Challenges in Separation Technologies

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1 Challenges in Separation Technologies Erin Shammel Baker Xing Zhang, Yehia Ibrahim, Matthew Monroe, Dennis Mehinagic, Justin Teeguarden, Thomas Metz and Richard D. Smith Pacific Northwest National Laboratory

2 Main challenges with xeno-metabolite measurements 1. Xeno-metabolites occur from very low to high concentrations (pm-µm) so high sensitivity and dynamic range measurements are essential 2. Biological changes are best understood when xeno-metabolites and endogenous metabolites are measured simultaneously 3. Measurements covering thousands of small molecules are desired to understand how they change over time and within large cohorts 4. Many small molecules have the same masses but a different chemical makeup so differentiating them using MS-based approaches can be difficult

3 MS measurement complexity for small molecules Testosterone Exact mass = In the NIST database there are 18 different options with exact mass = Using a mass range from to different options

4 Why are we interested in using IMS-MS in small molecule studies? 1. High Throughput: IMS is a fast separation technique that is easily coupled with MS 2. The extra IMS dimension provides a way of shortening LC separations or potentially eliminating them 3. Coupling IMS drift time and MS features increases sensitivity and confidence in xeno-metabolite discovery DRIFT CELL Sugars Peptides DNA Electric Field Drift Time

5 Ion mobility concept E F friction Ion F el p (Drift Gas) Drift Cell velocity is constant v = K E K = ion mobility

6 Ion mobility concept E in out Drift Time Pulse of 2 ions with same m/z but different shape Drift Cell Different conformers separate in time with peak heights representing the amount of each velocity is constant v = K E K = ion mobility

7 Ion mobility concept LC (minutes) IMS (~60 ms) MS (~100 µs) IMS MS Elution Time Drift Time m/z 1100 m/z 1100 m/z 1100 m/z Drift Time (ms) Drift Time (ms) Drift Time (ms) Intensity Elution Time (minutes)

8 Isomer separations difficult with hydrophobic interaction liquid chromatography (HILIC) D-Ribulose 5-phosphate (Ru5P) α-d-ribose 5-phosphate (R5P) Ru5P R5P Ru5P R5P

9 Isomer separations difficult with hydrophobic interaction liquid chromatography (HILIC) H H D-Fructose-6-phosphate (f6p) D-Glucose-6-phosphate (G6P) α-d-glucose-1-phosphate (G1P) F6P G6P G1P F6P G6P G1P

10 Isomeric xeno-metabolite separations 2,3-Dihydroxynaphthalene 2,6-Dihydroxynaphthalene 1,5-Dihydroxynaphthalene

11 Isomeric xeno-metabolite separations 12-Hydroxybenzo(a)pyrene 7-Hydroxybenzo(a)pyrene

12 (Sugar+Na) + isomer separations with IMS

13 Creating an IMS-MS small molecule database to support high-throughput exposome analyses AMT Tag Database Known Standard IMS-MS Measurements Deisotope Feature Finding Add Masses & Drift Times that match standard to AMT tag DB Decon2Ls Feature Finder Repeat this process for each of the 800 standards Endogenous samples from Human Metabolome Project Xeno-metabolites from PNNL and OSU

14 Current metabolite database Analyzed ~400 metabolites (in both positive and negative mode) and see orthogonality with mass We have also analyzed an additional 500 lipids

15 Present limit of detection in water using IMS-MS Lowest detection at 10 pm for standards in water Linear concentration response

16 Present limit of detection in human plasma with IMS-MS Lowest detection at 10 nm in human plasma Lowest detection at 10 pm for standards in water Linear concentration response

17 FAIMS and IMS Differences Field Asymmetric Waveforms IMS Ion Mobility Spectrometry Scanning technique Attaches easily to instruments Operates at atmospheric pressure Alternating low/high electric field Ions partially orient by their dipole High-throughput technique Doesn t attach easily to instruments Operates at low pressure (~4 Torr) Low electric field Ions tumble through drift cell

18 FAIMS-IMS-MS in 5 seconds 1000 CF = 3.1 Td drift time (ms) IMS FAIMS CF = 3.9 Td m/z CF (Td) m/z drift time (ms) DF= 250 Td, 100% N drift time (ms)

19 Sensitivity losses No FAIMS FAIMS Adding FAIMS drops sensitivity by at least 2-fold, and MUCH more as resolution is increased

20 Reduced feature numbers in complex samples Positive ESI, 5 µl of pooled urine prepared 400 feature found with IMS-MS 250 features found with FAIMS-IMS-MS Positive ESI, 5 µl of pooled urine + 15 mm sugars (glucose, xylose, mannose and galactose) 350 features found with IMS-MS 210 features found with FAIMS-IMS-MS

21 Limit of detection in IMS-MS and FAIMS-IMS-MS Lowest detection at 100 nm for FAIMS-IMS-MS Lowest detection at 10 pm for standards in water with IMS-MS and 100 pm for FAIMS-IMS-MS However, both have linear concentration response

22 RapidFire 1. Inject Sample SPE Cartridge

23 RapidFire 1. Inject Sample 2. Wash Cartridge SPE Cartridge SPE Cartridge

24 RapidFire 1. Inject Sample 2. Wash Cartridge 3. Reverse Flow Send to MS 15 sec analyses MS SPE Cartridge SPE Cartridge SPE Cartridge

25 RapidFire-IMS-MS analyses of different biological sources Metabolites extracted from mice plasma Metabolites extracted from human urine Isomeric Separation: m/z= Same nominal mass: m/z= , Isomeric Separation: m/z=

26 RapidFire-IMS-MS xeno-metabolite limit of detection human plasma 6 Calibration Curves Imazaquin Hexaconazole Log (Intensity) Imazaquin Hexaconazole Thiabendazole Metribuzin Tiabendazole 3.5 Napropamide 3 Metribuzin Log (Concentration) in pm Lowest detection at 500 pm for RapidFire-IMS-MS Napropamide

27 RapidFire-IMS-MS analyses Xeno-metabolites at 1 nm in human plasma Imazaquin Tiabendazole

28 Conclusions IMS-MS can separate metabolite and xeno-metabolite isomers, and eliminates the need for LC, greatly speeding up measurements Sample fractionation prior to IMS-MS analyses can avoid ionization suppression and increase sensitivity Rapid offline fractionation provides the means for high throughput studies Presently 15-sec xeno-metabolomic measurements are possible (240 analyzes per hr), with limits of detection at ~500 pm in plasma Pending developments with higher resolution and sensitivity IMS approaches will greatly increase sensitivity and metabolome coverage

29 Opportunities The very high-throughput of the RapidFire-IMS-MS removes some key obstacles to assessing the exposome Enables rapid generation of libraries Enables higher confidence identification of xeno-metabolites Enables evaluation of large cohorts Compatibility with lipid and endogenous metabolite analyses may allow a single instrument for measurements of biological response and exposure

30 Acknowledgements National Institute of Environmental Health Sciences of the NIH (R01ES022190) NIH: General Medical Sciences Proteomics Center at PNNL (2 P41 GM ), and National Cancer Institute PNNL Laboratory Directed Research and Development Program Environmental Molecular Sciences Laboratory Biological Separations & Mass Spectrometry Group