Comprehensive two-dimensional gas chromatography for the separation of fatty acids in milk

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1 Eur. J. Lipid Sci. Technol. 109 (2007) DOI /ejlt Bruno Vlaeminck a James Harynuk b, c Veerle Fievez a Philip Marriott b, c a Laboratory for Animal Nutrition and Animal Product Quality, Ghent University, Melle, Belgium b Australian Centre for Research on Separation Science, RMIT University, Melbourne, Australia c Victorian Institute for Chemical Sciences, RMIT University, Melbourne, Australia Comprehensive two-dimensional gas chromatography for the separation of fatty acids in milk Comprehensive two-dimensional gas chromatography (GC6GC) is a recent technique, rapidly gaining importance for the analysis of complex samples. Here, we evaluate the potential of GC6GC for the analysis of the fatty acid profile of milk from dairy cows fed either a control diet or the control diet supplemented with marine algae. Fatty acids were separated using two column combinations, a nonpolar/polar arrangement and a polar/nonpolar arrangement. Due to the difference in separation mechanism of the two columns, GC6GC resulted in an improved separation compared with analysis on the same column set without the use of the modulator. Displaying the peaks in a 2-D contour plot showed a well-ordered structure of fatty acids according to their number of carbon atoms and degree of unsaturation, facilitating identification of known and unknown compounds. Based on these relations, identification of carbon number and degree of unsaturation of several 22-fatty acids was possible. The large difference between the 22-fatty acids from milk fat of cows fed the control and the marine algaecontaining diet suggest that rumen hydrogenation of 22:6 n-3 results in a similar complex profile of hydrogenation intermediates as observed for 18:2 n-6 and 18:3 n-3. In conclusion, this experiment suggests GC6GC to be a powerful technique for the analysis of fatty acids. Nevertheless, further research on the optimization of GC6GC is needed to increase separation of trans- and cis-18:1 isomers, which may require a longer and/or more selective 1D column. Keywords: Comprehensive two-dimensional gas chromatography, fatty acids, milk. 1 Introduction Milk fats reportedly comprise up to 400 different fatty acids [1]. These include fatty acids differing in chain length, chain branching, unsaturation, geometric and positional configuration, and functional groups [1]. The complexity of these fatty acid profiles means that highly efficient separation methods are required for their analysis. Gas chromatography is by far the most widely used method for analysis of fatty acids, and the fatty acids are generally analyzed as their fatty acid methyl esters (FAME) (see e.g. [2, 3]). However, there seems no single chromatographic method available that can resolve all milk fatty acids [4, 5]. Indeed, many overlapping trans- 18:1, cis-18:1 and cis/trans-18:2 isomers are only partially resolved at best, whereas overlap of trans-16:1 with branched-chain 17-fatty acids and 18-fatty acids with 19-, 20- and 21-fatty acids has also been reported with the highly polar cyanoalkyl polysiloxane stationary phases Correspondence: Bruno Vlaeminck, Laboratory for Animal Nutrition and Animal Product Quality, Ghent University, Proefhoevestraat 10, 9090 Melle, Belgium. Phone: , Fax: , bruno.vlaeminck@ugent.be that have become popular for FAME analysis [4 9]. In addition, identification of the fatty acids is also challenging and usually is done solely by comparison of retention times with those of standards. Owing to the limited availability of standards and the occurrence of overlapping peaks, identification tends to be tentative at best [4]. The complexity of these fatty acid profiles led Kramer et al. [4] to state that what appears to be simple analysis, has proven to be most challenging, and far beyond the capability of a single GC analysis. In recent years, comprehensive two-dimensional gas chromatography (GC6GC) has proven to be a powerful separation method for many types of complex samples (see e.g. [10 12]). Comprehensive two-dimensional gas chromatography is a multidimensional separation technique where the initial sample is separated on two GC columns with different separation mechanisms connected in series and with a modulator located between them [12]. The modulator acts as both a collection zone and fast re-injection device, resulting in a series of sharp pulses eluting from the 2D column for each peak entering the cryomodulator from the 1D column [11, 12]. Lower minimum detectable concentration and greater resolution Research Paper

2 758 B. Vlaeminck et al. Eur. J. Lipid Sci. Technol. 109 (2007) as well as the presence of chemically ordered structures in the chromatograms are often stated properties of the GC6GC method (see e.g. [11 13]). The limited number of experiments describing the application of GC6GC for the analysis of methylated fatty acids [13 18] was based on the relatively simple fatty acid profile of various biological oils. Compared with these samples, milk fat has a more complex fatty acid composition. Thus far, there is only one study reporting the use of GC6GC for the analysis of fatty acids in ruminant milk [19]. The present study extends the work on the potential of the GC6GC technique to analyze fatty acids from ruminant milk fat using new combinations of columns. 2 Material and methods 2.1 Fat samples and preparation of FAME Milk fat was extracted according to Vlaeminck et al. [20] from milk samples of cows receiving a control diet or the control diet supplemented with marine algae. For a detailed description of the experimental set-up and dietary treatments, we refer to Boeckaert et al. [21]. In the current experiment, a total of eight milk samples were used, four from each dietary treatment. Fatty acids in the extracted lipids were methylated with NaOH in methanol (0.5 mol/l) (30 min, 50 7C) followed by HCl in methanol (1 : 1, vol/vol) (10 min, 50 7C) [20]. The FAME were extracted twice with 2 ml hexane, and pooled extracts were evaporated to dryness under N 2. The residue was dissolved in 1 ml hexane. Acid methylation is known to result in isomerization of conjugated fatty acids [22, 23]. Although the degree of isomerization of conjugated fatty acids was not tested in the current experiment, isomerization was reported to be limited under the conditions used in the current experiment [22, 24]. Further, isomerization of conjugated fatty acids, if it occurs, has no impact on the main conclusions of the current experiment. 2.2 Gas chromatographic analysis of FAME FAME (1 ml methyl esters in hexane injected at a 50 : 1 ratio) were analyzed on an Agilent 6890 gas chromatograph (Agilent Technologies, Little Falls, DE, USA) with split injector and flame ionization detector (FID). An Everest Model Longitudinally Modulated Cryogenic System (LMCS II; Chromatography Concepts, Victoria, Australia; [15, 25]) was retrofitted to the gas chromatograph. The cryogenic trap was maintained at ca. 0 7C for the duration of each analysis. For the nonpolar/polar column set, the modulation period was set to 3.0 s and for the polar/ nonpolar column set to 6.0 s. Two different column sets were used in the present study: (i) BPX5 column (30 m mm60.25 mm; 5% phenyl polysilphenylene-siloxane phase) connected to a BP20 column (0.85 m mm60.20 mm; polyethylene glycol phase) and (ii) a BPX80 column (30 m60.25 mm60.25 mm; 80% cyanopropyl-substituted polysilphenylene-siloxane phase) coupled to a BPX35 column (0.25 m60.10 mm mm; 35% phenyl polysilphenylene-siloxane phase). Columns were obtained from SGE International (Ringwood, Victoria, Australia). The temperature program on both column sets was 90 to 250 7C at27c/min. The carrier gas, H 2 and He for column set 1 and 2, respectively, was used at a constant flow of 1.0 ml/min. Injector and detector temperatures were set at 250 and 260 7C, respectively. 2.3 Data processing and calculations Data processing Chromatographic data were collected from the output of the FID at a rate of 100 Hz using Agilent Chemstation software. The raw GC6GC data were exported in ASCII file format (*.csv files) and then converted to matrix format as a function of the modulation period, start time and data acquisition rate using 2D GC Converter software (Chromatography Concepts, Victoria, Australia). Two-dimensional contour plots were generated by using Transform software (Fortner Software, VA, USA). FAME were identified from external standards (S37, Supelco, Poole, Dorset, UK; branched-chain fatty acids, Larodan Fine Chemicals AB, Malmö, Sweden). For quantification, peak area and retention time information obtained with the Chemstation software were exported to Microsoft Excel to collate and sum areas of GC6GC peaks according to their 2 t R, and modulation period difference. Differences between the two column sets were evaluated using a paired t-test Regression analyses Relations between number of carbon atoms and double bonds with retention time on the first and second column were estimated according to: Y =a1 b6 1 t R 1 c6 1 t R 2 1 d6 2 t R 1 e6 2 t R 2 with Y being the number of carbon atoms or double bonds, 1 t R the retention time on the 1D column and 2 t R the absolute retention time on the 2D column. Non-significant variables (p.0.05) were removed from the equation using the backward procedure. Absolute retention times were used to account for wrap-around (if a compound has wrapped around once, then one modulation period is

3 Eur. J. Lipid Sci. Technol. 109 (2007) GC6GC analysis of milk fatty acids 759 added to the apparent 2 t R ) and for the modulator start time [13]. Absolute retention times were determined according to the method described by Micyus et al. [26] Fractional chain length Equivalent chain length (ECL) values were calculated from the retention times of the unbranched saturated fatty acids using polynomial regressions [27]. The fractional chain length (FCL) is defined as the difference between the ECL value of the actual FAME molecule and the ECL value of the unbranched saturated molecule with the same number of carbons. 3 Results and discussion The GC6GC process involves modulation of GC peaks eluting from the 1D column through trapping, focusing and effectively slicing them into a number of peak pulses for subsequent rapid analysis on the 2D column. Each analyte will be presented in the GC6GC chromatogram as a series of peak pulses, with the envelope of the pulses forming the shape of the 1D GC peak. In Fig. 1, the 18- region obtained with the nonpolar/polar column set is depicted as an example. Fig. 1A is a traditional 1D GC analysis on the two-column set without using the modulator. Peak basewidths of about 5 s and a maximal peak Fig. 1. Comparative chromatograms of the 18-region on the nonpolar/polar column set (BPX56BP20). (A) Normal 1D GC chromatogram, (B) modulated GC6GC chromatogram, and (C) GC6GC chromatogram.

4 760 B. Vlaeminck et al. Eur. J. Lipid Sci. Technol. 109 (2007) response of about 30 pa were observed. Fig. 1B shows the same sample but now with modulation. Peak basewidths of individual pulses generated on the second dimension are now about 0.2 s and the maximal peak response is 500 pa. Comparison of the two figures shows a similar overall peak profile. However, each compound in the modulated chromatogram is now a sequence of pulses. Fig. 1C shows the contour plot of the 18-region. Due to the different separation mechanisms of the two columns, fatty acids co-eluting in the first dimension are now separated (Fig. 1C). The results obtained with GC6GC are discussed in detail further in the text (3.1.). In this study, two different column combinations were tested. The first column set was a nonpolar/polar arrangement. In the experiments described by Harynuk et al. [13] and Western et al. [15], a BPX5 column connected to a BP20 column was used for the separation of fatty acids. In both experiments, the film thickness of the second column was 0.10 mm. In the current experiment, we used an identical column set, but the second-dimension column had a film thickness of 0.20 mm, which was expected to increase retention and the separation on the second-dimension column. The second column set was a polar/nonpolar arrangement. Generally, highly polar cyanoalkyl polysiloxane stationary phases are used for the separation of milk fatty acids and hence, as a comparative system, the BPX80 column was used as the 1D column [28]. The short BPX35 secondary column was chosen based on acceptable retention characteristics for the second dimension. Harynuk et al. [13] and Hyotylainen et al. [19] used similar highly polar cyanoalkyl polysiloxane stationary phases as the 1D column, with the nonpolar BP1 [13] and HP-1 and HP-5 [19] phases as the 2D column. 3.1 Nonpolar/polar column set Fig. 2A shows the contour plot of the whole milk sample with the nonpolar/polar column set and a close-up of the region and region is presented in Fig. 2B and C, respectively. This column set represented the typical combination used in GC6GC analyses (nonpolar/ Fig. 2. GC6GC chromatogram of the FAME from milk fat (A) and close-up of the region (B) and region (C) separated on a nonpolar/polar column set (BPX56BP20). (D) is identical to (C) but presented at a less sensitive response scale, to highlight major components. The GC6GC chromatogram was shifted with 2.5 s to aid in visualization of the data.

5 Eur. J. Lipid Sci. Technol. 109 (2007) GC6GC analysis of milk fatty acids 761 polar arrangement) and similar column sets have been used before for fatty acid analysis. This column set-up approximates an orthogonal separation, where the separation on the 1D column is based approximately on boiling point and that in the 2D column is according to the polarity of the analytes. As expected, retention time on the 1D column increased with increasing carbon number and decreased with the number of double bonds, and the monounsaturated fatty acids with cis configuration elute before fatty acids with trans configuration. Due to the more polar characteristics of the 2D column, retention time on the 2D column increased with increasing number of double bonds, resulting in an improved separation (Fig. 2C). Indeed, 18:3 n-3 was clearly separated from cis-9 18:1 (Fig. 2C, D), whereas these fatty acids co-elute in 1D GC with such nonpolar columns. The higher film thickness of the 2D column in the current study compared with earlier reports (0.20 mm vs mm in [15, 18]) increased separation in the second dimension, as illustrated by the increased chromatographic resolution (R s = Dt R /o b ) in the second dimension, with Dt R being the retention time difference between the two peak maxima and o b the peak width at the baseline. Resolution of 18:3 n-3/cis-9 18:1 increased from 2.4 [15] to 2.9 whereas resolution of 18:0/cis-9 18:1 and cis-9 18:1/18:2 n-6 increased from 0.6 and 1.1 [18] to 1.2 and 2.6, respectively. Although overall separation increased using a 2D column, separation within a group of fatty acids (e.g. monounsaturated 18-fatty acids) was not substantial (Fig. 2C, D), since these groups of related FAME do not benefit from the 2D column and their resolution must rely upon the 1D column separation. 3.2 Polar/nonpolar column set The second column set was a polar/nonpolar arrangement (Fig. 3). Separation on the 1D column will depend on both boiling point and polarity of the fatty acids. Retention time on the 1D column increased with increasing carbon number and with the number of double bonds, and monounsaturated fatty acids with trans configuration elute before fatty acids with cis configuration. The elution pattern on polar columns is well described for fatty acids of ruminant products (see e.g. [3, 6]), as well as the main limitations of the highly polar columns, such as overlapping components of different chain lengths (see e.g. [2, 6 8]). Using GC6GC partially resolved these problems. Indeed, whereas analysis of branched-chain 17-fatty acids is generally complicated by the co-elution with monounsaturated 16-fatty acids using 1D GC [7, 8], using GC6GC resulted in separation of these fatty acids from each other (Fig. 3C). Similarly, GC6GC analyses resulted in class separation of 18-, 19-, 20- and 21-fatty acid isomers (Fig. 3D E), which is difficult in 1D GC (see e.g. [4, 6, 9]). GC6GC analyses further showed the presence of several minor fatty acids occurring in the monounsaturated 14- (Fig. 3B), 15- (Fig. 3B), 16- (Fig. 3C) and 17-region (Fig. 3C). In spite of this general improved separation of fatty acids compared with 1D GC methods, separation of some 18-fatty acids was not improved to a great extent compared with available 1D GC methods, with overlapping trans- and cis-18:1 [4 6]. Indeed, although the 2D column resulted in some separation of the cis isomers from trans isomers, the major improvement was the separation of 18-fatty acids from 19-, 20- and 21- fatty acids, resulting in, e.g., baseline separation of the branched-chain 19-fatty acids (Fig. 3D, E). The lack of major improvement in separation of 18:1 fatty acids was not unexpected as a relatively short 1D column was used with a simple temperature program. Hyotylainen et al. [19] reported separation of cis-18:1 from trans-18:1 isomers using a polar/nonpolar arrangement and isothermal conditions. Since isothermal conditions normally result in severe wrap-around of the analytes, accompanied with a decreased resolution, this might have created co-elution problems for the other fatty acids. Unfortunately, no information of the separation of other fatty acids was provided under these conditions [19]. Wrap-around was observed for fatty acids eluting at higher temperatures (Fig. 3). This phenomenon occurs for compounds with secondary retention times longer than the modulation period (i.e. 6 s). Relatively nonpolar compounds such as FAME will elute at substantially lower temperatures from highly polar columns (i.e. BPX80) than they would from a nonpolar column (i.e. BPX5) under identical conditions. For FAME, the decrease in elution temperature has been shown to be in excess of 45 7C when moving from a BPX5 to a BPX80 column [28]. This decrease in 1D elution temperature is accompanied by a corresponding increase in second-dimension retention factor. Consequently, when the compounds are introduced to the lower-polarity BPX35 second-dimension column, these will exhibit high retention times; so they require a very short column in this dimension. It was not possible to shorten the second dimension further because of instrumental constraints. Although wrap-around peaks break the structure of the chromatogram and can potentially create co-elution and identification problems, it is important to note that co-elution between analytes from different modulation periods was not observed and the separation obtained in the first dimension was preserved. 3.3 Ordered structures As has repeatedly been demonstrated [11 16], ordered structures are displayed in the GC6GC contour plot according to the chemical properties of the compounds.

6 762 B. Vlaeminck et al. Eur. J. Lipid Sci. Technol. 109 (2007) Fig. 3. GC6GC chromatogram of the FAME from milk fat (A) and close-up of the region (B), region (C) and region (D) on a polar/nonpolar column set (BPX806BPX35). (E) is identical to (D) but presented at a less sensitive response scale, to highlight major components. The GC6GC chromatogram was shifted with 3 s to aid in visualization of the data. Indeed, elution positions in the 2-D space were clearly related to the number of carbon atoms and degree of unsaturation of the compounds (Fig. 4A, B). As shown before for nonpolar/polar column sets [13 16], fatty acids with the same number of carbon atoms elute as clusters whereas second-dimension retention times increase with increasing number of double bonds, with the homologous series showing up as approximately parallel lines in the GC6GC chromatogram (Fig. 4A). With this column set, prediction of the number of carbon atoms and double bonds is mainly based on retention in the 1D and 2D column, respectively (Fig. 4A). In the inverse phase arrangement (polar/nonpolar column set), prediction of the number of carbon atoms and double bonds is related to retention in both the 1D and 2D columns (Fig. 4B). In addition, 1D retention, based on the fractional chain length, provided some information on the position of the double bond (Fig. 4C, D). It is clear that, due to this ordered structure, identification and classification of known and unknown compounds is greatly facilitated compared with 1D GC. In Tab. 1, regression equations for the prediction of the number of carbon atoms and

7 Eur. J. Lipid Sci. Technol. 109 (2007) GC6GC analysis of milk fatty acids 763 Fig. 4. Dependence of number of carbon atoms and double bonds on the first- and absolute second-dimension retention time of FAME in milk on a nonpolar/polar column set (BPX56BP20) (A) and on a polar/nonpolar column set (BPX806BPX35) (B). Dependence of fractional chain length of different positional isomers as a function of their number of double bonds on a nonpolar/polar column set (BPX56BP20) (C) and on a polar/nonpolar column set (BPX806BPX35) (D). For n-6, the mean of 18:2, 20:2 and 22:2 was used to represent compounds with two double bonds, the mean of 18:3 and 20:3 to represent compounds with three double bonds, and 20:4 as a compound with four double bonds. For n-3, the mean of 12:1 and 18:1 was used to represent compounds with one double bond, the mean of 18:3 and 20:3 to represent compounds with three double bonds, and 20:5 and 22:6 as compounds with five and six double bonds, respectively. Tab. 1. Equations for the prediction of the number of carbon atoms and double bonds based on the retention time on the first ( 1 t R ) and second ( 2 t R ) column using the polar/nonpolar column set. Intercept Independent variable Estimate SE p Variable Estimate SE p Eq. (1) to predict number of carbon atoms , t R t R 6 1 t R , t R , t R 6 2 t R ,0.001 Eq. (2) to predict number of double bonds , t R , t R , t R 6 2 t R ,0.001 double bonds are presented for the polar/nonpolar column set. These equations can be used to confirm or predict the structure of fatty acids. It should be noted that the dataset used to construct the predictive equations was based on retention times of fatty acids with both differences in chain length, degree of unsaturation and position

8 764 B. Vlaeminck et al. Eur. J. Lipid Sci. Technol. 109 (2007) and configuration of the double bond. Due to the limited number of standards available, no equations could be unequivocally constructed to predict the con figuration of the double bonds. Nevertheless, it is expected that similar relations can be drawn for the prediction of position and configuration of the double bonds as suggested by Harynuk et al. [13]. For this, exact knowledge of the position and configuration of the double bonds is required either by comparison with standards or analysis by GC6GC-MS, which is currently in progress at our laboratory. Fig. 5A, B shows an expansion of the area between 16:0 and 18:0 of a milk sample from a control cow and a cow receiving algae. Although only one sample for the control and algae diet is presented, similar conclusions could be drawn for all the samples analyzed as those obtained with the results presented in Fig. 5. Based on its 1 t R (38.3 min) and absolute 2 t R (6.431 s), the compound indicated by an arrow in Fig. 5A, B was predicted to be a fatty acid with 17 carbon atoms (predicted number of carbon atoms = 17.03) and one double bond (predicted number of double bonds = 1.00), and was tentatively identified as anteiso 17:1. Hay and Morrison [29] showed iso and anteiso 17:1 to be minor components in milk fat. Similarly, based on the prediction equations presented in Tab. 1, identification of carbon number and degree of unsaturation of several 20- and 22-fatty acids was possible, which would be very difficult with 1D GC as several of these fatty acids co-elute. The large difference between the 22-fatty acids from milk fat of cows fed the control (Fig. 5C) and the marine algae-containing diet (Fig. 5D) suggests that rumen biohydrogenation of 22:6 n-3 results in a similar complex profile of hydrogenation intermediates as observed for 18:2 n-6 and 18:3 n-3. As 20:5 n-3 was absent in the diet, the huge diversity of 20-fatty acids (Fig. 5D) was probably due to the metabolism of absorbed 22-fatty acids. 3.4 Quantitation of the fatty acids Tab. 2 shows quantitative data obtained for the GC6GC determination of some milk fatty acids on both column sets. The relative amounts of each fatty acid were not Fig. 5. GC6GC chromatograms of the FAME from milk fat of cows fed a control (A, C) or a marine algae-containing diet (B, D) on a polar/nonpolar column set (BPX806BPX35) of the region (A, B) and region (C, D). The compound indicated by the arrow (A, B) was tentatively identified as anteiso 17:1.

9 Eur. J. Lipid Sci. Technol. 109 (2007) GC6GC analysis of milk fatty acids 765 Tab. 2. Retention times and relative peak areas of selected fatty acids on a nonpolar/polar column set and on a polar/ nonpolar column set. Column set BPX80 BPX35 Column set BPX5 BP20 SEM { Area { 1 st dimension 2 nd dimension Area { 1 st dimension 2 nd dimension t R [min] VC [%] t R [s] VC [%] t R [min] VC [%] t R [s] VC [%] 10: : : : iso 13: : iso 14: : cis-9 14: iso 15: anteiso 15: : iso 16: : cis-9 16: iso 17: anteiso 17: : cis-9 17: : cis-9 18: trans : :2 n :3 n cis-9, trans-11 18: :6 n { Relative peak areas. { Standard error of the mean differences between the two column sets. A paired t-test revealed no differences between the two column sets (p.0.1). significantly different with the two column sets used (Tab. 2) and results were consistent with literature data [1]. The repeatability of retention times on the 1D and 2D columns is also presented in Tab. 2. The coefficient of variation for the 1D and 2D retention times was below 1 and 5% for both column sets, respectively. Logically, precision and accuracy of 1D and 2D retention times, as suggested by the low coefficient of variation, is a prerequisite for reliable identification and the future use of prediction equations as established in the current study. 4 Conclusions In conclusion, using the GC6GC technique resulted in an improved overall separation of FAME compared with 1D GC, and the well ordered structure of the compounds in a GC6GC contour plot facilitated identification and classification of known and unknown compounds. This suggests GC6GC to be a powerful technique for the analysis of fatty acids. Nevertheless, further research is needed to achieve increased separation of a number of specific peak pairs such as trans- and cis-18:1 isomers, which may require a longer and/or more selective 1D column. Acknowledgments B.V. is a Postdoctoral Fellow of the Fund for Scientific Research-Flanders (Belgium). The authors wish to acknowledge the technical support from Mr. Paul Morrison and SGE International for providing some of the columns used in this study. The stay of B.V. at the Australian Centre for Research on Separation Science (RMIT University, Australia) was supported by the Fund for Scientific Research Flanders (Belgium).

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