MS Proteomics Toolbox:

Multiproteomic Approachesto Decipher Cellular Signaling

Anna Malovannaya

Mass Spectrometry Proteomics CoreBaylor College of Medicine, Houston, TX

April 18, 2017

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Info

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Mass Spectrometry - Biomedical and Before

Proteomics

Metabolomics

Nucleic Acids (niche)

1900s and on1980s on

2000s

Inorganic/Organic Chemistry

�

Mass Spectrometry is the Ultimate Proteomics Tool

- most common tool for protein and PTM identification and quantification- can identify and quantify up to 10,000 proteins per day

Bottom-Up

proteins peptides peaks & spectradigest uHPLC

MS

(1)

Top-Down whole protein/domain, all sequential modification(2)

Native non-covalent protein interactions/complexes(3)

HDX-MS structure inferred from deuterium incorporation rates(4)

infer identities and quantities

today only this

The Astronomical Challenge: “The Meteor”

abundanceproteins cannot be amplified

r2=0.87

0 1 2 3 4 5 6 7 8 9

01

23

45

67

89

log10 expression

“housekeeping”

many peptidesover-sampledgood spectra

good quantificationlittle change

107-109 dynamic range

“regulatory”

fewer peptidesunder-sampledworse spectra

worse quantificationchange a lot:

kinasesTFs

coregulatorsubiquitin ligases

Proteomics (that works) =

My coregulator is 0.00001% of proteome…

~ 3% of it is activated by phosphorylation…

Can I detect it?

Can I measure it’s “activity”?

Can I identify the activating phosphosite?

What proteins does it work with?

Do those change upon activation?

mass spectrometry

enrichment

separation(fractionation)

(size)(physical properties)

affinity(antibody)

(physical properties)

+ biochemistry

Applications of Bottom-Up Proteomics in Biology

(1) Proteomic Profiling: “protein-seq”up to 10,000 proteins per day6,500-7,500 proteins in ½ day from ~5µg of tissue

(2) Post-Translational Modification (PTM) Profiling:targeting a class of PTMs, e.g. phospho-profiling10,000-20,000 sites per experiment

(3) Broad Affinities:targeting a whole class of interesting proteins300 DNA-bound transcription factors per sample300 inhibitor-bound kinases per sample

(4) Protein Interactions (AP/MS):targeting a specific protein

none

a lot

spec

ific

affin

ity /

enric

hmen

tcore SOP

core SOP

Applications: Proteome Profiling

- catalog all proteins present in a tissue or cell- quantify state-dependent changes in protein expression

(e.g. differentiation, disease state, drug treatment or stimulus)

Mouse Brain Proteome Atlas

Dr. Sung Yun JungDr. Jong-Min Choi

Dr. Huda Zoghbi’s LabDr. Jun Qin’s Lab

Jung SY, Choi JM, … , Zoghbi HY, Qin J. An Anatomically Resolved Mouse Brain Proteome Reveals Parkinson Disease-Relevant Pathways.

MCP 2017 Apr;16(4):581-593. PMID:28153913

1 mm3 punch5µg of tissue sequenced

< ½ day per sample~6,500 gene products>12,000 in all regions

Applications: 365 Proteome Profiling

Jung SY, Choi JM, et. al. An Anatomically Resolved Mouse Brain Proteome Reveals Parkinson Disease-Relevant Pathways.

MCP 2017 Apr;16(4):581-593. PMID:28153913

offlinereverse phase separation at pH10

online (uHPLC coupled to MS)reverse phase separation at pH2

Applications: 365 Proteome Profiling

Jung SY, Choi JM, et. al. An Anatomically Resolved Mouse Brain Proteome Reveals Parkinson Disease-Relevant Pathways.

MCP 2017 Apr;16(4):581-593. PMID:28153913

Applications: Post-Translational Modification (PTM) Profiling

digested lysate

GG

P Ac

MeP

GG

P

Ac

Me

P

Ac

MS

P Ac P

PP

phosphoproteome

antibody: pTyrSCX

IMAC; TiO2

AcMe Ac

P Ac

acetylome

antibody: Kac

MS

GG

GG

ubiquitome

antibody: diG

MS

Applications: Protein Interactions

multi-protein complexes for proteins of interest (targeted)state-dependent dynamic changes in protein-protein interactionscomplexome (HT large scale studies: yeast, drosophila, human)

immunoprecipitation(no epitope tagging)

IgG

Protein ABeads

2

1

CA

RM

1

HM

G20

B

IgG HC

IgG LC

22012080605040302015

M TRIP

4

CTB

P1H

DA

C1

HD

AC

2H

DA

C3

CR

EBB

PEP

300

MED

12M

ED28

PRM

T1R

BM

14

SRA

P1

Malovannaya A, Lanz RB, Jung SY, … O'Malley BW, Qin J.Analysis of the human endogenous coregulator complexome.

Cell 2011; PMID: 21620140also IP/MS methodology in PNAS 2010; PMID: 20133760

Bert O’Malley and Jun Qin Labs

antibodies1,796 experiments3,290identifications (redundant)315,245gene products (non-redundant)11,485protein-protein associations~400,000

# of spectratarget

Top 12 Experiments

POLR2BPOLR2A

POLR2GPOLR2J

2L2D

2ERNA Pol II

coregulator:MEDIATOR

Malovannaya A, Lanz RB, Jung SY, … O'Malley BW, Qin J.Analysis of the human endogenous coregulator complexome.

Cell 2011; PMID: 21620140also IP/MS methodology in PNAS 2010; PMID: 20133760

Applications: Protein Interactions

what’s the magic?

Basic Principle:

MS measures ionsmasses and charges

mz

mass spectrometer measures mass/charge ratio

spectrum: m/z on x-axis, intensity (how much) on y-axis

mp/f+miso+mmodi-mnl+mzzm

z=

Sample Prep - Protein to Peptide: Example of IP/MS

IgG

IgG

STEP1: immunoprecipitation (IP)

STEP2: SDS-PAGE

STEP3: digest

Endopeptidase Cleavage Site

Trypsin after K/R

Endoproteinase Lys-c after K

Endoproteinase Asp-N before D

Endoproteinase Arg-C after R

Chymotrypsin after F/W/Y/L

Pepsin after F/W/Y/L

Thermolysin before L/I/M/F/W

*

MAAFGILSYEHR PLK R PR LGPPDVYPQDPKQK EDELTALNVK QGFNNQPAVSGDEHGSAK NVSFNPAK ISSNFSSIIAEK LR CNTLPDTGR…

LALQLDGVSSHSSHVISAQSTSTLPTTPAPQPPTSSTPSTPFSDLLMCPQHR ...

tryptic peptides:

too small for ID

too big for some analyzers

1324.67

L-G-P-P-D-V-Y-P-Q-D-P-KH+

H+

b-ions y-ionsMS2: fragments

MS2-Based Sequencing

m/z200 350 500 650 800 950

1

2

abun

danc

e

b3+

b8+

y9+

y10+2

ms1 m/z =(m+2)/2663.40

MS1 : peptide

- 578.50L-G P-P-D-V-Y-P-Q-D-P-K H+

H+b2 y10+2

268.16 1058.51L-G-P P-D-V-Y-P-Q-D-P-KH+

H+b3+1 y9+1

839.43 487.25L-G-P-P-D-V-Y-P Q-D-P-KH+

H+b8+1 y4+1

Actual Spectrum of LGPPDVYPQDPK

PTMs in Mass Spec: MASS SHIFT

>> PTM changes mass of amino acid, but identification logic is the same

965.2

993.2(K+28)

SNPYYIVKQGK

SNPYYIVK(di-Me)QGK

SNPYYIVK(di-Me)+

SNPYYIVK+

Peptide Peaks?

Quantification

3 Dimensions of MS Data

m/z

RT

inte

nsity

RT

RT

inte

nsity

inte

nsity

total ion LC

mz 588.5 LC

m/z

inte

nsity

MS1 spectrum at 14.5 min

m/z

inte

nsity

MS1 spectrum at 27.0 min

Label-free: Quantitative and Semi-quantitative Quantification

AUC = area under the curvemuch larger dynamic range than SPCs

RT, min33.0 33.5 34.0 34.5 35.0

MS2 at 33.50

MS2 at 34.08

PSMs = spectral counts, semi-quantitative

for protein level: add up peptide levels(may need to normalize for protein size)(could also normalize for total amount)

AUC(mono)

1st iso

2st iso

Label-free: Quantitative and Semi-quantitative Quantification

Scientific Example:

Differential Interactomesof Estrogen Receptor Mutants

Leah Gates, Charles Foulds (also for slides)

Bert O’Malley LabJun Qin Lab

Proteomics Core

ERα Mutations in Metastatic Breast Cancer: Resistance to Treatment

Fusions: complete resistance

Ma CX et al. Nat Rev Cancer. 2015 Spoerke JM et al. Nat Comm 2016; Fribbens C et al. J Clin. Oncol. 2016

Mutants:partial resistance to drugs

need new drugs for these

Rel

ativ

e Li

ght U

nits

(RLU

)

ERE-Luc Reporter Assay in HeLa cells (E2-deprived)

0

100000

200000

300000

400000

500000

600000

ERα Mutant Proteins Drive Ligand-Independent ERE-Driven Transcription

ERα(N-term)

FLAG

FLAG

-WT

FLAG

-Y53

7S

FLAG

-ESR

-YAP

1

b-actin

Short exp.

Long exp.

WT ERα 1 595AF1 DBD Hinge AF2

Y537S ERα 1 595AF1 DBD Hinge AF2

Y537S

D538G ERα 1 595AF1 DBD Hinge AF2

D538G

What Coregulators Are Bound to LBD ERα Mutantson EREs as Compared to WT ERα?

3651

504AF1 DBD Hinge WW TAD

230

PDZ bindingSH3 bindingESR1-YAP1

recombinant proteins - Ping Yi

What Coregulators Are Bound to LBD ERα Mutantson EREs as Compared to WT ERα?

beads

PCR; bead binding

+

pUC57-4xERE

beadsERE1 ERE2 ERE4…

Y537S

beadsERE1 ERE2 ERE4…

beadsERE1 ERE2 ERE4…

D538G

ESR1-YAP1

+

analyze by MSand WB

nuclear extract (NE)

Foulds, C.E. et al. Mol Cell 2013Gates, L.A. will be submitted today

Y537S ERα Preferentially Recruits NCOAs andthe KMT2D (MLL4) H3K4 Methyltransferase Complex

ERα

NCOAs

MLL4

26S Proteasome Is Enriched with ERα-YAP1

ERα-YAP1

NCOAs

proteasome

“Take-Home” Messages:

Suggestions for inhibits ERα mutant cancer cell growth:

For LBD mutants: combo with SRC SMI may be “best”For ESR1-YAP1: proteasome inhibitor (may confer a “double-punch”)

ERE

Y537S D538G

ERE ERE

ESR1-YAP1

KMT2D HMT

complexKMT2D

GCN5HAT complex

GCN5

26S Proteasome

20S

19SSRC-1SRC-2 SRC-3

Multiproteomics with Broad Affinities:

Systems Biology of Pathway Discovery

Mei Leng, Alex Saltzman, Bhoomi BhattMalovannaya Lab

Andrew Rice Lab (HIV collaborators)

Applications of Bottom-Up Proteomics in Biology

(1) Proteomic Profiling: “protein-seq”up to 10,000 proteins per day6,500-7,500 proteins in ½ day from ~5µg of tissue

(2) Post-Translational Modification (PTM) Profiling:targeting a class of PTMs, e.g. phospho-profiling10,000-20,000 sites per experiment

(3) Broad Affinities:targeting a whole class of interesting proteins300 DNA-bound transcription factors per sample300 inhibitor-bound kinases per sample

(4) Protein Interactions (AP/MS):targeting a specific protein

none

a lot

spec

ific

affin

ity /

enric

hmen

tcore SOP

core SOP

catTFRE: unbiased DNA-binding activity profiling

1 reagent : catTFRE : 100 JASPAR motifs, in 2x tandem

Drs. Chen Ding & Doug ChanDr. Jun Qin Lab

Ding C, Chan DW, … , Qin J. Proteome-wide profiling of activated transcription factors with a concatenated tandem array

of transcription factor response elements.PNAS 2013 Apr 23;110(17):6771-6, PMID: 23553833

catTFRE: unbiased DNA-binding activity profiling

catTFRE DNA pull-down

beadsRE1 RE2 RE100…

TF1 TF2TF2 TF2 TF3

+ nuclear extract (NE)

TF1 TF2

TF2 TF3 TF5

beadsRE1 RE2 RE100…

beads

PCR; bead binding

+ pUC57-catTFRE

MS : ~2,000 proteins, enriched DBTFs and Coregulators

DNA-binding activity ≠ transcriptional activity

does not tell you where they are localized on genome

standalone higher binding could reflect either level OR “activity”

HIV Latency – issue of host transcriptional regulation

HIV Virus Particle image from http://viralzone.expasy.org/all_by_species/5182.html

naïve CD4+T cell

activatedresting

latent CD4+T cell

Multiple matched-sample proteomics:

- Proteome Profiling

- 3 DNA Pull-down Affinities

(1) catTFRE

(2) HIV genome

(3) HIV promoter (5’LTR)

rest

ing

CD

4+T

cells

(from

1 d

onor

)

activ

ated

rest

ing

+ PM

A/io

nom

ycin

4 bio-repeats 2 states 1 WCE profiling 3 DNA pull-downs

WCE

x x ( + )

same DPDs as above

com

pare

TF

TF

TF

TFWCE

compare

beads

TF TF

beadsLTR nef…

TF TF

gag pol

beadsRE1 RE2 RE100…

TF TF TF TF TFcatTFRE

HIV1

5’LTRD

NA

pull-

dow

ns

LTR

TF

Multiproteomic Atlas of CD4+T and HIV Activation

- from one 50 ml blood pack, purified resting CD4+Ts

20ug final lysate for WCE; 500ug lysate for each DPD

Overall enrichment is DNA pull-down specific

WCE

catTFRE

5’LTR

HIV1

TF TC KI UB PM

DPDs

- individual distribution is also not the same – reflects activity

donor #2

donor #1

RESTINGr2=0.87

donor #2

donor #1

ACTIVATEDr2=0.87

activated

resting

DONOR #1r2=0.71

WCE

donor #2

donor #1

RESTINGr2=0.82

donor #2

donor #1

ACTIVATEDr2=0.78

activated

resting

DONOR #1r2=0.65

catTFRE

Molecular response is stronger than donor variation

there are more changes overall in the matched resting/activated cellsthan between two donors in the same state

Did we discover anything new?

- filtered by PubMed abstract mining for HIV1 terms (count of PMIDs)

about 1/2 of candidates don’t have any HIV publicationseven less latency related

- genes with <5 publications on HIV1 were then prioritized

- performing validation with siRNA KDs and ChIPs

WCE

catTFRE5LTRHIV-1

8767

362134523351

total

558

495412395

totalTF

632

1249485

up

56

443532

upTF

266

775938

down

18

201814

downTF

NFKB1RELASTAT1

STAT5AAHR

BATF3NFIL3TBX21UBN2

WCE TFRE-

#1donors #2

+ - +PMA

#1 #2

KLF2BACH2KANSL3

ATF6ZNF398ZNF454ZBED2ZNF444

acro

ss a

ll D

PDs

spec

ific

5LTR- +

#1 #2

HIV1- +

#1 #2

DNA pull-downs

Expression and activity-driven changes are distinct

* not driven by expression***

*

****

*

*** expression driven*********

******

***

Imagine Regulatory Multi(prote)omics

P

PP

P

PP

P

cytoplasm

nucleus

transcriptionPOLR2B

POLR2A

POLR2CPOLR2G

POLR2J2L2D

2I

2EPOLR2HPol

II

MEDIATOR

chromatin TF

ERCC6/PGBD3

CHD4

CHD3

MTA1 MTA2

GATAD2A

MTA3

MBD2 MBD3

GATAD2B HDAC1

HDAC2

RBBP4

RBBP7CDK2AP1/2

membrane

RTK

kinase

P

activate !proteome profiling

kinome profiling

phosphoproteome

TF profiling

+

+

+

protein complex+

RNA-seq+

Acknowledgements

Funding and Support

Present:Alkek Center for Molecular Discovery at BCMVerna and Marrs McLean Foundation at BCMNIH P30 CA125123 DLDCCC Proteomics CoreCPRIT RP170005 CPRIT Proteomics CoreNIH U24 CA210954 PGDAC, CPTAC ConsortiumNIH U01 (pending) PTRC, CPTAC ConsortiumNIH U01 MH105026 IDG Consortium

Past:

NIH P30 AI036211 CFAR Developmental Award PINIH U19 DK62434 NURSA ConsortiumNIH T32 HD007165NIH R01 HD08188, DK059820, CA84199, M080703

Collaborators on HIV ProjectDr. Andrew Rice + Lab

Collaborators and ColleaguesDr. Jun Qin, Dr. Yi Wang + LabsDr. Bert O’Malley + LabDr. Charles Foulds + LabDr. Rainer LanzDr. Matthew Ellis + LabDr. Doug ChanDr. Beom-Jun Kim

Proteomics CoreDr. Sung Yun JungDr. Jong Min ChoiAntrix JainHamssika Chandrasekaran

LabDr. Mei LengAlexander SaltzmanBhoomi Bhatt