The new standard for shotgun proteomics. Innovation With Integrity

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1 The new standard for shotgun proteomics Innovation With Integrity

2 Shotgun/Bottom-up proteomics Proteome analyzer challenge Several million peptides Genes Expression >10 6 Proteoforms Digestion > N X 10 6 Peptides 10<N< orders of magnitude in concentration EXTREME COMPLEXITY Extract identification, PTM info and abundance info during the run time Hein et al., 2013, Handbook of Systems Biology 2

The Complexity of Shotgun Proteins is a Known Hurdle More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data dependent LC MS/MS.

3 The Complexity of Shotgun Proteins is a Known Hurdle More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data dependent LC MS/MS. Annette Michalski, Jürgen Cox, Matthias Mann J Proteome Res, 2011, 10(4),1785. The extremely high complexity of proteomics data acquired from a complete mammalian cell lysate separated over a two hour gradient.

4 Separations and MS Sampling Rate Understanding the interplay between Separations and MS sampling rate impacts proteomics at every level Coon et al., 2016, Cell Systems 3, October 26, 2016

Thus peak capacity is a measure of the separation potential of the technique and depends on the resolution of the individual systems and difference in

5 Better Separations: How about the Gas Phase? Diminishing rate of return on nano LC columns and time; 2h 4h gradients, longer columns have their compromises, so can gas phase separations help? Thus peak capacity is a measure of the separation potential of the technique and depends on the resolution of the individual systems and difference in their separation mechanism (orthogonality). A 2D separation technique will have very high ϕ value if the fundamental separation mechanisms of individual highresolution systems are completely different such as in LC MS [110,111]. Dwivedi et al., Int. J. Mass. Spectrom. 298, 2010

6 Then why isn t IMS on every MS? Mike Bowers Lab UC Santa Barbara 2m drift tube with microtof Dual TIMS analyzer Complexity Ion Losses Low Duty cycle

7 The Right Way to do IMS-MS Dual TIMS Parallel accumulation capability from spray chamber Deflection Plate Gas Cap. Exit Ions Accumulate Trap Elute Entrance Funnel Analyzer 2 Exit Funnel Analyzer 1 Gas to mass analyzer E Z TIMS is not just an additional separation device; it allows us for the first time ever to perform experiments that take full advantage of the speed of QTOF Analyzers with nearly 100% Duty cycle! 9

8 How Does TIMS Work? Very Different from Conventional IMS from spray chamber Deflection Plate E Gas Cap. Exit Ions Accumulate Trap Elute Parallel accumulation: Usage of Analyzer 1 nearly all ions (100% duty cycle) Entrance Funnel Analyzer 2 Exit Funnel Gas Z to mass analyzer TIMS resolution depends on buffer gas velocity (v g ) and the time (t p )spent traversing the EFG plateau. Hence, dramatic improvement in R is obtained in relative short path lengths.tims does not have a dependency on the L term like traditional drift tubes. Time focusing: Ion species are accumulated for ms in the TIMS tunnel, however elution of each ion species from the TIMS tunnel happens within 2 5 ms Space focusing: Ion packages eluted at a specific time point dependent on their mobility, resulting in cleaner MS/MS spectra

9 How Does TIMS Work? Advantage of Time and Space focusing from spray chamber Deflection Plate Gas Cap. Exit Ions Accumulate Trap Elute Entrance Funnel Analyzer 1 Analyzer 2 Exit Funnel Gas to mass analyzer Time focusing: Ion species are accumulated for ms in the TIMS tunnel, however elution of each ion species from the TIMS tunnel happens within 2 5 ms Time & Space Focusing using TIMS Space focusing: Ion packages eluted at a specific time point dependent on their mobility, resulting in cleaner MS/MS spectra Analyzer 1 TIMS Separation intensity intensity intensity intensity ms (Time) 5 ms (Time) 5 ms (Time) 5 ms (Time) Concept courtesy of Gary Kruppa

10 Introducing timstof PRO powered by PASEF A revolutionary product for Shotgun/Bottom-up proteomics Increased Speed with improved separation > 100 Hz MS/MS Increased Sensitivity > 20X increase Uncompromised resolution > all MS/MS speed Robust performance Maintenance interval x3 2

11 Ion Optics and HPLC-IM-MS-MS timing HPLC TIMS Quadrupole Filter Time of Flight MS Chromatography Ion Mobility Separation Mass Selection Mass scan FWHM ~ 7 s ms Hz ms precursors/s 110 µs 9.1 khz

12 Ion Optics Detector Orth. Accelerator Dual Stage Reflectron ImpacTEM Schematic-w/o-ETD Dual TIMS analyzer quadrupole filter collision cell TOF MS

13 Can TIMS Orthogonality Help Reduce Complexity? Using the 4 th Dimension (TIMS) Retention time MS MS/MS Ret. time TIMS MS MS/MS *Data courtesy Scarlet Beck (Ph.D. thesis)

(N=29,770) MS/MS at 4x sequencing rate (N=219886) peptide features (N=248,512) targeted for

14 2. PASEF- Parallel Accumulation Serial Fragmentation Addressing the challenges in bottom up proteomics with PASEF peptide features (N=248,512) targeted for MS/MS (N=45,863 identified (N=29,770) MS/MS at 4x sequencing rate (N=219886) peptide features (N=248,512) targeted for MS/MS (N=45,863 identified (N=29,770) MS/MS at 3x sequencing rate and 3x sensitivity(n=171,468) 2

15 PASEF MS Scan (Parallel Accumulation Serial Fragmentation) from Source Dual TIMS with accumulation/analyzer regions gives 100% duty cycle. accumulation (100 ms)

16 PASEF MS Scan transfer (2 ms)

17 PASEF MS Scan parallel accumulation TIMS scan (100 ms) 1/k0 [Vs/cm 2 ] MS Heat Map m/z

18 PASEF MS Scan parallel accumulation TIMS scan 1/k0 [Vs/cm 2 ] precursor selection m/z

19 PASEF MSMS Scan parallel accumulation TIMS scan isolation fragmentation (~3 ms / precursor) 1/k0 [Vs/cm 2 ] MSMS Heat Map 1/k0 [Vs/cm 2 ] MS Heat Map m/z

20 PASEF MS - MSMS alignment 1/k0 [Vs/cm 2 ] MSMS Heat Map 1/k0 [Vs/cm 2 ] MS Heat Map m/z m/z

21 PASEF MS - MSMS alignment Mobility 1/K0 1.4 MSMS Heat Map Mobility 1/K0 1.4 MS Heat Map m/z m/z 1/k0 [Vs/cm 2 ] MSMS Heat Map 1/k0 [Vs/cm 2 ] MS Heat Map m/z

22 PASEF example data

23 HeLa Experiment Instrumentation: nanoelute (Bruker) 25cm X 75µm 1.8 µm C18 column, (IonOpticks, Australia) column oven, (Sonation) CaptiveSpray Ion Source, (Bruker) timstof, (Bruker) Method: 200ng HeLa digest 90min gradient LC-IM-autoMSMS run: 1.1s cycle with 1 MS + 10 PASEF MSMS

24 HeLa MS Heatmap as function of retention time size weight MQSS L7 - IM-MS for fastest DDA proteomics - Oliver Raether

25 PASEF precursor selection 60 min 12 MSMS spectra acquired in 66 ms #34234

26 PASEF scan #34235 #34235

27 PASEF scan #34236 #34236

28 PASEF scan #34237 #34237

29 PASEF scan #34238 #34238

30 PASEF scan #34239 #34239

31 PASEF scan #34240 #34240

32 PASEF scan #34242 #34242

33 PASEF scan #34243 #34243

34 PASEF scan #34244 #34244

35 PASEF precursor selection #34230

36 PASEF precursor selection Mobility 1/K0 Int int m/z 10 0

PASEF precursor selection Mobility 1/K0 Int. 1.4 10 3 1.

37 PASEF precursor selection Mobility 1/K0 Int x int m/z 10 0

38 PASEF precursor selection Mobility 1/K0 Int. 1.4 Mass: m/z CCS: Å² Intensity: Mass: m/z CCS: Å² Intensity: Mass: m/z CCS: Å² Intensity: int m/z 10 0

39 PASEF scan MSMS identification Precursor Mass: m/z CCS: Å² Intensity: Fragment Repetitions: 3 Mascot Ions Score: 62 Expectation Value: 6.7e-7

40 PASEF scan MSMS identification Precursor Mass: m/z CCS: Å² Intensity: Fragment Repetitions: 4 Mascot Ions Score: 72 Expectation Value: 6.9e-8

41 PASEF scan MSMS identification Precursor Mass: m/z CCS: Å² Intensity: Fragment Repetitions: 5 Mascot Ions Score: 35 Expectation Value: 3.0e-5

42 PASEF: Maximizes Sensitivity # # # scan 1 scan 2 scan 3 scan m/z # Intens APEPPALIVR # Sum # Data courtesy of Oliver Raether

Results of MS-MSMS experiment #34230 117 MSMS spectra 37 precursor

43 Results of MS-MSMS experiment # MSMS spectra 37 precursor scheduled 3.2x spectra per Precursor 19 Identifications 51% ID Rate #34230

Proteomics ID results Frequency Prediction: Peptide features (N = 248,512) targeted for MS/MS (N = 45,863) Identified (N = 29,770) PASEF at 3x sequencing rate and 3x sensitivity (N = 171,468) Meier

44 Proteomics ID results Frequency Prediction: Peptide features (N = 248,512) targeted for MS/MS (N = 45,863) Identified (N = 29,770) PASEF at 3x sequencing rate and 3x sensitivity (N = 171,468) Meier et al., JPR, 2015 LOD Result: Lubeck et al., ASMS, 2017 and later work Total number of MSMS spectra Precursors targeted Peptide spectrum matches Unique peptide sequences, FDR < 1%, (Mascot with Percolator) Protein groups (Mascot with Percolator) TIMS PASEF 610, ,000 >80,000 >40,000 >5,500 TIMS off 105, ,000 29,000 20,000 3,200

45 PASEF Sensitivity Experiments 60 min gradients 60 min gradients 25 ng, ~23,000 peptides Approximately 50 cells Data courtesy of Heiner Koch

46 PASEF Sensitivity Experiments 100ng HeLa digest 30 90min gradients Protein groups 25k 45K unique peptides Avg. 800 unique peptides/min Protein groups min 60 min 90 min unique peptides min 60 min 90 min unique peptides/ min retention time [min] Data courtesy of Heiner Koch

47 Evosep One and the timstof Pro Bruker and Evosep Announce New Integrated Clinical Research Proteomics Solution to Quantify Over a Thousand Proteins in Five Minutes Minneapolis, MN March 12, 2018 At the 2018 US HUPO Conference Press release 8:00 a.m. today

48 Evosep One

49 Evosep One simplified diagram Low Pressure pumps Evotip High Pressure pump

50 Evosep One Low overhead LC-MS

51 EvoSep 5 min gradient results # PSMs TIC variation [%] Run # # Proteins Identified Quantified Run # 80 runs in less than 10 hours Reproducible ID results, TIC intensities.

52 Application: Phosphoproteomics non-phosphorylated: 47% singly charged phosphorylated: 27% singly charged Non phosphorylated: 200ng HeLa digest Phosphorylated: Enrichment of phosphopeptides from 300µg HeLa digest by Fe IMAC chromatography Approximately ng after enrichment 90min gradient 100ms ramp time 100% duty cycle For both experiments # precursors non phosphorylated phosphorylated charge state Phosphopeptides have more missed cleavage sites than non phosphorylated ones. Hence, they are longer, have more charges and appear in the bottom right corner of the heatmap (next slide). Heiner Koch

8 200 400 600 800 1000 1200 1400 1600 m/z 2 10 1 10 0

53 Heatmap of peptides and phosphopeptides at the same retention time Mobility 1/K0 1.4 Peptides RT 58 min Int m/z Mobility 1/K p peptides RT 58 min m/z Int Score >20 Heiner Koch

size to charge unique p peptides 16000 14000 12000 10000 8000

54 Uncover the functionality of the proteome - Phosphoproteomics Accumulation of a 90min run: p-peptide separation on m/z and size to charge unique p peptides min LCMS/MS p-peptide composition 1% PSM FDR

55 PASEF for increased selectivity TIMS separation of co-eluted isobaric peptides from mouse heart Precursor m/z RT min Precursor m/z RT min Without ion mobility separation these overlapping precursors would give chimeric MSMS spectra

56 PASEF for increased selectivity TIMS separation of co-eluted isobaric peptides from mouse heart Those two peptides are co-eluted They are 0,0009Da apart Distinguishing them, based on resolution only, would have required a resolving power > ! and that alone would not have allowed to isolate them separately Precursor m/z PASEF DOES > 100 Hz MS/MS Without ion mobility separation these While preserving sensitivity! overlapping precursors would give chimeric MSMS spectra Precursor m/z

57 PASEF for PTM analysis TIMS separation of co-eluted isobaric HEK Phosphopeptides Similar seqences Several Phosphoryation sites on the sequence Probable isoforms

58 PASEF for LFQ : reproducibility protein groups > 5300 protein groups per run total replicates 200 ng Hela Cell digest, 90 min gradient In 1 replicate Higher number of quantified proteins Increased selectivity vs DDA & DIA in 3 replicates > 93 % In 2 replicates In all 3 replicates

59 PASEF for LFQ : Accuracy 4931 quantified proteins 4 orders of magnitude 2 proteome mixture digest Hela Cell / E.Coli Sample A Sample B min gradient PASEF Acquisition

60 PASEF for LFQ : Accuracy 2 proteome mixture digest Hela Cell / E.Coli Theory 1:0,5 Sample A Sample B Measured 1,16:0, ,5 1,16 0,58 90 min gradient PASEF Acquisition N.B. : the 1:2 ratio between Human and E.Coli is preserved possible pipetting issue during sample preparation

61 timstof Pro : Processing Software OPEN File format: Freely available MaxQuant Identifications LF Quant Labelled Quant Peaks Studio Identifications LF Quant Labelled Quant Skyline 8

62 Summary TIMS PASEF allows for up to 10 times higher acquisition speed during data dependent AutoMSMS. TIMS PASEF more than doubled the number of peptide spectrum matches per analysis time as compared with TIMS off operation. LC-IM-MSMS method optimized for low sample amount Evosep One support for robust, high throughput proteomics Open file format and support by multiple software packages

63 Acknowledgements Bremen Colleagues Thomas Betz Sven Brehmer Jens Decker Nicole Drechsler Hartmut Geerken Niels Goedecke Stefan Harsdorf Joerg Hoffmann Werner Imhoff Stephanie Kaspar Michael Krause Markus Lubeck Karsten Michelmann Sven Meyerdierks Henning Peise Juergen Suetering Bernhard Sajnog Wiebke Timm Scarlet Koch Heiner Koch Research Group, Billerica Mel Park Mark Ridgeway Max Planck Institute of Biochemistry Juergen Cox Matthias Mann Florian Meier Andreas Brunner Evosep One Christian Ravnsborg Nicholai Brache Michael Andersen

Application Note # LCMS-89 High quantification efficiency in plasma targeted proteomics with a full-capability discovery Q-TOF platform

Application Note # LCMS-89 High quantification efficiency in plasma targeted proteomics with a full-capability discovery Q-TOF platform Abstract Targeted proteomics for biomarker verification/validation