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[email protected] SWATH™: next generation data-independent (DIA) mass spectrometry for complete qualitative and quantitative sample analysis

SWATH™: next generation data-independent (DIA) …·ал...700 800 900 1000 1100 1200 0 m/z min 10 20 30 40 50 60 70 80 90 100 110 SWATH-MS Acquisition Principle m/z range = [400-1200]

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[email protected]

SWATH™: next generation data-independent (DIA) mass spectrometry for complete qualitative and

quantitative sample analysis

[email protected]

Data-independent SWATH™ acquisition onAB SCIEX TripleTOF® mass spectrometers

[email protected]

SWATH™: Recent advances in data-independent acquisition and the creation of the OneOMICS™

cloud ecosystem

[email protected]

SWATH™: Recent advances in data-independent acquisition and the creation of the OneOMICS™

cloud ecosystem

5 © 2015 AB Sciex

Proteome 1 Proteome 2 Proteome 3 Proteome 4 Proteome 5 Proteome 6 Proteome 7

“omics”: it is all about time courses

6 © 2015 AB Sciex

“omics”: it is all about time courses

Proteome 1 Proteome 3 Proteome 4 Proteome 5 Proteome 6 Proteome 7Proteome 2

7 © 2015 AB Sciex

8 © 2015 AB Sciex

9 © 2015 AB Sciex

Mixed (“Chimeric”) MSMS Spectra

− Two co-eluting species identified from isotope patterns; separating monoisotopic peaks requires > 200K!

− MS/MS spectra would be mixed (“chimeric”) even if the precursors were detected in real-time

− Search engines don’t handle this well…

Precursor Window (Q1)

for MSMS

MNIENLK +2

FATHGGYLLQGK +3

Precursor Window (Q1)

for MSMS

2 peaks!

Note!Repeat analysis of the same E. coli

sample gave 10% ID variation!

10 © 2015 AB Sciex

Chimeric MSMS Spectrum

− Seems to affect 30-40% of all spectra – with 0.7 amu selection…

− …how much worse will it be at 3 amu or 4 amu− Really bad would be identifying a completely different

peptide/protein – never happens…− Does it?

MNIENLK +2 FATHGGYLLQGK +3

a1

Y9

Y10

Y11

Y7

Y8

11 © 2015 AB Sciex

12 © 2015 AB Sciex

SWATH™Conventional Proteomics

Targeted Proteomics

Conventional StrategiesDDA

SWATH™ StrategyDIA

Gold Standard QuantitationSRM/MRM

13 © 2015 AB Sciex

DDA vs. DIA vs. MRMDiscovery

(DDA)Targeted (MRM)

on almost everything

DIA

on targetson semi-random subset

Jarrett Egertson, MacCoss Lab

14 © 2015 AB Sciex

DDA vs. DIA vs. MRMDiscovery

(DDA)Targeted (MRM)

on almost everything

DIA

on targetson semi-random subset

Jarrett Egertson, MacCoss Lab

15 © 2015 AB Sciex

The goal: a complete picture

Jarrett Egertson, MacCoss Lab

16 © 2015 AB Sciex

DIA

semi-random subsets

Achieving the goal: data dependent acquisition?

Jarrett Egertson, MacCoss Lab

17 © 2015 AB Sciex

DIA

on targetson semi-random subset

Achieving the goal: MRM/SRM?

Jarrett Egertson, MacCoss Lab

18 © 2015 AB Sciex

DIA

on targetson semi-random subset

Achieving the goal: MRM/SRM?

Jarrett Egertson, MacCoss Lab

19 © 2015 AB Sciex

DIA

on targetson semi-random subset

Achieving the goal: data independent acquisition?

Jarrett Egertson, MacCoss Lab

on almost everything

20 © 2015 AB Sciex

Targeted (MRM)

Discovery (DDA)

on almost everything

DIA

on targetson semi-random subset

Achieving the goal: data independent acquisition?

Jarrett Egertson, MacCoss Lab

21 © 2015 AB Sciex

DIA

on targetson semi-random subset

Achieving the goal: MRM/SRM?

Jarrett Egertson, MacCoss Lab

22 © 2015 AB Sciex

DIA

on targetson semi-random subset

Achieving the goal: MRM/SRM?

Jarrett Egertson, MacCoss Lab

23 © 2015 AB Sciex

DIA

on targetson semi-random subset

Achieving the goal: MRM/SRM?

Jarrett Egertson, MacCoss Lab

Targeted (MRM)

24 © 2015 AB Sciex

1 amu 1 amu

1amu 0.01 amu 0.01 amu0.01 amu

MRM/SRM

MRMHR

Precursors FragmentsCID

MS/MS quantitation techniques

Triple quadrupole

TripleTOF™5600+

Transition

X amu

TripleTOF™5600+ SWATH-MS™

m/z m/z

How big can X be?

25 © 2015 AB Sciex

Q0 High Pressure Cell

LINAC®

collision cell

Accelerator TOF™ Analyzer

40 GHz Multichannel TDC Detector

Two-stage reflectron

30kHz Accelerator

15 kV Acceleration

voltage

Ion compression optics

QJet® Ion Guide

High Frequency

Q1

The AB SCIEX TripleTOF® Systems

26 © 2015 AB Sciex

Nature Methods - Method of the year 2012

27 © 2015 AB Sciex

February 6 (2013) AB Sciex press release

28 © 2015 AB Sciex

Sequential Window Acquisition of all THeoretical Fragment Ion Spectra (SWATH™)

Conceived at Ruedi Aebersold’s lab @ ETH ZürichImplemented on SCIEX TripleToF™ systemsData-Independent Acquisition (DIA)

29 © 2015 AB Sciex

Sequential Window Acquisition of all THeoretical Fragment Ion Spectra (SWATH™)

Conceived at Ruedi Aebersold’s lab @ ETH ZürichImplemented on SCIEX TripleToF™ systemsData-Independent Acquisition (DIA)

30 © 2015 AB Sciex

Sequential Window Acquisition of all THeoretical Fragment Ion Spectra (SWATH)

• Conceived at Ruedi Aebersold’s lab @ ETH Zürich• Implemented on AB SCIEX TripleToF 5600+ QqToF

• Data-Independent Acquisition (DIA) on the LC time scale with generic methods

• Focus on precursor ion swathes, instead of individual precursors

31 © 2015 AB Sciex

Sequential Window Acquisition of all THeoretical Fragment Ion Spectra (SWATH)

• Conceived at Ruedi Aebersold’s lab @ ETH Zürich• Implemented on AB SCIEX TripleToF 5600+ QqToF

• Data-Independent Acquisition (DIA) on the LC time scale with generic methods

• Focus on precursor ion swathes, instead of individual precursors

32 © 2015 AB Sciex

33 © 2015 AB Sciex

34 © 2015 AB Sciex

Sequential Window Acquisition of all THeoretical Fragment Ion Spectra (SWATH™)

Conceived at Ruedi Aebersold’s lab @ ETH ZürichImplemented on SCIEX TripleToF™ systemsData-Independent Acquisition (DIA)

35 © 2015 AB Sciex

400

500

600

700

800

900

1000

1100

1200

0

m/z

min10 20 30 40 50 60 70 80 90 100 110

SWATH-MS Acquisition Principle

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36 © 2015 AB Sciex

400

500

600

700

800

900

1000

1100

1200

0

m/z

min10 20 30 40 50 60 70 80 90 100 110

SWATH-MS Acquisition Principle

m/z range = [400-1200] � at 25Da per swath ó 32 swaths required� at 100ms per isolation window ó 3.2s cycle time

A swath = the ensemble of fragment ion spectra acquired through the chromatographic range and for a defined isolation window

Cycle time: time required to come back to the acquisition of the same isolation window

Aebe

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37 © 2015 AB Sciex

400

500

600

700

800

900

1000

1100

1200

0

m/z

min10 20 30 40 50 60 70 80 90 100 110

SWATH-MS Acquisition Principle

=> complete MS/MS maps for all the analytesin a single sample injection

Aebe

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Zur

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38 © 2015 AB Sciex

MRMHR Workflow

Time, min

**

*

39 © 2015 AB Sciex

MS/MSAll with SWATH Acquisition

Time, min

******

40 © 2015 AB Sciex

MS/MSAll with SWATH Acquisition

Time, min

41 © 2015 AB Sciex

SWATH™ Acquisition

MRM Workflow

High Res XICs

Targeted Quantitative WorkflowsTop Two Techniques

42 © 2015 AB Sciex

Gillet et al., MCP 2012, Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis.

Figure by Christina Ludwig

SWATH-MS: Data-independent acquisition with targeted data extraction

SRM TARGETED data

acquisition

precursor selection

fragmentation fragment selection

0.7 Da

Q1 Q3

0.7 Da

Q2

inte

nsity

time

SWATH-MS data-independent

acquisition

precursor selection

fragmentation scanning

25 Da

inte

nsity

time

Q1 TOF

time time

TARGETED data extraction

Q2

10 ppm

43 © 2015 AB Sciex

m/z

Ion

trans

mis

sion

Desired instrument performanceNormal transmission Transmission through 5600

m/z

Ion

trans

mis

sion

Independent control over the RF and DC power supplies on a resolving Quadrupole with novel methods for determining the “offset” provide accurate windows of isolation

44 © 2015 AB Sciex

m/z

Ion

trans

mis

sion

Normal transmission “SWATH” Transmission

m/z

Independent control over the RF and DC power supplies on a resolving quadrupole provides accurate windows of isolation

SWATH Hardware: Q1 isolation windows

Ion

trans

mis

sion

45 © 2015 AB Sciex

Transmission window of TripleTOF 5600

MS/MS Experiment of SWATH 874-900 without CE

TOF MS Experiment

Relative intraspectral intensities of TOF MS and SWATH MSMS experiments are similar, even at the edges of the SWATH mass window.

46 © 2015 AB Sciex46

TIC

MS1 map

SWATH-MS principle: Acquisition & Targeted analysis

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47 © 2015 AB Sciex

Aebe

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SWATH-MS principle: Acquisition & Targeted analysis

47

TIC

MS1 map

MS2/swath map [swath 600-625 m/z]

855.5395742.4556 671.4180 600.3368

327.1295

Peptide of interest

<<

<

<

<

XICs of fragment ion traces:855.5395742.4556671.4180 600.3368 327.1295

<<

<

<<

<<

<

<

<

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48 © 2015 AB Sciex

Targeted Analysis of SWATH-MS Data

Courtesy of Ruedi Aebersold

49 © 2015 AB Sciex

Comparison of Data Independent Acquisition methods

Publication Purvine et al.Proteomics 2003

Plumb et al.Rapid CommMass Spec 2006

Geiger et al. MCP 2010

Gillet et al. MCP 2012

Venable et al. Nat Meth 2004

Panchaud et al. Anal Chem 2011

First time a method combines the speed, sensitivity, resolution and specificity

Data Independent Acquisition (DIA)

Isolation width 25 Da 10 Da 2.5 Dano windows (800 Da)

MSE AIFShotgun CID SWATH DIA PAcIFICDIA method

Duty Cycle ~2s ~2s ~2s 3.2s ~4s 5.4s

Specificity 7% 7% 7% 89% 16% 68%

Dynamic range nd 3-4 logsacross LC

4 logsacross LC

4 logsintrascan

nd 7 logsacross LC

Nb injection(s)for full coverage

1 1 1 1 >4 >20

Instrumentation Q-TOF QqTOF Orbitrap QqTOF LTQ LTQ

Aebersold and coworkers, ETH Zurich

50 © 2015 AB Sciex

Specificity of SWATHSWATH-MS Specificity

Gillet et al. Mol Cell Prot, manuscript O111.016717

51 © 2015 AB Sciex

VTLTSEEEAR from Lactate Dehydrogenase

Peptide quantified over putative loading between 500 pg and 5 µg with R2 0.999, without replicates.

XICs from SWATH™ data.Data from Tom Knapman, AB SCIEX

52 © 2015 AB Sciex

First SWATH publications

53 © 2015 AB Sciex

Validation of predicted splice forms

Courtesy of Ruedi Aebersold

54 © 2015 AB Sciex

Validation of predicted splice forms

Courtesy of Ruedi Aebersold

55 © 2015 AB Sciex

A biological Question

56 © 2015 AB Sciex

Proof of principle: Extending the quantification analysis to 40 “more” mitochondrial proteins involved in the yeast respiratory chain (not initially anticipated)

SWATH-MS added value: quantification analysis extension

Condition 1: SWATH MS run 1

Condition 2: SWATH MS run 2 > 10 fold up 5-10 fold up 2-5 fold up 1-2 fold up 1-2 fold down > 2 fold down

ACP1

NDE2

NDI1

NDE1

Mitochondrial Matrix

Inter Membrane

Space

Cytosol “Complex I”

NADH dehydrogenase

Complex II succinate

dehydrogenase

SDH2 SDH1

SDH4 SDH3

Complex III ubiquinol

cytochrom-c reductase

Complex IV cytochrom-c

oxydase Complex V ATP synthase

PMA1

PMA2

IPP1

PPA2

PPi ATP + H2O

ATP1 ATP2 ATP3

ATP4 ATP5 ATP6

ATP7 ATP8 OLI1

ATP14 ATP15 ATP16

ATP17 ATP18 ATP19

ATP20 TIM11

RIP1 COB

BI2 BI3

CYB2

COR1 QCR2

QCR6 QCR7

QCR8 QCR9 QCR10

MCR1

COX1 COX2 COX3

AI4 AI5

COX4

COX5A COX5B

COX6 COX7 COX8 COX9

COX10

COX12 COX13 COX11

COX15 COX17 CCP1

HFA1 CTP1

ILV3 HEM15

DLD3

LYS4

LYS12 LYS21

ERG11 ILV5 ODC2

PRX1 MIR1

GRX5 NCP1

TRX3

Other mitochondrial proteins

GRX2

TCA cycle

NADH

Succinate

Not detected

COQ5

395 – 5’000 copies per cell

5’000 – 100’000 copies per cell

100’000 – 1E6 copies per cell

no abundance data

COQ9 COQ4

CYT1

CYB5

CBR1 CYC1 CYC7

Gillet et al. (2012) Mol Cell Prot manuscript O111.016717

57 © 2015 AB Sciex

Recent SWATH publications

58 © 2015 AB Sciex

BosentanPhenol

Hydroxy

Hydroxy-Phenol

MS/MSALL with SWATH™ AcquisitionTIC after Mass Defect Filter

Filter applied to all SWATH Acquisition windows (no additional filter based on mass region of interest)

59 © 2015 AB Sciex

Recent SWATH publications

60 © 2015 AB Sciex

46 SWATH posters and orals @ ASMS 2014

A novel SWATH-MS platform for comprehensive characterization of epigenetic histone modifications

AP-SWATH dynamic interactome of DJ-1 under oxidative stress: Implications for

Parkinson's Disease

Integration of SWATH and MRM for biomarker discovery of esophageal

squamous cell carcinoma

Combining derivatization and SWATH for the integrated quantification and identification

of aldehydes and ketones in biological samples

Differential Mobility Separation (DMS) to improve spectral correlation in

SWATHTM acquisition.Direct Non-Targeted Protein

Identification from SWATH Data Using Database Search

Discovery of Glycoprotein Signatures for Aggressive Prostate

Cancer via SWATH MS

Evaluation of SWATHTM as a diagnostic tool for Bacterial Identification Using a

Strain's Specific Library

Expansion of ion library for mining SWATH data through fractionation

proteomics

Harnessing the power of SWATH-MS for unbiased identification of O-

GlcNacylated proteins

61 © 2015 AB Sciex

SWATH publications – Nature Methods

62 © 2015 AB Sciex

SWATH publications – Mol Sys Biol

63 © 2015 AB Sciex

SWATH publications – Mol Sys Biol

64 © 2015 AB Sciex

Recent forensic publications

65 © 2015 AB Sciex

SWATH publications - HHE

66 © 2015 AB Sciex

Recent SWATH publications - HHE

PCA analysis

67 © 2015 AB Sciex

Recent SWATH publications - HHE

Protein/peptide candidates

68 © 2015 AB Sciex

Protein Expression Profiling Example

CDC37 HSP90A HSP90B

69 © 2015 AB Sciex

S L Y A S Sp P G G V Y A T Ry6 y5 y4 y3y8 y7

b3 b4 b5

S L Y A S S P G G V Y A T Ry6 y5 y4 y3y8 y7

b3 b4 b5

y7 y6 y5 y4 y3

b3 b4

Common transitionsy8 y7 y6 y5 y4 y3

b3 b4

Common transitionsy8

SWATH [700-725] SWATH [750-775]

Detection of phospho-peptide from the naked peptide transitionsSWATH-MS specials: peptide modification analysis – Phospho-peptides

70 © 2015 AB Sciex

S L Y A S Sp P G G V Y A T Ry6 y5 y4 y3y8 y7

b3 b4 b5

y12 y11 y10 y9

b7 b9

S L Y A S S P G G V Y A T Ry6 y5 y4 y3y8 y7

b3 b4 b5

y12 y11 y10 y9

b7 b9

Differential transitions

y12 y11 y10 y9 y8

y7 y6 y5 y4 y3

b3 b4

Common transitionsy8 y7 y6 y5 y4 y3

b3 b4

Common transitionsy8

b7 b9

Differential transitions

y12 y11 y10 y9 y8 b7 b9

SWATH [700-725] SWATH [750-775]

SWATH [700-725] SWATH [750-775]

Detection of phospho-peptide from the naked peptide transitionsSWATH-MS specials: peptide modification analysis – Phospho-peptides

Using SWATH™ Acquisition for Characterization and Quantification of the Epigenetic Histone Modifications

Sahana MollahHUPO 2014

72 © 2015 AB Sciex

ARTKQTARKSTGGKAPRKQLATKAARKSAPATGGVKKPHR…

SGRGKGGKGLGKGGAKRHRKVLR…

Jenuwein and Allis. Science, 2001, 293, 1074.

SGRGKQGGKARAKAK…

H3

H4

H2A

H2BPEPSKSAPAPKKGSKKAITKAQKKDGK…

ING HP1 Pc Eaf3

Histone acetylation (ac)-Transcriptional activation

Histone methylation (me1, me2 and me3)-Transcriptional activation or silencing

MethylationAcetylationphosphorylation

Luger et al. Nature, 389, 251-260, 1997.

Brd

Histone Code Hypothesis

• Specific set of histone PTMs function as a binding platform for recruiting proteins leading to transcriptional activation or inactivation

73 © 2015 AB Sciex

MS for Studying Histone ModificationsQualitative and Quantitative

GKGGKGLGKGGAK[Ac]R• MS/MS provides detailed

characterization of peptide sequence and PTM location

• Quantitation of various forms using unlabeled or labeled strategies

• Challenging for histone PTM study due to multiple isoforms

• Isobaric and difficult to separate by LC

Endogenous

Heavy labeled

74 © 2015 AB Sciex

Defining the Ideal Method for Histone PTM Analysis

• High Specificity required to resolve isoforms‒ MS/MS based strategy to obtain PTM location information‒ Narrow isolation window to ensure for better specificity for each isoform

• Highly Quantitative‒ Work on LC/MS time scale for when isoforms cannot be resolved‒ High reproducibility

• Broad Dynamic range‒ Good relative quantitation even when different isoforms have very different

occupancy levels

• Highly Multiplexed‒ Within a histone preparation, multiple protein forms and many different

modifications of interest

MS based Strategy

75 © 2015 AB Sciex

Data Independent Acquisition

ØMS/MSALL

• A data-independent workflow enabled by TripleTOF® system technology that use a Q1 isolation window to step across a mass range, collecting high resolution MS/MS spectra for all detectable analytes in a complex sample, in a single run

• Use variable Q1 isolation window with smaller window especially for m/z dense regions for better specificity

MS/MSALL with SWATH™ Acquisition

76 © 2015 AB Sciex

Smaller Q1 Window for better Specificity

• Reduce number of precursors in a window for increased specificity of quantification

• Set Q1 isolation window to 6 Da for MS/MS analysis

- A large number of modifiedhistones are 14 Da apart

(1Me, 2Me, 3Me, Ac). Use a Q1 window smaller than the + 2 charge state of the delta mass (7 Da)

6

The other aspect of increasing specificity is using site specific fragment ions from full scan MS/MS Data

77 © 2015 AB Sciex

Improving Specificity for Histone Isoforms

• Due to presence of different modification patterns with similar masses, tighter windows can in some cases provide improved specificity, reduced noise and provide better peak group detection

Narrow Q1 Window thru Variable Window SWATH™ Acquisition

25 Da x 100 msec 6 Da x 20 msec

Histone H4 (4-17): -GKGGKGLGKGGAK[Ac]R

More Selective Q1 window

GK[1Me]GGKGLGKGGAK[AC]R

78 © 2015 AB Sciex

K(3Me)STGGKAPR

K(Ac)STGGKAPR

KSTGGK(Ac)APR

Improving Specificity for Histone Isoforms

• Isoforms of H3 peptide (9-17) KSTGGKAPR

• MS level shows the presence of multiple peaks for m/z 528.314 +/0.03amu

• XIC of unique MS/MS fragment pattern is used to differentiate the isoforms

Using MS/MS Fragments for Specific PTM Localization

MS Data

MS/MS Data

KSTGGK(3Me)APR

MS PeakXIC of m/z 528.314 + 0.03

XIC of differentiatingMS/MS fragments

79 © 2015 AB Sciex

Distinguish Co-Eluting Histone Isoforms

• Selection of the key fragment ions is critical for differentiation

• MS/MS provides resolution of two isobaric forms that cannot be chromatographically resolved

SWATH™ Acquisition Fragment Ions can Differentiate

MS PeakXIC of m/z 768.9465 + 0.025

XIC of differentiatingMS/MS fragments

GKGGK[Ac]GLGKGGAKR

GKGGKGLGK[Ac]GGAKR

GKGGKGLGKGGAK[Ac]R

Modified GKGGKGLGKGGAKR

80 © 2015 AB Sciex

Quantitation of H4 peptideAcetylated Isoforms of H4 peptide: GKGGKGLGKGGKAR

Sample Peptide

MS/MS modified/unmodified

ratio (y9 ion)

MS/MS modified/unmodified

ratio (y7 ion)

%CV of sum of MS/MS fragments (triplicate

analysis)

Human H9 cell RA untreated GK[1AC]GGKGLGKGGAKR <0.01 <0.01 22.9GKGGK[1AC]GLGKGGAKR 0.10 0.08 13.4GKGGKGLGK[1AC]GGAKR 0.06 0.03 12.6GKGGKGLGKGGAK[1AC]R 0.38 0.32 9.6

4.3Human H9 cell RA treated GK[1AC]GGKGLGKGGAKR <0.01 <0.01 10.4

GKGGK[1AC]GLGKGGAKR 0.03 0.03 5.6GKGGKGLGK[1AC]GGAKR 0.01 0.01 6.7GKGGKGLGKGGAK[1AC]R 0.50 0.42 3.0

mouse TS cell undiff GK[1AC]GGKGLGKGGAKR <0.01 <0.01 6.6GKGGK[1AC]GLGKGGAKR 0.07 0.07 7.2GKGGKGLGK[1AC]GGAKR 0.11 0.09 4.8GKGGKGLGKGGAK[1AC]R 0.26 0.22 4.4

mouse TS cell diff GK[1AC]GGKGLGKGGAKR <0.01 <0.01 10.8GKGGK[1AC]GLGKGGAKR 0.06 0.05 3.6GKGGKGLGK[1AC]GGAKR 0.09 0.07 5.2GKGGKGLGKGGAK[1Ac]R 0.23 0.18 5.7

• Absolute quantitation by one point calibration by spiking in heavy form of peptide

81 © 2015 AB Sciex

Highly Multiplexed

Sample Modified PeptideMS/MS modified/unmodified ratio (y7

ion) Histone H3 (9-17) K[3Me]STGGKAPR 0.09

K[1Ac]STGGKAPR 0.05KSTGGK[1Ac]APR 0.21

H9 cell RA treated K[1Me]STGGK[Ac]APR 0.42K[2Me]STGGK[Ac]APR 0.01K[3Me]STGGK[1Ac]APR 0.03K[1Ac]STGGK[1Ac]APR 0.02K[1Me]STGGKAPR 1.53K[2Me]STGGKAPR 0.01KSTGGKAPR

K[3Me]STGGKAPR 0.05K[1Ac]STGGKAPR 0.10KSTGGK[1Ac]APR 0.45

H9 cell RA untreated K[1Me]STGGK[Ac]APR 0.49K[2Me]STGGK[Ac]APR 0.01K[3Me]STGGK[1Ac]APR 0.01K[1Ac]STGGK[1Ac]APR 0.06K[1Me]STGGKAPR 0.96K[2Me]STGGKAPR 0.01KSTGGKAPR

82 © 2015 AB Sciex

Conclusions

• SWATH™ provides MS/MS information for unambiguous assignment of modification sites

• Retention time MS profiles coupled with fragment ion XICs can disambiguate the different forms

- complete separation of histone isoforms is less critical

• A highly quantitative method with %CV similar to MRM quantitation

83 © 2015 AB Sciex

Acknowledgements

• University of Pennsylvania ‒ Benjamin Garcia‒ Zuo-Fei Yuan‒ Kelly R. Karch‒ Natarajan Bhanu ‒ Shu Lin

• AB SCIEX‒ Lei Xiong‒ Eric Johansen‒ Christie Hunter

84 © 2015 AB Sciex

SWATH™ Acquisition for MetabolomicsQualitative and Quantitative Analysis of Metabolites

− Linking LC-MS/MS data to Metabolomics Library

screening

XIC Manager can implement any AB

SCIEX library, list of chemical formulas or outputs from METLIN

software for metabolite screening

85 © 2015 AB Sciex

Acylcarnitine QuantitationXIC Manager for Targeted Extraction of MS or MS/MS

Acylcarnitine C18C25H49NO4

MS/MS for confirmation

86 © 2015 AB Sciex

Variations on a theme…

� Abundant protein has many non-specific cleavages� likely dependent on sample prep

and variable between samples

� What should be used for normalization?

� Which peptide should be used for quantitation?CIFAEMFRRKPLFCGNSEADQLGKIFDLIGLPPEDDWPRDVSLPRGAFPPRGPRPVQSVVPEMEESGAQLLLEMLTFNPHKRISAFRALQHSYLHKDEGNPE

PPRGPRPVQSVVPEMEESGAQLLLEMLTFNPHK RGPRPVQSVVPEMEESGAQLLLEMLTFNPHK GPRPVQSVVPEMEESGAQLLLEMLTFNPHKR GPRPVQSVVPEMEESGAQLLLEMLTFNPHK GPRPVQSVVPEMEESGAQLLLEMLTFNPH PRPVQSVVPEMEESGAQLLLEMLTFNPHK RPVQSVVPEMEESGAQLLLEMLTFNPHK PVQSVVPEMEESGAQLLLEMLTFNPHKR PVQSVVPEMEESGAQLLLEMLTFNPHK PVQSVVPEMEESGAQLLLEMLTFNPH VQSVVPEMEESGAQLLLEMLTFNPHK SVVPEMEESGAQLLLEMLTFNPH SVVPEMEESGAQLLLEMLTFNPHK VVPEMEESGAQLLLEMLTFNPH VVPEMEESGAQLLLEMLTFNPHK PEMEESGAQLLLEMLTFNPHK EMEESGAQLLLEMLTFNPH EMEESGAQLLLEMLTFNPHK MEESGAQLLLEMLTFNPH MEESGAQLLLEMLTFNPHK EESGAQLLLEMLTFNPH EESGAQLLLEMLTFNPHK ESGAQLLLEMLTFNPH ESGAQLLLEMLTFNPHK SGAQLLLEMLTFNPHK SGAQLLLEMLTFNPH GAQLLLEMLTFNPHK GAQLLLEMLTFNPH AQLLLEMLTFNPHK LLLEMLTFNPHK LLLEMLTFNPH LLEMLTFNPH LEMLTFNPH SGAQLLLEML PVQSVVPEMEESGAQLLLEMLT GPRPVQSVVPEMEESGAQLLLEMLT PVQSVVPEMEESGAQLLLEML GPRPVQSVVPEMEESGAQLLLEML PVQSVVPEMEESGAQLLLEM GPRPVQSVVPEMEESGAQLLLEM PVQSVVPEMEESGAQLLLE GPRPVQSVVPEMEESGAQLLLE GPRPVQSVVPEMEESGAQLLL PVQSVVPEMEESGAQLLL GPRPVQSVVPEMEESGAQLL

IFAEMFR CIFAEMFRRKPLFCGNSEADQLGK AEMFRRKPLFCGNSEADQLGK RKPLFCGNSEADQLGK KPLFCGNSEADQLGK PLFCGNSEADQLGKIFDLIGLPPEDDWPR CGNSEADQLGKIFDLIGLPPEDDWPR GKIFDLIGLPPEDDWPR IFDLIGLPPEDDWPR IFDLIGLPPEDDWP IFDLIGLPPEDD IFDLIGLPPED IFDLIGLPP FDLIGLPPEDDWPR DLIGLPPEDDWPR LIGLPPEDDWPR IGLPPEDDWPR GLPPEDDWPR LPPEDDWPR PPEDDWPR

MATSRYEPVAEIGVGAYGTVYKARDPHSGHFVALKSVRVPNGGGGGGGLPISTVREVALLRRLEAFEHPNVVRLMDVCATSRTDREIKVTLVFEHVDQDLRTYLDK VPNGGGGGGGLPISTVR VPNGGGGGGGLPISTV PNGGGGGGGLPISTVR GGGGGGGLPISTVR

YEPVAEIGVGAYGTVYK DPHSGHFVALK YEPVAEIGVG YEPVAEIGVGAY EPVAEIGVGAYGTVYK PVAEIGVGAYGTVYK VAEIGVGAYGTVYK IGVGAYGTVYK

RLEAFEHPNVVR LEAFEHPNVVR EAFEHPNVVR AFEHPNVVR FEHPNVVR PNVVRLMDVCATSR TSRTDREIKVTLVFEHVDQDLR SRTDREIKVTLVFEHVDQDLR REIKVTLVFEHVDQDLR EIKVTLVFEHVDQDLR KVTLVFEHVDQDLR VTLVFEHVDQDLR VTLVFEHVDQD VTLVFEHVDQ VTLVFEHVD TLVFEHVDQDLR LVFEHVDQDLR VFEHVDQDLR FEHVDQDLR

APPPGLPAETIKDLMRQFLRGLDFLHANCIVHRDLKPENILVTSGGTVKLADFGLARIYSYQMALTPVVVTLWYRAPEVLLQSTYATPVDMWSVG APEVLLQSTYATPVDM APEVLLQSTYATPVD APEVLLQSTYATP APEVLLQSTYA APEVLLQSTY STYATPVDMWSVG

GLDFLHAN GLDFLHANCIVHR VHRDLKPENILVTSGGTVK RDLKPENILVTSGGTVK DLKPENILVTSGGTVK LKPENILVTSGGTVK KPENILVTSGGTVK PENILVTSGGTVK ENILVTSGGTVK ILVTSGGTVK

APPPGLPAETIK APPPGLPAETIKDLMR

IYSYQMAL IYSYQMALTPVVV IYSYQMALTPVVVT IYSYQMALTPVVVTLWYR YSYQMALTPVVVTLWYR SYQMALTPVVVTLWYR YQMALTPVVVTLWYR QMALTPVVVTLWYR MALTPVVVTLWYR MALTPVVVTLWYR ALTPVVVTLWYR LTPVVVTLWYR TPVVVTLWYR PVVVTLWYR VVVTLWYR ALTPVVVTLW ALTPVVVTL

LADFGLAR

� Select peptides for MRM analysis

� Monitor data for QC

87 © 2015 AB Sciex

SWATH Initiatives

88 © 2015 AB Sciex

Human Spectral LibraryLibraries: Public Domain

89 © 2015 AB Sciex

M. tuberculosis Spectral LibrarySRMAtlas

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Libraries: Public Domain

90 © 2015 AB Sciex

M. tuberculosis Spectral LibrarySRMAtlas

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Libraries: Public Domain

91 © 2015 AB Sciex

M. tuberculosis Spectral LibrarySRMAtlas

Libraries: Public Domain

http://www.srmatlas.org/mtb/swath.php

92 © 2015 AB Sciex

M. tuberculosis Spectral Library

� Covered additional proteins with synthetic peptides (MtbAtlas*)

� 38,482 unique proteotypic peptides

� 3,838 proteins ( 96% of the annotated proteome)

� Download library from SWATHAtlas website -http://www.srmatlas.org/mtb/swath.php

SRMAtlas

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Libraries: Public Domain

93 © 2015 AB Sciex

SRMAtlas

Libraries: from IDA experiments

94 © 2015 AB Sciex

Processing SWATH-MS/MS Data

Libraries: Theoretical

Appendix A: Text File Field Requirements and Descriptions The text file must be a tab-delimited .txt file containing all of the following fields. Field name

Description

Q1 Q1 m/z (precursor m/z) Q3 Q3 m/z (fragment m/z) RT_detected retention time isotype isotype type (for example, Heavy, Light, M00, M04,

M08). Default is Light. uniprot_id database accession number (regardless of the type

of database used, use “uniprot_id” as the field name)

relative_intensity fragment ion intensity stripped_sequence peptide sequences without modifications, for

example, DEYELLCLDGSR modification_sequence peptide sequences with modifications, for example,

DEYELLC[CAM]LDGS[Dhy]R prec_z peptide charge protein_name protein name frg_type fragment type (b or y ion) frg_z fragment charge frg_nr ion number (for example, y3 ion = 3)

95 © 2015 AB Sciex

Processing SWATH-MS/MS Data

Libraries: Theoretical

96 © 2015 AB Sciex

97 © 2015 AB Sciex

Processing SWATH-MS/MS Data� Same as MRMHR

– User tells software the mass of the parent ion, and the fragment ion– Software automatically extracts XIC from the appropriate SWATH scan

(i.e. the mass range containing the parent ion)

• MS/MS Library Purity Score • Mass Error• Isotopic Pattern• Retention Time

98 © 2015 AB Sciex

� Novel normalization scheme– compensates for differences; allows smaller changes to be detected

� Weighted statistics give fold change and confidence

Visualization

Proteins Peptides

Log fold change

2 sample comparison

Confidence

Each column compares 2 samples Each rectangle compares 2 samples

99 © 2015 AB Sciex

SWATH™ Acquisition 2.0

100 © 2015 AB Sciex

Variable Window SWATH™ Acquisition� Adjust Q1 selection window

maintain roughly constant number of peptides to maintain specificity

– Narrower window in m/z dense regions

– Optimal cycle time maintained by adjusting accumulation time

� Reduce number of precursors in window for increased specificity of quantification

� Data acquisition supported in Analyst® Software TF 1.7

101 © 2015 AB Sciex

Improving Specificity of Detection

� While many low level peptide detections are good, there are some that have interferences

� Tighter windows can in some cases provide improved specificity, reduced noise and provide better peak group detection

Variable Window SWATH™ Acquisition

Fixed windows - 24 Variable Windows - 40

16.0 16.5 17.0Time, min

0

300

16.30

15.5 16.0Time, min

0

300

Inte

nsity

, cps

GLNEEQGNVVSRMore Selective Q1 window

(25 Da)(11 Da)

102 © 2015 AB Sciex

Adjust Fragment Ions

� Automatic fragment ion selection is intensity driven

� Full scan data is present in SWATH™ Acquisition data, therefore different fragment ions can be chosen when required

� Using the Edit Transitions dialogue, select desired transitions

61.2 61.6 62.0 62.4Time, min

0

3000

600061.83

62.22

61.2 61.6 62.0 62.4Time, min

0

3000

600061.84

Inte

nsity

, cps

Inte

nsity

, cps

103 © 2015 AB Sciex

Digging deeper and Maintaining Quantitation Quality� More confident detections are found at

lower abundances with the more narrow Q1 windows– # of fragment ions from the 1% FDR

peptides plotted vs. their peak areas

� As depth of coverage increases, it is important to ensure this is not at the expense of quantitation quality

104 © 2015 AB Sciex

Leveraging Expanded Dynamic Range

� Key figures of merit:– 1% FDR cutoff = confident

detection– <20% CV quant quality cutoff

Higher Loads of yeast on TripleTOF® 6600 System

Increase Specificity

3 µg 120min VW_6022%3 µg 60min VW_60

1 µg 60min VW_60

31%

3 µg 120min VW_10020%

~22,100 peptides

~11,600 peptides

90% more peptide coverage Increase Signal

105 © 2015 AB Sciex

Highly Multiplexed Quantification with Variable Windows

SWATH™ Identification & Quantification Dashboard – 60 VW x 37msec

90% of peptides with <20% CV

2%30%

Low median CV’s across

intensity range

� E.coli lysate, 1 µg load, 60 min gradient, 75µm x 30cm cHiPLC® column

4 ordersdynamic range

106 © 2015 AB Sciex

107 © 2015 AB Sciex

Recent SWATH publications

108 © 2015 AB Sciex

SWATHTM vs label free MS1 quant in DDA‘’MRM like’ quality: improved specificity & sensitivity

MS1 traceClear interference

SWATH MS/MStrace

MS1 traceNot detected

SWATH MS/MStrace

Data courtesy of Ludovic Gillet ETH

109 © 2015 AB Sciex

Easy Building of Variable Window Methods

• Simple interface for automated acquisition method building1. Import text file for full control over acquisition windows2. Set MS and MS/MS parameters3. Automatically build variable window SWATH™ acquisition method

For Increased Specificity

Q1 Start Q1 Stop CES

1

2

3

Variable Window Calculator Tool

• Open TIC of target proteome and extract out a MS spectrum of the whole LC run

• Generate m/z vs intensity list to paste into Excel

• Set assay parameters and build method

• www.absciex.com\VariableWindowsCalculator‒ Includes E.coli histogram for getting started

Excel Sheet for Designing based on Constant Precursor Density

600 800 1000 1200 1400Mass/Charge, Da

0

15000

687.8690

577.2933

Inte

nsity

, cps

Averaged Averaged MS Spectrum

m/z vs. Intensity list

20 30 40Time, min

0

5e7

29.479

23.012

Inte

nsity

, cps

TOF MS TOF MS TIC

Computation Computation of Windows

111 © 2015 AB Sciex

Assessing Impact of Window Sizes

• Fixed window (400-1000m/z)‒ 24 windows - 25 Da x 90 msec‒ 30 windows - 20 Da x 70 msec‒ 40 windows - 15 Da x 54 msec

• Variable window (400-1250m/z)‒ 24 windows - VW x 90 msec‒ 30 windows - VW x 70 msec‒ 40 windows - VW x 54 msec‒ 60 windows - VW x 37 msec

• Replicate injections were performed with each method using E. colidigest

112 © 2015 AB Sciex

Improving Peptide Detection and Quantitation

• Filter peptides at 1% FDR then count peptides at 20% CV or better

• Decreasing window size (increased # of windows) provided more peptide detections at 1% FDR with high quality quantitation across replicates

• 35% gain at peptide level

• 21% gain at protein level

1% Peptide FDR

More Selective Q1 window

34% gain in peptides21% gain in proteins

113 © 2015 AB Sciex

Variable Window SWATH™ Acquisition

114 © 2015 AB Sciex

Variable Window SWATH™ Acquisition

115 © 2015 AB Sciex

Variable Window SWATH™ Acquisition

116 © 2015 AB Sciex

The Complexity of Systems Biology

metabolomicshormones

metabolismLesi

hman

ia

Amino acids

signaling

neurodegenerative disorders

cardiovascular

obesitymass spectrometryDMS

Receptor signaling

Mem

bran

e tr

affic

king

bioc

hem

istry

membrane protein receptor

lipidomics

epigenetics

inflammation

microRNAparasites

molecular biology

next-gen sequencingBa

cter

ial p

atho

gens

cancer

transcriptomics

DNAproteomics

tuberculosisProtein kinases

cytokines

Histones

Alzheimer’s disease

Prio

ns

SWATHOneOmics™

Leading to a systems-level understanding

117 © 2015 AB Sciex

OneOmics™ in the CloudNext-gen sequencing meets Next-gen proteomics

• Cloud computing‒ Simple and scalable‒ Universal access to data‒ Fast processing

• Next-gen proteomics‒ Quantify thousands of proteins‒ Excellent repeatability and quantitation‒ Data completeness >98%

• Next-gen sequencing‒ Fast and inexpensive‒ Highly accurate and repeatable‒ Comprehensive

118 © 2015 AB Sciex

The OneOmics™ Project

1

Omics integration

OMX @ SCXGenomics

TranscriptomicsNext-gen

sequencing (NGS)

Proteomics Next-gen proteomics (NGP)

SWATH® & immunoMRM

Lipidomics Next-gen lipidomics (NGL)

3

App Store innovation

2

Collaborate securely

Metabolomics

Next-gen metabolomics (NGM)

119 © 2015 AB Sciex

Illumina® BaseSpace®

• Web-based data management and analysis

• Eliminates need for onsite storage and computing power

• Tools for collaboration and sharing

• NEW Up to 50x faster than desktop processing of SWATH Proteomics

Omics? There are Apps for that.

120 © 2015 AB Sciex

AB SCIEX SWATH™ Proteomics Cloud Tool Kit

• Input: SWATH Acquisition data from TripleTOF® systems

• Processing: Extracts and integrates the peptide/protein peaks using an Ion Library

• Output: Generates peak area results files

Value – up to 30x faster processing

121 © 2015 AB Sciex

AB SCIEX SWATH™ Proteomics Cloud Tool Kit

• Input: Peak areas from Extractor

• Processing: Normalizes data and computes the differential protein expression levels between the samples. Annotated with important meta data.

• Output: Protein ratios between samples and confidence metrics.

Value – processing with study level considerations

122 © 2015 AB Sciex

AB SCIEX SWATH™ Proteomics Cloud Tool Kit

• Input: Peak areas from Extractor

• Processing: Normalizes data and computes the differential protein expression levels between the samples. Annotated with important meta data.

• Output: Protein ratios between samples and confidence metrics.

123 © 2015 AB Sciex

AB SCIEX SWATH™ Proteomics Cloud Tool Kit

• Input: Protein expression ratios and confidence metrics from Assembler

• Processing: Detailed review of protein expression data (protein/peptide level). Informative visualizations of protein differences between samples with biological annotation. Changes mapped at the protein and gene level, allowing modifications, splice variants, etc to be visualized.

• Output: Visualization plots, publication ready

Beta App

Value – high value figures reflecting biology

124 © 2015 AB Sciex

AB SCIEX SWATH™ Proteomics Cloud Tool Kit

• Input: Protein expression ratios and confidence metrics from Assembler

• Processing: Detailed review of protein expression data (protein/peptide level). Informative visualizations of protein differences between samples with biological annotation. Changes mapped at the protein and gene level, allowing modifications, splice variants, etc to be visualized.

• Output: Visualization plots, publication ready

Beta App

125 © 2015 AB Sciex

AB SCIEX SWATH™ Proteomics Cloud ToolkitProtein Expression Browser

126 © 2015 AB Sciex

AB SCIEX SWATH™ Proteomics Cloud Tool Kit

• Input: Protein expression ratios and confidence metrics from Assembler

• Processing: Detailed review of protein expression data. Informative visualizations of data reproducibility, data normalization and FDR analysis.

• Output: Visualization plots

Beta App

Value – results you can trust

127 © 2015 AB Sciex

From Genomics to Proteomics and Beyond

Gene Expression

SWATHIon library

ProteinPilotAB SCIEX

Protein Exp. AssemblerAB SCIEX

Protein Exp. ExtractorAB SCIEX

Protein Expression

Value – Serious Science!!

128 © 2015 AB Sciex

From Genomics to Proteomics and Beyond

Gene Expression

SWATHIon library

ProteinPilotAB SCIEX

Protein Exp. AssemblerAB SCIEX

Protein Exp. ExtractorAB SCIEX

Protein Expression

Combining Next Generation Proteomics and NGS through OneOmics™ to gain new insights into human spermatogenesis

[email protected]

130 © 2015 AB Sciex

Multi-Omics Analysis of Primary Cytotrophoblasts from Second Trimester and

Term Placentas

Katy Williams1, Christie L. Hunter2; Andrew Olson3

1University of California San Francisco, USA; 2SCIEX, USA; 3Advaita Biosciences, USA

For Research Use Only. Not for use in Diagnostic Procedures

131 © 2015 AB Sciex

For those wishing to keep their feet on the ground …

• Position desktop vs cloud? – 5 mins - ChristieSWATH™ Acquisition 2.0

Data Acquisition

Ion Library

XIC Generation

Profiling

Value – Industry Standard for DIA

132 © 2015 AB Sciex

For those wishing to keep their feet on the ground …

• Position desktop vs cloud? – 5 mins - ChristieSWATH™ Acquisition 2.0

Data Acquisition

Ion Library

XIC Generation

Profiling

133 © 2015 AB Sciex

SWATH Digital Recordrecord once - analyse for ever

134 © 2015 AB Sciex

Conclusions

• Pilot study for a combined workflow for Transcriptomics and Proteomics

• OneOmics™ in combination with iPathwayGuideprovided a seamless pipeline from data to biological answers‒ Fast data processing of SWATH® Acquisition -

Extractor‒ Study level quantitation with normalization and

fold change computation – Assembler‒ View protein expression changes and data

quality – Browser / Analytics‒ Determine biological significance –

iPathwayGuide

• BaseSpace cloud environment for secure collaboration

135 © 2015 AB Sciex

Conclusions

• designing OMICS experiments needs careful planning

• we can now describe samples in (nearly) complete details

• identification and quantitation can be done on one system

• speed @ sensitivity @ resolution will be the key

136 © 2015 AB Sciex

ThanksDanke

Merci

Hvala

Gracias

Grazie

Děkuji

Ačiu

Eucaristw

Dank

Tak

ありがとう

Tack

Obrigado

Спасибо

Tesekkurler

谢谢

감사 Kiitos

MulţumescKöszönöm

( شكریھ) بہت

Salamat po

תודה רבה

ขอบคุณБлагодаря!

Děkuij

дєкуюPaldies

Dziękuję

감사

cảm ơn

Tapadh leibh

Niżżik ħajr

متشکرم

Þakka þér

Гялайлаа ধন বাদ

Thank you for your attention

137 © 2015 AB Sciex

Thank you!

138 © 2015 AB Sciex

139 © 2015 AB Sciex

140 © 2015 AB Sciex

Questions ?

141 © 2015 AB Sciex

AB SCIEX MS/MSusers only

Thank you for listening !

Thank You

143 © 2015 AB Sciex

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