Metabolomics Strategies

Transcription

1 Metabolomics Strategies using GC-MS/MS-Technology Hans-Joachim Hübschmann GC/MS Technology Manager, Austin/Singapore Proteomics/Metabolomics Seminars March 2012

2 Thermo Scientific GC and GC-MS Product Line Matrix Selectivityit DFS TSQ Quantum XLS ITQ Magnetic Sector MS Trace GC 1300 ISQ Ti Triple Quadruple MS Ion Trap MS Single Quadruple MS FID, ECD, NPD, FPD, PID, PDD, FID and TCD Capability from Screening to Confirmation 2

3 What is Metabolomics? The Metabolome can be defined as: a snapshot of the quantitative complement of all the low molecular l weight molecules present in a cell analyzed at a particular physiological or developmental stage The concept of Metabolomics is the global analysis of all metabolites in a sample (Oliver Fiehn, 1998). The Roche Biochemical Pathway Wallchart 3

4 What are Metabolites? Metabolites represent all native small molecules (non polymeric compounds) are participants in general metabolic reactions (Goodacre et al., 2004) are substrates, intermediates or products of biochemical i pathways are involved in plant development, growth, reproduction as well as stress response mechanisms. The Levels of Metabolites can be considered as the response of biological systems to genetic or environmental changes (Weckwerth, 2003). Needs analytical methods 1. to identify the compounds 2. to quantify the compounds 4

5 Central Analytical Strategy in Metabolomics Phase I: Identification Phase II: Quantitation 5

6 Phase I: Identification Semi-quantitative discovery phase Identify as many metabolites as possible by GCMS Full Scan analysis, small molecules after derivatization (silylation) Developed reference libraries existing reference libraries are continuously updated with novel compounds or chemical synthesis O 74 HO O Si O O Si O HO O (mainlib) Butanedioic acid Succinic Acid (NIST) (mainlib) Butanedioic acid, bis(trimethylsilyl) ester Succinic Acid TMS (NIST, Reference Lib) 247 6

7 Chromatogram Deconvolution MS Libraries for Deconvolution and Identification Reference library - project specific, known targets Spectrum Name, CAS# Retention time information NIST, Wiley etc - general commercial libraries for unknown spectrum search - ca mass spectra for identification Fiehn Library - ca metabolite compounds (NIST imported) 7

8 Xcalibur Deconvolution - How AMDIS Works Found Compounds 14 Targets From Reference 196 Unknowns From NIST Target Compound Fragment profiles Spectrum Check Extracted ag. Raw spectrum Library spectrum Target example caffeine, m/z 194 8

9 AMDIS Deconvolution for Unknowns in a Sample Calculates the compound mass spectrum from overlapping peaks: Automatically in the complete chromatogram Chromatogram Single masses Proportion calculation for each mass Clean Spectrum Compare to raw Then: Do Library search 9

10 TSQ Quantum XLS for Discovery and Quantitation Untargeted Analysis Discovery, Deconvolution and Identification Fast, high sensitive full scan GC-MS analysis Reference library - project specific, known targets NIST, Wiley etc - general library, spectrum search Targeted Analysis - Quantification of Single Compounds Ideally performed with GC-MS/MS-technology using multiple reaction monitoring (MRM profiling) Both the Discovery and the Targeted Phase with one instrument TSQ Quantum XLS guaranteeing reproducibility in fragmentation, peak intensities, mass accuracies References: 10 Glinski and Weckwerth, 2005; Wienkoop and Weckwerth, 2006; Lehmann et al., 2008; Picotti et al., 2008; Weckwerth, 2008; Wienkoop et al., 2008a; Wienkoop et al., 2010

11 Sample Preparation Leaf material of Arabidopsis thaliana Homogenized under liquid nitrogen about 50mg applied to extraction Water/chloroform/methanol mixture to extract water soluble metabolites (Weckwerth et al., 2004) Polar phase dried in a vacuum centrifuge 2-Step derivatization: Methoxyamination (methoxyamin hydrochlorid in pyridine) to suppress keto-enol tautomerism, followed by Silylation using MSTFA to derivatize polar functional groups. Total derivatization volume 100µl. Standards dissolved in methanol or water, diluted into various concentrations, dried and derivatized according to plant material. 11

12 GC-MS/MS Conditions GC: Trace GC Ultra and Triplus Autosampler Column: 5% Phenyl, TR 5ms SQC 15m x 0.25mm ID x 0.25um He, constant flow at 1ml/min Injection: 1µl at 230 C splitless 2min splitflow 10ml/min Oven: 70 C hold 1min 1 C/min to 76 C 6 C/min to 330 C Transferline: 340 C hold for 5 min Postrun 10 min at 325 C 12

13 GC-MS/MS Conditions Mass Spectrometer: TSQ Quantum GC Ionization mode: EI, emission current: 100µA Ion source temp.: 250 C Phase I: Identification Scan mode 1: Full Scan, m/z , fast scan time 250 ms Phase II: Quantitation Scan mode 2: SRM (Selected Reaction Monitoring) Indole-3-acetic acid: m/z > , 24 CE 20 V Glucose: m/z > , CE 20 V Salicylic acid: m/z > ; 73.08, CE 15 V Scan time: 10 ms Peak width Q1 0.7 Da (FWHM) Collision Gas: Argon, 1 mtorr 13

14 Arabidopsis Thaliana Metabolite Profile A complex metabolite profile measured in the full scan mode of the TSQ Quantum instrument. Chemical classes are assigned to the corresponding chromatographic regions. 14

15 Classification by PCA of Different Biological Samples To classify the samples quantitative full scan metabolite profiles were measured with the GC-MS/MS. Biological replicates are shown in the same colour. Each biological sample can unambiguously distinguished from the others. Individual metabolites are identified by this multivariate analysis which discriminate the biological samples (for detailed information see Weckwerth and Morgenthal, 2005). 15

16 Analytical Challenges in Metabolomics Greatest challenge: Requires high dynamic range from very low abundance metabolites like phytohormones to highly concentrated compounds, like energy-related carbohydrates. Low concentrated metabolites especially the analysis of chromatographic regions with ultracomplex coelution of different compounds, MRM-strategies are developed. Very low detection limits and a dynamic range of 4 orders of magnitude can be presented for phytohormones. High sensitivitys The TSQ triple quad shows up to 10 folds more sensitivity than single quadrupole and ion trap MS instruments for indole-3-acetic acid (IAA), and up to 20 times for salicylic acid (SA) (Mueller et al., 2002; Birkemeyer et al., 2003). Selectivity (as presented in next slide) The TSQ triple quad separates coeluting analytes, using different SRM transitions. Indole-3-acetic acid and glucose have similar retention times and the same parent ion, however, they are well separated by the GC-MS/MS-MRM analysis. 16

17 Selectivity IAA/Glucose Separation Glucose: m/z > Indole-3-acetic acid: m/z > SRM chromatogram of IAA and glucose reference compounds at the level of 50 pmol injected amount 17

18 Calibration curves using GC-MS/MS-MRM analysis Glucose from 1 fmol to 1 nmol on column, 18 levels 6 orders of magnitude! R 2 = Indole-3-acetic acid from 10 fmol to 1 nmol on column. Salicylic acid from 7.5 fmol - 1nmol on column 18

19 Food Safety Application of GC-MSMS Metabolomics Scores plot (A) and loadings plot (B) of the principal components analysis of headspace-spme samples.: TSB (C), E. coli O157:H7 (O), Salmonella, Hartford (H), Salmonella Typhimurium (T), Salmonella Muenchen (M), nonpathogenic Salmonella (NP), E. coli K12 (K), S. aureus (ST), S. cerevisiae (SC), and A. oryzae (AO) Rapid Detection of Escherichia coli and Salmonella Bacteria GC-MS Based Metabolomics for Rapid Simultaneous Detection of Escherichia coli O157:H7, Salmonella Typhimurium, Salmonella Muenchen, and Salmonella Hartford in Ground Beef and Chicken (Cevallos-Cevallos 2011) 19

20 Conclusions GC-MS/MS with the TSQ Quantum provides both Phase I: Discovery phase analysis Selective identification Fast full scan analysis with deconvolution Reference library building Phase II: Quantitation Very accurate quantification high dynamic range for interesting metabolite markers complex mixtures analysis using the MRM mode Compounds not be separated by GC, get separated by compound-specific MRM The TSQ Quantum XLS is the optimal instrument For use in metabolomics to perform the metabolite screening For targeted metabolite quantitation in complex samples For the analysis of hundreds of target metabolites in one GC-MS/MS-MRM run For high sample throughput work 20

21 Acknowledgements Lena Fragner Prof. Wolfram Weckwerth Department of Molecular Systems Biology University of Vienna Austria 21