Accelerated Protein Signaling Signatures:

Highly Multiplexed Assays to Monitor Perturbations of Serine/Threonine Phosphosignaling

Jacob D. Jaffe 1 , Michael MacCoss 2

1 Broad Institute, Proteomics Platform, Cambridge MA 2 Department of Genetics, University of Washington, Seattle WA

Phospho-signaling q Gene Expression • q is large (hopefully) • Phospho-signaling is inaccessible through expression profiling • Phospho-signaling can be acute or sustained

Phosphoproteomics: current developments Phosphosite.org database (CST) Non-redundant sites: 97,222 Non-redundant proteins: 13,384 94,031 Sites curated from literature: Sites using site-specific (SS) methods: Sites using only discovery mode MS (MS) methods: Sites using both SS and MS methods: 10,006 86,378 4,773

• There are a lot of phosphosites! ( > # genes) • How can we study these systematically?

Interrogation of extant CMAP Data

PO 4

• No DNA/RNA involved • Kinases and phosphatases are the key regulators • Therefore, perturbagens that modulate kinase/phosphatase expression or activity should have effects on phosphosignaling

ATP-competitive kinase inhibitors staurosporine:MCF7 sanguinarine:MCF7 sanguinarine:HL60 PPAR agonists TK inhibitors tyrphostin AG 1478:MCF7 tyrphostin AG 825:MCF7 gefitinib:HL60 imatinib:MCF7 imatinib:PC3

Perturbations

cardiovascular agents digitoxigenin:HL60 digitoxigenin:MCF7 digitoxigenin:PC3 digoxigenin:HL60 digoxigenin:MCF7 digoxin:HL60 digoxin:MCF7 helveticoside:HL60 helveticoside:MCF7 helveticoside:PC3 lanatoside C:HL60 lanatoside C:MCF7 HDAC Inhibitors trichostatin A:PC3 trichostatin A:MCF7 valproic acid:MCF7 valproic acid:HL60 valproic acid:PC3 valproic acid:ssMCF7 valproic acid:SKMEL5

Step 1: Discovery and learning

‘Light’ Cells ‘Medium’ Cells Control Tx Tx 1 Digest Fractionate 2.8x ↑ 2.4x ↓ ‘Heavy’ Cells Tx 2 Mix Phosphopeptide Enrichment Mass Spectrometry • Cells are colored by isotopic labels (i.e., 13 C, 15 N, but not radioactive) • Generic technology enriches all phosphopeptides • However, most phosphosites are Ser or Thr and NOT Tyr • Ser/Thr phosphorylation is low hanging fruit • Mass Spec provides both identification AND quantification

We propose to do for phosphosignaling what the Broad LINCS group has done for gene expression

A.

Cell Lines/Conditions

B.

3 2 5 4 1 0 -1 -2 -3 -4 -5 Example Coherent Cluster Cluster avg.

C.

Select Representative Member(s) Expert Criteria

Conditions

FNHM(pS)QQGPR LLWIDA(pT)AGGNK ...

• Natural synergy between projects • Exploit existing robust methods

Step 2: Equivalent of L1000 – the “P100”

• • • • • Assay time Use synthetic peptide internal standards for better quantification and proof of ID LOD/LOQ /copies per cell

When you want to guarantee you measure it each and every time!

Next-gen instruments will make this even more selective

May enable us to skip phosphopeptide enrichment altogether

What should we see?

Protein Copy #/cell

1,000 1,000 1,000 10,000 10,000 10,000 100,000 100,000 100,000

Phosphorylation Stoichiometry

1% 10% 50% 1% 10% 50% 1% 10% 50%

# cells req to see phospho (250 amol)

1.51E+07 1.51E+06

3.01E+05

1.51E+06

1.51E+05 3.01E+04 1.51E+05 1.51E+04 3.01E+03 # cells req to see protein (250 amol)

1.51E+05 1.51E+05

1.51E+05 1.51E+04 1.51E+04 1.51E+04 1.51E+03 1.51E+03 1.51E+03

• Assays will be constructed such that we will always monitor the phospho- and non phospho-states of the site as well as a different peptide to serve a surrogate for total protein levels.

End result

• ~100-plex phosphosite MRM-MS assay – – 60-90 minutes/sample $100-200/sample • Reduced representation suitable for signature generation • Requirements compatible will low cell numbers or tissue samples • Absolute stoichiometry on every site, every time

Step 3: Standardize and Disseminate

LINCS Repository LINCS Member Labs

• • Standard software platform (MacCoss Lab, U. Wash.) Cross-laboratory reproducibility

Other public databases

Call for nominations!

• Perturbations – – – Exploit extant CMAP data Look for kinase and phosphatase modulators Can be small molecule, shRNA, or “other” • Systems – Relevant cell lines / disease models – Should cover “signaling space” • Cancer signaling • Immune Signaling • Cell cycle

Acknowledgements

• LINCS Program and Program Officers – U01 CA164186-01/Jaffe • MacCoss Lab, Univ. of Washington – Brendan MacLean • Broad Institute Proteomics Platform – Philipp Mertins – Steve Carr • Broad Institute LINCS Centers – – Todd Golub Aravind Subramanian