Moving from targeted towards non-targeted approaches

Transcription

1 Gesundheitsdirektion Moving from targeted towards non-targeted approaches Anton Kaufmann Official Food Control Authority of the Canton of Zurich () Switzerland

2 2 Overview I From single residue to multi residue II Data dependent acquisition (DDA) III Data independent acquisition (DIA) IV Deconvolution based approaches V Data mining of compound lists

3 3 Overview I From single residue to multi residue II Data dependent acquisition (DDA) III Data independent acquisition (DIA) IV Deconvolution based approaches V Data mining of compound lists

4 4 Food matrices can be extremely complex Even the combination of UHPLC and HRMS will not resolve all trace analytes from the matrix peaks Product ion information is essential for unequivocal identification of trace analytes

5 5 Single Target 1 SRM Product ion

6 6 Multiple Targets many SRM s

7 We got a hit! Kanton Zürich 7

8 Positive findings frequently generate new questions Kanton Zürich 8 Now; since drug A is present, how about related drugs, how about metabolites?

9 9 Tandem quadrupole is not the technique to navigate in an ocean of data

10 10 Overview I From single residue to multi residue II Data dependent acquisition (DDA) III Data independent acquisition (DIA) IV Deconvolution based approaches V Data mining of compound lists

11 Data dependent acquisition (DDA) Kanton Zürich 11 - Checking the chromatogram for the accurate mass of suspected analytes (inclusion list) - MS/MS triggering of any sufficiently abundant chromatographic peak

12 12 Data dependent acquisition (DDA)

13 Signal intensity Point of triggering Kanton Zürich 13 time

14 Correct triggering Kanton Zürich 14 - Complex set-up - Inclusion & exclusion list (targeted) - Thresholds (un-targeted) - No guarantee that every compound of interest will be triggered (how to validate limits of detection?)

15 Signal intensity Library based Ion ratio Kanton Zürich 15 Two ions for the calculation of an ion ratio DDA based Ion ratio Product ion 1 Peak area based Ion ratio Product ion 2 time

16 16 Overview I From single residue to multi residue II Data dependent acquisition (DDA) III Data independent acquisition (DIA) IV Deconvolution based approaches V Data mining of compound lists

17 Data independent acquisition (DIA) Kanton Zürich 17 - Monitoring different MS experiments Sequentially isolating mass ranges which afterwards undergo fragmentation (SWATH) Low and high collision energy traces (all ion fragmentation) e.g. assisted by ion mobility separation

18 SWATH Kanton Zürich 18 m/z

19 19 SWATH Scan 1 Scan 2 Scan 3 Scan 4 Scan 5 Scan 6 Scan 7 Scan 8 m/z :

20 20 Overview I From single residue to multi residue II Data dependent acquisition (DDA) III Data independent acquisition (DIA) IV Deconvolution based approaches V Data mining of compound lists

21 Deconvolution Kanton Zürich Chart Title TIC Analyte A Analyte B Retention time

22 Principle of Deconvolution Kanton Zürich 22 Ions originating from the same compound will be correlated across the time range of a chromatographic peak - Based on calculation of coefficient of correlation - Based on principle component analysis (All techniques require a prior peak alignment)

23 rel. Response rel. Response Kanton Zürich 23 5 µg/kg methyltestosterone in bovine liver unit mass resolution based product ion (PRM) spectrum MRM Peak apex) Apex All ion fragmentation (AIF) spectrum (peak Peak apex) Apex m/z m/z

24 rel. Response rel. Response 4000 Correlation across a chromatographic peak versus spectra at the peak apex MRM (PRM) e Kanton Zürich 24 AIF (AIF) e m/z m/z

25 rel. Response rel. Response Kanton Zürich 25 SWATH produces DIA data with MRM spectra quality 4000 (PRM) MRM e (SWATH) e m/z m/z

26 The Potential Kanton Zürich 26 - Deconvolution algorithms isolate all chromatographic peaks from the three dimensional landscape (e.g. UNIFI) - Spectra clean up by ion mobility assisted AIF - Scan based or nested window SWATH

27 The Limitations Kanton Zürich 27 - Fast acquisition speed is essential in order to: Do as many experiments as possible (narrow SWATH windows and possibly multiple collision energies))

28 28 Extracting all components (compounds) and not just spectra precursor + isotopes

29 29 Cutting the mountain tops above a certain threshold (deconvolution)

30 30 Grouping the mountains into ridges (componentization)

31 Peak deconvolution and componentization Synchronizing drift time with m/z Kanton Zürich 31 Column bleed m/z noise Retention time

32 32 Componentization does more than only finding isotopes - Product ions - In source fragments of labile precursor ions - Adducts (e.g Na + ) or dimers

33 33 Component list instead of mass traces Reten tion time Precursor ion m/z Product ions m/z m/z min m/z Abundance Abundance Abundance Abundance Possibly s of components (compounds)

34 Data Mining Kanton Zürich 34

35 35 Data mining tools - Filters - MS/MS Library search

36 36 Filters - Halogen & Sulfur - Characteristic product ion - Neutral loss filter - Removal of multiple charged ions (e.g. peptides) - Mass defect filter

37 MS/MS library based search Kanton Zürich 37 - MS/MS Library search ( red, exogenous compounds) - In silico fragmentation for suspect screening - TIC clean-up (not simple baseline subtraction but removal of green endogenous compounds)

38 38 The problem: Finding the needle in the haystack

39 39 Solution step 1: Getting rid of endogenous signals

40 Orthogonal filter Kanton Zürich 40

41 41 Solution step 2: Utilizing the specific properties of the exogenous compound

42 42 True non-target in complex matrices still needs some additional innovations In the future we shall travel in the air