchange resins as well as HILIC have different advantages and drawbacks, but none has led to a clear, robust separation. Fig demonstrates the separation of different standards containing common fiber sugars with three commonly used columns for carbohydrate analysis, with the resolution and sensitivity listed in Table Ligand-exchange separation against calcium (Fig A and Table 2.2-2) led to the lowest number of resolved peaks for standards with complete co-elution of galactose, xylose and rhamnose, as documented previously [37]. The stronger complexation of the carbohydrates with lead provides higher resolution between all fiber sugars, in particular xylose and galactose (Fig. James Oliver CE for bioethanol research 39

64 2.3-1B and Table 2.2-2), which is of high importance in fiber analysis and fermentation studies. Although rhamnose still co-elutes with galactose, it is generally only found in trace amounts in the woody biomass that is typically investigated. The weakness of both columns is their inability to tolerate salt and acids. Fiber samples, after being pre-treated with sulfuric acid at high temperatures, require neutralization [38]. This can be achieved with calcium hydroxide or barium hydroxide due to the low solubility of barium sulfate and calcium sulfate; however, trace amounts of salts still rapidly displace calcium or lead. The use of hydroxide additives or hydroxide form resins also adds to the sample preparation. Deashing systems are also available; however, they significantly add to the cost and the cartridges have short lives. HILIC does provide resolution between the sugars of interest (Fig C and Table 2.2-2), however, galactose is still not baseline resolved from the glucose. In this case ACN needs to be added to the sample prior to injection to decrease the eluent s strength which can lead to precipitation of compounds insoluble in ACN such as polysaccharides. Table 2.2-2: Resolution values for consecutive peaks on each column and in CE. Carbohydrate peaks HPLC HPX-87C HPX-87P HPX-87H LC-NH 2 (Calcium (Lead (Hydrogen (Amino CE form) form) form) form) Glucose galactose < Glucose rhamnose Glucose xylose Glucose arabinose Glucose mannose NA 4.32 NA NA 1.71 Xylose galactose < < Xylose rhamnose < Xylose arabinose Xylose mannose NA 2.95 NA NA 5.76 Arabinose galactose Arabinose rhamnose < Arabinose mannose NA 0.74 NA NA 1.93 Rhamnose mannose NA 2.06 NA NA 0.83 Rhamnose galactose <0.5 < Galactose mannose NA 2.06 NA NA 3.42 Sensitivity SNR a 11,000 1,500 10,000 2,100 1,800 NA denotes that one of the carbohydrate was not injected a Signal-to-noise ratios (SNR) are indicated for glucose with 2 significant digits. James Oliver CE for bioethanol research 40

65 One of the most widely used columns in the literature is the hydrogen exchange HPX- 87H, due to its tolerance to low ph samples and its ability to detect acids, alcohols, as well as mono- and disaccharides [12]. Investigations of wood acid hydrolysates have been carried out on this column as the acidity of the sample can be tolerated by the column negating the need for a tedious neutralization step [38]. The issues with this approach are the co-elution of galactose and mannose, which are only trace amounts in wood, with xylose, the acidic mobile phase degrading some disaccharides such as sucrose and the co-elution of acids, ketones and aldoses from the plant degradation with the carbohydrates [12]. In the fiber sample (Fig A), peak 9 elutes close to cellobiose, however its UV spectrum reveals it is not cellobiose. In the case of more complex carbohydrate mixtures the HPX-87H column gives robust separations, but still co-elution (Fig and Table 2.2-2). Figure 2.2-1: Separation of a fiber sample (A) and mixture of standard (B) and using HPX-87H column 1: cellobiose, 2: glucose, 3: galactose, 4: xylose, 5: rhamnose, 6: arabinose, 7: void volume, 8: galacturonic acid, 9: unknown. James Oliver CE for bioethanol research 41

66 3.2. Separation of monosaccharides in fiber samples using capillary electrophoresis The use of CE provides an alternative separation technique with a lower running cost. To run 50 samples via HPLC, the cost of the column, guard column with holder is larger than that of the running cost of capillary electrophoresis for the same purpose for a higher throughput of the latter (see Table 2.3-3). The same standard and sample shown in Fig were separated via CE with direct detection and without any pre-derivatization (Fig ). The sample did not need neutralization before injection saving preparation time and cost. All the common fiber sugars are resolved with baseline resolution maintained for standard concentrations up to 250 mg.l -1, after which glucose and rhamnose start to lose baseline resolution. The peaks can be identified by the electrophoretic mobility and the precision of the mobility is greatly improved by the use of an electro-osmotic flow marker as well as an internal standard (see Table 2.3-2). The addition of an internal standard improved also the repeatability of the peak area which this study showed to be better than published values [34]. The calibration curves obtained with different capillaries, reprepared standard solutions and a different CE machine exhibit good reproducibility (Fig and Table 2.2-3). One of the most significant benefits is the flexibility of the separation in comparison to all HPLC modes compared. Capillary length, buffer concentration and type can be optimized with minimal cost and time in CE compared to optimization of the eluent concentration and nature, and stationary phase in HPLC. James Oliver CE for bioethanol research 42

67 Figure 2.2-2: Fiber standard 250 m gl -1 (A) and sample (B) plotted with electrophoretic mobility and migration time (C-i). Separation by CE via Rovio et al. s method [33]. 1: Cellobiose, 3: galactose, 2: glucose, 5: rhamnose, 4: arabinose, 6: xylose and corresponding UV absorption spectra (C-ii) for glucose (dashed line), xylose (solid line) and arabinose (dotted line). James Oliver CE for bioethanol research 43

68 The electrophoretic mobility is not only a parameter to enable the quantitative determination of the sugars but it also characterizes the molecule and relates to its structure [39-41]. The electrophoretic mobility of each sugar measured in this work (Table as well as reproduced data in Table 2.3-1) was lower than that published by Rovio et al. [33] and by Gürel et al. [30] (Table 2.3-2). The latter used methanol (direct detection) and water (indirect detection) as electro-osmotic flow markers, respectively. Water and methanol have a low but significant effective charge at ph 12 and should not be used as electro-osmotic flow markers in these conditions. Consistent with this we found that when DMSO was used to mark the electro-osmotic flow, methanol had a non-zero electrophoretic mobility (Fig ). The ramping of the separation voltage in the first 2 min from 0 to 16 kv of the run was taken into account in this calculation. Table 2.2-3: Electrophoretic mobility (µ ep) with its relative standard deviation (RSD) and calibration of response at 270 nm with its correlation coefficient R 2, for the sugars in our fiber standard (capillary of 66 cm total length). Sugar µ ep (10-8 m 2 V -1 s -1 ) RSD (%) Calibration (270 nm) b R 2 Lactose a Cellobiose x Galactose x Glucose x Rhamnose x Mannose x Arabinose x Xylose x a Lactose was used as an internal standard b When the internal standard is equal to 1 and x is the sugar concentration James Oliver CE for bioethanol research 44

69 The aim of this work was to quantify carbohydrates in the fiber sample by CE and HPLC with the determined sugar concentrations compared in Table (and Table 2.3-4). Separation and quantification of three sugars had been compared for HILIC and CE with indirect detection [24]. The repeatability showed a higher relative standard deviation (RSD) than our own results since no internal standard and limited flushes between injections were used in CE and the refractive index detection used in HPLC suffered from poor temperature control. The RSD of the HPLC system shows it to be a more precise system. However, mannose, galactose and xylose coelute in HPLC while they can be quantified separately in CE (Table 2.2-2). Taking this into account the total concentration of these three sugars determined by HPLC is compared with the sum of the peaks determined in CE and the concentrations determined by HPLC are systematically lower than those determined by CE: % lower on the total sugar content and up to % lower on glucose. These separations have been fully reproduced with fresh solution and new capillaries and led to similar results shown on Table Lower sugar concentrations determined in HPLC may be attributed to non-quantitative recovery due to absorption of the sugars onto the stationary phase. Such incomplete recovery has been observed previously on this HPLC column once [42]. The incomplete recovery cannot be explained by limited sensitivity since the signal-tonoise ratio is above 1000 for all peaks quantified in Table on the fiber sample. It is to be noted that the capillary electrophoresis instrument we used leads to a more than sufficient sensitivity for fiber samples, but in other cases, such as trace detection, other instruments lead to higher sensitivity [43]. Fractions were collected after LC separation and injected in CE (Table 2.3-5) but the results only indicate a possible additional influence of column bleeding in LC. James Oliver CE for bioethanol research 45

70 Table 2.2-4: Comparison of the determined sugar concentration C (g L -1 ), with their relative standard deviation RSD (%), by CE (capillary of 66 cm total length) and HPLC with HPX-87H column. System CA a Glucose Rhamnose Arabinose A+R c Mannose Galactose Xylose G+M+X b Recovery Total (g L -1 ) C RSD C RSD C RSD C RSD C RSD C RSD C RSD C RSD CE HPLC to to Diff. d 24% 21% to 16% 27% to 18% 19% CE HPLC to to Diff. d 35% 13% to 8% 23% to 14% 17% CE HPLC to to Diff. d 44% 17% to 12% 25% to 14% 22% Loss in HPLC e [42] Sample quantification without internal standard f [34] 4.3 to to to to to 11 a C A is the original acid concentration of the sample before dilution (% v/v) b galactose, mannose and xylose co-elute in HPLC. Values based on the refractive index of xylose (max) and galactose (min) c arabinose and rhamnose co-elute in HPLC. Values based on the refractive index of arabinose (min) and rhamnose (max) d The relative difference Diff. is in % and is calculated as the difference of the concentrations determined by CE and HPLC divided by their average, for recovery only the higher values were used e Loss in HPLC is a comparison to a recovery study previously carried out with this column under these conditions [42]. The study found a loss of recovery for different sugars; the relevant ones are listed in this row. f As mentioned previously, repeatability (as measured by RSD) is improved with the use of an internal standard, the values in this row show the RSD as measured previously by [34] for comparison. James Oliver CE for bioethanol research 46

71 3.3. Investigation of the detection in capillary electrophoresis Monosaccharides do not normally absorb UV at 270 nm however Rovio et al. proved that sensitive detection at this wavelength is obtained at ph 12.6 [33] with the mechanism for this detection of the sugars at 270 nm still under debate. The complex mechanism of CE direct detection at 270 nm, which has recently been pointed out by Sarazin et al.[25], was further investigated in this study. Rovio et al. hypothesized an alkaline degradation of the sugars with the formation of an enediolate absorbing at 270 nm that is unable to proceed to a carboxylic acid due to complexation with the sodium ion [33]. Sarazin et al. subsequently argued that such a mechanism would not be as universal as observed experimentally since it is impossible for sucrose. They proposed instead a photo-oxidation of the saccharides in the detection window [43]. This mechanism is consistent with the mechanism proposed by Gilbert et al. after monitoring the degradation of carbohydrates by hydroxyl radicals using Electron Spin Resonance spectroscopy (ESR) [44]. The reaction pathway is shown in Figure The difference we observe between the UV spectra of glucose and that of xylose and arabinose (Fig C-ii) confirms that there is a difference in the structure of the absorbing molecule between five and six carbon sugars. In elucidating the actual detection mechanism a possible electrochemical reaction should be considered. Since a sucrose solution can be detected by CE in the absence of electric field as previously shown by Sarazin et al. [43], the role of the electric field in the detection of sugars at 270 nm was further investigated. Glucose (1 g L -1 in water) was injected into a 51.5/60 cm capillary with 130 mmol Na as the background electrolyte. The migration of glucose was obtained first by applying voltage; it was independently obtained applying the same voltage for 2 min to allow for adequate mixing of the glucose with the electrolyte shown by the separation of a water peak, then applying a 42 mbar pressure to the capillary inlet for migration. Both types of migrations lead to detection at 270 nm (Fig ). However, the peak area is close to 4 times larger in the presence of electric field, demonstrating that the electric field plays a part in the detection (as well as the photoirradiation). James Oliver CE for bioethanol research 47

72 Figure 2.2-3: Migration of 1 g L -1 of glucose into 130 mmol Na electrolyte by 16 kv electric field (solid line) and with voltage for 2 min followed by 42 mbar pressure (dashed line). Detection via enediolate formation as suggested by Rovio et al. [33] was further investigated in this study. A glucose sample (1 g L -1 in 130 mmol Na) was injected into the CE with 130 mmol Na as the back ground electrolyte at regular intervals and migrated alternatively by voltage (Fig , as well as pressure Fig ). Over a period of 46 h the intensity of the glucose peak decreased and some negatively charged products formed (Table 2.3-6). The products do not have UV spectra distinctive from that of glucose, but a higher mobility (possibly explained by a lower friction through a smaller size). James Oliver CE for bioethanol research 48

73 Figure 2.2-4: Degradation of glucose in 130 mmol Na monitored by migration with voltage. The arrows indicate the evolution with increasing time (0 h: bold solid line, 1.5 h: bold dashed line, 4 h: solid line, 7 h: dotted line, 27 h: dashed line, 46 h: bold dotted line). Migration by pressure reveals a decrease in the amount of compounds detected at 270 nm after more than 4 h. Migration by voltage reveals that the usual glucose peak reduces in intensity decreasing in an apparent first order reaction with respect to glucose (Fig ). After 4 h, degradation products with higher electrophoretic mobility than glucose are separated and they are also detected at 270 nm. Alkaline degradation of glucose is documented in the literature [45-47] but it is important to note that the degradation is very slow compared to the residence time of the monosaccharides in alkaline conditions before the detection (30-40 min) even in the presence of electric field. The alkaline degradation of glucose, as well as sucrose, in alkaline solution, was characterized by 1 H NMR using water suppression. No structural change was observed with glucose within the first 2 h confirming the monitoring of this alkaline degradation by CE as described above. No structural change was observed with sucrose even after a week (Fig B), as predicted by Sarazin et al. [43]. The potential formation of enediolates is definitely too slow to explain the James Oliver CE for bioethanol research 49

74 detection in CE at 270 nm, thus the hypothesis presented in Rovio s pioneering work cannot explain the detection at 270 nm: the photo-irradiation is necessary for these species to be detected. We further investigated the mechanism of the photoreaction by attempting the identification of the potential products by NMR. NMR analysis can be quantitative in a deuterated solvent, since the water peak does not have to be suppressed. We first tested if the photochemical reaction still takes place by replacing water with deuterated water. When injected into the CE with 130 mmol Na in D 2O, the electrophoretic mobility is 20 % lower than in H 2O, consistent with the difference in viscosity of D 2O and H 2O [48], leading to difference in hydrodynamic friction. In both cases the peak absorbance was still at 270 nm (Fig ). The detection mechanism is still possible in the absence of water; however, the peak area observed was five times smaller than that in H 2O. The difference in injection volumes can only be a minor contribution to this difference, since the difference of viscosities for our hydrodynamic injections is only of the order of 20 % and the difference might rather be due to the NaOD in D 2O being significantly less alkaline than sodium hydroxide in H 2O. The sample of glucose (1 g L -1 ) in 130 mmol Na in D 2O was then exposed directly to the HP 3D deuterium lamp (Scheme S-1) for a time significantly longer than the residence time in the CE detection window and then characterized by 1 H NMR with no water suppression (Fig ). After 60 min of irradiation a minor structural change was seen by 1 H NMR at 4 ppm. It is thus clear than on the detection timescale, only a minimal fraction of glucose is photo-oxidized (and the decomposition product absorbing at 270 nm has to be in minimal amount and thus highly UV-absorbing at 270 nm). James Oliver CE for bioethanol research 50

75 Figure 2.2-5: 1 H NMR of glucose (1 g L -1 with 130 mmol Na in D 2O) before (A) and after irradiation with CE deuterium lamp for 5 min (B), 30 min (C) and 60 min (D). The arrows indicate the region in which new signals appear. Sarazin et al. [43] and our results suggest that detection in CE is made possible by a photooxidation similar to the one observed in sodium borate solutions at ph 9 [49] but the extent and rate of the reaction is not clear. In Sarazin et al. s experiments the sugar was moved into the window with pressure and made stationary for the photo-reaction to proceed [43]. However our results have shown that the electric field plays an essential role in the detection. To investigate the photooxidation reaction in the presence of the electric field, glucose (1 g L -1 in water) was injected into 130 mmol Na as for the usual separation. After the peak was detected, the voltage was inverted and the glucose band passed through the detection window a second time. The voltage was inverted again. This was repeated 15 times in total. The peak retained the same electrophoretic mobility; however, its area was not constant, increasing during the first 6 passes and then decreasing (Fig ). This variation in peak intensity with the residence time is qualitatively similar to the one observed by Sarazin et al. [43] in the absence of electric field. In our experiment, the band is in the dark for several minutes between each pass/photo-irradiation. The putative intermediates and mechanism proposed by Gilbert et al. and then Sarazin et al. cannot solely explain our results since all the James Oliver CE for bioethanol research 51

76 proposed intermediates are unstable radicals with lifetimes significantly shorter than one minute. It is possible that some intermediates might accumulate under photo-irradiation and be stable enough to remain in the capillary for the next pass, consistent with the detection of minimal degradation products detected by NMR. The decrease of the signal intensity after the 6 th pass might be due to build-up of oxygen arising from side reaction from the UV degradation of water and consistent with a photo-oxidation process enhanced by the electric field, however could not be definitely confirmed from these experiments. Figure 2.2-6: Detection of glucose (1 g L -1 ) in 130 mm Na with 16 kv separation. Each peak represents a pass of the sugar though the lamp, after which the voltage was inverted. 4. Conclusions HILIC, ligand exchange and other LC methods conventionally used for carbohydrates provide an inadequate separation of all sugars in acid-hydrolyzed plant fiber and none of the columns examined provide both a robust and clear separation. In order to maintain separation on the calcium and lead form resins a tedious neutralizing step must be carried out. This study showed free solution CE to be a superior quantitative method to HPLC in terms of robustness and resolution, as well as recovery. In comparison to HPLC, CE has a significantly lower running cost, a higher throughput and a James Oliver CE for bioethanol research 52

77 greater flexibility. The direct detection of deprotonated saccharides is unexpectedly possible at 270 nm but it is neither due enediolate formation nor to alkaline degradation, which is slow compared to the residence time in the detection window. The detection is likely due to an intermediate in a photo-oxidation process that we showed to be enhanced by the electric field. Despite a still controversial mechanism, the detection is robust (possible for example in deuterated solvent although with lower sensitivity), although the presence of oxygen might be of importance. CE is thus a robust and simple method to study polysaccharides degradation in general. Acknowledgements PC and MG thank the College of Health and Science of the University of Western Sydney for a College Equipment Grant for the purchase of the Agilent Capillary Electrophoresis and the School of Natural Sciences for Small Equipment grant. Support from the Australian Research Council is gratefully acknowledged: EFH is recipient of an ARC Future Fellowship (FT ). We thank Dr Michael Phillips, Dr Paul Peiris, Dr Mark Williams and Julie Markham (UWS), Mark Thomas, Dr Artaches (Tom) Kazarian, A/Prof Michael Breadmore, Dr James Horne (University of Tasmania), Dr Yohann Guillaneuf and Dr Jean-Louis Clement (Aix-Marseille University) for fruitful discussions. 5. References [1] Y.J. Jeon, Z. Xun, P.L. Rogers, Lett. Appl. Microbiol. 51 (2010) 518. [2] T.A. Lloyd, C.E. Wyman, Bioresour. Technol. 96 (2005) [3] A. Esteghlalian, A.G. Hashimoto, J.J. Fenske, M.H. Penner, Bioresour. Technol. 59 (1997) 129. [4] Y. Sun, J.J. Cheng, Bioresour. Technol. 96 (2005) [5] R. Torget, P. Walter, M. Himmel, K. Grohmann, Appl. Biochem. Biotechnol (1991) 75. [6] B.S. Dien, H.-J.G. Jung, K.P. Vogel, M.D. Casler, J.F.S. Lamb, L. Iten, R.B. Mitchell, G. Sarath, Biomass Bioenergy 30 (2006) 880. [7] L. da Costa Sousa, S.P.S. Chundawat, V. Balan, B.E. Dale, Curr. Opin. Biotechnol. 20 (2009) 339. [8] A.A. Ben-bassat, E. Grushka, J. Liq. Chromatogr. 14 (1991) [9] G. Bonn, J. Chromatogr. 322 (1985) 411. [10] G. Bonn, J. Chromatogr. 350 (1985) 381. [11] H. Caruel, L. Rigal, A. Gaset, J. Chromatogr. 558 (1991) 89. [12] R. Pecina, G. Bonn, E. Burtscher, O. Bobleter, J. Chromatogr. A 287 (1984) 245. [13] M. D'Amboise, D. Noēl, T. Hanai, Carbohydr. Res. 79 (1980) 1. [14] H. Alwael, D. Connolly, B. Paull, Anal. Methods 3 (2011) 62. [15] M. Verzele, G. Simoens, F. Van Damme, Chromatographia 23 (1987) 292. [16] J.B. Sluiter, R.O. Ruiz, C.J. Scarlata, A.D. Sluiter, D.W. Templeton, J. Agric. Food Chem. 58 (2010) [17] A.I. Ruiz-Matute, O. Hernández-Hernández, S. Rodríguez-Sánchez, M.L. Sanz, I. Martínez- Castro, J. Chromatogr. B 879 (2011) [18] D.R. Knapp, Handbook of Analytical Derivatization Reactions., Wiley, New York, [19] M.J. Villanueva-Suárez, A. Redondo-Cuenca, M.D. Rodríguez-Sevilla, M. de las Heras Martínez, J. Agric. Food Chem. 51 (2003) James Oliver CE for bioethanol research 53

78 [20] Z. El Rassi, Electrophoresis 20 (1999) [21] G. Hanrahan, Chemometric Methods in Capillary Electrophoresis, Wiley, Hoboken, NJ, USA, [22] C.W. Klampfl, M. Himmelsbach, W. Buchberger, in N. Volpi (Editor), Capillary Electrophoresis of Carbohydrates, Humana Press, 2011, p. 1. [23] O. Dahlman, A. Jacobs, A. Liljenberg, A.I. Olsson, J. Chromatogr. A 891 (2000) 157. [24] J. Cabálková, J. Žídková, L. Přibyla, J. Chmelík, Electrophoresis 25 (2004) 487. [25] D. Harvey, Modern Analytical Chemistry, McGraw-Hill, Boston, [26] P. Schmitt-Kopplin, K. Fischer, D. Freitag, A. Kettrup, J. Chromatogr. A 807 (1998) 89. [27] H. Schwaiger, P.J. Oefner, C. Huber, E. Grill, G.K. Bonn, Electrophoresis 15 (1994) 941. [28] A. Vorndran, P. Oefner, H. Scherz, G. Bonn, Chromatographia 33 (1992) 163. [29] T. Soga, D.N. Heiger, Anal. Biochem. 261 (1998) 73. [30] A. Gürel, J. Hızal, N. Öztekin, F. Erim, Chromatographia 64 (2006) 321. [31] T.J. O'Shea, S.M. Lunte, W.R. LaCourse, Anal. Chem. 65 (1993) 948. [32] T. Soga, M. Serwe, Food Chem. 69 (2000) 339. [33] S. Rovio, J. Yli-Kauhaluoma, H. Siren, Electrophoresis 28 (2007) [34] S. Rovio, H. Simolin, K. Koljonen, H. Siren, J. Chromatogr. A 1185 (2008) 139. [35] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, P. Gareil, Talanta 99 (2012) 202. [36] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, P. Gareil, Talanta 103 (2013) 301. [37] T. Foyle, L. Jennings, P. Mulcahy, Bioresour. Technol. 98 (2007) [38] T. Irick, K. West, H. Brownell, W. Schwald, J. Saddler, Appl. Biochem. Biotechnol. 17 (1988) 137. [39] M.E. Starkweather, D.A. Hoagland, M. Muthukumar, Macromolecules 33 (2000) [40] H. Cottet, P. Gareil, Electrophoresis 21 (2000) [41] H. Cottet, P. Gareil, O. Theodoly, C.E. Williams, Electrophoresis 21 (2000) [42] G. Zeppa, L. Conterno, V. Gerbi, J. Agric. Food Chem. 49 (2001) [43] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, J.M. Mallet, P. Gareil, Anal. Chem. 83 (2011) [44] B.C. Gilbert, D.M. King, C.B. Thomas, J. Chem. Soc., Perkin Trans. 2 (1982) 169. [45] J.C. Sowden, R. Schaffer, J. Am. Chem. Soc. 74 (1952) 499. [46] E.R. Garrett, J.F. Young, J. Org. Chem. 35 (1970) [47] G. De Wit, A.P.G. Kieboom, H. van Bekkum, Carbohydr. Res. 74 (1979) 157. [48] J. Kestin, N. Imaishi, S.H. Nott, J.C. Nieuwoudt, J.V. Sengers, Physica A 134 (1985) 38. [49] B. Roig, O. Thomas, Anal. Chim. Acta 477 (2003) 325. James Oliver CE for bioethanol research 54

79 2.3 Publication supporting information Supporting Information for Simple and robust separation of monosaccharides in complex mixtures by capillary electrophoresis and high performance liquid chromatography James D. Oliver, 1 Marianne Gaborieau, 2 Emily F. Hilder, 3 Patrice Castignolles* 1 1 University of Western Sydney (UWS), Australian Centre for Research on Separation Science (ACROSS), School of Science and Health, Locked Bag 1797, Penrith NSW 2751, Australia, james.oliver@uws.edu.au, p.castignolles@uws.edu.au 2 University of Western Sydney (UWS), School of Science and Health, Nanoscale Organisation and Dynamics group, Locked Bag 1797, Penrith NSW 2751, Australia, m.gaborieau@uws.edu.au 3 Australian Centre for Research on Separation Science (ACROSS), School of Chemistry, University of Tasmania, Hobart TAS 7001, Australia, emily.hilder@utas.edu.au * Corresponding author: p.castignolles@uws.edu.au 1. High Performance Liquid Chromatography (HPLC): The common HPLC separations discussed and quantified in the manuscript are shown on Figure S-1. James Oliver CE for bioethanol research 55

80 Figure 2.3-1: HPLC Separation of sugars on HPX-87C with water mobile phase (A), HPX-87P with water mobile phase (B) and LC-NH2 with 75:25 ACN:water mobile phase (C). Sol: Solvent peak. 1: Cellobiose, 2: Glucose 3: Galactose 4: Xylose 5: Rhamnose 6: Arabinose 7: Mannose James Oliver CE for bioethanol research 56

81 Figure 2.3-2: Calibration curve of response with RID for the sugars in our fiber standard on the HPX- 87H column. Table 2.3-1: Calibration of response with RID with its relative standard deviation (RSD) of response at 270 nm with its correlation coefficient R2, for the sugars in our fiber standard on the HPX-87H column Sugar Calibration (RID) R 2 Glucose x Mannose x Galactose x Xylose x Rhamnose x Arabinose x James Oliver CE for bioethanol research 57

82 2. Capillary Electrophoresis: The electrophoretic mobility µ ep was determined using the following equation [1]: μμ eeee = ll LL VV 1 tt m 1 tt eeee where l is the capillary length to the detection window, L is the total length of the capillary, V is the voltage, t m is the migration time of the analyte, t eo is the migration time of the neutral species. The ramping was taken into account by averaging the voltage at t m. The electrophoretic mobility values are then given on Table 3 and on Table S-1 (the latter is based on the same method as for Table 4 but with new injections of new solutions in a new capillary) and the difference with values published by Rovio et al. is explained by Figure S-3. Table 2.3-2: Electrophoretic mobility (10-8 m 2 V -1 s -1 ) of common fiber sugars determined in this study (35 injections), before and after correction using lactose as the internal standard. RSD is the relative standard deviation (%). The values are compared with published values. Our work Literature Sugar Mobility RSD (before) RSD (after) Rovio a Diff. b Gürel c Diff. b Lactose Cellobiose Galactose Glucose Rhamnose Arabinose Xylose a S. Rovio, et al.[2] b relative difference calculated as the difference of our corrected mobility and the literature mobility divided by the average of both mobilities. c A. Gürel, et al. [3] James Oliver CE for bioethanol research 58

83 Figure 2.3-3: Comparison of electrophoretic mobility of DMSO (1) and methanol (2) in 130 mmol Na and 36 mmol Na 2HPO 4, detected at 200 nm. The calibration curves used for the quantification of the carbohydrates using CE are given on Figure S-4. Figure 2.3-4: Calibration curves with standards, showing R 2 values (capillary of 60 cm total length). Equations are given in Table 2. James Oliver CE for bioethanol research 59

84 3. Quantitative Comparison of HPLC and CE: The comparison of CE and common HPLC is given on Table S-3 in terms of cost and in Table S-4 in terms of carbohydrates quantification. It is important to note that Table S-4 give the same comparison as in Table 4 but from different experiments reproducing Table 4 ones with a different capillary and solutions. The results of the analysis of HPLC fractions by CE are given on Table S-5. Table 2.3-3: Estimate of the cost of the typical CE and HPLC separations ($ is for Australian dollar and prices are as for 2012). HPLC System CE System HPX-87P HPX-87H LC-NH 2 Column $2,096 $2,096 $731 Capillary $7.2 Guard Column $537 $517 Guard Column Holder $848 $848 $355 Total $3,481 $3,461 $1,086 Total $7.2 Table 2.3-4: Comparison of the determined sugar concentration C (g L-1), with their relative standard deviation RSD (%), by CE (capillary of 66 cm total length) and HPLC with HPX-87H column. Compared to Table 4, these separations have been fully reproduced with fresh solution and new capillaries. a System C A Glucose Rhamnose Arabinose Mannose Galactose Xylose M+G+X b C RSD C RSD C RSD C RSD C RSD C RSD C RSD CE HPLC to Diff. c CE HPLC to Diff. c CE HPLC to Diff c a C A is the acid concentration of the sample (% v/v) b galactose, mannose and xylose co-elute in HPLC. Values based on the refractive index of Xylose and Galactose c The relative difference Diff. is in % and is calculated as the difference of the concentrations determined by CE and HPLC divided by their average. James Oliver CE for bioethanol research 60

85 To investigate a potential loss in the LC system, fractions were collected after LC separation and analyzed by capillary electrophoresis. 20 µl of glucose standards (10 or 20 g L -1 ) and fiber samples (equivalent to the 4% (v/v) acid sample) were injected on a HPX-87H column and the glucose peak was collected as one fraction after the RID detector. The fractions were then injected in CE for quantification of the glucose (as it had the highest difference between CE and HPLC). The fiber sample (same 4% (v/v) acid treated sample) was also diluted to the same concentration, injected directly into CE for quantification. The glucose fractions led to quantification of glucose by the CE 24 % lower than the original amount for the 20 g L -1 standard while it is 15 % higher for the 15 g L - 1 standard. This is not consistent with the repeatability of both LC and CE quantifications. One explanation might be column bleeding. Common LC columns for sugars are a relatively old technology (prior to online light-scattering detection) and column bleeding is expected. The limited results we have are consistent with bleeding, with an overestimate of the glucose content as the injected amount decreases. On the fiber samples, RID detection on the HPLC quantified the samples at 2.49 g L -1, however the CE quantified the fractions at 3.3 g L -1 (see table S-5). Incomplete separation in LC could lead to overestimate of the sugar amounts. The total peak area in LC treated with the different possible calibration curves lead to 3.9, 6.9 and 7.8 % variation for the 1%, 3% and 4% acid samples respectively in the total sugar amount quantified by LC. Deconvolution of the peak is thus not necessary to discard the hypothesis that the limited resolution could explain the lower recovery observed in LC than in CE: deconvolution would not significantly change the total amount of quantified sugars. Finally, our investigation of the detection mechanism in CE does not indicate any likelihood of overestimating of the sugar content in fiber samples. We conclude that a loss of carbohydrates in the LC system likely explains the difference between our CE and LC quantification. The fact that the difference is larger than the loss observed in LC in the literature might be explained by column leaching or to a lesser extent the incomplete separation in LC. James Oliver CE for bioethanol research 61

86 Table 2.3-5: Fraction experiments to determine the loss in HPLC in comparison to CE: comparison of the concentrations of glucose injected in HPLC, C inj, eluted from HPLC according to RID detection, C RID, and as determined from CE, C CE. Sample C inj (g L -1 ) C CE (g L -1 ) C RID (g L -1 ) NA Glucose pure NA in water NA (Fraction) NA Fibre sample (Fraction) Fibre sample Direct Injection NA NA NA NA NA 3.22 NA NA 3.35 NA 4. Investigation the CE detection mechanism: Additional information about the investigation of the detection in CE is given below. The setup used to produce the samples for Figure 5 is given in Scheme S-1. Monitoring of glucose degradation is illustrated on Table S-2 and Figure S-4 and S-5. The assumed reaction scheme for the photo-oxidation is given on Figure S-6. The difference in separation in D2O and H2O is shown on Figure S-7, while the NMR monitoring of alkaline degradation of glucose is shown on Figure S-8. Scheme 2.3-1: Set-up of CE photo-oxidation experiment. James Oliver CE for bioethanol research 62

87 Table 2.3-6: Peak areas of glucose degrading in 130 mm sodium hydroxide, separated by CE with 16 kv. Time (h) Peak 1 Peak 2 Peak E E E E E E E E E E E E E-09 Figure 2.3-5: Evolution of the area of the glucose peak monitored by CE for a solution of glucose 1 g.l-1 in 130 mm Na. James Oliver CE for bioethanol research 63

88 Figure 2.3-6: Degradation of glucose in 130 mmol Na monitored by migration with pressure. The arrows indicate the evolution with increasing time (0 h: bold solid line, 1.5 h: bold dashed line, 4 h: solid line, 7 h: dotted line, 27 h: dashed line, 46 h: bold dotted line). James Oliver CE for bioethanol research 64

89 H H HO HO H H O H H HO HO H H O H H O H H H 2 O HO HO H H H H O - H O + H + HOCH 2 - H H O H H - H2 O O H O HOCH 2 H + HO H + - O H H - HO CH 2 O C C HO O CH 2 + H H O O C C O O Figure 2.3-7: Photo-oxidation of glucose in CE. Adapted from Gilbert et al. (1982) [5]. James Oliver CE for bioethanol research 65

90 Figure 2.3-8: Separation and detection of glucose (1 g L-1) in 130 mmol Na in water (dotted line) and in D2O (solid line). James Oliver CE for bioethanol research 66

91 Figure 2.3-9: 1H NMR of 1 g L -1 glucose (A) in 130 mmol of Na after 2 hours (A-I) and 5 days (A-II) and of sucrose (B) in water (B-I), 130 mmol Na after 2 hours (B-II) and after 5 days (B-III) References: [1] H. Susumu, Journal of Chromatography A 720 (1996) 337. [2] S. Rovio, J. Yli-Kauhaluoma, H. Sirén, Electrophoresis 28 (2007) [3] A. Gürel, J. Hızal, N. Öztekin, F. Erim, Chromatographia 64 (2006) 321. [4] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, J.-M. Mallet, P. Gareil, Analytical Chemistry 83 (2011) [5] B.C. Gilbert, D.M. King, C.B. Thomas, J. Chem. Soc., Perkin Trans. 2 (1982) 169. James Oliver CE for bioethanol research 67

92 3. Publication Understanding and improving direct UV detection of monosaccharides and disaccharides in free solution capillary electrophoresis Contribution to PhD work, field, and candidates personal and professional development Investigation of the photo-oxidation reaction CE with direct UV detection has the ability to separate all the fiber sugars of interest and has, so far, shown to be robust against acid treated fiber samples from our last publication. The previous publication also showed that a photo-oxidation reaction was the cause of the detection. The lack of understanding behind the photo-oxidation reaction still remained a drawback of the detection. This understanding is required if the method is going to continue being utilized. Before proceeding to apply the method to fermentation samples a study of the photo-oxidation reaction was undertaken. Mass Spectrometry (MS) was considered and CE-MS would have allowed us to study the products of the photo-reaction however a BGE compatible with MS detection (volatile) could not be found. MS is incompatible with the BGE s high salt concentration. A MS compatible organic solvent, methyl amine, was tested as a BGE for CE-MS however the photo-oxidation detection was no longer observed suggesting an inhibition of the reaction. The organic solvent also stripped the polyimide coating off the outside of the capillary. In discussions with Prof. Wolfgang Buchberger of Johannes-Kepler-University it was suggested that a compatible BGE would be difficult to find, however it is still a subject of interest to his group [144] Theory of radical chemistry in relation to carbohydrate photo-oxidation Sarazin et al. (2011) proposed that the radical photo-oxidation pathway was initiated by a hydroxide radical ( ). Such radicals can be formed by the decomposition of water under hv <190 nm irradiation where H 2O can be decomposed to and H (see Equation next subchapter). - Superoxide radicals (O 2 ) can also be formed following the same irradiation (see Equation next subchapter). Radicals only exist in low concentration, since increases of the radical concentration lead to increased termination reactions. Irradiation is suggested to originate from the CE s DAD lamp where wavelengths below 190 nm initiate the irradiation and wavelengths 270 nm detect the UV absorbing intermediate. In studies by Gilbert et al. (1982) on the radical reaction of carbohydrate, the radicals were produced chemically instead of being photo-initiated. Gilbert et al. (1982) used ESR to study formation of radicals. In this work, however, the lamp did not provide sufficient radicals in James Oliver CE for bioethanol research 68

93 the ESR cavity. The pathway that was proposed in this publication also involved the presence of oxygen biradicals that form carboxylates. Oxygen biradicals are a mesomer of oxygen molecules (Equation 3.1-1). Equation 3.1-1: Formation of oxygen biradicals. The research question of the 2 nd publication was What is the reaction pathway that makes the photo-oxidation detection possible? Contribution to my personal development This publication contributed to the field of study by providing a reaction pathway explaining the direct UV detection seen in CE. This new understanding ensured the method is quantitative for all foreseen applications to fibers and fermentations and gave the potential to increase the sensitivity of the detection though the use of radical photo-initiators. For my personal development, this work gave me the opportunity to give an oral presentation at the 6th International Symposium on the Separation and Characterization of Natural and Synthetic Macromolecules in Dresden (SCM-6; see Conference and seminar presentations ). While attending this conference I was able to meet with Prof Pierre Gareil and Dr Nathaline Delaunay (Chimie ParisTech, France) to discuss this publication and the 4 th publication. I was provided training on the important analytical techniques of 13 C NMR (at UWS) and ESR spectroscopies (at Aix-Marseille Université). I was also exposed to quantum mechanics calculations when studying the detection mechanism. Professional development was achieved through my collaboration with Dr Yohann Guillaneuf and Dr Jean-Louis Clement from Aix-Marseille Université, France where ESR experiments were carried out and radical pathways (work of Gilbert et al. 1982) was discussed. Collaboration with Dr Christopher Fellows and Adam Rosser from University of New England, Australia (UNE) yielded the quantum mechanics calculations. This publication had 6 co-authors. The last author, Dr Patrice Castignolles provided the direction of the paper and help formulate the ideas behind the experiments. He also facilitated the collaboration with UNE and Aix-Marseille Université. Dr Marianne Gaborieau provided assistance with performing 13 C NMR spectroscopy experiments. Dr Christopher Fellows help formulate the idea James Oliver CE for bioethanol research 69

94 behind predicting the intermediate s absorption and his student Adam Rosser carried out the calculations. Dr Yohann Guillaneuf and Dr Jean-Louis Clement gave feedback on the reaction schemes as well as training on ESR spectroscopy. Although the method seemed promising, I felt that the biggest drawback was the lack of understanding of the detection. I considered different methods to study the detection mechanism. ESR was chosen based on its use in previous research studied in the literature however it proved to be limited. I selected 13 C NMR for its potential to identify key chemical groups in the end products of the photo-oxidation reaction. The idea of simulating the UV spectra was developed in discussion between Dr Chris Fellows, Patrice and myself. The theoretical calculations were performed by Adam Rosser, a PhD student supervised by Dr Chris Fellows. I performed all background research, experiments and data acquisition except for the quantum mechanics calculations. I performed all data analysis and wrote the first draft of the publication. I developed the reaction mechanism, the key finding of this paper, based on the data I had analyzed from the NMR results. I designed and carry-out the experiments that linked the previous research of Gilbert et al (1982) with the NMR data and the theoretical calculations carried out at UNE. James Oliver CE for bioethanol research 70

95 3.2 Publication Understanding and improving direct UV detection of monosaccharides and disaccharides in free solution capillary electrophoresis James D. Oliver 1, Adam A. Rosser 3, Christopher M. Fellows 3, Yohann Guillaneuf 4, Jean-Louis Clement 4, Marianne Gaborieau 2, Patrice Castignolles 1 * 1) University of Western Sydney, Australian Centre for Research On Separation Sciences (ACROSS), School of Science and Health, Parramatta Campus, Locked Bag 1797, Penrith NSW 2751, Australia 2) University of Western Sydney, Molecular Medicine Research Group (MMRG), School of Science and Health, Parramatta Campus, Locked Bag 1797, Penrith NSW 2751, Australia 3) University of New England, School of Science and Technology, Armidale NSW 2351, Australia 4) Aix-Marseille Université, CNRS, Institut de Chimie Radicalaire UMR 7273, Avenue Escadrille Normandie-Niemen, Marseille Cedex 20, France Graphical abstract Figure 3.2-1: Proposed sequence of events leading to UV-absorbing intermediates and carboxylated end-products. James Oliver CE for bioethanol research 71

96 Abstract Direct UV detection of carbohydrates in free solution capillary electrophoresis at 270 nm is made possible by a photo-oxidation reaction. Glucose, rhamnose and xylose were shown to have unique UV absorption spectra hypothesizing different UV absorbing intermediates for their respective photo-oxidation. NMR spectroscopy of the photo-oxidation end products proved they consisted of carboxylates and not malondialdehyde as previously theorized and that oxygen thus plays a key role in the photo-oxidation pathway. Adding the photo-initiator Irgacure 2959 in the background electrolyte increased sensitivity by 40 % at an optimum concentration of 1 x 10-4 mm and 1 x 10-8 mm for conventional 50 µm i.d. capillaries and for the corresponding extended light path capillaries, respectively. Keywords: Free solution capillary electrophoresis, Direct UV detection, Radical photo-oxidation, Nuclear magnetic resonance spectroscopy, Saccharide, Photo-initiator 1 Introduction Carbohydrate analysis is required for a variety of purposes such as food and beverage analysis, plant characterization and metabolic studies. Gas Chromatography (GC) or GC with mass spectrometry (GC-MS) is a common technique for carbohydrate analysis, however multi-step derivatization is essential for the sugars to become volatile [1, 2]. High performance liquid chromatography (HPLC) can separate carbohydrates without derivatization using ligand exchange [3, 4], hydrophilic interaction liquid chromatography (HILIC) [5, 6], or on a cation exchange resin [7, 8]. However, complex mixtures of common carbohydrates cannot be fully separated utilizing these separation modes [9]. Direct detection of carbohydrates in HPLC requires the use of a Refractive Index Detector (RID), a universal detector than can also detect interfering compounds with similar elution times. High performance anion exchange chromatography (HPAEC) coupled to pulsed amperometric detection (PAD) is a sensitive alternative technique for trace analysis of carbohydrates [10, 11]. Although the technique is flexible, some sample pre-treatment may be required to remove interfering compounds present in some complex matrices that can affect detection [12, 13]. Capillary electrophoresis (CE) has become a popular technology for carbohydrate analysis [14]. CE has two distinct advantages over HPLC for sample analysis: undesirable sample components can be flushed out after analysis, and a new capillary is less costly than a new HPLC column [14]. Previous CE methods for carbohydrate analysis have used either indirect UV detection [15], contactless conductivity detection (C 4 D) [16, 17] or complexation with ions such as borate [18] or copper (II) [19]. The borate complex is detected only at wavelengths close to 190 nm, which is not James Oliver CE for bioethanol research 72

97 discriminating from other compounds, while copper may induce the formation of supramacromolecular structures with other compounds in biological matrices and leads to poor sensitivity. PAD can also be coupled to CE [20, 21]; however this is not currently commercially available. Capillary electrophoresis with direct UV detection has been shown to be a reliable and robust technique for the analysis of carbohydrates in analysis of plant fiber [9], juice [22] as well as forensic, pharmaceutical and other beverage samples [23]. Direct UV detection of carbohydrates at 270 nm was initially proposed to be due to an enediolate formation [22]. This mechanism was disproved in later studies [9, 24] and also does not explain the detection of sucrose. The UV absorption is now believed to arise from an intermediate generated during the photo-oxidation [24] of the carbohydrate. This photo-oxidation reaction is enhanced by the electric field [9]. The efficiency of the photo-oxidation detection varies between different CE diode array detectors (DAD) with only detectors capable of irradiation at low wavelength giving trace detection [9, 24]. While higher sensitivity is preferred, it requires stronger irradiation at low wavelength and this might lead to chemical degradation; however, this potential degradation has never been investigated. Sensitivity of the carbohydrate is also dependent on the residence time in the detection window and the structure of the carbohydrate, in particular the number of free hydroxyl groups [24]. The aim of this study was to shed light onto the photo-oxidation reaction taking place in the detection window. Despite direct detection being available, other indirect methods are still utilized [25], one reason may be the limited understanding of the direct detection mechanism and the limitations of this detection mode. The direct detection mechanism was studied in this work by analysis and modeling of possible photo-oxidation products, with the long-term aim of increasing the sensitivity of detection while retaining the flexibility and robustness of the CE method. 2 Materials and methods 2.1 Materials and reagents Sodium hydroxide pellets 98 %, glycerol 99 %, malondialdehyde tetrabutylammonium salt 96%, gluconolactone (USP testing specifications), L+arabinose 99 %, and rhamnose monohydrate 99 % were sourced from Sigma-Aldrich (Castle Hill, NSW, Australia). Sucrose 99 %, glucose 99 %, L-arabitol 98 % and D-xylose 99 % were sourced from Alfa Aesar (Ward Hill, MA, USA). Potassium gluconate 98 % and fructose 99 % were sourced from BDH (Poole, Dorset UK). Deuterium oxide (D,99.9 %) and fully 13 C-labelled glucose 99 % were sourced from Cambridge Isotope Laboratories (Tewksbury, MA, USA). Hydrogen peroxide 30 % (v/v) was sourced from Chem-Supply (Gillman, SA, Australia). Formic acid 99 % and oxalic acid 99.5 % were from Univar (Ingleburn, NSW, Australia). James Oliver CE for bioethanol research 73

98 Glycolic acid 70 % (w/w) was from Ajax chemicals (Australia). The photo-initiator Irgacure 2959 was from Ciba (Switzerland). Water was of Milli-Q quality (Millipore, Bedford, MA, USA). Fused-silica capillaries (50 µm i.d., 360 µm o.d.) were obtained from Polymicro (Phoenix, AZ, USA). High sensitivity capillaries (50 µm i.d., 360 µm o.d with extended light path at the window) were from Agilent Technologies (Agilent Technologies, Waldbronn, Germany). 2.2 Capillary electrophoresis Free solution capillary electrophoresis was carried out on an Agilent 7100 instrument (or a HP3D instrument where specified) (Agilent Technologies, Waldbronn, Germany) equipped with a Diode Array Detector. A capillary with a 35 cm total length (26.5 cm effective length), was filled with 130 mm Na as the background electrolyte (BGE) which was prepared daily. The capillary was pretreated prior to use by flushing for 20 min in turn with 1 M Na, 0.1 M Na and water. The sample was injected hydrodynamically by applying 34 mbar of pressure for 4 s followed by BGE at 34 mbar for 5 s. A voltage of 9.6 kv was ramped up over 1 min and signals were monitored at 200 nm and 266 nm with a 10 nm bandwidth. Between consecutive runs, the capillary was flushed with fresh BGE. After the final injection, the capillary was flushed for 1 min with Na 1M, 10 min with water and 10 min with air. Dimethyl sulfoxide (DMSO, 1 µl/500 µl) was added to each sample to mark the electro-osmotic flow (EOF). The EOF was determined at 200 nm. Integration was performed on signals at 266 nm with Origin Pro 8.5 (Northampton, MA, USA). 2.3 Nuclear magnetic resonance (NMR) The photo-oxidized sample was prepared by dissolving 13 C labeled glucose in 130 mm Na in D 2O at 1 g L -1. The sample was pressure injected continuously at 10 mbar into a 35 cm capillary (26.5 cm effective length) with the lamp on. The sample (200 µl) was collected, made up to 600 µl with 130 mm Na in D 2O, and analyzed by both 1 H and 13 C nuclear magnetic resonance (NMR). Standards of sodium gluconate, gluconolactone, malondialdehyde and glycerol were prepared at 100 g L -1 in 130 mm Na in D 2O. Standards of sodium methanoate, sodium glycolate and sodium oxalate were prepared from the acids dissolved at 100 g L -1 in Na in D 2O; the Na concentration was chosen to yield a final calculated pd (-log[d + ]) of 13.1 (2.30, 0.63 and 2.25 M respectively). 1 H NMR, 13 C NMR and DEPT-135 NMR spectra were recorded at room temperature on a Bruker DRX300 spectrometer (Bruker, Alexandria, NSW, Australia) operating at 300 MHz for 1 H, equipped with a 5 mm 1 H- 13 C dual probe. 1 H NMR spectra were recorded with a 5.3 µs 30 pulse, a 5 s repetition delay and 8 to 6,000 scans. 13 C NMR spectra were recorded with a 7 µs 90 pulse, a 3.3 s James Oliver CE for bioethanol research 74

99 repetition delay and 40 to 122,880 scans. The DEPT-135 NMR spectrum was recorded with a 8.7 µs 1 H 90 pulse, a 9.7 µs 13 C 90 pulse, a 145 Hz 1 H- 13 C coupling constant, a 3 s repetition delay and 61,440 scans. 1 H and 13 C chemical shift scales were externally calibrated with the resonance of the methyl signal of ethanol in D 2O at 1.17 and ppm, respectively [26]. 2.4 UV-Vis spectra prediction GaussView was used to construct and visualize all species investigated. Energy calculations and spectra predictions were executed using Gaussian 03W[27]. Molecules were structurally optimized at the B3LYP/6-31++G(d) level, followed by an energy calculation at the TD- B3LYP/6-31++G(2d, 2p) level (where TD is Time Dependent). UV-Vis spectra were extracted from the latter calculation approximating 20 excitations for each spectrum. 3 Results and discussion Previous CE separations of carbohydrates with direct UV detection have been made faster with a polymer coating [24, 28]. The reversal of the EOF also decreases the residence time in the detection window and when used with a CE DAD with limited emission below 190 nm, the limit of detection is reached (see Figure 3.3-1). The sensitivity of the detection also depends on the life time of the lamp as well as on the design of the DAD optics, residence time of the carbohydrate in the CE window, and the carbohydrate structure. To increase the sensitivity of the detection, an understanding of the electric field assisted photo-oxidation is required. 3.1 Understanding the electric field assisted photo-oxidation reaction. Direct UV detection of carbohydrates is made possible through a photo-oxidation reaction in the detection window [24] where a hydroxyl radical ( - ) or superoxide (O 2 ) is assumed to oxidize the carbohydrate to malondialdehyde [29] or dihydroxyacetone [24] while some of the intermediate species absorb UV at about 270 nm. Hydroxyl or superoxide radicals can be formed by the splitting of water at wavelengths lower than 190 nm [30], although the extent is expected to be limited with the deuterium lamp used in CE detectors [31]. The pathway of monosaccharide oxidation by hydroxyl radicals has been studied previously by Electron Spin Resonance (ESR) spectroscopy at ph 5-10 under inert atmosphere [29]. In that study, the hydroxyl radicals were formed by a continuous reaction of titanium (Ti III ) and hydrogen peroxide in the ESR cavity. Two types of semidiones (A and B) were found (Schemes 1 and 2 respectively), stemming from two different reaction pathways. Type James Oliver CE for bioethanol research 75

100 A semidiones (Scheme 1) were detectable from ph 6 and above as both cis and trans-isomers. Type A semidiones were detected for glucose, mannose, glucuronic acid, galactose, galacturonic acid, rhamnose, xylose, arabinose, ribose, fructose, sorbose and maltose. However no type A semidiones were detected for sucrose. Type B semidiones (Scheme 2) were formed in basic media, and increased in concentration as the ph increases, but not at the expense of semidione type A, proving two different reaction mechanisms were taking place. Type B semidiones were detected for glucose, mannose, galactose, rhamnose, xylose, arabinose, ribose, fructose, sorbose and sucrose. No type B semidiones were detected for maltose; however colorimetric tests for malondialdehyde, an end product of the type B semidione pathway, showed a positive result for maltose as well suggesting a third route [29]. HO HO H H H H O H H H 2 O HO HO H H O H H H 2 O HO HO H H O O H HO HO H H H O O H H HO HO H H O H O H H 2 O HO HO H H O O H O H 2 O H HO HO H H O O H Scheme 3.2-1: Formation of semidione A from β-d-glucose adapted from Gilbert et al. [29]. H HO HO H H O H H H H 2 O HO HO H O H H H H 2 O HO HO H O H H O H HO HO H 2 O H O H H O HO H O H H HO O H HO H H H O H H H 2 O O H HO H H H O H H H O H O O HO HO H O H 2 O O H HO O HO O H O Scheme 3.2-2: Formation of semidione B from β-d-glucose adapted (and corrected to place missing radical in 1 st and 2 nd molecule), from Gilbert et al. [29]. It is noted that between the 4 th and 5 th stage, protonation followed by de-protonation of the alcohol on the 4 th carbon is not necessary. James Oliver CE for bioethanol research 76

101 In this work, ESR was attempted for the purpose of identifying the resulting UV-absorbing intermediate(s) as they have been shown previously to have lifetime of less than 2 min [9, 24]. Direct observation of photo-oxidized radicals in an ESR cavity was attempted by irradiating (with a Lumatec lamp) either a pure sucrose solution at ph 13 or a sucrose solution in the presence of hydrogen peroxide, both purged under argon gas, however no radicals were observed (see Supporting information). Our previous NMR study demonstrated that only a small fraction of the carbohydrate is oxidized during the detection process even after relatively long exposure to UV irradiation [9]. We also showed that the presence of electric field increased the sensitivity of the detection thus potentially explaining the absence of detected radicals in our ESR experiment by the absence of electric field. To further investigate the UV absorbing product, carbohydrates were injected and the UV absorption spectra and peak area per mm of the mobility based electropherogram at 266 nm of carbohydrate were determined (Table 3.2-1). James Oliver CE for bioethanol research 77

102 Table 3.2-1: Relationship between carbohydrate, UV absorbance and possible UV absorbing intermediate. HO Arabitol HO Carbohydrate O n.a. pka (25 C) [41] Wavelength at peak apex on the UV absorption spectrum Peak Area per mm of carbohydrate (10-11 ) ** Possible photooxidation pathway * Unknown A,B Structure of type B semidiones[29] * Maltose Sucrose Glucose HO O O HO HO HO HO HO O HO HO O O O [41] [41] B+B A,B Not recorded HO HO O O O H H O HO Rhamnose HO Xylose O n.a O [41] A,B A,B *Pathway for formation of semidiones is shown in Scheme 1 and 2. ** measured on the mobility plot monitored at 266 nm H 3 C O H 3 C O H O H O O H H O H O O H The separation and thus the photo-oxidation pathway take place at a ph above the pk a of the sugars. The absorbance at the maximum of the UV absorption spectrum and the normalized peak area on the related electrophoretic mobility plots were compared for each carbohydrate: Table lists these values obtained in our work and compares them with the type A or B predicted by Gilbert. Gilbert predicted three main different type B semidiones could be formed and this is consistent with the three different values measured for wavelength at the maximum of the UV James Oliver CE for bioethanol research 78

103 spectra for glucose, rhamnose and xylose. Although type B semidiones were not originally detected for maltose [29], the wavelength at the maximum of absorbance would suggest that the same UV absorbing intermediate would be produced as for glucose in similar relative amounts. The highest normalized peak area is obtained for sucrose, which would be consistent with photo-oxidation of both fructose and glucose moieties or possibly an increase in reaction rate of sucrose in comparison to glucose/fructose. Although arabitol might not be fully ionized at this ph, the UV absorption suggests that the same intermediate as for glucose might be formed. 3.2 Simulation of the UV absorption spectra of the potential intermediates in the photo-oxidation reactions In order to determine if the UV absorbing intermediates relevant for CE are linked to semidiones A or B and the pathway proposed by Gilbert et al. [29], the UV-Vis absorption spectra of the latter were predicted (Figure and Table 3.2-2). Most intermediates give theoretical peak UV absorptions in the same range where maximum absorptions are found experimentally, with relative experimental absorption values in reasonable agreement with the relative oscillator field strengths calculated. Peak absorption positions for the type B semidiones and relative intensities (assuming a predominantly transoid conformation) of absorption fitting the results for glucose and sucrose photo-oxidation reasonably well, while the fit is poorer for the other carbohydrates. While the predicted position of the type B semidione absorption maxima derived from xylose are similar to the experimental values (Table 3.2-2), the relative intensities are much greater than observed experimentally (Fig 3.3-2C). James Oliver CE for bioethanol research 79

104 Table 3.2-2: Simulated spectral properties of possible UV absorbing intermediates. Structure of semidiones[29] Carbohydrate Postulated Sucrose, Glucose Calculated wavelength at maximum 261 Experimental wavelength at maximum 266 Calculated oscillator strength at maximum (nonradical) (0.022) B Possible photooxidation pathway Sucrose, Glucose (0.070) B Rhamnose 283 (233) (0.015) B Rhamnose (0.032) Xylose (0.045) B Xylose (0.06) Glucose All monosaccharides 314, 260 (238) (0.09) A Glucose All monosaccharides 280 (247) (0.07) A James Oliver CE for bioethanol research 80

105 3.3 Characterization of the products of the photo-oxidation reaction by 13 C and 1 H NMR. The end products of the photo-oxidation reaction were characterized by NMR spectroscopy. A sample of 13 C-labelled glucose (1 g L -1 ) in 130 mm Na in D 2O was continuously injected into the CE at 10 mbar with no electric field as done previously [24] and proved to give the same UV absorption although four times less intense [9]. 600 µl sample was collected and 13 C and 1 H NMR spectra were recorded. Controls consisting of 13 C-labelled glucose in D 2O and of an untreated 13 C- labelled glucose (1 g L -1 ) in 130 mm Na in D 2O were also measured. Figure shows the 13 C NMR spectrum of the degradation products only: the control spectrum (in 130 mm Na in D 2O) was subtracted from the one of the irradiated solution following normalization on the maxima of the two peaks between 90 and 100 ppm that are only present in glucose. Figure 3.2-2: 13 C NMR spectrum of 1 g L C-labelled glucose continuously and hydrodynamically injected into CE, after subtraction of the spectrum of the control glucose. Both original spectra are shown in supporting information (Figure 3.3-4). Corresponding molecules taken from [40] where R refers to a saturated alkyl group. James Oliver CE for bioethanol research 81

106 The highest 13 C chemical shift experimentally observed in the photo-oxidized 13 C glucose was below 181 ppm (Figure 3.2-2). The mechanism proposed by Gilbert et al. [29] leads to malondialdehyde as an end product that produced one signal with a 13 C chemical shift above ppm under our conditions (Table and Figure 3.3-5A). Sarazin et al. adapted a mechanism from Bucknall et al. [32] predicting dihydroxyacetone as an end product of the photo-oxidation. One of dihydroxyacetone s 13 C chemical shifts is predicted to be around 201 ppm (Figure 3.3-5B). If either mechanism were present, the corresponding concentration would be negligible, as no signal is detected above 181 ppm which could correspond to either malondialdehyde or dihydroxyacetone. 13 C chemical shifts observed below 181 ppm with no corresponding signal between 160 and 80 ppm are consistent with sodium carboxylate functional groups and possibly esters, and disproves the presence of alkenes. Carboxylates have been observed previously in the degradation of glucose in an alkaline solution catalyzed by an electric field in the presence of oxygen forming sodium gluconolactone, sodium gluconate and sodium oxalate as end products [33]. 1 H and 13 C NMR spectra of sodium oxalate, sodium gluconate and gluconolactone were recorded in 130 mm Na in D 2O to facilitate the identification of the observed 1 H and 13 C NMR signals (See Figure and and Table 3.2-3). Note that some 13 C NMR signals of the degradation products of 13 C-labelled glucose are split into multiplets due to coupling with neighboring 13 C nuclei, which is not the case of the measured standard compounds; for that reason multiple signals of the degradation products of 13 C- labelled glucose are sometimes assigned to a single signal of a measured standard compound. Sodium oxalate was not detected in the 13 C NMR spectrum of the photo-oxidized 13 C glucose sample, as shown by the absence of 13 C NMR signal around ppm. 1 H and 13 C chemical shifts are however consistent with the presence of sodium gluconate as a product of the photo-oxidation. Gluconolactone was however not observed through its signal at ppm (Table and Figure 3.3-8) despite the suggested presence of sodium gluconate supporting that the first step in the photo-oxidation reaction is the opening of the ring structure as suggested previously (Scheme and Scheme 3.2-2). The 13 C and 1 H signal assignment in Table shows that the products of the photooxidation contain carboxylates consistent with sodium gluconate but also sodium methanoate, sodium glycolate, and possibly glycerol. The presence of sodium methanoate and sodium glycolate was confirmed by DEPT-135 NMR through the detection of a positive CH signal for sodium methanoate at 172 ppm and the absence of CO signal for sodium glycolate at 180 ppm (Figure 3.3-6). The presence of sodium glycolate and sodium methanoate might be explained by adding oxygen as reactant in the 6 th step of Scheme as hypothesized on Scheme James Oliver CE for bioethanol research 82

107 HO O O O H HO O O O O OR H R H R R O O O HO O O H or HO O O HO H O 2 O R HO O O H HO O O H HO O H R H R O O H HO O O H or R H R O O O H O O O H R O O 2 R O O O O O RO O H or Scheme 3.2-3: Photo-oxidation of glucose in the presence of oxygen: possible reaction pathway leading to sodium methanoate and sodium glycolate (a second possible reaction pathway is shown in Scheme 3.3-2). Gamma irradiation of glucose in the presence of oxygen showed the presence of methanoic acid and glycolic acid as well as various others such as gluconic acid, D-arabino-hexulosonic acid and various compounds with aldehyde functions [34]. Molecules containing aldehyde functional groups are however not detected by 13 C NMR in this study (no peak is present in the region above 190 ppm as expected for aldehyde functional groups). The NMR spectrum of D-arabino-hexulosonic acid is known [35] and include a peak at 104 ppm that our photo-oxidized glucose does not contain. Only gluconic acid is present in our work. This can either be due to the high ph used in our study restricting the pathway, or the use of UV radiation and not 60 Co gamma rays [34] or even the use of D 2O in the sample. Several 13 C NMR signals are still unidentified: a doublet at 61.4 and 60.9 ppm, as well as less intense signals at 167.9, 59.1, 40.0, and 20.0 ppm. This shows the complexity of the photo-oxidation reaction. Additionally, the area of the NMR spectrum of the irradiated glucose and of the scaled NMR spectrum of the initial glucose might allow us to estimate the fraction of glucose photooxidized for the NMR experiment (Equation 3.3-1). James Oliver CE for bioethanol research 83

108 Table 3.2-3: Possible identification of some products from photo-oxidation of 13 C glucose according to their 13C and 1H NMR chemical shifts δ. The individual 1 H and 13 C NMR spectra are shown in supporting information. All compounds listed except sodium oxalate, malondialdehyde and sodium gluconolactone are potentially present in the sample. Sodium Sodium Sodium Sodium Malondial Gluconol Sample Glycerol Methanoate Glycolate Gluconate Oxalate dehyde actone δ( 13 C), ppm , 74.5, 75.8, , 72.8, , 70.6, , , , 74.0, 73.0, , , , 40.0, 20.0 δ ( 1 H), ppm , , , 5.3, 4.1 (massif) (massif) (massif) , , , 63.4, (massif) James Oliver CE for bioethanol research 84

109 3.4 Increasing sensitivity utilizing photo-initiators If the formation of hydroxyl or superoxide radical was the limiting step of the photooxidation, then it would be possible to increase the amount of radical intermediates in the detection window and therefore the sensitivity of the detection by increasing the radical formation. Radical photo-initiators are molecules that form free radicals under UV-Vis light irradiation. In this work, water produces some hydroxyl radicals by Eq. (1) and superoxide radicals can be formed by Eq. (2): H 2 O hv < 190 nm + H Equation e a q + O 2 hv < 190 nm O 2 - Equation The efficiency of the production of hydroxyl radicals depends on the CE lamp intensity (determined by lamp life) as well as the CE detector optics and the intensity of the lowest wavelength (below 190 nm) irradiation reaching the solution. Strong UV irradiation around 190 nm may however not be suitable for most application in CE since it could lead to unwanted degradation reactions. The photo (and thermal) radical initiator hydrogen peroxide (H 2O 2) also generates hydroxyl radicals under UV light (Eq. 3). hv < 190 nm H 2 O 2 2 Equation Hydrogen peroxide (H 2O 2) was tested as a photo-oxidant for detection in CE with varying concentrations of hydrogen peroxide ( to M) present in a BGE of 130 mm Na within the capillary as well as the reservoirs. A sample of 1 g L -1 sucrose was injected and the increase in peak area in the presence of hydrogen peroxide was determined (Fig 3.2-3). James Oliver CE for bioethanol research 85

110 Figure 3.2-3: effect of hydrogen peroxide in BGE on peak area of 1 g L -1 sucrose in 130 mm Na. The Increase in peak area is relative to 1 g L -1 sucrose injected with 130 mm Na BGE (no hydrogen peroxide). The error bar in this graph indicates the highest and lowest value (n=2) for a given run, while the different points indicate different runs. Runs were carried out on the HP3D instrument (n=2) as well as the Agilent The peak area increased in the presence of 130 mm Na with to H 2O 2, but it suffered from poor repeatability. The poor thermal stability of H 2O 2 and the Joule heating within the capillary might have caused excessive thermal degradation of the peroxide leading to a variation in the results (Figure 3.2-2). The capillary is air cooled to 15 C externally with a calculated internal temperature increase of only 2 C (see Equation [36]), so thermal degradation should be very limited. Alternatively, the poor repeatability may also be explained by the strong oxidizing potential of H 2O 2 leading to significant reduction reaction at the cathode. The highest concentrations ( to M) led to the poorest repeatability and/or to a peak of inverse polarity, possible due to the high amount of water produced by peroxide decomposition (water having a very low refractive index) or the high radical concentration causing side reactions. It was thus decided to rather use a true photo-initiator (thermally stable and with a poor oxidizing potential). The most characterized radical photo-initiator, 2,2-dimethoxy-2-phenylacetophenone, DMPA, has very limited aqueous solubility [37]. Irgacure 2959 (1-[4-(2-hydroxyethoxy)-phenyl]-2-hydroxy-2-methyl-1-propan-1-one) was chosen instead as a photo-initiator since it is water-soluble. Irgacure 2959 is more thermostable then hydrogen peroxide and should not be reduced at the cathode during electrophoresis separation. Irgacure 2959 was added to 130 mm Na at varying concentrations (10-3 to 10-9 M), see Figure James Oliver CE for bioethanol research 86

111 Figure 3.2-4: The effect of Irgacure 2959 in BGE on peak area of 1 g L -1 sucrose. (A) The increase in peak area is shown relative to 1 g L -1 sucrose injected with 130 mm Na BGE. Separations were carried out in a conventional capillary (solid line) and a high sensitivity capillary (dotted line). Error bar indicates relative standard deviation (n=5) (B) Overlay of sucrose peak in a conventional capillary without Irgacure 2959 (dash line) and with M Irgacure 2959 (solid line), in a high sensitivity capillary without Irgacure 2959 (dotted line) and with M Irgacure 2959 (dash dotted line). James Oliver CE for bioethanol research 87

112 The addition of Irgacure 2959 led to a significant increase in peak area at the lowest Irgacure 2959 concentrations. This may be due to an enhanced photo-oxidation reaction. The photolysis of Irgacure 2959 led to a variety of free radicals [38] (and Figure 3.3-9). These radicals could lead to hydroxyl radicals as in the pathway previously discussed or some may directly photooxidize the carbohydrate. The maximum increase of 42 % is observed with no significant difference between M and M in a standard bare fused silica capillary. The RSD up to M has a maximum of 12 %, that can relate to fluctuations in the injection amount not accounted for by an internal standard, as observed in previous studies [9, 39]. Using a high-sensitivity capillary the concentration of Irgacure 2959 that yielded the highest increase in peak area shifts from M to M. The shift may be due a more efficient photo-decomposition producing radicals caused by the extended light path in the capillary window and the fact that the bubble shape of the detection window may focus the irradiation. This leads to a strong reduction in the amount of required photo-initiator, but no change in the maximum increase in sensitivity. A higher concentration of radicals likely leads to terminations or other side reactions and do not increase the sensitivity of the detection in CE. The system can thus be considered as optimized in terms of the addition of photo-initiator. A lower concentration of photo-initiator is preferred as Irgacure 2959 absorbs at nm and at a concentration of M its absorbance is negligible (Figure ). At M in both capillaries types, there is a large error consistent with a large amount of free radicals being produced, leading to an uncontrolled reaction with alternative pathways. The increase in radical concentration also leads to an increase in band broadening. Joule heating from high salt concentration in the capillary window may contribute to it. These use of the high sensitivity capillary lead to a change in peak shape (Figure 3.2-4B) however no change in peak shape was observed due to the addition of the photo-initiator, only an increase in peak area. Additionally no change in peak shape between conventional and high sensitivity capillaries has been observed in other separations with direct UV detection and no photo-oxidation reaction (Figure ). The change of peak shape is therefore likely a result of differences in the photo-oxidation detection between a conventional and a high sensitivity capillary and is not related to the separation, for example to stacking. The limit of detection (LOD) of various carbohydrates were determined (Table 3.2-4) in a high sensitivity capillary with 130 mm Na containing M Irgacure Direct detection with the photo-initiator resulted in a lower LOD than the popular HPLC-RID separation detection modes that are currently used in biotechnology. In comparison the CE-contactless conductivity detection (C 4 D) [17] that has recently been developed has a lower (better) LOD. Detection with C 4 D James Oliver CE for bioethanol research 88

113 requires limiting the ionic strength, thus the BGE concentration to values lower than the ones leading to optimal resolutions [9, 22, 24]. Table 3.2-4: Comparison of limit of detection (LOD) between different analytical separation and detection methods. CE separation with direct UV detection (this study) was at 24 kv in 90 cm (81.5 cm effective length) high sensitivity capillary in 130 mm Na with M Irgacure System Mode Detector Analyte LOD * Ref (mg L -1 ) High performance liquid HILIC RID Glucose 130 [6] chromatography (HPLC) Ligand exchange (Pb 3+ ) Glucose 21 [4] Cation exchange resin Glucose 70 [8] Ion chromatography (IC) HPAEC PAD Glucose [11] Capillary High ph buffer Contactless Glucose 0.11 [17] Electrophoresis (CE) conductivity Direct UV Glucose 1.8 This study Arabitol 0.87 Sucrose 1.6 Maltose 2.8 Xylose 3.4 Limit of detection (LOD) as defined by [17] as the signal to noise ratio equal to 3. Noise level in CE (in this study) with a BGE of 130 mm Na = 0.01 mau. 4 Conclusions The photo-oxidation pathway in the direct detection of carbohydrates in CE is different from the ones previously proposed. The products of the reaction were characterized for the first time using NMR spectroscopy of photo-oxidized, fully 13 C labeled glucose and potential end products. This discarded the presence of some end products of previously suggested pathways, such as malondialdhyde and dihydroxyacetone. The end products of the photo-oxidation were shown to include carboxylates that are consistent with glucose being photo-oxidized into sodium gluconate, sodium glycolate, sodium methanoate and possible glycerol. Oxygen may play a role in the formation of these products and might also then play a role in the formation of the intermediate(s) absorbing UV at about 266 nm. The sensitivity of the detection was improved by increasing the amount of free radicals present by the use of photo-oxidants. Hydrogen peroxide is unstable leading to a decrease in repeatability. Irgacure 2959 was more repeatable and was able to increase the peak area by up to 42 % at a concentration of M in a high sensitivity capillary and M in a standard fuse silica capillary. Alternative photo-initiators may further increase sensitivity, but their selection would first require a more precise identification of the UV-absorbing intermediate. The increase in James Oliver CE for bioethanol research 89

114 sensitivity will enable the use of coated capillaries that will decrease analysis time for all DAD types. The improved method will be useful for analysis of carbohydrates in plant, food, fermentation and metabolic studies. Acknowledgements: The authors would like to acknowledge the Key Centre for Polymer and Colloids at the University of Sydney for donating photo-initiators. We wish to thank Dr Michael Phillips, Prof Paul Peiris, Julie Markham, Danielle Taylor, Adam Sutton, David Fania (UWS), and Prof Emily Hilder (UTas) for fruitful discussions as well Joel Thevarajah (UWS) for the oligoacrylates injection. References [1] A.I. Ruiz-Matute, O. Hernández-Hernández, S. Rodríguez-Sánchez, M.L. Sanz, I. Martínez- Castro, J. Chromatogr. B, 879 (2011) [2] D.R. Knapp, Handbook of analytical derivatization reactions., Wiley, New York, [3] H. Caruel, L. Rigal, A. Gaset, J. Chromatogr., 558 (1991) 89. [4] S. Meisen, J. Wingender, U. Telgheder, Anal. Bioanal. Chem., 391 (2008) 993. [5] M. D'Amboise, D. Noēl, T. Hanai, Carbohydr. Res., 79 (1980) 1. [6] J.L. Chávez-Servıń, A.I. Castellote, M.C. López-Sabater, J. Chromatogr. A, 1043 (2004) 211. [7] R. Pecina, G. Bonn, E. Burtscher, O. Bobleter, J. Chromatogr., 287 (1984) 245. [8] F. Chinnici, U. Spinabelli, C. Riponi, A. Amati, Journal of Food Composition and Analysis, 18 (2005) 121. [9] J.D. Oliver, M. Gaborieau, E.F. Hilder, P. Castignolles, J. Chromatogr. A, 1291 (2013) 179. [10] R.D. Rocklin, C.A. Pohl, J. Liq. Chromatogr., 6 (1983) [11] V.P. Hanko, J.S. Rohrer, Anal. Biochem., 283 (2000) 192. [12] T.R.I. Cataldi, C. Campa, G.E. De Benedetto, Fresenius J. Anal. Chem., 368 (2000) 739. [13] H.P. Smits, A. Cohen, T. Buttler, J. Nielsen, L. Olsson, Anal. Biochem., 261 (1998) 36. [14] C. Klampfl, M. Himmelsbach, W. Buchberger, in: N. Volpi (Ed.), Capillary Electrophoresis of Carbohydrates, Humana Press, 2011, p. 1. [15] A. Gürel, J. Hızal, N. Öztekin, F. Erim, Chromatographia, 64 (2006) 321. [16] A.Z. Carvalho, J.A.F. da Silva, C.L. do Lago, Electrophoresis, 24 (2003) [17] P. Tůma, K. Málková, E. Samcová, K. Štulík, Anal. Chim. Acta, 698 (2011) 1. [18] S. Hoffstetter-Kuhn, A. Paulus, E. Gassmann, H.M. Widmer, Anal. Chem., 63 (1991) [19] A. Bazzanella, K. Bächmann, J. Chromatogr. A, 799 (1998) 283. [20] T.J. O'Shea, S.M. Lunte, W.R. LaCourse, Anal. Chem., 65 (1993) 948. [21] L.A. Colon, R. Dadoo, R.N. Zare, Anal. Chem., 65 (1993) 476. [22] S. Rovio, J. Yli-Kauhaluoma, H. Sirén, Electrophoresis, 28 (2007) [23] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, P. Gareil, Talanta, 99 (2012) 202. [24] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, J.-M. Mallet, P. Gareil, Anal. Chem., 83 (2011) [25] M. Vaher, M. Koel, J. Kazarjan, M. Kaljurand, Electrophoresis, 32 (2011) [26] H.E. Gottlieb, V. Kotlyar, A. Nudelman, The Journal of Organic Chemistry, 62 (1997) [27] R. Dennington, T. Keith, J. Millam, GaussView Version 4.1.2, Semichem Inc., Shawnee Mission, KS, [28] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, P. Gareil, Talanta, 103 (2013) 301. [29] B.C. Gilbert, D.M. King, C.B. Thomas, J. Chem. Soc., Perkin Trans. 2 (1982) 169. [30] M.G. Gonzalez, E. Oliveros, M. Wörner, A.M. Braun, J. Photochem. Photobiol. C: Photochem. Rev., 5 (2004) 225. James Oliver CE for bioethanol research 90

115 [31] Agilent, Personal Communication on Agilent 7100 DAD specifications (2013). [32] T. Bucknall, H.E. Edwards, K.G. Kemsley, J.S. Moore, G.O. Phillips, Carbohydr. Res., 62 (1978) 49. [33] M. Tominaga, T. Shimazoe, M. Nagashima, I. Taniguchi, Electrochem. Commun., 7 (2005) 189. [34] M.N. Schuchmann, C. von Sonntag, J. Chem. Soc., Perkin Trans. 2, 0 (1977) [35] A.F. Cirelli, E.M. Oliva, R.M. De Lederkremer, Phytochemistry, 28 (1989) [36] C.J. Evenhuis, R.M. Guijt, M. Macka, P.J. Marriott, P.R. Haddad, Anal. Chem., 78 (2006) [37] I. Lacik, S. Beuermann, M. Buback, Macromolecules, 34 (2001) [38] H. Fischer, R. Baer, R. Hany, I. Verhoolen, M. Walbiner, J. Chem. Soc.-Perkin Trans. 2 (1990) 787. [39] S. Rovio, H. Simolin, K. Koljonen, H. Sirén, J. Chromatogr. A, 1185 (2008) 139. [40] J.B. Lambert, Organic Structural Spectroscopy, Prentice Hall PTR, [41] Y.H. Lee, T.I. Lin, J. Chromatogr. B, 681 (1996) 87. James Oliver CE for bioethanol research 91

116 3.3 Publication supporting information Supporting information for: Understanding and improving direct UV detection of monosaccharides and disaccharides in free solution capillary electrophoresis James D. Oliver 1, Adam A. Rosser 3, Christopher M. Fellows 3, Yohann Guillaneuf 4, Jean-Louis Clement 4, Marianne Gaborieau 2, Patrice Castignolles 1,2 * 1) University of Western Sydney, Australian Centre for Research On Separation Sciences (ACROSS), School of Science and Health, Parramatta Campus, Locked Bag 1797, Penrith NSW 2751, Australia 2) University of Western Sydney, Molecular Medicine Research Group (MMRG), School of Science and Health, Parramatta Campus, Locked Bag 1797, Penrith NSW 2751, Australia 3) University of New England, School of Science and Technology, Armidale NSW 2351, Australia 4) Aix-Marseille Université, CNRS, Institut de Chimie Radicalaire UMR 7273, Avenue Escadrille Normandie-Niemen, Marseille Cedex 20, France James Oliver CE for bioethanol research 92

117 1 Capillary electrophoresis separation with dynamic coating A typical separation was performed with a dynamic coating adapted from [1]. The separation was faster but the sensitivity poor (compare Figure A and B). Materials: L+xylitol 99 % was sourced from Alfa Aesar (Ward Hill, MA, USA).Mannose 99 %, L+arabinose 99 %, poly(diallyldimethyl ammonium chloride) (polydadmac) solution 20 % (w/w), alginic acid sodium salt and lithium hydroxide monohydrate 98 % were sourced from Sigma-Aldrich (Castle Hill, NSW, Australia). D+galactose 99 % was sourced from Scharlau (Barcelona, Spain). Other materials are as in manuscript. Method: Capillary electrophoresis was carried out as in manuscript with the following alterations. The capillary was 60 cm (51.5 cm effective length) and coated during preparation by flushing with 1 % w/v polydadmac in water for 30 min followed by with 1 % w/v alginic acid in water for 17 min and polydadmac again for a further 30 min. The back ground electrolyte (BGE) was 110 mm lithium hydroxide. The standard was injected at 34 mbar for 5 sec followed by an injection of BGE in the same manner. The voltage was ramped to 16 kv over 1 min. Signals were monitored at 200 nm and 270 nm with a 10 nm bandwidth. James Oliver CE for bioethanol research 93

118 Figure 3.3-1: Separation of fibre standard in a fused silica capillary (A) and with the coated capillary (B) in 110 mm Li. Capillary was coated with alginic acid and polydadmac (previous page). Fibre standard of arabitol, xylitol, galactose, glucose, rhamnose, mannose, arabinose and xylose (1 g L -1 each). James Oliver CE for bioethanol research 94

119 2 Electron Spin Resonance (ESR) spectroscopy Method ESR studies were carried out on a Bruker EPR spectrometer. A Lumatec lamp, with a peak intensity at 350 nm, was used to irradiate the samples just before the ESR cavity. A solution of 100 mm Na with 25 mm H 2O 2 and 2 g L -1 sucrose, purged under argon, was continuously pumped through the quartz flow cell at 400 ml min -1. The H 2O 2 was varied between 25 mm and 2.78 M with the highest concentration leading to bubbles formation in the cavity. The Na concentration was varied between 100 and 200 mm. 8 g L -1 of ethanol was added to the solution to test the system. Results It was expected the lamp would break down the H 2O 2 into hydroxyl radicals which would then react with sucrose to form radicals that were described by Gilbert et al.[2]. At hydrogen peroxide concentrations of 2.78 M, bubbles were observed after the cavity, assumingly due to formation of oxygen. However the absence of signal from both sucrose but also ethanol indicates that the hydrogen peroxide under this irradiation generates no free radical stable enough to be detected, contrary to Gilbert s observations with a different system generating hydroxyl radicals. James Oliver CE for bioethanol research 95

120 3 Prediction of UV-Vis absorption spectra As the formation of semidione B was similar to the pattern of detection in capillary electrophoresis (higher the ph, high the amount of UV absorbing species) the UV absorbing species may be one of the intermediate leading to the formation of semidione B. In order to determine this, UV-Vis absorption spectra predictions were carried out based on the HOMO-LUMO gap (method in manuscript). Scheme 3.3-1: List of potential UV absorbing intermediates based on Gilbert et al.[2] and the assignments. James Oliver CE for bioethanol research 96

121 Table 3.3-1: Results of TD-B3LYP/6-31++G(2d, 2p) Calculations. Electronic energies (E), zero point energies (E ZPE), thermal energies (U), enthalpies (H) and Gibbs Free Energies (G) in hartrees and entropies (S) in cal mol 1 K 1. Molecule E E ZPE U H G S TBsfG TBsfG1_nr TBsfG TBsfG2_nr TBsfR TBsfR1_nr TBsfR TBsfR2_nr TBsfX TBsfX1_nr TBsfX TBsfX2_nr TAS TAS1_nr TAS TAS2_nr James Oliver CE for bioethanol research 97

122 Table 3.3-2: Principal Features of Predicted Spectra. Molecule HOMO-LUMO N=3 (3 predicted excitations, major λ max gap (hartrees) contributor in bold) TBsfG , 505, TBsfG1_nr , 528, TBsfG , 490, TBsfG2_nr , 459, TBsfR , 543, TBsfR1_nr , 604, TBsfR , 571, TBsfR2_nr , 601, TBsfX , 525, TBsfX1_nr , 530, TBsfX , 524, TBsfX2_nr , 495, TAS , 445, TAS1_nr , 387, TAS , 471, TAS2_nr , 421, James Oliver CE for bioethanol research 98

123 James Oliver CE for bioethanol research 99

124 Figure 3.3-2: UV absorption spectra of glucose (A) rhamnose (B) and xylose (C) during CE separation (solid line) overlaid with predicted spectra of type B semidione with radical (dashed line and dotted line). James Oliver CE for bioethanol research 100

125 4 1 H and 13 C NMR spectroscopy Figure and Figure show the 1 H and 13 C NMR spectra, respectively, of 13 C labelled glucose before and after irradiation. Figure 3.3-3: 1 HNMR spectra of 1 g L C glucose in 130 mm Na before (black) and after (red) continuous and hydrodynamic injection into CE. James Oliver CE for bioethanol research 101

126 Figure 3.3-4: 13 CNMR spectra of 1 g L Cglucose in 130 mm Na before (black) and after (red) continuous hydrodynamic injection into a capillary. The fraction of glucose degraded under irradiation was estimated as follows. The spectrum of the initial glucose has been scaled to fit the glucose left in the irradiated sample. The area of the scaled spectrum of the initial glucose, A G thus represents the non-degraded glucose. The difference of the area of the spectrum of the irradiated glucose, A I, with A G thus represents the degraded glucose in the irradiated sample. The fraction of degraded glucose, F, is calculated as: F=( A I - A G) / A I Equation F is estimated at 80 % in our pressure mobilization experiment using the 13 C NMR spectra. For this particular experiment, the velocity of glucose in the capillary was 1.23 cm min -1, while glucose migrates at 25 min in a 90 cm capillary, at a velocity of 3.6 cm min -1. Taking the ratio of the velocities into account, the fraction of glucose photo-oxidised in a typical CE separation can thus be estimated at 27 % of the glucose in a 90 cm capillary. This large glucose consumption would not be consistent with the previous observation of the change of absorbance with residence time in the window [3] or multiple passes through the window [4]. This would not be consistent either with James Oliver CE for bioethanol research 102

127 previous NMR results on irradiated non-labelled glucose [4]. Note that the relaxation times were not determined and the values given in our conditions with the Equation above are thus only crude estimates HO O (B) Figure 3.3-5: Experimental 13 C NMR spectrum for malondialdehyde tetrabutylammonium salt in the same conditions as Figure (A) and predicted 13 C NMR chemical shifts for dihydroxyacetone (B) (predictions performed with ChemNMR at neutral ph). James Oliver CE for bioethanol research 103

128 Figure 3.3-6: 13 C NMR spectrum (black) and DEPT-135 NMR spectrum (red) of 1 g L C glucose in 130 mm Na after continuous hydrodynamic injection into a capillary. A DEPT-135 NMR spectrum exhibits positive CH and CH 3 signals, negative CH 2 signals, and no signal for other carbons. James Oliver CE for bioethanol research 104

129 Figure 3.3-7: 1 H NMR spectra of A. glycerol (solid black), B. sodium oxalate (solid red), C.sodium glycolate (dotted black), D. sodium gluconate (dotted red), E. sodium methanoate (dashed black) and F. gluconolactone (dashed red). The chemical shifts predicted with ChemNMR are shown on the molecules on the left. James Oliver CE for bioethanol research 105

130 Figure 3.3-8: 13 C NMR spectra of A. glycerol (solid black), B. sodium oxalate (solid red), C. sodium glycolate (dotted black), D. sodium gluconate (dotted red), E. sodium methanoate (dashed black) and F. gluconolactone (dashed red). The chemical shifts predicted with ChemNMR are shown on the molecules on the left. James Oliver CE for bioethanol research 106

131 HO O H HO H O O H HO (Multiple steps ) O H O H HO H O HO O O HO HO H O Scheme 3.3-2: A second possibility for the oxidation of glucose in the presence of oxygen leading to sodium methanoate and sodium glycolate as well as sodium glycerate. James Oliver CE for bioethanol research 107

132 5 Temperature increase in the capillary The Joule heating inside the capillary was measured by the sum of the Equations to All equations and nomenclature were from [5]. The radial temperature difference ΔT radial across the electrolyte was calculated using Equation The temperature difference ΔT across wall across the fuse silica wall as well as the polyimide coating was calculated using Equation The temperature difference ΔT air across the air layer surrounding the capillary was calculated using Equation ΔΔTT rrrrrrrrrrrr = TT aaaaaaaa TT wwrrrrrr = = ΔΔTT aaaaaaaaaaaa wwwwwwww = ΔΔTT cccccccccccccc = VVVV λλ wwrrrrrr llll dd oo dd ii PP LL λλ cccccccccccccc llll dd oo dd ii PP LL λλ eeeeeeeetttttttttttttt PP LL Equation ΔΔΔΔ aaaaaa = xx aaaaaa PP = ππdd 00 λλ aaaaaa LL 11 PP ππdd 00 hh LL Equation Equation In these equations, λλ electrolyte is the thermal conductivity of the electrolyte, d 0 is the external diameter of the capillary, d i ids the internal diameter of the capillary, P/L is the power per unit length, V is the applied voltage, I is the electric current, L is the total length of the capillary, X air is the thickness of the stationary layer surrounding the capillary, λλ air is the thermal conductivity of air, and h is the heat transfer co-efficient. λλ wall and λλ coating are the thermal conductivities of the capillary wall and polyimide coating respectively. The thermal conductivities values used for the fuse silica wall and the polyimide coating were 1.40 and W.m -1.K -1 respectively [5-7]. James Oliver CE for bioethanol research 108

133 6 Increasing sensitivity utilizing photo-initiators HO O O hv HO O + O Figure 3.3-9: First step in photolysis of Irgacure 2959 adapted from [8]. Products react further to form a variety of radicals. Figure : UV absorption spectra of Irgacure 2959 at M (red) and M (black) in 130 mm Na, obtained using pressure mobilization in the 7100 CE instrument using a high sensitivity capillary and pressure mobilization. James Oliver CE for bioethanol research 109

134 Figure : Separation of oligoacrylate in a high sensitivity capillary (black) and normal fuse silica capillary (red). The initiated monomer (AA1) peak [9] is identified with the blue box. Separation conditions: 30 kv, 25 C, 75 mm sodium borate buffer. 7 References [1] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, P. Gareil, Talanta, 99 (2012) 202. [2] B.C. Gilbert, D.M. King, C.B. Thomas, J. Chem. Soc., Perkin Trans. 2 (1982) 169. [3] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, J.-M. Mallet, P. Gareil, Anal. Chem., 83 (2011) [4] J.D. Oliver, M. Gaborieau, E.F. Hilder, P. Castignolles, J. Chromatogr. A, 1291 (2013) 179. [5] C.J. Evenhuis, R.M. Guijt, M. Macka, P.J. Marriott, P.R. Haddad, Anal. Chem., 78 (2006) [6] T. Nishikawa, H. Kambara, Electrophoresis, 17 (1996) [7] J.H. Knox, Chromatographia, 26 (1988) 329. [8] H. Fischer, R. Baer, R. Hany, I. Verhoolen, M. Walbiner, J. Chem. Soc.-Perkin Trans. 2 (1990) 787. [9] M. Gaborieau, T.J. Causon, Y. Guillaneuf, E.F. Hilder, P. Castignolles, Aust. J. Chem., 63 (2010) James Oliver CE for bioethanol research 110

135 4. Publication Ethanol determination using pressure mobilization and free solution capillary electrophoresis by photo-oxidation assisted ultraviolet detection Contribution to PhD work, field, and candidates personal and professional development Ethanol determination with CE The limitation of the direct UV detection for monitoring fermentations was that ethanol produced by fermentation (as discussed in ) could not be detected. There is no single method that can determine ethanol and carbohydrates in a complex sample (see 1.4). HPLC on a hydrogen form resin cannot resolve the common fiber sugars xylose and galactose and HPAEC does not resolve the sample matrix from the ethanol. In CE, determination had only been achieved with MKCE which is incompatible with complex samples (see 1.4). Recently headspace CE has been investigated [145] however ethanol could still not be detected. In previous work (unpublished), ammonium hydroxide and methyl amine were both used to raise the ph instead of Na in the BGE in an attempt to adapt the method for use the CE-MS (Mass Spectrometry). It was found that the use of methyl amine in the BGE resulted in a loss of signal, likely by interfering with the photo-oxidation reaction. Similarly in a different experiment, 1 % (v/v) methanol was added to the BGE in order to slow the EOF and increase the resolution (4 th publication supporting information; Figure 5.3-4). Methanol was also found to inhibit the signal. Due to these unexpected results and the understanding gained in the 2 nd publication, it was successfully hypothesized in the 3 rd publication that ethanol could be detected by photo-oxidation interference. The interference was investigated by 13 C NMR, as with the previous (2 nd ) publication. It was found that the modified reaction did not produce any new end products. In order to determine if this new photo-oxidation interference detection was quantitative, it was tested with a simple pressure mobilization experiment and a vodka sample. The method showed excellent recovery for ethanol. For samples requiring separation, such as fermentation samples, a CE method was developed and tested with a simple spiked fermentation sample, which had good recovery (110 % without an internal standard). The method was used to detect ethanol production in fiber fermentation samples. When combined with an adequate separation of the carbohydrates, both injections could give an overview of the fermentation process. James Oliver CE for bioethanol research 111

136 The complex samples produced by lignocellulosic fiber hydrolysis (as discussed in section and 1.2.2) and the following fermentation (as discussed in section 1.2.3) requires a separation method with high resolution. The number of samples produced requires a method with high throughput. The 4th publication looked at improving both the resolution and throughput in CE by determining the influence the BGE has on the separation. As all the resolutions studied were with CE, and thus all asymmetrical peaks, a resolution equation was chosen that was tailored for asymmetrical peaks as opposed to the typical resolution equation used in the first publication that assumes the peaks are symmetrical. The 4 th publication provides a list of recommended BGEs that would provide the best separation depending on the type of fermentation. Fermentation samples with known sugar amounts were quantitatively compared by CE, HPLC and HPAEC and the results showed that the three methods were quantitative and the values were in close agreement (less than 7 % difference from the average total detected amount). A fermentation of hydrolyzed plant fiber from Opuntia ficus-indica was fermented to arabitol and ethanol by the yeast Pichia stipitis. The hydrolyzed sugars and the end-product arabitol were monitored by CE. Ethanol was monitored by CE coupled to pressure mobilization which was developed in the 3 rd publication. Together these 2 methods gave an overview of the fermentation process. The research question of the 3rd publication was Can the photo-oxidation detection be used to quantify ethanol in fermentation samples? Contribution to my personal development This publication contributed to the field of study by providing a new method for the detection of ethanol and other non-uv absorbing molecules. This new method is quantitative with both simple pressure mobilization as well as CE coupled to pressure mobilization. This publication contributed to my personal development by increasing my understanding of radical chemistry. This publication contributed to my professional development by its presentation at the 2013 HPLC conference in Hobart, Australia. The talk given by Dr Patrice Castignolles showcased some of the work and the interest generated led to an invitation to publish the work in a special issue of the Journal of Chromatography A that was related to the HPLC conference. This publication had 2 co-authors. The last author, Dr Patrice Castignolles provided the direction of the paper. Dr Marianne Gaborieau provided assistance with performing 13 C NMR spectroscopy experiments. James Oliver CE for bioethanol research 112

137 I was able to overcome the main weakness of CE with direct UV detection in regards to its application in ethanol fermentation monitoring, the impossibility to detect and quantify ethanol. I performed some experiments with head space GC however I decided not to pursue since this meant having to use two different instruments. I, along with Patrice, developed the theory of detection of alcohols by photo-oxidation interference after observations made from previous experiments in our laboratory (now seen in fourth publication supporting information). I developed the method for the detection using pressure mobilization and using CE. I also selected the standard beverage and fermentation sample and applied the method to them. I performed all background research, experiments, data acquisition and analysis as well as writing the first draft of the publication. James Oliver CE for bioethanol research 113

138 4.2 Publication Ethanol determination using pressure mobilization and free solution capillary electrophoresis by photo-oxidation assisted UV detection James D. Oliver, a Marianne Gaborieau, b and Patrice Castignolles* a a University of Western Sydney (UWS), Australian Centre for Research on Separation Science (ACROSS), School of Science and Health, Locked Bag 1797, Penrith NSW 2751, Australia, james.oliver@uws.edu.au, p.castignolles@uws.edu.au b University of Western Sydney (UWS), Molecular Medicine Research Group (MMRG), School of Science and Health, Locked Bag 1797, Penrith NSW 2751, Australia, m.gaborieau@uws.edu.au * Corresponding author: p.castignolles@uws.edu.au Abstract: Free solution capillary electrophoresis (CE) can separate and quantify carbohydrates using a simple direct UV detection based on a photo-oxidation reaction taking place in the detection window without any labeling. Ethanol interferes with this photo-oxidation reaction. We thus present the first detection and quantification of ethanol using either a simple pressure mobilization set-up or CE. Ethanol can be detected down to 34.9 mg L -1 and quantified in the range 117 mg L mg L -1 through the interference with photo-oxidization of 2 g L -1 sucrose. CE can thus separate and quantify both carbohydrates and ethanol, for example to monitor a lignocellulosic fermentation process. The method is not limited to ethanol and applies to alkyl amines and other alcohols and likely to most molecules possessing the ability to react with free radicals assuming they can be sufficiently separated from each other. Keywords: ethanol detection; pressure mobilization; capillary electrophoresis; photo-oxidation detection; nuclear magnetic resonance spectroscopy 1 Introduction The determination of ethanol is essential for the analysis of ethanol fermentations and related alcoholic beverages. Bioethanol fermentation of lignocellulosic material is an important process that will hopefully significantly reduce the global demand on fossil fuels. Available methods for the detection and quantification of ethanol in complex matrices are few. Typical methods for the determination of ethanol include Gas Chromatography with Flame Ionization Detection (GC-FID) [1], High Performance Liquid Chromatography (HPLC) with Refractive Index detection (RI) on a cation exchange resin [2] or High Performance Anion Exchange Chromatography (HPAEC) with Pulsed James Oliver CE for bioethanol research 114

139 Amperometric Detection (PAD) [3]. The detection of underivatised ethanol is challenging due to its lack of UV absorption or fluorescence emission. In ethanol fermentation, an analytical method is more advantageous if it can determine both carbohydrates and ethanol. GC methods require derivatization of carbohydrates to make them volatile like ethanol [4], while HPLC [5] and HPAEC have high running costs and, in the case of HPLC, may suffer from poor robustness and recovery [5]. Additionally, no single separation technique can determine simultaneously ethanol and a complex mixture of carbohydrates in a complex matrix such as that of a lignocellulosic fermentation. Some modes of Capillary Electrophoresis (CE) have previously been used in the detection of ethanol. Ethanol and other solvents have been previously quantified by Micellar ElectroKinetic capillary Chromatography (MEKC) with indirect detection [7] however it requires the use of sodium dodecyl sulfate (SDS) surfactant that may interact with proteins and lipids present in complex samples, such as lignocellulosic fermentations. CE with PAD [8] or indirect UV detection [9] was able to detect ethanol however no quantification was carried out. CE with direct UV detection at high ph is a simple and robust method developed for carbohydrate analysis [10]. The separation has been applied to wide variety of complex matrices including forensic, food, beverage and pharmaceutical samples [6], fruit juices and cognac [10], and complex acid treated plant fiber samples [5,11]. Ethanol was however never determined by this method limiting its application for monitoring ethanol fermentations. Direct UV detection of carbohydrates in CE at high ph was originally suggested to be due to enediolate formation [6,10] but later shown to be due to be a photooxidation reaction [5,6]. This photo-oxidation reaction takes place directly in the detection window [12,13]. Hydroxyl and/or superoxide related radicals may be produced following minimal but sufficient decomposition of water at the low wavelength UV irradiation in the detection window [14], then react with the carbohydrates. Alternatively the carbohydrates may be directly photodecomposed by the irradiation [15]. In both cases the radicals obtained from the carbohydrates decompose through a pathway containing UV-absorbing ( nm) intermediates [13,16] to carboxylate decomposition products [13]. Multiple passes through the detection window in one experiment (reversing the electric field after each pass) revealed that the electrophoretic mobility of the carbohydrates is constant but the peak intensity increases for 6 passes before decreasing [5]. The UV absorption at nm is observed with a CE Diode Array Detector (DAD) but not with a classical grate spectrophotometer [12]. Ethanol might also encounter some photo-oxidation under these conditions [17], but it does not lead to any UV absorption. Ethanol undergoes hydrogen abstraction in the presence of some free radicals e.g. in the presence of peroxides [18] or in radical polymerization [19,20]. We hypothesized that ethanol would interfere with the photo-oxidation reaction and hence the detection of the carbohydrate and this interference would lead to a change James Oliver CE for bioethanol research 115

140 in direct UV detection in carbohydrates proportionally to the amount of ethanol present. The aim of this study was to investigate a detection method for ethanol with free solution CE equipment compatible with both pressure mobilization and free solution CE through its interference with the photo-oxidation reaction, to investigate how ethanol could interfere with the detection of carbohydrates and to apply the detection method to fermentation samples and alcoholic beverages. The long term goal is to develop a separation method that can determine both ethanol and carbohydrates in a complex sample such as the fermented lignocellulosic plant fiber. 2 Materials and methods 2.1 Materials Water was of MilliQ quality (Millipore, USA). Sodium hydroxide pellets (Na) 98 %, absolute ethanol 99.5 % and magnesium chloride hexahydrate 99 % were obtained from Sigma- Aldrich (Australia). Xylitol 99 %, sucrose 99 % and ammonium sulfate 99 % were obtained from Alfa Aesar (USA). Fused-silica capillaries (50 µm i.d., 360 µm o.d.) were obtained from Polymicro (USA). Triethylamine 99.5 % and tert-butanol 99 % was obtained from BDH (UK). Deuterium oxide (D, 99.9 %) and fully 13 C-labeled glucose 99 % were sourced from Cambridge Isotope Laboratories (USA). Yeast extract was obtained from Oxoid (Australia). Monopotassium phosphate 99 % was obtained from Univar (Australia). Vodka (declared alcohol content 37 %) was produced commercially in Australia and purchased locally. The fermentation sample, after dilution, was comprised of 500 mg L -1 of each glucose, fructose and yeast extract and of 0.50 mg L -1 of each MgCl 2, (NH 4) 2SO 4 and KH 2PO Free solution capillary electrophoresis (CE) and pressure mobilization The instruments were a MDQ P/ACE (Beckman) and a 7100 CE (Agilent) with DADs monitoring at 200 nm and 266 nm with a 10 nm bandwidth. Samples were injected by applying 14 mbar of pressure for 8 s ( 10 nl) followed by mobile phase or background electrolyte (BGE) injected in the same manner. At the end of a series of injection, the capillary was flushed 1 min with Na 1 M, 10 min with water and 10 min with air. Integration was performed using Karat 32 (Beckman) or Chemstation (Agilent) software. James Oliver CE for bioethanol research 116

141 2.2.1 Pressure mobilization The capillary length was 90 cm with an effective length of 10 cm on the MDQ P/ACE (Beckman) and of 8.5 cm on the 7100 CE (Agilent) instruments. The mobile phase was comprised of 130 mm Na unless otherwise specified. Sucrose and xylitol do not reduce in the presence of 130 mm Na in water and therefore their solutions were prepared in such medium. The capillary was pre-treated prior to use and between each run by flushing with the mobile phase for 5 min. Pressure mobilization was at 50 mbar unless otherwise specified. For NMR spectroscopy, 1 g L -1 of 13 C labeled glucose and 2 g L -1 of ethanol in 130 mm Na in D 2O was pressure injected continuously at 50 mbar into a 35 cm capillary (26.5 cm effective length) on the 7100 CE instrument with the lamp on; 130 µl was collected, and made up to 580 µl with 130 mm Na in D 2O Free solution capillary electrophoresis (CE) The capillary length was 90 cm with an 81.5 cm effective length on the 7100 CE (Agilent). The BGE consisted of 130 mm Na with 2 g L -1 of sucrose in the capillary and 130 mm Na only, in the inlet and outlet vials. The capillary was pre-treated prior to use by flushing with 1 M Na for 20 min followed by water for 5 min then the BGE for 10 min. The BGE containing sucrose was then flushed between injections for 10 min. The electric field was applied for 12 min at 24 kv followed by pressure mobilization at 50 mbar. 2.3 NMR 1 H NMR and 13 C NMR spectra were recorded at room temperature on a Bruker DRX300 spectrometer (Bruker, Alexandria, NSW, Australia) operating at 300 MHz for 1 H, equipped with a 5 mm 1 H- 13 C dual probe. 1 H NMR spectra were recorded with a 5.3 µs 30 pulse, a 5 s repetition delay and ,480 scans. 13 C NMR spectra were recorded with a 7 µs 90 pulse, a 3 s repetition delay and 20,358 to 184,320 scans. 1 H and 13 C chemical shift scales were externally calibrated with the resonance of the methyl signal of ethanol in D 2O at 1.17 and ppm, respectively [21]. James Oliver CE for bioethanol research 117

142 3 Results and discussion: 3.1 Photo-oxidation assisted detection of ethanol Pressure mobilization of sucrose dissolved in 130 mm Na led to a Gaussian peak, which intensity decreased when ethanol was added to the sucrose (Figure 4.2-1A). Sucrose peak area, height and shape are increasingly affected by ethanol when the ethanol concentration increases. Ethanol interferes with the photo-oxidation reaction of sucrose and suppresses the sucrose signal because of a decrease in concentration of UV absorbing intermediate(s). The signal is monotonically decreasing with the amount of ethanol added. Ethanol disruption occurs in a narrower band than that of the sucrose peak (Figure 4.2-1B): ethanol thus suppresses the signal corresponding to the center of the sucrose peak, but not the tail, creating a valley. Considering the Taylor Dispersion Analysis of pressure mobilization [22], this means that ethanol diffuses faster than sucrose in Na 130 mm, which is indeed expected from the difference of sizes of the molecules: ethanol diffuses faster than glucose [23], which in turn diffuses faster than sucrose [24]. If sucrose is placed in the mobile phase, then ethanol can be detected indirectly as a negative peak (Figure 4.2-1B). The (negative) peak is then Gaussian confirming that the unusual peak shape in direct detection is due to the difference of diffusion coefficients of the ethanol and the carbohydrate. The peak shape is of importance for determining the ethanol concentration through either the loss in peak area or the loss in peak height (discussed later). James Oliver CE for bioethanol research 118

143 Figure 4.2-1: Pressure mobilization at 50 mbar: (A) of 2 g L -1 sucrose in 130 mm Na not spiked (solid line) or spiked with ethanol at 250 mg L -1 (dotted line), 1 g L -1 (dashed line) and 2 g L -1 (dotteddashed line), with Na 130 mm as the mobile phase. (B) of 2 g L -1 sucrose in 130 mm Na (with 130 mm Na as the mobile phase, dotted line) and of 1 g L -1 ethanol in 2 g L -1 sucrose and 130 mm Na (with 130 mm Na with 2 g L -1 sucrose as the mobile phase, solid line). Performed on MDQ instrument (n=5). James Oliver CE for bioethanol research 119

144 3.2 Understanding ethanol interference with carbohydrate photo-oxidation Reactions of some free radicals with ethanol have been previously extensively studied [19,20,25] especially with ethanol as a transfer agent during radical polymerization. The free radical abstracts a hydrogen from the carbon bearing the alcohol group (α-carbon), and not from the hydroxyl group itself (consistent with the bond dissociation energies, BDE, Table 4.3-1), producing a carbon centered radical [18,26] depicted in Figure Figure 4.2-2: Hydrogen abstraction from ethanol by a free radical R. Adapted from [18]. To investigate this mechanism and ensure that it is not due an impurity in ethanol, interference from ethanol, methanol, iso-propanol, tert-butanol and triethylamine with sucrose photo-oxidation was compared. The interference is also observed for these four other compounds confirming that the detection is not due to an impurity present in ethanol. The transfer coefficient to ethanol, methanol and iso-propanol has been determined previously in the radical polymerization of alkyl acrylates [25]. The transfer coefficient to isopropanol is 3 times higher than the one to ethanol and 29 times higher than the one to methanol. This trend indicates a higher reactivity of alcohols toward the acrylate carbon-centered radicals when the alkyl group (on the alcohol) increases in size. The BDE [27] indicate the same trend (Table 4.3-1), increasing from isopropanol, to ethanol and methanol, with tert-butanol having the highest BDE of all while the BDE of ethanol and methanol have a lot closer values. Triethylamine has a slightly lower BDE than isopropanol. The BDEs of the alcohols and amines and their relative ability to interfere with the photo-oxidation of carbohydrates were compared. At the lower alcohol/amine concentration, ethanol has the highest inference and tert-butanol and methanol have the lowest. Although methanol has a more favorable BDE, tertbutanol has more hydrogens to abstract. iso-propanol has the highest peak difference, however not significantly different from that of ethanol (Figure 4.2-3). The trend in the inhibition of photooxidation is quantitatively but also qualitatively different from that in transfer in polymerization and that of the BDEs, therefore the hydrogen abstraction on the ethanol is likely not a critical step in the kinetics of the reaction. James Oliver CE for bioethanol research 120

145 Figure 4.2-3: Interference of alcohols and triethylamine at 5 mm (white) and 44 mm (striped) with the photo-oxidation of 2 g L -1 sucrose during pressure mobilization. Relative difference in peak height (PH RD) is calculated as PPPP RD = PPPP S PPPP Et PPPP S where PH S is the height of the sucrose peak, PH Et is the height of the peak of sucrose spiked with ethanol. 10 cm effective length, 50 mbar pressure mobilization (n=3), performed on MDQ instrument. To investigate if the change in signal was due to difference of Refractive Index (RI), the concentration of the analyte by the analytes RI [28] was plotted against the relative difference in peak height. If the change in signal was due to a difference in RI, the relationship would have been linear, but this is not the case as seen on Figure A control injection of pure ethanol also shows that RI does not play a significant role in the observed interference (Figure 4.3-2). Interference with the photo-oxidation of sucrose may be due to ethanol reacting with the hydroxide/superoxide radical initiator or the carbon or oxygen centered radical of the sucrose during photo-oxidation (Figure 4.2-4). To determine whether sucrose and/or ethanol were consumed or regenerated after passing the detection window, a multiple passing experiment was performed similar to what has been done previously [5] but using pressure mobilization and in the presence of ethanol. Sucrose was passed in front of the detection window, then the pressure was reversed and the sucrose James Oliver CE for bioethanol research 121

146 passed again. This was done to a total of 28 passes for sucrose with and without ethanol. Sucrose on its own showed results similar to the previous passing experiment [5] with a buildup of UV absorbing species in the first five passes of the detection window followed by a decrease (Figure 4.2-5A). This change of the signal intensity with the number of passes would not happen if the detection was due to differences in refractive index and thus confirms that the detection of ethanol is due to photooxidation and not to a difference in refractive index. In the presence of 250 mg L -1 and 1 g L -1 ethanol the highest peak is observed at the 7th pass and the peak height is lower than with sucrose. The difference in peak height decreases in parallel, with the number of passes and then becomes constant, within the (large) experimental error after 10 passes (Figure 4.2-5B). The decrease of the peak height difference may indicate a faster consumption of ethanol than sucrose over time. As expected, the peak height difference is smaller with 250 mg L -1 than 1 g L -1 ethanol, but the behavior, decrease of the peak height differences for the first 10 passes and plateau is similar. After 10 passes, the large amount of RSD makes the difference not significant. The multiple passes of sucrose in the detection window showed that interference of ethanol is at a maximum on its first pass. Figure 4.2-4: Possible reaction scheme for the interference of ethanol with glucose photo-oxidation. James Oliver CE for bioethanol research 122

147 Figure 4.2-5: Peak heights in the pressure mobilization of 2 g L -1 sucrose (black square), 2 g L -1 sucrose and 250 mg L -1 ethanol (circle) and 2 g L -1 sucrose and 1 g L -1 ethanol (cross) in 130 mm Na passing the detection window multiple times (A) and the relative difference in their peak height (B). Initial pressure was 50 mbar (outlet to inlet) for 6 min then reversed (inlet to outlet) for 3 min and reversed every 3 min for a total of 28 passes. Error bars show standard deviation (n=3). Peak overlay can be seen in Figure Performed on MDQ instrument. The role of ethanol was further investigated by 1 H and 13 C NMR. As NMR experiments require a deuterated solvent, it was first checked that the same interference of ethanol was observed in D 2O as in H 2O. Injections were carried out with 130 mm Na in H 2O as well as in D 2O: the relative peak height difference between sucrose peaks with and without ethanol in D 2O is only slightly larger in D 2O (Table 4.3-2). This indicates that either the reactivities of the radicals and OD toward carbohydrate are not significantly different or more likely that water is not a reactant in the ethanol interference with the photo-oxidation reaction, the carbohydrate UV irradiation being directly responsible for the hydrogen abstraction and free radical formation. The differing values between the D 2O and H 2O can be attributed to the change in peak tailing (Figure 4.3-4) due to the higher viscosity of D 2O. Assuming that the photo-oxidation reaction as well as the ethanol interference are similar in D 2O and H 2O, a sample of 1 g L -1 glucose ( 13 C fully labelled) in D 2O was James Oliver CE for bioethanol research 123

148 continuously pressure injected at 50 mbar for 94.5 hours (after 89 h, pressure was increased to 100 mbar to offset backpressure from the outlet vial), as previously performed [13], but in the presence of 2 g L -1 ethanol. The sample was consecutively analyzed by 1 H (Figure and Figure 4.3-5) and 13 C NMR (Figure and Figure 4.3-6). To determine whether ethanol was consumed or regenerated after passing the detection window, the area of the 1 H NMR signal areas of the methyl group of ethanol were compared for the sample, control as well as fresh control (Figure 4.2-6). The sum of total area of the normalized peaks was respectively 30 for the sample, 69 for the control and 191 for the fresh control. The loss of ethanol in the control shows that ethanol underwent thermal decomposition over the period of 8 days (at 4 C). Taking temperature and time into account (Table 4.3-3) ca 17 % of the ethanol was consumed by the photo-oxidation reaction. This is consistent with the multiple pass experiment and a faster consumption of ethanol than carbohydrate. Ethanol can be directly photo-oxidized to some acetate (Figure 4.3-7) and aldehydes [17] and in high alkaline conditions used in this work acetaldehyde (ethanal) would further react to form sodium acetate. The radical formed from ethanol abstraction reaction (Figure 4.2-2) might also interfere with the photooxidation of glucose. Numerous possible interferences of the ethanol with glucose photo-oxidation are consistent with the NMR results; they are represented on Figure James Oliver CE for bioethanol research 124

149 Figure 4.2-6: 1 H NMR of 2 g L -1 ethanol in the presence of 1 g L -1 fully labelled 13 C glucose continuously and hydrodynamically injected into a 7100 CE instrument (solid line) with nonirradiated control of the same age (dotted line) as well as freshly prepared control (dashed line).the spectra were normalized by the number of scans (20480, 2400 and 800 respectively) and the dilution factor (the controls were undiluted, sample was diluted 1/4.46 as described in section 2.2.1). The photo-oxidation of glucose under these conditions has been studied previously [13,29]. The possible products of the interference that are not consistent with the NMR results are represented on Figure At point (a) of the reaction on Figure 4.2-4, glucose would form a carbon centered radical from hydrogen abstraction by a hydroxyl radical formed by the splitting of water or more likely by direct photo-irradiation [15]. The glucose carbon-centered radical is a tertiary radical that is thus unlikely to abstract a hydrogen from ethanol regenerating glucose and forming a secondary radical on ethanol. Abstraction of hydrogen from ethanol might also occur on the free radicals (b) following the ring opening step which was described previously [13]. A glucose would be regenerated in an altered open form containing an aldehyde functional group and thus more prone to thermal degradation. Similar to this, ethanol might interfere with the production of free radicals formed by the low-uv irradiation of water (Figure 4.3-9) but this is unlikely as D 2O would give a different interference. The carbon centered free radical of glyceraldehyde (c) (2,3- James Oliver CE for bioethanol research 125

150 dihydroxypropanal) might also abstract the same hydrogen from ethanol displacing the equilibrium from the semidiones previously identified as possible UV absorbing intermediates [13]. Glyceraldehyde can be oxidized to form glyceric, glycolic, acetic and methanoic acid as well as carbon dioxide (d) [30]. Hydrogen abstraction from ethanol would most likely occur from oxygen centered radicals (e) rather than carbon centered radicals. The resulting product, (Z)-prop-1-ene- 1,2,3-triol (f), was not observed in 13 C NMR (Figure 4.3-8) (alkene would produce signals between130 and 160 ppm), but it may rather be simply an intermediate. Alternative end products such as malondialdehyde would still be formed then oxidized to carboxylates (g). Figure 4.2-7: 13 C NMR of 1 g L -1 fully labelled 13C glucose in the presence of 2 g L -1 ethanol continuously and hydrodynamically injected into a 7100 CE instrument (solid line, top) and control (dotted line, bottom). The rectangles indicate the ethanol signals. The ethanol was not 13 C labeled in this experiment but it is detected with a signal-to-noise ratio of 43 for the fresh control and 6.5 for the sample for the shift at 18 ppm. Any products of reactions with ethanol representing less than 20 % of the initial ethanol should thus not be detected (Table 4.3-4). In previous work [13] glucose did not significantly thermally degrade on a month scale in 130 mm NaOD in D 2O. In the control experiment of this work some glucose was degraded James Oliver CE for bioethanol research 126

151 thermally by the alkaline conditions in D 2O in the presence of the ethanol after 14 days. Ethanol might form transient hemiacetal and acetal leading to higher proportion of open glucose making its aldehyde functional group more prone to thermal degradation. The products from such degradation have the same functional groups, carboxylates, as that from the photo-oxidation as shown by identical shifts at 170, 180 as well as similar massifs between 60 and 80 ppm (Figure 4.2-7). The photo-oxidation by the CE s deuterium lamp speeds up the formation of carboxylates ( 170 and 180 ppm) and produced other end products ( 20 and 40 ppm) seen previously [13]. The formation of glycolate and methanoate, as discussed previously [13], as well as glycerate and malonate (Table 4.3-5) would fit the shifts observed in the 13 C NMR. Glucose, in its cyclic form, is observed in the control sample through signals at 98 and 102 ppm. The loss of these signals indicates complete degradation of glucose either by photo-oxidation or alkaline degradation. The photo-oxidation of glucose in the presence of ethanol did not lead to the identification of any new end products thus ruling out combination reactions of ethanol based radicals with glucose based radicals leading to larger unique end products (Figure 4.3-8), however 2 ethanol based radicals could form butan-2,3- diol (Figure 4.3-8) that cannot be ruled out as an end product (Table 4.3-5). Ethanol is still present in the NMR spectra after UV irradiation, thus ethanol is not completely photo-oxidized to its end products acetic acid and its aldehyde [17]. Previous studies have investigated the potential end products (D-Glucose penta-acetate, D-Gluconic acid, D-Glucuronic acid and D-Glucosaccharic acid) [31] and UV absorbing intermediates (Asorbic acid, (Z)-3-hydroxyacrylaldehyde, 2-keto-gluconic acid and 4-deoxy-5-keto-3,6-manno saccharolactone) [16] of the photo-oxidation of glucose solutions in the presence of oxygen, however none of these are observed in our 13 C NMR spectrum (Table and 4.3-6). 3.3 Quantification of ethanol by pressure mobilization Before application to samples analysis, the effect of carbohydrate concentration, residence time in the detection window and ethanol concentration were determined Effect of sucrose concentration and residence time on ethanol determination. As mention in 2.2.1, sucrose was chosen as it does not reduce in basic conditions. To determine the effect of residence time in the detection window, the difference in peak height from ethanol interference was measured with pressure mobilization at pressures of 10, 50 and 100 mbar. As shown previously [12], pressure mobilization at 10 mbar creates the highest signal due to the prolonged residence time in the detection window (Figure ) allowing more time for photooxidation to take place. However this also results in the longest analysis time (17 min for 10 cm). The James Oliver CE for bioethanol research 127

152 differences in peak height between sucrose with and without ethanol (Table 4.3-7) are not significantly different at 10 and 50 mbar, and using 50 mbar instead of 10 mbar reduces analysis time from 17 to 4.6 min (3-5 fold increase when 15 % error is taken into account). The effect of sucrose concentration on the difference in peak height from ethanol interference was studied in the range of 0.25 to 8 g L -1 sucrose in 130 mm Na spiked with 1 g L -1 ethanol (Figure 4.2-8). The largest difference in peak height is observed at 2 g L -1 sucrose. At 4 g L -1 sucrose the difference in peak height decreases and the difference in area even decreases to zero (see Figure ). The difference in peak height above 4 g L -1 sucrose is thus likely only due to peak broadening but not to the photo-oxidation process. Overloading of the capillary is shown by peak tailing (Figure ) especially at 8 g L -1 likely due to viscous fingering. To avoid tailing the difference in viscosity of the sample and the mobile phase needs to be kept minimal. Above 2 g L -1 sucrose, the free radical concentration formed during the photo-oxidation may be too high and induce more termination reactions: the ethanol is then not playing a role any more. This is similar to the increase of the detection sensitivity adding a photo-initiator only up to a certain photo-initiator concentration in previous work [13]. To analyze samples which do not contain photo-oxidizing carbohydrates, carbohydrates need to be added but no more than 2 g L -1 should be added as it provides optimal peak height as well as the largest difference in peak height making the detection more sensitive. The analysis of samples already containing photo-oxidizing carbohydrates is a challenge with the pressure mobilization method. The total sugar concentration could be controlled, possibly by dilution into a known concentration of carbohydrates where the concentration in the sample is negligible compared to that of the added sucrose. CE is a preferable alternative over pressure mobilization in this case as it can separate the carbohydrates, as well as other compounds, from ethanol (discussed later). Using separation by CE, the ethanol band is free of carbohydrates and ethanol can be detected if a known amount, such as 2 g L -1 sucrose, of carbohydrate is added to the BGE at the time the ethanol reaches the detection window to obtain indirect detection of ethanol as on Figure 4.2-1B. The effect of sucrose concentration on the signal-to-noise ratio (S/N) was also considered (Figure ) and S/N was found to be optimal between 2 and 8 g L -1 sucrose. James Oliver CE for bioethanol research 128

153 Figure 4.2-8: Sucrose peak height (solid line), sucrose spiked with 1 g L -1 ethanol peak height (dotted line) and difference between sucrose peak heights with and without ethanol (dashed) after pressure mobilization at 50 mbar in a 90 cm (10 cm effective length) capillary (n = 5). Error bars on peak height difference are ± sum of the standard deviations of both peaks (n=5). Performed on MDQ instrument Performances of the quantification of ethanol method Using pressure mobilization, ethanol can be quantified by either the peak area or peak height. The precisions of both methods were compared (Table 4.2-1). The RSD values are of the order of 2-10 % above 125 mg L -1 of ethanol at this stage since no internal standard is used. Quantification by peak height is more precise than that by peak area. This may be due to the irregular peak shape and some pressure variation during the injection. Slight variation in pressure results in variation in the width of the ethanol band: the peak tail is affected by these variations, thus the peak area, while the peak height is not influenced. As expected, the RSD values increase when the ethanol concentration decreases. James Oliver CE for bioethanol research 129

154 The limit of detection (LOD) and the limit of quantification (LOQ) were also compared in BGEs containing sucrose and xylitol (same molar concentration) with 130 mm Na (Table 4.2-2). There is in fact a range of concentration in which ethanol can be detected: too low of an ethanol concentration leads to no interference of the photo-oxidation, while too high of an ethanol concentration leads to complete inhibition of the photo-oxidation. The lower LOD is taken as the concentration for which S/N is equal to 3 [13,32]; where S/N was determined as the ratio of the signal taken as the difference of the peak heights between the sucrose only injection and the sucrose and ethanol injection, and of the noise over estimated as the sum of the noises of each signal. The lower LOQ is defined for the same reason as the ethanol concentration for which S/N is equal to 10, with S/N determined as above. The upper LOQ is related to the blank injection of pure ethanol and defined as the ethanol concentration for which the peak has a S/N equal to the sum of 10 and of the S/N of pure ethanol, with the signal taken as the one of the ethanol injections (the lowest point in the middle valley of the peak, Figure 4.2-1A, in the presence of sucrose). Sucrose and xylitol were chosen as they are stable in basic media. Table 4.2-1: Comparison of peak height and peak area in the pressure mobilization of xylitol and sucrose (2 g L -1 ) in 130 mm Na for the quantification of ethanol (n=5). Peak height was measured to the lowest valley point (Figure 4.2-1A). Performed on MDQ instrument. Sucrose Xylitol Concentration of ethanol (mg L -1 ) Relative difference in peak RSD (%) Relative difference in peak RSD (%) Relative difference in peak RSD (%) Relative difference in peak RSD (%) area height area height < James Oliver CE for bioethanol research 130

155 Table 4.2-2: Linearity of ethanol quantification, LOD, LOQ and recovery in pressure mobilization and CE with sucrose and xylitol as background carbohydrates. n=5 for all standards and samples. Carbohydrate Linear Equation R 2 LOD (Lower) LOQ (Lower) LOQ (Upper) Sample recovery Quantification by pressure mobilization Sucrose y 1/3 = 8.67x mg L mg L c mg L % a Xylitol y 1/3 = 8.18x mg L mg L c mg L -1 - Quantification by CE Sucrose y = 8.76x mg L mg L % b a From a sample of vodka b From a spiked fermentation sample c Calculated with the S/N ratio of pure ethanol at 2 g L -1 A linear fit, determined by best empirical fit, can be achieved when the relative difference in peak height is plotted over the cube root of the ethanol concentration. A cubic fit is likely due to the reaction not being first order. The standard curve obtained with the MDQ maintained a similar cubic fit when the standard was injected on 4 different days over a month were analyzed together. A combination of the standard curves obtained by the MDQ and 7100 has a correlation coefficient of 0.98 (Figure ) and thus indicate no significant difference between the standard curves obtained from the MDQ or from the The curve for xylitol and sucrose are similar (Figure ) and may suggest a universal calibration with all photo-oxidizing carbohydrates. Sucrose leads to more repeatable peak heights than xylitol as the photo-oxidizing even though a more regular peak shape is obtained with xylitol in the presence of ethanol (Figure ). The S/N was also compared between the 7100 CE and the MDQ instruments (Figure ). The latter instrument was found to be more sensitive for ethanol detection, by 40 % (S/N of 149 for the 7100 CE and of 209 for the MDQ), as was previously observed for carbohydrates [12]. The lamp usage time may play a role and the MDQ instrument had a more recent lamp (990 h) than the 7100 CE one (1950 h). Pressure mobilization was applied to the determination of ethanol in a real wellcharacterized sample to benchmark the method: vodka was chosen since as it has a considerable ethanol concentration, no carbohydrates and minimal interfering compounds. The declared ethanol concentration was 37 %, the sample was diluted by 1:600 with a solution of 2 g L -1 sucrose in 130 mm Na. Quantification of the ethanol content was found identical to the one determined by the vodka manufacturer (to 2 significant digits) indicating that trace amounts of other compounds [33] did not have an impact on the quantification of ethanol by photo-oxidation interference. To measure ethanol in samples containing both carbohydrates and ethanol, a CE method was developed as follows. James Oliver CE for bioethanol research 131

156 3.3.2 Quantification of ethanol in real samples by CE As mentioned previously, samples containing both carbohydrates and ethanol require separation before ethanol determination. CE was used to separate ethanol in a standard containing glucose and fructose. A BGE of 130 mm Na was placed in the inlet and outlet vials and the capillary was flushed with a BGE containing 130 mm Na with 2 g L -1 of sucrose. Sucrose, as a disaccharide, has an apparent mobility lower than the EOF marker but higher than the glucose and fructose, and thus should completely migrate past the detection window before glucose and fructose migrate past the detection window. Ethanol, due to its higher pk a than that of sucrose, should pass the detection window whilst sucrose is still in the background. As a result, ethanol can be detected by interference with the photo-oxidation of sucrose only, while glucose and fructose can be detected directly by photo-oxidation (Figure 4.2-9). When the electric field was applied for the entire duration of the separation, the detection of the ethanol peak was not repeatable due to a large amount of instability (Figure ). When the electric field was stopped after 12 min and 50 mbar pressure applied, the ethanol peak was repeatable (Figure 4.2-9B) and separated sufficiently from the carbohydrates. The carbohydrates were incompletely separated from each other in comparison to separations seen previously in similar conditions [5,13]. In this case, a reinjection in conditions optimal to the separation of carbohydrates should be done separately. As expected there was a drop in the baseline at min indicating that the sucrose has completely migrated out of the capillary. As in pressure mobilization, the extent of interference was proportional to the amount of ethanol added (Figure 4.2-9B). James Oliver CE for bioethanol research 132

157 Figure 4.2-9: Detection of ethanol and carbohydrates via CE (A) and detection of varying concentrations of ethanol by interference with the photo-oxidation (B). BGE in outlet and inlet was 130 mm Na, BGE in capillary was 130 mm Na + 2 g L -1 of sucrose. Migration was by electric field (24 kv) for 12 min followed by pressure mobilization at 50 mbar. Assignment of ethanol concentrations for (B): 2 g L -1 (solid line), 1 g L -1 (short dotted line), 500 mg L -1 (short dashed line), 250 mg L -1 (dotted line), 125 mg L -1 (dashed line) and 0 mg L -1 (dashed-dotted line). Current was 147 µa. Performed on 7100 CE instrument. The maximum increase in temperature inside the capillary due to Joule heating was only 1.9 C as calculated previously [13,34]. The LOD, and LOQ and recovery were determined (Table 4.2-2) and are similar to the one obtained by pressure mobilization only on simpler samples. The LOD of the CE method (34.4 mg L -1 ) can compete with the sensitivity of an optical alcohol meter (LOD < 1580 mg L -1 [35]) for the ability to determine carbohydrates with the same equipment. The instability was similar with BGEs containing either 2 g L -1 or 0.5 g L -1 sucrose (Figure ). A diluted fermentation sample spiked with 500 mg L -1 of ethanol was used to test the recovery of the method. The sample showed 110 %. The precision may be improved with an internal standard as discussed in previous work [5]. The accuracy and robustness of the method are however demonstrated using this complex matrix without any filtration being required. Vials for online fermentation monitoring by CE James Oliver CE for bioethanol research 133

158 were recently developed and tested on acids [36]. The CE separation presented in this work will allow the method to be extended to the quantification of both ethanol and carbohydrates in complex mixtures (not in the same injection) for a comprehensive online monitoring of ethanol fermentations. 4 Conclusions Ethanol can be detected and quantified by interference with carbohydrate photo-oxidation. Methanol, propanol or triethylamine are also shown to be detected by this method. The presence of ethanol during photo-oxidation did not lead to the observation by 1 H or 13 C NMR of any endproducts that were not seen previously in the absence of ethanol. The photo-oxidation might be due to direct UV irradiation of the carbohydrate leading to the formation of free radicals and then UV absorbing intermediate. Ethanol might react with oxygen centered radicals along this reaction pathway and partially suppress the UV absorption. This detection can be utilized with pressure mobilization for a simple and fast detection of ethanol with a capillary electrophoresis instrument or an even simpler set-up. When sucrose is used as the photo-oxidizing carbohydrate in pressure mobilization, the optimal concentration is 2 g L -1. This detection has a LOD and LOQ of 34.9 and 117 mg L -1 respectively. The quantitative recovery (100%) was measured with a sample of vodka. CE was used to determine ethanol in spiked fermentation samples containing glucose and fructose. Ethanol in CE can be detected as an indirect peak when sucrose is placed in the BGE in the capillary. A fermentation sample spiked with ethanol showed 110 % recovery, showing that the robustness of the CE with direct UV detection of carbohydrates also applies to ethanol quantification. The ability of CE with direct UV detection to monitor both complex mixtures of carbohydrates, as shown by previous research, and now to monitor ethanol, makes it highly promising method to monitor ethanol fermentations online. The method can be applied to a number of compounds, for example antioxidants, taking advantage of the robustness of the method. 5 Acknowledgements The authors wish to acknowledge Dr Yohann Guillaneuf (Aix-Marseille University) for discussions and David Fania and Prof. Kamali Kannangara for 13 C glucose. James Oliver CE for bioethanol research 134

159 References [1] M.J. Playne, J. Sci. Food Agric. 36 (1985) 638. [2] R. Pecina, G. Bonn, E. Burtscher, O. Bobleter, J. Chromatogr. 287 (1984) 245. [3] V.P. Hanko, J.S. Rohrer, Anal. Biochem. 283 (2000) 192. [4] A.I. Ruiz-Matute, O. Hernández-Hernández, S. Rodríguez-Sánchez, M.L. Sanz, I. Martínez-Castro, J. Chromatogr. B 879 (2011) [5] J.D. Oliver, M. Gaborieau, E.F. Hilder, P. Castignolles, J. Chromatogr. A 1291 (2013) 179. [6] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, P. Gareil, Talanta 99 (2012) 202. [7] K.D. Altria, J.S. Howells, J. Chromatogr. A 696 (1995) 341. [8] L.A. Colon, R. Dadoo, R.N. Zare, Anal. Chem. 65 (1993) 476. [9] T. Soga, M. Serwe, Food Chem. 69 (2000) 339. [10] S. Rovio, J. Yli-Kauhaluoma, H. Siren, Electrophoresis 28 (2007) [11] S. Rovio, H. Simolin, K. Koljonen, H. Siren, J. Chromatogr. A 1185 (2008) 139. [12] C. Sarazin, N. Delaunay, C. Costanza, V. Eudes, J.M. Mallet, P. Gareil, Anal. Chem. 83 (2011) [13] J.D. Oliver, A.A. Rosser, C.M. Fellows, Y. Guillaneuf, J.-L. Clement, M. Gaborieau, P. Castignolles, Anal. Chim. Acta 809 (2014) 183. [14] M.G. Gonzalez, E. Oliveros, M. Wörner, A.M. Braun, J. Photochem. Photobiol. C: Photochem. Rev. 5 (2004) 225. [15] G.O. Phillips, in: L.W. Melville, R.S. Tipson (Eds.), Advances in Carbohydrate Chemistry, Academic Press, 1963, p. 9. [16] T.C. Laurent, J. Am. Chem. Soc. 78 (1956) [17] J.L. Bolland, H.R. Cooper, Proc. R. Soc. London, Ser. A 225 (1954) 405. [18] W.H. Urry, F.W. Stacey, E.S. Huyser, O.O. Juveland, J. Am. Chem. Soc. 76 (1954) 450. [19] G.A. Mortimer, J. Polym. Sci., Part A1: Polym. Chem. 4 (1966) 881. [20] B. Grassl, A.M. Alb, W.F. Reed, Macromol. Chem. Phys. 202 (2001) [21] G.R. Fulmer, A.J.M. Miller, N.H. Sherden, H.E. Gottlieb, A. Nudelman, B.M. Stoltz, J.E. Bercaw, K.I. Goldberg, Organomet. 29 (2010) [22] T. Le Saux, H. Cottet, Anal. Chem. 80 (2008) [23] B.J.M. Hannoun, G. Stephanopoulos, Biotechnol. Bioeng. 28 (1986) 829. [24] L.G. Longsworth, J. Am. Chem. Soc. 75 (1953) [25] U.S. Nandi, M. Singh, P.V.T. Raghuram, Makromolekul Chem 183 (1982) [26] M.S. Kharasch, J.L. Rowe, W.H. Urry, J. Org. Chem 16 (1951) 905. [27] Y.-R. Luo, Handbook of bond dissociation energies in organic compounds, CRC Press, Boca Raton, Fla., [28] D.R. Lide, Hdbk of Chemistry & Physics 74th Edition, Taylor & Francis, [29] B.C. Gilbert, D.M. King, C.B. Thomas, J. Chem. Soc., Perkin Trans. 2 (1982) 169. [30] L.M. Andronov, Z.K. Maizus, B Russ Acad Sci Ch+ 16 (1967) 504. [31] G.O. Phillips, G.J. Moody, J Chem Soc (1960) [32] A.Z. Carvalho, J.A.F. da Silva, C.L. do Lago, Electrophoresis 24 (2003) [33] L.-K. Ng, Anal. Chim. Acta 465 (2002) 309. [34] C.J. Evenhuis, R.M. Guijt, M. Macka, P.J. Marriott, P.R. Haddad, Anal. Chem. 78 (2006) [35] M. Rocchia, M. Ellena, G. Zeppa, J. Agric. Food Chem. 55 (2007) [36] H. Turkia, S. Holmström, T. Paasikallio, H. Sirén, M. Penttilä, J.-P. Pitkänen, Anal. Chem. 85 (2013) James Oliver CE for bioethanol research 135

160 4.3 Publication supporting information Supporting information for: Ethanol determination using pressure mobilization and Free Solution Capillary Electrophoresis (CE) by photo-oxidation assisted UV detection James D. Oliver, 1 Marianne Gaborieau, 2 and Patrice Castignolles* 1 1 University of Western Sydney (UWS), Australian Centre for Research on Separation Science (ACROSS), School of Science and Health, Locked Bag 1797, Penrith NSW 2751, Australia, james.oliver@uws.edu.au, p.castignolles@uws.edu.au 2 University of Western Sydney (UWS), Molecular Medicine Research Group (MMRG), School of Science and Health, Locked Bag 1797, Penrith NSW 2751, Australia, m.gaborieau@uws.edu.au * Corresponding author: p.castignolles@uws.edu.au This supporting information contains supplementary chromatograms and electropherograms as well as peak heights and peak areas values from the Pressure Mobilization and Free Solution Capillary Electrophoresis (CE) experiments. It also contains supplementary NMR spectra and data on the 1 H and 13 C NMR experiments and hypothesized reaction schemes. If the detection of ethanol described in this work was due to refractive index detection, then the relative different in peak height should be proportional to the difference of refractive index of the analyte and sucrose multiplied by the ethanol concentration. Such a plot is given a Figure and is not linear. James Oliver CE for bioethanol research 136

161 Figure 4.3-1: Relationship between the multiplication of the analyte Refractive Index (RI) by the concentration of the analyte and the relative peak difference. The analytes are methanol (square), ethanol (triangle), isopropanol (star), tert-butanol (pentagon) and triethylamine (circle). RI values are 20 C [1]. James Oliver CE for bioethanol research 137

162 Figure 4.3-2: Blank of injection 130 mm Na (green), 1 g L -1 Ethanol in 130 mm Na (blue), 2 g L -1 sucrose in 130 mm Na (black) and 1 g L -1 Ethanol in 2 g L -1 sucrose in 130 mm Na (red). The bond dissociation energy (BDE) are lower for the C-H bond in alpha position of an alcohol than for the O-H bond of the alcohol functional group. Table 4.3-1: BDE from [2]. Molecule Bond BDE (kj/mol) Uncertainty Methanol H-CH Ethanol CH 3-C-H na Propan-2-ol (CH 3) 2C-H methylpropan-2-ol (CH 3) 3CO-H Triethylamine (CH 3CH 2) 2NC-H(H)CH Water H Methanol H 2CO-H Ethanol H 3CCH 2O-H Propan-2-ol (CH 3) 2CHO-H Vinyl alcohol H 2C=C(H)O-H na 2-methylpropan-2-ol (CH 3) 3CO-H James Oliver CE for bioethanol research 138

163 Passing experiment with pressure mobilization Figure 4.3-3: Pressure mobilization of 2 g L -1 sucrose (black), 2 g L -1 sucrose and 250 mg L -1 ethanol (red-1 min offset) and 2 g L -1 sucrose and 1 g L -1 ethanol (blue-2 min offset) in 130 mm Na passing the detection window multiple times. Initial pressure was 50 mbar (outlet to inlet) for 6 min then reversed (inlet to outlet) for 3 min and reversed every 3 min for a total of 28 passes. Performed on MDQ instrument. James Oliver CE for bioethanol research 139

164 Table 4.3-2: Comparison of the effects of ethanol inhibited photo-oxidation of sucrose in 130 mm Na in H 2O and in D 2O. Values are normalized by migration time. Examples of the corresponding elugrams are shown on Figure Concentration of ethanol in 2 g L -1 sucrose in 130 mm Na (mg L -1 ) Sucrose peak area (x 10 4 ) RSD (%) Relative difference in peak area (%) RSD (%) Sucrose peak height (mau) RSD (%) Relative difference in peak height (%) 130 mm Na in H 2O mm Na in D 2O RSD = Relative standard deviation RSD (%) Figure 4.3-4: Pressure mobilization of sucrose in 130 mm Na in H 2O (solid line) and 130 mm NaOD ind 2O (dotted line). Performed on MDQ instrument. James Oliver CE for bioethanol research 140

165 1 H and 13 C NMR of fully labeled 13 C glucose in the presence of ethanol, before and after irradiation Figure 4.3-5: 1 H NMR of 1 g L -1 fully labelled 13 C glucose in the presence of 2 g L -1 ethanol continuously and hydrodynamically injected into a 7100CE instrument for 94.5 h (black), control with no UV exposure for the same length of time (blue) and prepared fresh (red). James Oliver CE for bioethanol research 141

166 Figure 4.3-6: 13 C NMR of 1 g L -1 fully labelled 13 C glucose in the presence of 2 g L -1 ethanol continuously and hydrodynamically injected into a 7100CE instrument for 94.5 h (black), control with no UV exposure for the same length of time (blue) and freshly prepared control (red). Table 4.3-3: Calculation of rate of ethanol thermal decomposition obtained from the integration of Figure Time spent at 4 C Time spent at 20 C Total equivalent time at 20 C * Total loss in peak area Loss in peak area due to thermal decomposition Rate of thermal decomposition at 20 C (loss/hour) Peak area loss by photooxidation Peak area loss by photooxidation (%) Control Sample # * assuming that the decomposition reaction is 3 times slower at 4 C than 20 C. # calculated as the loss of peak area in the control multiplied by the ratio of time spent at 20 C by the control and the sample. James Oliver CE for bioethanol research 142

167 Table 4.3-4: Estimate of the minimal concentration (E) of end products that, resulting from decomposition of ethanol, could be detected by 13 C NMR. Signal to Noise ratio (S/N) of ethanol signal at 18 ppm in fresh control (A) Number of scans of fresh control (undiluted) (B) Signal to Noise ratio (S/N) of ethanol signal at 18 ppm in sample Dilution factor of sample (C) Number of scans of sample (D) 3 EE = 100 AA CC DD BB % NB: this calculation assumes that all signals of interest are fully relaxed between scans in the 13 C NMR experiment. Table 4.3-5: Predicted 13 C shifts of potential end products of carbohydrate photo-oxidation in the presence of oxygen. Prediction done with ChemDraw Ultra 12. Bold, underlined chemical shifts are not observed in the 13 C NMR spectrum (Figure 4.2-4). D-Glucose pentaacetate [3] D- Gluconic acid [3] D- Glucuronic acid [3] D- Glucosaccharic acid [3] Malonic acid (Malonate) Glyceric acid (Glycerate) Butan- 2,3-diol , Table 4.3-6: Predicted 13 C shifts of potential UV absorbing intermediates from carbohydrate photooxidation as studied by [4]. Prediction done with ChemDraw Ultra 12. Bold, underlined chemical shifts are not observed in the 13 C NMR spectrum (Figure 4.2-4). Asorbic acid (Z)-3- hydroxyacrylaldehyde (reductone) 2-keto-gluconic acid (diol form) 4-deoxy-5-keto- 3,6-manno saccharolactone , 75.9 James Oliver CE for bioethanol research 143

168 Mechanism of the photo-oxidation and of the interference with ethanol Figure 4.3-7: Oxidation of ethanol radical to acetic acid (a-d) adapted from [5] and to butan-2,3-diol (e). G-H represents glucose and G represents glucose derived radical as shown in Figure James Oliver CE for bioethanol research 144

169 Figure 4.3-8: Possible but unobserved products of glucose photo-oxidation in the presence of ethanol. Unobserved chemical shifts are in brackets. Figure 4.3-9: Possible interference of water derived radicals by ethanol. James Oliver CE for bioethanol research 145

170 Effect of pressure, sucrose concentration, CE instrument and photo-oxidizing sugar on the detection of ethanol in pressure mobilization Table 4.3-7: Effect of pressure on the peak height (n=5) of sucrose with and without ethanol (Figure 4.3-5). Pressure (mbar) 2000 mg L -1 sucrose, A Peak height (mau) SD 2000 mg L -1 sucrose spiked with 1000 mg L -1 ethanol, B Peak height SD (mau) Difference (A-B) Peak height (mau) Sum of SDs (Difference in peak height) x (sucrose velocity) Value SD James Oliver CE for bioethanol research 146

171 Figure : The velocity of sucrose at 10, 50 and 100 mbar (A) is indicated by star symbols on dashed line Error bars are ± 15 % to account for pump fluctuations. Effect of residence time in the window (B) on peak height of sucrose 2 g L -1 (squares on dotted line) and sucrose spiked with 1 g L -1 ethanol (squares on solid line) in pressure mobilization at different pressures. Error bars are ± standard deviations (n=5). Performed on MDQ instrument. James Oliver CE for bioethanol research 147

172 Figure : Peak areas of sucrose (solid line) and sucrose spiked with 1 g L -1 ethanol (dotted line), as well as difference between sucrose peak areas with and without ethanol (dashed) after pressure mobilization at 50 mbar in a 90 cm (10 cm effective length) capillary (n = 5). Error bars on peak area difference are ± sum of the standard deviations of both peaks (n=5). Performed on MDQ instrument. James Oliver CE for bioethanol research 148

173 Figure : Sucrose peak at 500 mg L -1 (black solid), 1000 mg L -1 (black dotted), 2000 mg L -1 (red solid) 4000 mg L -1 (red dotted) and 8000 mg L -1 (blue solid) without ethanol (A) with 1000 mg L -1 ethanol (B). Performed on MDQ instrument. James Oliver CE for bioethanol research 149

174 Figure : Effect of sucrose concentration on the signal to noise ratio (S/N). Figure : Standard curve obtained from MDQ (red) obtained from 4 separated days spaced over a month, 7100 (black) and a combination of the 2 (blue). James Oliver CE for bioethanol research 150

175 Figure : Calibration curve of ethanol concentration against difference in peak height for sucrose (black circles) and xylitol (red triangles) (n=5). Figure : Pressure mobilization of 5.8 mm sucrose (black) and xylitol (red) in the presence of 1 g L -1 ethanol. Performed on MDQ instrument. James Oliver CE for bioethanol research 151

176 Figure : Comparison of the signal to noise ratio of a sucrose peak (2 g L -1 ) between the 7100 CE and the MDQ instruments (n=5). Figure : CE of ethanol when the electric field (24 kv) was applied for the entire separation. Performed on 7100 CE instrument. James Oliver CE for bioethanol research 152

177 Figure : Detection of 1 g L -1 ethanol via CE by interference with the photo-oxidation of sucrose. Indirect ethanol peak is shown in the dashed boxes. BGE in outlet and inlet was 130 mm Na, BGE in capillary was 130 mm Na + 2 g L -1 of sucrose (black, S/N = 37) and 130 mm Na g L -1 of sucrose (red, S/N = 36). Migration was by electric field (24 kv) for 12 min followed by pressure mobilization at 50 mbar. Current was 160 µa. Performed on 7100 CE instrument. References: [1] D.R. Lide, Hdbk of Chemistry & Physics 74th Edition, Taylor & Francis, [2] Y.-R. Luo, Handbook of bond dissociation energies in organic compounds, CRC Press, Boca Raton, Fla., [3] G.O. Phillips, G.J. Moody, J Chem Soc (1960) [4] T.C. Laurent, J. Am. Chem. Soc. 78 (1956) [5] J.L. Bolland, H.R. Cooper, Proc. R. Soc. London, Ser. A 225 (1954) 405. James Oliver CE for bioethanol research 153

178 5. Publication Simple and robust monitoring of ethanol fermentations by capillary electrophoresis Contribution to PhD work, field, and candidates personal and professional development Fermentation monitoring by CE Lignocellulosic fermentations have a complex carbohydrate mixture and sample matrix. In this project, CE with direct UV detection has been shown to be a simple and robust method for carbohydrate determination in lignocellulosic fiber samples. With ethanol determination by a compatible method a possibility after the 3 rd publication, various ethanol fermentation samples including ones from lignocellulosic fermentations were studied. This publication was undertaken to determine the best BGE for separation of carbohydrates in a fermentation samples as well as comparing them to HPAEC and HPLC on a cation exchange resin. The final experiment demonstrated the monitoring of sugars, sugar alcohols and ethanol in a lignocellulosic fiber fermentation. The acid pre-treatment and an enzymatic hydrolysis were used to maximize the liberation of fermentable carbohydrate available for fermentation to ethanol and arabitol. Two ethanologens were used in this study to generate fermentation samples. Simple fermentation samples were produced by fermenting glucose and fructose by the bacterium Zymomonas mobilis. More complex mixtures including lignocellulosic samples were fermented by the yeast Pichia stipitis. Both organisms have been previously used successfully ( ). The research question of the 4 th publication was Can CE be used for monitoring of lignocellulosic fermentations? This publication contributed to the field of study by providing an in-depth investigation on the effect the BGE has on the analyte s electrophoretic mobility, resolution and the resolution achieved per min (denoted T res in this publication). Based on this study, we were able to recommend the conditions that would maximize the throughput or resolution depending on the complexity of the mixture and demonstrate the ability of CE to determine sugars, sugar alcohols and ethanol in complex lignocellulosic fiber fermentation samples. James Oliver CE for bioethanol research 154

179 5.1.2 Contribution to my personal development This publication contributed to my personal development by giving me the opportunity to present a poster at the international conference located in Dresden, the 6th International Symposium on the Separation and Characterization of Natural and Synthetic Macromolecules (SCM- 6 see Conference and seminar presentations ). I was also provided training on HPAEC. Professional development was achieved through my continued collaboration with Professor Emily Hilder and a new collaboration with Dr Naama Karu both from ACROSS at UTas. Determination of resolution in CE, which is unusual in comparison to HPLC and HPAEC was discussed with statistician Dr Glenn Stone of UWS (mentioned in Acknowledgements). I also trained undergraduate student and coauthor Adam Sutton in CE. This publication had 7 co-authors. The last author, Dr Patrice Castignolles provided the direction of the paper. Adam Sutton reproduced some of the injections that determined the optimal concentration for the BGE. These results are presented in the supporting information. Prof. Emily Hilder had the idea to use HPAEC and Dr Naama Karu provided training on HPAEC. Michael Phillips, Julie Markham and Paul Peiris provided direction and feedback on carrying out the fermentations that were used as samples for this publication. I performed all background research, experiments and data acquisition except for some of the injections noted in the supporting information (Table 5.3-2) which were performed by Adam Sutton. I performed all data analysis as well as writing the first draft of the publication. I developed the idea of comparing different mixtures of BGE and comparing simple BGE quantitatively in regards to electrophoretic mobility, resolution and time of separations. I developed the idea to compare not only HPLC as done in the first publication but also do a comparison of CE to HPAEC building on Prof. Hilder s idea to use HPAEC. HPAEC was not available at UWS even though it is a preferred method in the field for its high sensitivity and flexible separation. A second trip to UTas was organized for the purpose of using HPAEC. James Oliver CE for bioethanol research 155

180 5.2 Publication Simple and robust monitoring of ethanol fermentations by capillary electrophoresis James D. Oliver, 1,2 Adam T. Sutton, 1 Naama Karu, 3 Michael Phillips, 2 Julie Markham, 2 Paul Peiris, 2 Emily F. Hilder, 3 Patrice Castignolles 1* 1 University of Western Sydney, Australian Centre for Research On Separation Sciences (ACROSS), School of Science and Health, Parramatta Campus, Locked Bag 1797, Penrith NSW 2751, Australia 2 University of Western Sydney, School of Science and Health, Hawkesbury Campus, Locked Bag 1797, Penrith NSW 2751, Australia 3 Australian Centre for Research on Separation Science (ACROSS), School of Chemistry, University of Tasmania, Hobart TAS 7001, Australia, emily.hilder@utas.edu.au *Corresponding author p.castignolles@uws.edu.au Running title: capillary electrophoresis to monitor fermentations Synopsis Free solution capillary electrophoresis (CE), or capillary zone electrophoresis, with direct UV detection was used for the first time for the determination of mono- and disaccharides, sugar alcohols and ethanol in fermentation broths. Sample preparation proved to be minimal: no derivatization or specific sample purification was needed. The CE conditions can be adapted to the type of fermentation by simply altering the background electrolyte (BGE). 130 mm K or 130 mm Na as the BGE led to the fastest analysis time when monitoring simple fermentations. A mixture of 65 mm Na and 65 mm Li led to a 19 % improvement in resolution for a complex mixture of carbohydrates. Quantification of a simple carbohydrate fermentation by CE showed values in close agreement with that of High Performance Anion Exchange Chromatography (HPAEC) and High Performance Liquid Chromatography (HPLC) on a cation exchange resin. For complex fermentations, quantification of carbohydrates by HPLC and CE led to similar results while CE requires an injection volume of only nl. Analysis of an ethanol fermentation of hydrolyzed plant fiber demonstrated the robustness of the separation and detection of carbohydrates, as well as ethanol. Ethanol determination is by coupling the CE method to pressure mobilization, using the same instrument and the same sample. Keywords: capillary electrophoresis, carbohydrate, fermentation, high performance anion exchange chromatography (HPAEC), high performance liquid chromatography (HPLC), resolution James Oliver CE for bioethanol research 156

181 1 Introduction: Research on ethanol fermentations has been increasing due to its ability to replace petroleum as a liquid fuel or building block for commodity plastics. Significant advances have been made in relation to the biomass to ethanol conversion process (1). Methods for analyzing the feedstock and monitoring the fermentation substrates and products have not progressed as rapidly. Gas Chromatography (GC) is commonly used to monitor ethanol as well as other fermentation products (2) however carbohydrates require derivatization to become volatile for separation (3, 4). High Performance Liquid Chromatography (HPLC) using Hydrophilic Interaction Liquid Chromatography (HILIC), ligand exchange and ion exchange resins have proven useful in monitoring ethanol fermentations from carbohydrates with little sample preparation (5). HILIC can provide separation of most carbohydrates and is particularly useful for oligosaccharides. However, samples need to be diluted in a relatively polar organic mobile phase such as acetonitrile which can cause precipitation of proteins and polysaccharides in the sample. For higher recovery and resolution, solid phase extraction needs to be carried out for removal of interfering compounds (6). Lead based ligand exchange columns are popular for analyzing both acid treated fiber and fermentation samples (7-9). Fermentation monitoring with this column, as with most, requires sample pre-treatment, centrifugation, filtration of the supernatant and in some cases sample neutralization (10). Sample preparation can lead to variability in the amount of carbohydrates determined (7). Columns based on hydrogen-form exchange resins are popular in monitoring fermentation of complex mixtures based on their ability to separate carbohydrates as well as the fermentation products ethanol and acetic acid (11-13). Samples only require filtration prior to injection on this column (10) however there are issues with the plant fiber carbohydrates galactose, xylose and mannose co-eluting (14, 13). Reverse phase liquid chromatography leads to higher resolution of these sugars (15) however retention as well as selective and sensitive UV or visible detection require derivatization, which is tedious and may introduce errors. High Performance Anion Exchange Chromatography (HPAEC) utilizing pulsed amperometric detection (PAD) was previously used to monitor carbohydrates in fermentation media with filtration and dilution as the only pre-treatment (16, 17). PAD provides higher detection sensitivity and can be used with a gradient flow in contrast to Refractive Index (RI) detection which is most suitable for the HPLC methods previously mentioned. HPAEC has been used for substrate analysis and monitoring fermentation of carbohydrates utilizing a column with a Microbead TM pellicular resin (18, 19). A separate column containing a macroporous polymeric anion exchange resin was required for the determination of ethanol and sugar alcohols in samples (20). James Oliver CE for bioethanol research 157

182 Free solution capillary electrophoresis (CE) is a fast and robust technique for monitoring complex carbohydrate samples obtained from plant fibers and it requires minimal injection volumes and sample treatment (21, 22). CE enables the detection of carbohydrates with indirect UV detection, mass spectrometry and also, more recently, a simple direct UV detection.(23) CE in highly alkaline electrolytes (ph 12.6) has shown to be successful for the separation of carbohydrates in fruit juice (24), hydrolyzed plant fiber (22, 21) and glycoproteins (25), but it has never been applied to fermentation monitoring. In this system, the ph of the electrolyte is above the pk a of the carbohydrates, thus the analytes are charged and separated based on their charge-to-size ratio. The flow of ions adsorbed on the capillary surface creates an electro-osmotic flow (EOF), marked by an uncharged molecule. The electrophoretic velocity of the carbohydrates is in the opposite direction to the EOF, the separation thus being counter-eof (Figure and Equation 5.3-1). An unexpected yet sensitive and robust direct UV detection at nm is made possible by an electric field assisted photo-oxidation reaction (25, 21, 26). The application of free solution CE with direct UV detection in biotechnology is increasing (27, 28, 22). Previous work has demonstrated the superior robustness and resolution of CE with direct UV detection over HPLC with a cation exchange resin for the analysis of treated plant biomass (21). Similar work has investigated the detection of carbohydrates in biomass based samples with comparison to HPAEC (22) and HPLC with ligand exchange (28). Detection of ethanol from fermentation samples via photo-oxidation interference has been developed very recently: the free solution CE method is used to separate ethanol from the matrix and is coupled to a simple pressure mobilization in the presence of sucrose for an indirect detection of ethanol (29). When combined with adequate separation of carbohydrates, an ethanol fermentation may thus be monitored online with the same equipment both in terms of carbohydrates and ethanol. Analysis of fermentation samples by CE with direct UV detection as well as its comparison to HPLC and HPAEC have not previously been undertaken. The aim of this paper was to develop and evaluate a simple and robust method of monitoring carbohydrates and end products, including ethanol, in fermentation samples using CE with direct UV detection. CE with direct UV detection was then quantitatively compared to established methods of HPLC on an ion exchange resin and HPAEC for fermentation samples with model carbohydrate mixtures. The method was then used to monitor the ethanol fermentation of a lignocellulosic fiber. James Oliver CE for bioethanol research 158

183 2 Materials and Methods: 2.1 Materials MilliQ quality water (Millipore, USA) was used throughout the research. Ammonium sulfate 99 %, L-arabitol 98 %, xylitol 99 %and xylose 99 % were obtained from Alfa Asear (Ward Hill, MA, USA). Sodium hydroxide pellets (Na) 99.8 %, disodium hydrogen phosphate powder 99 %, lithium hydroxide monohydrate 98 %, dimethyl sulfoxide (DMSO) 99.5 %, magnesium chloride hexahydrate 99%, D+glucose 99.5 %, D+galactose 99 %, L-rhamnose monohydrate 99 %, D+fructose 99 % L-arabinose 99 % and absolute ethanol 99.5 % were obtained from Sigma- Aldrich (Sydney, Australia). Potassium hydroxide 85 % was obtained from Chemsupply (Adelaide, Australia). Monopotassium phosphate 99 %, and lactose ( % water, other impurities < 0.3 %) were obtained from Univar (Ingleburn, Australia). Mannose (Lot # 76585) was obtained from AJAX Chemicals (Sydney, Australia). Malt extract agar, technical agar and yeast extract were obtained from Oxoid (Thermo Fisher Scientific, Adelaide, Australia). ph was measured with a Mettler Toledo (Melbourne, Australia) InPro 3250/120/Pt1000 ph electrode with a Seven Compact ph/ion S220 ph meter utilizing ph standards of 7.00 and Microorganisms, Media and Fermentation Parameters Zymomonas mobilis (ATCC 10988) was obtained from the University of New South Wales. Z. mobilis was cultured on glucose agar (20.0 g L -1 glucose, 10.0 g L -1 yeast extract, 15.0 g L -1 technical agar and 2.0 g L -1 KH 2PO 4) at 30 C for 48 h. Pichia stipitis (WM 810) was obtained from Westmead Clinical School, University of Sydney, originally from Centraalbureau voor Schimmelcultures (CBS No. 5773). P. stipitis was cultured on malt extract agar. Inocula were prepared in 50 ml of liquid glucose medium (20.0 g L -1 glucose, 10.0 g L -1 yeast extract, 1.0 g L -1 MgCl 2, 1.0 g L -1 (NH 4) 2SO 4 and 1.0 g L -1 KH 2PO 4) in a 250 ml conical flask and incubated at 30 C for 12 h stationary for Z. mobilis and at 100 rpm for P. stipitis. The fermentation was initiated by centrifuging the inoculum, removing the supernatant and re-suspending the pellet in the fermentation medium (yeast extract, 1.0 g L -1 MgCl 2, 1.0 g L -1 (NH 4) 2SO 4 and 1.0 g L -1 KH 2PO 4) with carbohydrates or plant fiber (composition and concentrations described in the results and discussion section) in a 250 ml conical flask and incubated at 30 C. All samples were syringe filtered through a 0.2 µm nylon membrane (Grace, Sydney, Australia) for sterilization. James Oliver CE for bioethanol research 159

184 2.3 Preparation of plant fiber Cladodes of Opuntia fiscus-indicia were obtained from the wild in Richmond, NSW, Australia in November 2010 and identified by the National Herbarium of New South Wales. They were homogenized with water and centrifuged at 3000 rpm for 30 min. The insoluble fraction was dried to a constant weight at 75 C and milled to fit through a 1 mm sieve. Fiber was pre-treated by acid hydrolysis; 5 % (w/v) of dried fiber was added to a 2 % (v/v) sulfuric acid and heated by reflux to 134 C for 2 h. The ph of the solution was adjusted to 5.0 with barium hydroxide and enzyme hydrolysis was carried out at 40 C, ph 5 with 1 g of Viscozyme L (Novozymes, Denmark). 2.4 High performance liquid chromatography (HPLC) Separations were performed on a Shimadzu 20A Series System with a RID-10A refractive index detector (Shimadzu Scientific Instruments, Rydalmere, Australia) and a Sidewinder column heater (Restek, Bellefonte, PA, USA). Separations were performed using a Bio-Rad HPX-87H (Hercules, CA, USA) column at 60 C with an aqueous mobile phase containing 5 mm H 2SO 4, at a flow rate of 0.6 ml min µl of the sample was injected into the column. Data acquisition and analysis was by VP class v7.3 software from Shimadzu. 2.5 Free Solution Capillary electrophoresis (CE) Separations were performed on an Agilent 7100 (Agilent Technologies, Waldbronn, Germanry) with a Diode Array Detector (DAD) monitoring at 200 and 266 nm with a 10 nm bandwidth (except where noted otherwise in the supporting information). Fused-silica capillaries (50 µm i.d., 360 µm o.d.) were obtained from Polymicro (Phoenix, AZ, USA). Capillary length was 90 cm with an 81.5 cm effective length. The capillary was pre-treated prior to use by flushing with 1 M Na followed by water then the background electrolyte (BGE) for 20 min each. The sample was injected by applying 17 mbar of pressure for 8 s ( 10 nl in 130 mm Na) followed by BGE, injected in the same manner. Between each run, the capillary was flushed with BGE for 10 min. At the end of a series of injections, the capillary was flushed for 1 min with 1M Na, 10 min with water and 10 min with air. DMSO was added to each sample to make a concentration of 1 % (v/v) to mark the electro-osmotic flow (EOF) and 1 g L -1 of lactose was added as an internal standard. The EOF was determined at 200 nm. Integration was performed with Origin Pro 8.5 (Northampton, MA, USA) on electropherograms corrected for the EOF by plotting the intensity against the electrophoretic mobility (µ ep) (see supporting information, Equation 5.3-2). µ ep for each analyte was measured at the peak maximum. James Oliver CE for bioethanol research 160

185 2.6 Ethanol determination by capillary electrophoresis coupled with pressure mobilization Ethanol was determined by photo-oxidation inhibition as previously described (29) using the same instrument as above for CE. A 90 cm capillary (81.5 cm effective length) was pre-treated as described above for CE. It was then flushed with BGE (65 mm Na and 65 mm Li) containing 2 g L -1 of sucrose for 10 min before each injection. The sample was injected at 17 mbar of pressure for 8 s followed by BGE (without sucrose) in the same manner. The electric field was then applied for 12 min (BGE without sucrose in the inlet and outlet vials) followed by pressure at 50 mbar until ethanol detection at 266 nm. 2.7 High Performance Anion Exchange Chromatography (HPAEC) HPAEC was conducted on a Dionex (Thermo Scientific, Sunnyvale, CA, USA) IC system consisting of a GP50 gradient pump and LC30 column oven. Pulsed amperometric detection was conducted using an ED40 electrochemical detector in an amperometric cell mode using a gold working electrode. 10 µl of 1:300 diluted samples (in water) were injected onto a Dionex CarboPac PA1 column (4 x 250mm) with a PA1 guard column (4 x 50mm) at a flow rate of 1 ml min -1. Separation of glucose, fructose, arabinose and ethanol was under isocratic conditions of 30 mm Na for 10 min followed by a gradient to 100 mm Na in 1 min and held for 8 min then returned to 30 mm over 1 min for pre-equilibration of 4 min, adapted from (16). The mobile phase was degassed with nitrogen at 3.5 bar at the headspace of eluent bottles. Data acquisition was performed by Chromeleon V6.5, and post-processing was conducted using Origin Pro Results and Discussion: 3.1 Choice of standard mixture Fermentation samples of plant fiber can contain a large variety of both saccharides and sugar alcohols. CE in highly alkaline conditions has the potential to separate these analytes, but it had never been applied to these fermentation samples so it was not known which BGE and conditions CE best correspond for a given fermentation sample. A mixture of the common fiber monosaccharides galactose, glucose, rhamnose, mannose, arabinose and xylose as well as the valueadded fermentation end products, arabitol and xylitol were chosen as a representative standard. Lactose was added to the mixture as it has been used in a previous study as internal standard for quantification and a mobility marker for identification (21). James Oliver CE for bioethanol research 161

186 3.2 Electrophoretic mobilities of carbohydrates in CE: Effect of the BGE Separation of glucose, rhamnose and mannose is a known challenge in CE (24) and a relevant one for fermentation monitoring. In order to achieve baseline separation of these sugars a large selectivity (difference in electrophoretic velocity and thus electrophoretic mobility) is desired. Band-broadening also plays a role, as discussed in the next paragraph together with resolution values. Separation in the simplest BGE (to lead to the most robust separation) was examined first. Separations were performed in this work using Na (25) but also Li and K (30), as well as various mixtures (Table 5.2-1). The maximum relative standard deviation (RSD) for any electrophoretic mobility value of a carbohydrate was 2.5 % (n=3). The electrophoretic mobility values in Table allow identification of the carbohydrates separated by CE in the relevant BGE irrespective of the capillary length and electric field. James Oliver CE for bioethanol research 162

187 Table 5.2-1: Electrophoretic mobility (µ ep) of carbohydrates and related fermentation end products (0.5 g L -1 each) in different BGE (a more extensive version is given as Table 5.3-1). Conditions: Voltage 24 kv, temperature 15 C, current of 160 ± 6 µa. The values are an average of three sequential injections. Carbohydrate Background Electrolyte (BGE) 52 mm K 130 mm K 26 mm Li 52 mm Na µ ep ( m 2 V -1 s 1 ) 130 mm Na 130 mm Li Xylitol Arabitol Lactose Galactose Glucose Rhamnose Mannose Arabinose Xylose Time of EOF marker (min) [RSD (%)] Viscosity (η) (mpa s) of the BGE at 25 C a Time of EOF/Viscosity (mpa -1 ) Rhamnose relative position in relation to glucose and mannose b Difference in µ ep between mannose and glucose (10 8 m 2 V [3.95] [1.47] [1.13] [2.61] 130 mm Na 36 mm Na 2HPO [0.54] 2.2 Not measured Not measured s 1 ) ph c Not measured a Interpolated from the correlation in (31). b Calculated by the difference in µ ep between rhamnose (m R) and glucose (m G) over the difference in µ ep between rhamnose and mannose (m M) x = ( (mm RR mm GG ) ). x = 1 when rhamnose is equal distance (mm MM mm RR ) between glucose and mannose, x> 1 when rhamnose is closer to mannose, x<1 when rhamnose is closer to glucose. c Experimental ph, (the theoretical ph, assuming the activity co-efficient is 1, would be 13.1). James Oliver CE for bioethanol research 163

188 An increase in BGE concentration from 30 to 170 mm resulted in an increase in the electrophoretic mobilities (due to higher ph) as well as the separation selectivity (Table 5.3-2). A concentration of 170 mm however resulted in a total poor resolution (Table 5.3-3; discussed later) and an increased analysis time. Therefore a concentration of 130 mm was chosen for this study as the BGE concentration as it provided adequate resolution in an appropriate time and has been used in previous studies (25). At 130 mm, K provided the highest electrophoretic mobilities and the largest selectivity between the carbohydrates (lactose xylose x 10 8 m 2 V -1 s 1 ) as well as the fastest EOF. 130 mm Li provided the smallest electrophoretic mobilities and the smallest selectivity ( x10 8 m 2 V -1 s 1 ) and EOF (Table 5.2-1). The electrophoretic mobility of the carbohydrates depends on the ratio of the charge to the product of hydrodynamic radius and BGE viscosity (See Equation 5.3-4). Taking the differences in viscosities into account (see Equation 5.3-4), the hydrodynamic radius of the carbohydrate in K might be larger than in Na or Li (Table 5.3-5). Viscosity might be the main contributor to the lowest EOF (see Equation 5.3-3) and higher electrophoretic mobilities of the carbohydrates in K. The increase in carbohydrate size in K might be due to a stronger complexation of the carbohydrates with K + leading to a larger hydrodynamic radius than with Na + or Li + in the conditions used (32, 33), ion pairing or a difference in the structure of the carbohydrate in the presence of the cation (34) as observed with the helix conformation of gellan gums induced by K + but not by Na + (35). Although the carbohydrates have a larger electrophoretic mobility in K than in Na, the sugar alcohols have a smaller electrophoretic mobility: sugar alcohols may not complex with K +. The electrophoretic mobility of rhamnose is also affected differently by the change in counterion compared to the electrophoretic mobility of glucose and mannose. To achieve complete separation, one needs both a large difference in electrophoretic mobility between mannose and glucose (i.e. a larger window of separation), and rhamnose in the middle. The electrophoretic mobilities in several mixtures of Li, Na and K BGE were compared (Table and Table 5.3-1) on a contour plot (Figure 5.3-2). The optimal position of rhamnose was achieved with 43.3 mm K, 43.3 mm Li and 43.3 mm Na (designated M4), while the optimal (largest) selectivity was with 130 mm K. M4 is a good candidate for separation of complex fermentation samples containing glucose, rhamnose and mannose, while K is a good candidate for less complex fermentations that do not contain rhamnose (Figure 5.2-1). James Oliver CE for bioethanol research 164

189 Figure 5.2-1: Separation of carbohydrates and related fermentation end products (0.5 g L -1 each) in M4 BGE comprised of 43.3 mm K, 43.3 mm Li and 43.3 mm Na (A) and 130 mm K (B). An illustration of the peak to valley ratio is given in C and of the orthogonal peak to valley ratio is given in D. Conditions: Capillary length 90 cm (81.5 cm effective length), voltage 24 kv, temperature 15 C, current of 160 ± 6 µa. Peak assignments: (1) xylitol, (2) arabitol, (3) lactose, (4) galactose, (5) glucose, (6) rhamnose, (7) mannose, (8) arabinose, (9) xylose. The separation time is shorter in K than M4 however this results in poorer sensitivity, since the sensitivity is proportional to the residence time in the detection window, as it is linked to the photo-oxidation reaction that allows direct UV detection (25, 26). Resolution of carbohydrate separation by CE and choice of the BGE The effect of the counterion on the separation of carbohydrates has been qualitatively studied (24, 30). Colon et al. compared the separation of a carbohydrate mixture with a BGE containing Na +, Li + or K + as well as a different Na + concentration. They concluded that Na gave a good resolution in a suitable time (41 min for xylose), however resolution values were not quantified. The typical resolution equation used for chromatographic separations (Equation 5.3-6, Figure 5.3-4) is not an appropriate tool to determine the quality of the separations in this work since James Oliver CE for bioethanol research 165

190 peaks are highly asymmetric (36), which is typical of CE, and cannot be described by a Gaussian function. Resolution in CE can be predicted but only if the exact diffusion coefficient is known for each analyte (37). Resolution (R vp) of the separation of asymmetric peaks can be instead measured by the valley to peak ratio (38) or an improved version proposed as the orthogonal valley to peak ratio (R ovp) (39). R ovp or R vp = 100 VV s PP Equation In the case of R vp, V s is the height of the valley (defined as the minimum between the two apexes) between the two peaks and P is the height of the lowest peak (Figure 5.2-1C), whereas in the case of R ovp, V s is defined as the height of the valley and P is the distance from the baseline to the interpolated peaks height at the same time (Figure 5.2-1D); the valley is in this case determined as the largest P-V s distance obtained when a straight line orthogonal to the interpolation of the peaks is moved from one maximum to the other one. The orthogonal valley to peak ratio was used to determine the resolutions of the separations in this work (Table 5.2-2). The valley to peak ratios, shown in Table and Table 5.3-3, are less time-consuming to determine manually. For both R vp and R ovp, the lower the ratio, the better the resolution. Resolution of all the studied analytes in different BGE concentrations from 30 to 170 mm Li were determined and 130 mm gave the best resolution (Table 5.3-3) for the sugars while 170 mm led to slightly better resolved separations of the sugar alcohols. James Oliver CE for bioethanol research 166

191 Table 5.2-2: Resolution (expressed as orthogonal valley to peak ratio expressed as 100 x V s/p) of the mixture of carbohydrates (the lowest value is given in bold). Separation conditions: 24 kv, 90 cm capillary (81.5 cm effective length). Mixture contains 0.5 g L -1 xylitol, arabitol, lactose, galactose, glucose, rhamnose, mannose, arabinose and xylose. n=3. The lowest values are indicated in bold. 130 mm Na 130 mm Li 130 mm K 65 mm Li 65 mm Na (M1) 43.3 mm K, 43.3 mm Li 43.3 mm Na (M4) 130 mm Na, 36 mm Na2HPO4 Xylitol-Arabitol Glucose-Rhamnose Rhamnose-Mannose Mannose-Arabinose Sum of R ovp RSD (%) R ovp RSD (%) R ovp RSD (%) R ovp RSD (%) R ovp RSD (%) Product of all R ovp RSD (%) Time of last peak (min) James Oliver CE for bioethanol research 167

192 The greatest difference in electrophoretic mobility was observed with 130 mm K buffer (Table 5.2-1), although this resulted in poor resolution (Table 5.2-2), likely due to the fastest EOF resulting in insufficient time for the analytes to separate. Rhamnose had the optimal electrophoretic mobility value in M4 BGE, being between glucose and mannose electrophoretic mobility values, but did not lead to the optimal resolution of these three sugars, partially due to the second fastest EOF. For separations of complex mixtures with a single electrolyte (contain only one counter-ion; simplest to prepare), 130 mm Na, provided the best resolution overall however not noticeably different from Li. Separation of rhamnose-mannose and arabitol-xylitol was better achieved with 130 mm Li. An even combination of the two electrolytes (designated M1) gave a better overall resolution (19 % improvement relative to 130 mm Na). There was a decrease in resolution between glucoserhamnose in M1 in comparison to 130 mm Na due to the rhamnose s electrophoretic mobility shifting closer to glucose (see Table and Figure 5.3-2). Comparison of the resolution with different counterions in the BGE was previously conducted at the same EOF by Colon et al. (30). This was achieved by altering the electric field while keeping EOF constant. Although altering the electric field should not alter the electrophoretic mobility of the charged species for the same BGE, it may affect the resolution and therefore a fair comparison cannot be made with other BGEs unless the same electric field is used. Resolution in CE generally increases with analysis time which can be achieved by increasing the capillary length (without changing the electric field) or slowing down the EOF. The EOF can be slowed by increasing the viscosity of the BGE, lowering the temperature (Figure 5.3-5), adding an organic solvent (40) or adding a buffering agent such as Na 2HPO 4 to the BGE. The latter is more difficult without changing the conductivity of the buffer which was shown previously to be an factor influencing the separation (41). The addition of 36 mm Na 2HPO 4 to 130 mm Na slowed the EOF by 1.5 min (Table 5.2-1) but also decreased all electrophoretic mobilities (Table 5.2-1): contrary to previous reports (24) it did not result in greater resolution. The addition of methanol (Figure 5.3-5) to the BGE led to loss of signal, due to inhibition of the photo-oxidation reaction that allows detection of the carbohydrates (26, 29). Alternatively, pressure may be applied to the outlet vial (or vacuum to the inlet vial) (42) to slow the separation (Figure 5.3-5). This improves resolution but at the cost of analysis time (Table 5.3-7, and 5.3-9). For a complex fermentation sample containing glucose, rhamnose and mannose, a mixture of 65 mm Li and 65 mm Na is recommended, although this results in an increase of analysis time. James Oliver CE for bioethanol research 168

193 Throughput of carbohydrate separation by CE and choice of the BGE Throughput is also important in monitoring fermentation. To account for time and resolution of the separation, the orthogonal valley to peak ratio was multiplied by the migration time at the valley (t) (Equation 5.2-2). For a biotechnological process, this quantity might be referred as efficiency ; the term efficiency in CE (and separation science in general) however already has an existing and different definition (plate count). Equation accounts for both resolution and the time taken for that resolution to be achieved: T res is the time in min to achieve a given resolution and the objective is to minimize T res. T Res = VV stt PP Equation where V S and P are defined in Equation (R ovp). Separation of a carbohydrate mixture in 130 mm Na, K and Li was carried out and the T res was measured for each (Table 5.3-8). T Res values calculated with the valley to peak ratio (instead of the orthogonal valley to peak ratio) are also shown in Table Comparing the separation in BGE with individual compounds at concentrations of 130mM, Li led to the lowest (best) T Res for the sugar alcohols and highest (worse) T Res for rhamnose and glucose as expected from the selectivity. 130 mm Na as a simple BGE, led to lowest T Res for the mono- and di-saccharide separation as well as overall (shown by the product of all the resolutions for each analyte measured). The BGE M4 does not give a lower T Res than 130 mm Na (Table 5.3-8) nor does it give a better resolution (Table 5.2-2). The M1 mixture, giving a better resolution than 130 mm Na, did not lead to a significantly lower T Res. The 130 mm Na BGE, led to the lowest T Res of all separations except for the sugar alcohols. The use of 130 mm Na as a BGE was compared to the sodium phosphate buffer by both Rovio et al. (24) and Sarazin et al. (25). Rovio et al. (24) noted that the detection in disodium phosphate benefited from lower baseline noise and resolution of the separation improved between glucose, mannose, rhamnose and arabinose. In contrast Sarazin et al. (25) noted similar analytical performance between the two BGEs in terms of separation efficiencies, corrected peak areas and limits of detection as well as a simpler buffer preparation, but for less complex samples. In this study, a more complex sample was analyzed and it was found that 130 mm Na/36 mm Na 2HPO 4 did not perform better than 130 mm Na in both resolution and T Res for the peaks measured. A mixture of 65 mm Li and 65 mm Na is recommended for separation of the most complex James Oliver CE for bioethanol research 169

194 mixtures, such as the fermentation of plant fiber to sugar alcohols (Table 5.2-3). However, for fiber fermentations where the rhamnose is negligible, 130 mm Na would give lower (better) T Res. For the simplest fermentation sample such as the glucose-xylose or a single sugar, 130 mm K would provide separation in less than 15 min (Table 5.2-3). It is to be noted that use of pressure to slow down the separation lead to higher (worse) T res. Table 5.2-3: List of current/potential fermentation substrates and the recommended BGE to monitor the fermentation using CE. Substrate sugar cane Juice switch grass corn stover, wheat straw, rice straw, rice hulls, cotton gin trash, Douglas fir Opuntia sp. Fermentable carbohydrates of interest glucose, fructose, sucrose glucose, xylose glucose, mannose, galactose, xylose, arabinose galactose, rhamnose, glucose, xylose, mannose, arabinose Recommended BGE 130 mm K (or 130 mm Na with 30 kv) 130 mm K (or Na with 30 kv) Reference for the substrate composition (43) (44) 130 mm Na (45) 65 mm Li + 65 mm Na (21) sugar cane bagasse glucose, xylose, arabinose 130 mm Na (46) A list of current and potential bioethanol substrates and the recommended BGE can be found in Table Based on results reported above, the BGE was chosen to give the optimal analysis time with adequate resolution for the reported composition of the substrates. Various fermentations were analyzed with the recommended BGE. A fermentation of glucose and fructose was analyzed by CE with 130 K BGE, a fermentation of glucose, galactose, arabinose and xylose was analyzed by CE with 130 Na BGE and a fermentation of plant fiber from Opuntia ficus-indica was monitored with a BGE of 65 mm Na and 65 mm Li. Under some hydrolysis methods, the plant fiber Opuntia ficus-indica may yield rhamnose (21) which can be the most challenging to separate. This BGE may also be used to monitor the fermentation of other lignocellulosic material that can also contain rhamnose (22). The results are shown and discussed in the next section. James Oliver CE for bioethanol research 170

195 3.3 CE Performance comparison to HPLC and HPAEC on simple fermentations To examine the quantitative ability of CE, fermentation was carried out and separation performance of CE compared to two commonly used chromatographic methods. A mixture of glucose and fructose (10.0 g L -1 glucose and 10.0 g L -1 fructose) was fermented by Zymomonas mobilis and the carbohydrates were monitored by HPLC, HPAEC and CE (Figure 5.2-2). In CE, the BGE comprised of 130 mm K, as the sample contained only two carbohydrates that were easily separated and detected. James Oliver CE for bioethanol research 171

196 Figure 5.2-2: Quantitative comparison of glucose (A), fructose (B) and total carbohydrate (C) in terms of absolute concentration (bar graph) and remaining fraction (line graph) in a simple fermentation sample by HPAEC ( and ), HPLC ( and ) and CE ( and ). Error bars indicate ± standard deviation (n=3). The sugar concentrations were in close agreement between CE, HPLC and HPEAC with a less than 7 % difference from the average total detected amount (Table ). While CE is less precise than HPAEC and HPLC, no method is clearly more accurate than another (standards curves for each method had a correlation co-efficient > 0.97). Retention times for the three methods (electrophoretic mobility for CE) were determined with similar precision (Tables , and ). Separation of glucose and fructose in CE was achieved in less than 16 min separation time (26 min total time, including the time needed to flush the capillary with fresh BGE in between injections) in comparison to 12 min with HPLC (23 min total elution time, including the time needed to ensure everything is eluted from the column) and 13 min with HPAEC (30 min total time, including the time needed to flush the column between injections). However, electropherograms exhibited an elevated baseline between the two carbohydrates peaks (Figure 5.3-6), which reduced the precision of peak integration and possibly contributed to the outlying values for glucose at the higher concentrations (0 hour sample Figure 5.2-2A and 5.2-2C). Asymmetric peaks are common in CE, but integration is still easily achieved, e.g. in (47). James Oliver CE for bioethanol research 172

197 A fermentation with a larger variety of sugars, glucose, galactose, arabinose and xylose (12.0 g L -1 of each) to ethanol and arabitol by Pichia stipitis, was monitored by HPLC and CE (Figure 5.2-3). Figure 5.2-3: Quantitative comparison of glucose (A), arabinose (B) and arabitol (C) in a complex fermentation sample by HPLC ( ) and CE ( ). Error bars represent ± STD (n=3). Xylose and galactose were quantified by CE; however, as they co-eluted using the HPLC column and conditions used in this study, no comparison was made for these two individual sugars. The concentration values of the analytes measured by CE and HPLC were in close agreement, however arabinose was marginally higher using HPLC and arabitol was marginally higher using CE. The comparison for quantitative analysis shows that the detection by photo-oxidation in CE, although not fully understood (26), was not affected by this sample matrix. For fiber samples, the CE method detected a larger amount of several carbohydrates compared to HPLC (21), while this was not the case for the other fiber samples tested by HPAEC (22) or for the fermentation samples in this work. The more complex matrix in fiber samples might have led to the loss of some carbohydrates in the HPLC column, while this was not observed in fermentation samples. James Oliver CE for bioethanol research 173

198 3.4 Determination of carbohydrates and ethanol during fermentation of lignocellulosic plant fiber by CE. The CE method was used to analyze the fermentation of carbohydrates from hydrolyzed plant fiber to the end products ethanol and arabitol. The hydrolyzed plant fiber of Opuntia ficusindica has a complex mixture of carbohydrates (21) and, arising from the mucilage, uronic acids (48) as well as incompletely hydrolyzed oligo- and polysaccharides. Based on a previous study, the matrix was expected to contain trace amounts of hydroxymethylfurfural (HMF) and furfural as by-products arising from the acid pre-treatment (28), products from the enzyme solution (e.g. stabilizers) and trace amounts of barium sulfate from neutralization (max 3.1 mg/l (49)). A BGE of 65 mm Li and 65 mm Na was used for the optimal separation of carbohydrates (see Table 5.2-3). Ethanol was determined via photo-oxidation inhibition as detailed in one of our recent papers (29). Figure 5.2-4: Fermentation of hydrolyzed plant fiber to ethanol. Samples taken at 0 hours (A), 6 hours (B) and 24 hours (C). Peak assignments: (1) lactose (internal standard), (2) galactose, (3) glucose, (4) mannose, (5) fructose, (6) arabinose, (7) xylose, (8) arabitol, (9) unknown (for migration plot see Figure 5.3-8). Ethanol peak in sequential injection given as inverted peak for 0 h ( ), 6 h ( ) and 24 h ( ). James Oliver CE for bioethanol research 174

199 The analysis of the hydrolyzed plant fiber revealed 4 minor peaks (S/N 10; unnumbered) as well as the most predominant peaks of glucose, galactose, mannose, arabinose and xylose which were identified by their electrophoretic mobility. Fructose was identified by an electrophoretic mobility higher than mannose and lower than arabinose as observed in a previous study (28). Over the course of the fermentation all peaks decreased to undetectable levels, with the exception of arabinose which was only in minor amounts (S/N = 10) after 24 hours, indicating that all analytes were utilized by the organism. Arabitol was detected (see Table 5.2-4). It was observed, after 24 hours of fermentation when arabinose began to be utilized by the organism. Other peaks were identified with electrophoretic mobilities close to that of arabitol. Table 5.2-4: Precision of mobility measured in standard and fiber fermentation samples. Standards Sample Electrophoretic Electrophoretic Mobility a SD RSD ( m 2 V -1 s -1 (- 10 ) m 2 V -1 s -1 n = Mobility ) (%) SD RSD ( m 2 V -1 s -1 (- 10 ) m 2 V -1 s -1 ) (%) n= Arabitol Galactose Glucose Rhamnose N.D Mannose Arabinose Xylose a electrophoretic mobility calculated using lactose internal standard as mobility marker (µ ep = x 10-8 m 2 V -1 s -1 ) and not from the EOF marker as in Table and (Equation 5.3-7). The precision of the electrophoretic mobility for each analyte was excellent in both the standards as well as the fiber fermentation samples. The electrophoretic mobility of arabitol in the sample has the highest variability as it is the furthest from the mobility marker. If peaks were observed close to arabitol then a double mobility correction would need to be used (with sucrose for example).the high precision of the electrophoretic mobility allows for accurate identification of the carbohydrates of interest. The complex matrix of hydrolyzed plant fiber in fermentation media did not hinder the identification of the analytes by their electrophoretic mobility. This illustrates the robustness of the CE method. James Oliver CE for bioethanol research 175

200 Figure 5.2-5: Quantification of carbohydrates, arabitol and ethanol during ethanol fermentation of plant fiber. Samples were analyzed (n=5) at 0 h ( ), 6 h ( ) and 24 h ( ). The fermentation followed the expected trend with glucose and mannose being utilized within the first 6 h and the pentoses being utilized last (no significant decrease of arabinose and xylose in the first 6 h). Determination of ethanol is essential in fermentation monitoring. The inability to determine ethanol at all was a significant disadvantage of HPLC with ligand exchange and CE in highly alkaline electrolyte. HPLC on a cation exchange resin is able to determine ethanol as well as some carbohydrates, however not all fiber sugars are resolved (21). HPAEC can also determine ethanol in standards with the column used in this study, however, in fermentation samples, it coelutes with other fermentation media components that are as weakly charged (Figure 5.3-9). Very recently, we showed that ethanol can be detected by the interference of the sugars photo-oxidation (29) and ethanol is observed by indirect detection in a BGE containing sucrose during pressure mobilization (Figure 5.2-4). While both sugars and ethanol are separated within one run, the presence of sucrose results in a high level of noise for the sugar detection: ethanol cannot yet be determined in the same injections as the CE of carbohydrates (29). This is a limited issue in terms of James Oliver CE for bioethanol research 176

201 sample amount, as only 10nL is injected in both cases, but this results in a longer total separation time as 2 injections need to be performed sequentially. The same capillary is used in both separations. Applying this new method to fermentation monitoring, ethanol was quantified with a 6 % and 10 % RSD for the 6 and 24 hour sample respectively. Although this is not as precise as headspace GC (RSD 2 % (50)), the accuracy of the CE coupled to pressure mobilization to determine ethanol has been positively assessed in our previous paper (29). CE has the advantage of monitoring carbohydrates and other end products such as arabitol without derivatization or without timeconsuming or costly sample preparation. The separation time was min (43-48 min total time) for determination of carbohydrates for the most complex fermentation samples and 21 min (31 min total elution time) for determination of ethanol in the following injection, so min total time. The simultaneous determination of ethanol and carbohydrates in this complex mixture with a single instrument and capillary could not be accomplished by any other method in the literature. The ethanol yield was 105 % of the theoretical maximum after 6 hours as calculated from the quantified carbohydrates, likely because the carbohydrates below quantifiable levels also contributed to the ethanol production. The last sample showed a decrease in ethanol (ethanol yield of 59 % of the theoretical maximum) when arabitol was being produced from arabinose. A similar observation has been made during the production of ethanol and xylitol by yeasts (51). A summary of some of the advantages and drawbacks in CE, HPLC with a cation exchange resin and HPAEC are given in Table James Oliver CE for bioethanol research 177

202 Table 5.2-5: Advantages and drawbacks in CE, HPLC with a cation exchange resin and HPAEC for determination of carbohydrates Parameter CE HPLC (cation exchange resin) HPAEC Robustness a Total Time (Glucose Fructose sample) 26 min 23 min 30 min Set-up time (Column pre-equilibrium time /capillary flush time) 35 min min d 30 min (min) Determination of ethanol and fiber sugars f with the same yes no no capillary/column LOD b (Glucose) 1.8 mg L -1 (26) 3.7 mg L -1 (28) c (3.3 mg L -1 rhamnose 70 mg L -1 (52) mg L -1 (20) (28)) c Pre-filter required for separation no yes yes Dilution required 1:5 1:20 None 1:50 1:300 Injection volume nl µl µl Mobile phase or BGE volume per run 0.5 ml 13.8 ml 30 ml Set-up cost e AU$7.2 (21) AU$3461 (21) AU$2100 a defined as a method that can be applied to analytes in a wide variety of matrices (53) b Limit of detection (LOD) calculated as a Signal-to-noise = 3 c LOD calculated by (28) using analytical curve parameter evaluation d Heated column e cost of setting up the system before performing the separation. Inclusive of purchasing columns/capillaries as for Dec 2013 estimated as in (21). Not inclusive of purchasing instrument. f in lignocellulosic fermentation sample James Oliver CE for bioethanol research 178

203 4 Conclusions: Free solution capillary electrophoresis (CE) is a good candidate for routine analysis of carbohydrates, sugar alcohols and also ethanol in fermentation samples. The composition of the BGE can be adjusted to the complexity of the carbohydrate mixture to improve separation and/or throughput. Adjusting the composition of the BGE in CE is equivalent to using a different column in HPLC and this confers CE a high flexibility at a very affordable cost. Although K provided the best selectivity, the low viscosity of the BGE and the resulting size to charge ratio of the carbohydrates did not lead to the highest resolution of complex mixtures. 130 mm Na resulted in the best resolution amongst single-salt BGEs while a mixture of 65 mm Li and 65 mm Na increased the resolution but increased analysis time. Quantification of carbohydrates in a simple fermentation with CE shows values in close agreement with HPAEC and HPLC using a cation exchange column. Quantification of a more complex fermentation by CE in comparison to HPLC also shows values in close agreement. CE has the advantages of requiring no sample preparation (other than dilution) and set-up costs lower than that of HPLC, a significant advantage over HPLC and HPAEC. CE has the ability to monitor carbohydrates including arabitol and xylitol in a fermentation of plant fiber without the need for sample preparation other than dilution. In a subsequent injection of the same sample in the same capillary, ethanol can be determined by coupling the CE separation to pressure mobilization with indirect detection. The ability to monitor ethanol as well as carbohydrates on the same instrument and capillary to provide a complete picture of the fermentation sample is a major advantage over other methods currently used. Another advantage of free solution CE, especially given the recent developments in coupling CE systems to bioreactors (54), is that it can be used without filtration in most situations (35), including online fermentation monitoring. Sensitivity may be increased through the use of photo-initiators (26) if needed. 5 Acknowledgments The authors wish to acknowledge Dr Marion Gaborieau (UWS) for discussions, Dr Glenn Stone (UWS) for discussions regarding resolution, Prof. Peter Rogers (University of New South Wales) for providing the Zymomonas mobilis strain, Prof. Wieland Meyer (Westmead Clinical School, University of Sydney) for providing the Pichia stipitis strain, Dr Greg Dicinoski (UTas) and Dr Sara Sandron (UTas) for setting up the IC system with PAD. Support from the Australian Research Council is gratefully acknowledged: EFH is recipient of an ARC Future Fellowship (FT ). James Oliver CE for bioethanol research 179

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206 35. Taylor, D. L., Ferris, C. J., Maniego, A. R., Castignolles, P., in het Panhuis, M. and Gaborieau, M. (2012) Characterization of Gellan Gum by Capillary Electrophoresis. Aust. J. Chem., 65, Song, D. and Wang, J. (2003) Modified resolution factor for asymmetrical peaks in chromatographic separation. J. Pharm. Biomed. Anal., 32, Weinberger, R. (1993) Practical capillary electrophoresis. ed. Academic Press San Diego, CA. 38. Christophe, A. B. (1971) Valley to peak ratio as a measure for the separation of two chromatographic peaks. Chromatographia, 4, López-Grıó, S. J., Vivó-Truyols, G., Torres-Lapasió, J. R. and Garcıá-Alvarez-Coque, M. C. (2001) Resolution assessment and performance of several organic modifiers in hybrid micellar liquid chromatography. Anal. Chim. Acta, 433, Schwer, C. and Kenndler, E. (1991) Electrophoresis in fused-silica capillaries: the influence of organic solvents on the electroosmotic velocity and the.zeta. potential. Anal. Chem., 63, Sarazin, C., Delaunay, N., Costanza, C., Eudes, V., Gareil, P. and Vial, J. (2012) On the use of response surface strategy to elucidate the electrophoretic migration of carbohydrates and optimize their separation. J. Sep. Sci., 35, Leclercq, L. and Cottet, H. (2012) Fast characterization of polyelectrolyte complexes by inline coupling of capillary electrophoresis to Taylor dispersion analysis. Anal. Chem., 84, Grote, W. and Rogers, P. L. (1985) Ethanol production from sucrose-based raw materials using immobilized cells of Zymomonas mobilis. Biomass, 8, Alizadeh, H., Teymouri, F., Gilbert, T. I. and Dale, B. E. (2005) Pretreatment of switchgrass by ammonia fiber explosion (AFEX). Appl. Biochem. Biotechnol., 124, Lee, J. (1997) Biological conversion of lignocellulosic biomass to ethanol. J. Biotechnol., 56, Jeon, Y. J., Xun, Z. and Rogers, P. L. (2010) Comparative evaluations of cellulosic raw materials for second generation bioethanol production. Lett. Appl. Microbiol., 51, Ibrahim, A., Ohshima, H., Allison, S. A. and Cottet, H. (2012) Determination of effective charge of small ions, polyelectrolytes and nanoparticles by capillary electrophoresis. J. Chromatogr. A, 1247, Trachtenberg, S. and Mayer, A. M. (1981) Composition and properties of Opuntia ficus-indica mucilage. Phytochemistry, 20, Lide, D. R. (2004) CRC Handbook of Chemistry and Physics, 85th Edition. ed. Taylor & Francis. 50. Li, H., Chai, X.-S., Deng, Y., Zhan, H. and Fu, S. (2009) Rapid determination of ethanol in fermentation liquor by full evaporation headspace gas chromatography. J. Chromatogr. A, 1216, Jeon, Y. J., Shin, H. S. and Rogers, P. L. (2011) Xylitol production from a mutant strain of Candida tropicalis. Lett. Appl. Microbiol., 53, Chinnici, F., Spinabelli, U., Riponi, C. and Amati, A. (2005) Optimization of the determination of organic acids and sugars in fruit juices by ion-exclusion liquid chromatography. J Food Comp Anal, 18, Harvey, D. (2000) Modern Analytical Chemistry. ed. McGraw-Hill, Boston. 54. Turkia, H., Holmström, S., Paasikallio, T., Sirén, H., Penttilä, M. and Pitkänen, J.-P. (2013) Online Capillary Electrophoresis for Monitoring Carboxylic Acid Production by Yeast during Bioreactor Cultivations. Anal. Chem., 85, James Oliver CE for bioethanol research 182

207 5.3 Publication supporting information Supporting information for Simple and robust monitoring of ethanol fermentations by capillary electrophoresis James Oliver, 1,2 Adam T. Sutton, 1 Naama Karu, 3 Michael Phillips, 2 Julie Markham, 2 Paul Peiris, 2 Emily F. Hilder, 3 Patrice Castignolles 1 1 University of Western Sydney, Australian Centre for Research On Separation Sciences (ACROSS), School of Science and Health, Parramatta Campus, Locked Bag 1797, Penrith NSW 2751, Australia 2 University of Western Sydney, School of Science and Health, Hawkesbury Campus, Locked Bag 1797, Penrith NSW 2751, Australia 3 Australian Centre for Research on Separation Science (ACROSS), School of Chemistry, University of Tasmania, Hobart TAS 7001, Australia, emily.hilder@utas.edu.au This supporting information contains supplementary equations and electrophoretic mobilities values as well as electropherograms from the free solution Capillary Electrophoresis (CE) experiments. It also contains supplementary data on the quantification of sugars by CE as well as High Performance Anion Exchange Chromatography (HPAEC) and High Performance Liquid Chromatography (HPLC) on a cation exchange resin. Free solution capillary electrophoresis: Separation of carbohydrates Figure 5.3-1: Mechanism of separation by free solution capillary electrophoresis. James Oliver CE for bioethanol research 183

208 The electrophoretic velocity is weaker than the EOF and so the sugars migrate toward the cathode. The difference between the EOF and the apparent velocity of the sugars corresponds to the electrophoretic velocity. The electrophoretic velocity is directly proportional to the electric field strength, and the proportionality constant between these variables is the electrophoretic mobility (which is proportional to the charge-to-size ratio). Equation 6.3-1: relationship between apparent velocity (v app), electroosmotic velocity (v eof) and electrophoretic velocity (v ep) v app = v eof + v ep The electrophoretic mobility µ ep was determined the following equation (1): Equation 6.3-2: Formula used to calculate the experimental electrophoretic mobility values μμ ep = ll LL VV 1 tt m 1 tt eo Where l is the length to the detection window (effective length), L is the total length of the capillary, V is the applied voltage, t m is the migration time of the carbohydrate, t eo is the migration time of the electro-osmotic flow (EOF) marker (2). James Oliver CE for bioethanol research 184

209 Table 5.3-1: Comparison of various Background Electrolytes (BGE) and their effect on electrophoretic mobility and electro-osmotic flow (EOF). Electrophoretic mobility was calculated using Equation Background Electrolyte (BGE) Carbohydrate 130mM K 65 mm K 65 mm Na (M2) 52 mm K 52 mm Na 26 mm Li (M5) mm K mm Na mm Li (M4) 52 mm K 26 mm Na 52 mm Li (M6) 130 mm Na 26 mm K 52 mm Na 52 mm Li (M7) 65 mm K 65 mm Li (M3) 65 mm Li 65 mm Na (M1) 130 mm Li 130 mm Na 36 mm Na2HPO4 + (3) 98 mm Na 120 mm NaCl ++ (4) Electrophoretic mobility (-10 8 m 2 V -1 s 1 ) Arabitol Xylitol Lactose Galactose Glucose Rhamnose Mannose Arabinose Xylose EOF (min) James Oliver CE for bioethanol research 185

210 Table 5.3-2: Electrophoretic mobility of carbohydrates and related fermentation end products (0.5 g L -1 each) in Li with varying concentration. Conditions: Voltage 24 kv, temperature 15 C. Background Electrolyte (BGE) Carbohydrate 30 mm 60 mm 90 mm 130 mm 170 mm µ ep (-10 8 m 2 V -1 s 1 ) Xylitol Arabitol Glucose Rhamnose Mannose Arabinose Time of EOF marker (min) Viscosity (η/mpa s) of the BGE at C * Time of EOF marker/ Viscosity (mpa ) The electrophoretic mobility values and EOF are 9-16 % higher in Table than the values in Table The standard solution had 1 g L -1 of each analyte, as opposed to 0.5 g L -1 in Table 5.2-1, which would alter the EOF and mobility due to a change in sample viscosity. Injections were performed on a different instrument (HP-3D, also from Agilent Technologies, USA) with a different capillary of the same length with the signal was monitored with a diode array detector (DAD) at 270 nm. However the resolution values (Table 5.3-3) were very similar. The contour plot on Figure shows the relative position of rhamnose in-between glucose and mannose as well as the absolute difference in electrophoretic mobility between glucose and mannose. To achieve complete separation, one needs both a large difference in electrophoretic mobility between mannose and glucose (i.e. a larger window of separation), and rhamnose in the middle. The difference in electrophoretic mobility (selectivity; defined differently by other authors (7)) of glucose and mannose was calculated by 1 (mm MM mm GG ) were mm and mg are the electrophoretic mobility of mannose and glucose respectively. The relative position of rhamnose is expressed as (mm RR mm GG ) where a value of 1 corresponds to rhamnose at equal distance between glucose and (mm MM mm RR ) James Oliver CE for bioethanol research 186

211 mannose, a value above 1 corresponds to rhamnose closer to mannose than glucose and a value below 1 corresponds to rhamnose closer to glucose than mannose. Figure 5.3-2: Contour plot of the varying K and Li proportion in 130 mm total alkaline concentration (when relevant the third component is Na). Contour shows the distribution of inverse difference in electrophoretic mobility of glucose and mannose where the lowest value is shown by the darkest region. The labels (stars) display the relative position of rhamnose to glucose and mannose defined as (mm RR mm GG ) (mm MM mm RR ). In Li, rhamnose migrates at a similar velocity to glucose, while it migrates faster than glucose in both K and Na as it is detected closer to mannose. The lower ph of Li BGE than that of Na and K BGEs might cause a stronger decrease in charge for rhamnose than for glucose and mannose at these high phs. James Oliver CE for bioethanol research 187

212 Table 5.3-3: Resolution (expressed as R vp = 100 x V s/p) of a mixture of carbohydrates in varying concentrations of Li (the best values are given in bold). Separation conditions: 24 kv, 90 cm capillary (81.5 cm effective length). Mixture contains 0.5 g L -1 xylitol, arabitol, lactose, galactose, glucose, rhamnose, mannose, arabinose and xylose. BGE R vp Xylitol- Arabitol Glucose- Rhamnose Rhamnose- Mannose Mannose- Arabinose 30 mm Li mm Li mm Li Total V/P Ratio 130 mm Li mm Li James Oliver CE for bioethanol research 188