1 Seminario di Spettrometria di Massa. Università degli studi di Milano 23/06/2017 The world leader in serving science

Transcription

1 Innovazioni tecnologiche per l analisi GC-MS in bassa ed alta risoluzione con il nuovo GC-Orbitrap Dott.ssa Cristina Neri, Ph.D Sales Specialist GC-GC&MS 1 Seminario di Spettrometria di Massa. Università degli studi di Milano 23/06/2017 The world leader in serving science

2 Agenda Bassa Risoluzione vs Alta Risoluzione Il GC-Orbitrap Untargeted Metabolomics using Orbitrap GC-MS Conclusioni Q&A 2

3 Bassa Risoluzione vs Alta Risoluzione 3 The world leader in serving science

4 Resolution- what is it? Ability of a mass spectrometer to distinguish between ions of nearly equal m/z ratios (isobars). m - measured mass Δm - peak width measured at 50% peak intensity (Full Width Half Maximum) - or the mass difference between two adjacent peaks of equal intensity, in this case 10% valley definition is used. 4

5 Resolution- what is it? Ability of a mass spectrometer to distinguish between ions of nearly equal m/z ratios (isobars). 5

6 Resolution- what is it? At minimum the resolution of the mass analyzer should be sufficient to separate two ions differing by one mass unit anywhere in the mass range scanned (unit mass resolution). typical values of resolution for low resolution mass analyzers (e.g. quadrupoles and ion traps) are below High resolution instruments have a resolution exceeding

7 Why resolution is important? Selectivity: High mass resolution can greatly reduce matrix interference. It can also reduce interference between ions of the same compound (e.g. fine isotopic structure). ±0.5 amu ± amu 7

8 Resolving Power: Selectivity Pyrimethanil in leek at 10 μg/kg < 5 ppm ID criteria Relative Abundance False negative Relative Abundance False negative Relative Abundance Positive Detection High Selectivity high sensitivity and confidence in identification 8

9 Mass Accuracy: what is it? Mass accuracy is the accuracy of which the mass is measured by the mass spectrometer. Typical way of reporting mass error in ppm (relative mass error): Absolute mass error can be used (mda). Main advantage: the possibility to determine the elemental composition of individual molecular or fragment ions, a powerful tool for the structural elucidation or confirmation. 9

10 Compound ID confirmation Chemical element No C 50 H 100 O 10 N 10 Cl No of Formulae , Mass Accuracy (ppm) 10

11 Il GC-Orbitrap 11 The world leader in serving science

12 Introduzione del GC-Orbitrap An Illustrated History of Gas Chromatography: Thermo Scientific Q Exactive GC 12

13 New Addition to the Orbitrap GC-MS Family Thermo Scientific Q Exactive GC system Unprecedented Depth in Analysis RP 120,000 m/z 200) EI/CI; Full-scan, Timed-SIM MS/MS capability Redefining Routine GC-MS RP 60,000 m/z 200) EI/CI; Full-scan; Timed-SIM Thermo Scientific Exactive GC system 13

14 Exactive GC system: The Technology Inside Orbitrap mass analyzer Incredible HRAM performance Highly regarded Q Exactive GC system platform Thermo Scientific TRACE 1310 GC System Unique modular injector and detector design Rapid heat cycling Thermo Scientific ExtractaBrite Ion Source technology Routine grade robustness Patented RF lens Removable without breaking vacuum 14

15 Bringing GC and Orbitrap Technology Together C-TRAP AQT Quadrupole Bent Flatapole HCD Cell Orbitrap Mass Analyzer ExtractaBrite Ion Source 15

16 What the Orbitrap Looks like Inner-electrode Split outer-electrode 16

17 Pulsing Ions into the Orbitrap: Curved Linear Trap (C-trap) Ions are stored and cooled in the RF-only C-trap Gate Deflector Push Trap Pull Lenses Ions are ejected along lines converging to the pole of curvature (which coincides with the Orbitrap entrance). As ions enter the Orbitrap, they are picked up and squeezed by its electric field Orbitrap 17

18 Retaining the Ions in the Orbitrap ω = k m / z Frequency of axial oscillations are independent of initial conditions of ions entering trap Therefore these oscillations used for mass determination Image current measured by outer split electrodes (no electron multiplier to replace!) Ion frequencies determine by complex superposition of measured ring oscillations through Fourier transform 18

19 GC-MS Until Now Challenge Compromised Options Limited GC-MS analysis No comprehensive quantitative & qualitative analysis For quantitation: targeted approaches required HR/AM Qualitative approaches compromised Multi-instrument approach Can be inefficient, convoluted and complicated GC single and triple quadrupole MS for target quantitation GC- Time-of-flight (Tof) MS with limited performance 19

20 Breakthrough in GC-MS Performance Resolution Mass accurancy Sensitivity Dinamic Range Up to 120,000 at m/z 200 < 1 ppm ppt & >6 Orders Highest available Maximum selectivity Fast enough for GC Every scan All concentrations In complex matrix In full scan High selectivity High spectra fidelity Excellent coverage in sample profiling Triple quad grade quantitation in full scan Across the mass range Everyday!! 20

21 Exactive GC System Main Workflows 1x Full-scan expected suspected unexpected Targeted Quantitation Targeted Screening Non-targeted Screening Scope 21

22 Non-targeted Screening Overview detect and refine 1 generate candidates 2 filter and identify 3 Sensitive and selective peak detection High resolution spectral deconvolution Clean spectrum Search spectra against spectral libraries HRAM or unit mass Candidates list generated High resolution filtering of candidates Putative identifications made Process semi/fully automated as preferred 22

23 Identify the compound searching NIST Hits from NIST are sorted based on: 1. Spectral matching. 2. High Resolution Filtering (HRF) score. % of the ions in the spectrum that can be explained by the element in the proposed compound. 23

24 Identify the compound searching NIST 14 Combined SI and HRF values give an overall score (%) to quickly and confidently identify the compound. Eliminates other hits that would be valid if only SI used. 24

25 Fragments can be explained with < 1ppm mass accuracy 25

26 Q Exactive GC: Compound Discovery and Identification Search Identify Known Unknown Library AM filtering Unknown Unknown 26

27 Q Exactive GC: Compound Discovery and Identification Remove entire ion source or change to CI source in under 2 minutes without venting 27

28 EI & PCI spectra for peak at mins. 28

29 MS/MS m/z to support proposed formula 08OCT15_01 # RT: AV: 10 NL: 1.19E7 T: FTMS + p CI Full ms @hcd10.00 [ ] Relative Abundance >13 fragments can be explained based on C 20 H 20 O C 7 H 5 O = ppm C 9 H 5 O 2 = ppm C 14 H 11 O = ppm C 15 H 11 O 2 = ppm C 17 H 15 O 2 = ppm C 18 H 15 O 3 = ppm m/z 29

30 No. of proposed formulae for m/z Top hit = C 20 H 20 O 4 25 No. proposed formulae ppm 1 3 ppm 5 ppm 10 ppm 20 ppm Elements used: C (1-30), H (1-60, N (1-5), O (1-5), P (1-2), S (1-2) 30

31 Untargeted Metabolomics using Orbitrap GC-MS 31 The world leader in serving science

32 Introduction Metabolomics aims to characterize and quantify the complete small molecule complement (the metabolome) of a biological system. The metabolome is very diverse mixture of small molecules (amino acids, sugars and phosphosugars, biogenic amines and lipids). Untargeted metabolomics - challenging due to the requirement to identify and quantify hundreds of different compounds with limited a priori knowledge. Ideally - use MS analytical platforms able of sensitive detection of molecules, in addition to providing accurate mass information for structural analysis of unknowns. 32

33 Introduction The goal of metabolomics is a comprehensive and systematic understanding of all metabolites in biological samples. 33

34 Challenges in metabolomics Targeted Define specific metabolites Detect them with appropriate parameters Identity is unambiguous Quantitation often absolute Interpretation relatively easy Validation Untargeted More challenging, less quantitative Identity ambiguous due to breadth of separation Greater coverage Detect unexpected or new compounds Interpretation and statistical analysis challenging Discovery 34

35 Metabolic Profiling of bacterial quorum sensing Developing a metabolomic toolbox for pathogen-pathogen interactions 1. Candia albicans: cells & media 2. Staphylococcus aureus: cells & media 3. C. albicans & S. aureus co-culture: cells & media Q Exactive GC MS Full MS Relative quantitation and identification Compound ID using NIST and pure standards 35

36 Staphylococcus aureus Candida albicans and Staphylococcus aureus dual-species biofilms Candida albicans Leading pathogens in bloodstream and systemic infections Major cause of morbidity and mortality Form biofilms 36

37 Staphylococcus aureus Staphylococcus aureus + Candida albicans Candida albicans Carlson, E., (1983), Infection and Immunity, 42 (1)

38 C. albicans S. aureus S. aureus added to C. albicans biofilm SEM images: 4000x magnification 38

39 Aims Characterise the dual-species biofilm Develop metabolomics methods for the analysis of polymicrobial biofilms Apply methods to determine the interaction between Candida albicans and Staphylococcus aureus 39

40 Media samples Chromatogram from GC-Orbitrap RT: Relative Abundance SM: 3B Time (min) NL: Media blank 2.84E7 TIC MS MO NL: 3.57E7 TIC MS CAM Candida media NL: 3.48E7 TIC MS SAM2 S. aureus media NL: 3.57E7 TIC MS SCM3 Co-culture 40

41 Principal Component Analysis Cells samples SCC SAC CAC MO Media samples SCM SAM CAM 41

42 Amino Acid Uptake: media samples Fresh Medium CAM SAM SCM L-Methionine, 2TMS L-Proline, 2TMS L-Histidine, 3TMS L-Threonine, 3TMS L-Glutamic acid, 3TMS L-Serine, 3TMS L-Leucine, 2TMS L-Isoleucine, 2TMS L-Phenylalanine, 2TMS L-Alanine, 2TMS L-Aspartic Acid, 3TMS L-Ornithine (and L-Argininine), 3TMS L-Valine, 2TMS L-Tryptophan, 3TMS L-Homoserine, 3TMS L-Tyrosine, 3TMS Glycine_3TMS L-Hydroxyproline, 3TMS L-Cysteine, 3TMS

43 Central carbon metabolism: media samples Fresh Medium CAM SAM SCM D-Glucose, 6TMS + Oxime Succinic acid, 2TMS Lactic Acid, 2TMS Fucose + 4TMS + Oxime Myo-Inositol + 6TMS D-Lactose + 8TMS + Oxime D-Arabinose + 4TMS + Oxime D-Ribose + 4TMS + Oxime Sucrose + 8TMS Maltose + 8TMS + Oxime D_Threose + 4TMS + Oxime ND 43

44 Intracellular sugar phosphates: cells samples Normalised CAC SAC SCC Myo-Inositol-1-phosphate + 7TMS D-Glucose 6-phosphate + 7TMS + Oxime Sedoheptulose 7-phosphate + 7TMS + Oxime D-ribose 5-phosphate + 5TMS + Oxime D-Erythrose 4-phosphate +5TMS 0 ND ND D-Fructose 1,6-bisphosphate + 6TMS + Oxime 0 ND ND D-Fructose 1-phosphate + 7TMS + Oxime 0 ND ND D-Fructose 6-phosphate + 6TMS + Oxime 0 ND 0.7 Ribulose-5-phosphate + 5TMS + Oxime 0 ND ND 44

45 Compound Discoverer 2.0 metabolomics workflow import.raw data (full scan EI or CI) Experiment definition (sample grouping) Data processing (peak alignment & extraction) Compound ID (NIST or user database) Statistical analysis (trend plot, PCA) Data export further statistical analysis using 3 rd party software Data review (based on %CV, p-values) 45

46 Compound Discoverer results browser 46

47 Untargeted Metabolomics Dr. Karl Burgess Application: Automated, untargeted metabolomics of decaying muscle tissue from various species Aim: Discovery of bio markers for time of death Glasgow Polyomics University of Glasgow, UK Results: PCA for time of death in Rats allowed group separation suggesting a prediction model for time of death can be obtained. Automatic identification of significant metabolites and potential biomarkers was possible with Q Exactive GC and intelligent deconvolution and identification software 47

48 GC-MS chromatograms of a rat muscle tissue sample RT: Relative Abundance Day 1 post-mortem T0 Immediately post-mortem T1 T2 Day 2 post-mortem T3 Day 3 post-mortem Time (min) NL: 1.00E9 TIC MS t0r1r NL: 1.00E9 TIC MS t1r3r NL: 1.00E9 TIC MS t2r5r NL: 1.00E9 TIC MS t3r7r 48

49 Peak Deconvolution Automated peak picking using TraceFinder resulted in 1193 distinct peak clusters detected, 156 peaks as TMS derivatives. Example of deconvoluted peak cluster putatively identified as glutamate: 49

50 Quantitation matrix of detected peak clusters Base Peak Mass. RT max intensity T0 T1 T2 T3 ttest: T0 ttest: T1 ttest: T2 ttest: T

51 Partial Least Squares-Discriminant Analysis Multivariate analysis that collapses high-dimensional data to principal components responsible for the majority of variance in the dataset. PC2 51 PC1

52 Variables trend Example of changing intensities of detected chemicals across biological groups (T0 T3). 52

53 Untargeted metabolomics Putative compound ID RT (min) NIST Forward Match Fold increase compared to T0 Base Peak Fragment elemental composition Ppm accuracy (base peak) ppm accuracy (Mol. ion) L-Threonine, 3TMS C9H24ONSi L-Aspartate, 3TMS C9H22NO2Si L-Methionine, 2TMS C7H18NSSi L-Glutamine-3TMS C7H14NOSi Putrescine, 4TMS C7H20NSi N/A 53

54 Conclusioni GC/MS market gap exists for simultaneous targeted and untargeted analysis with sensitivity and selectivity comparable to that of a triple quadrupole An Orbitrap based GC system provides the technology to fill this gap based on its sensitivity and ability to operate routinely at very high resolutions The very high resolution and accurate mass data the Orbitrap based GC system produces can increase confidence in unknown identification. Q Exactive GC is an easy-to-use, dedicated GC-MS that provides the highest confidence in compound discovery, identification and quantitation for a comprehensive understanding of your samples. This is achieved through the superior resolving power, mass accuracy and sensitivity that only Orbitrap technology can deliver. 54

55 Grazie per l attenzione!!! 55