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Biological Sciences Division Pacific Northwest National Laboratory

Studies of the yeast pheromone pathway using quantitative proteomics Episode IV: Phosphoproteomes. Biological Sciences Division Pacific Northwest National Laboratory. Initial goals of PNNL efforts.

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Biological Sciences Division Pacific Northwest National Laboratory

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  1. Studies of the yeast pheromone pathway using quantitative proteomics Episode IV: Phosphoproteomes Biological Sciences Division Pacific Northwest National Laboratory

  2. Initial goals of PNNL efforts • Identify phosphorylated species and quantify their changes in response to alpha factor treatment • Provide kinetic data for pathway modeling (e.g. time course studies)

  3. Identification of phosphorylated proteins by nanoLC-MS/MS of tryptic peptides [M+2H]2+=1031.6 [M+2H-98]2+= 98 =49 y8 y6 y9-H2O y10-H2O y7 y11 y5 b10 y13 y12 y4 400 600 800 1000 1200 1400 1600 1800 2000 m/z (K.FQS*EEQQQTEDELQDK.I)

  4. Challenges • Low abundance of pathway proteins - Ste5 ~500 molecules/cell and Fus3 ~20,000, molecules/cell vs. millions/cell for abundant proteins • Unknown number of pathway player modifications • Often low phosphorylation stoichiometry • Desire to make many quantitative measurements

  5. Focused analysis of affinity selected alpha pathway players and their complexes Tandem affinity purification (TAP) to expand results obtained from global view (identify other binding partners, verify and identify additional low level sites of modification, etc.) LC-MS

  6. To be continued……

  7. A first look via a seemingly strange path… Protein

  8. IMAC(Immobilized Metal ion Affinity Chromatography) Esterification of carboxylic groups O • To reduce interaction between COO and metal ion in IMAC enrichment - process aspartic acid (D) glutamic acid (E) C - terminus O H H O OH H H O N O N C C O N C C C O C H OR Fe3+ C H 2 P 2 C H O O C 2 O O C O O O OH2 + O O H + + C X H O H O C C 3 2 O H C X O 3 X : H or D

  9. Direct vs. IMAC enriched nanoLC-MS analyses K.FQS*EEQQQTEDELQDK.I 50.50 Before IMAC enrichment 28.83 22.35 33.70 62.87 42.56 57.13 20.17 41.08 Relative Abundance 29.16 K.FQS*EEQQQTEDELQDK.I After IMAC enrichment 61.97 39.27 50.60 74.59 36.65 27.90 0 10 20 30 40 50 60 70 80 90 100 Time (min)

  10. Yeast Strain: SUB592 • Obtained from Dan Finley’s lab (Harvard) (Peng et al., Nature Biotech vol. 21, 2003) • Endogenous ubiquitin genes knocked out • NH2-His-tagged ubiquitin gene supplied by plasmid • Cells grow and respond to alpha factor normally (in plate assay) Initial studies: Treat Yeast strain 592 with alpha factor, recover His-tagged proteins, greatly enrich phosphopeptides using IMAC, and identify peptides/proteins using nanoLC-MS/MS

  11. Proteins identified after dual His affinity purification and IMAC enrichment Untreated (757 total) Alpha treated (703 total) 384 373 330

  12. Alpha pathway phosphorylated proteins identified

  13. Use of Accurate Mass and Time (AMT) tags Shotgun peptide identification and generation of AMT tag look-up table High throughput analyses Proteins Proteins Digestion Digestion SCX LC fractionation Nano LC-FTICR MS ID using AMT tags nanoLC-MS/MS Peptides (or features) identified by their accurate masses and LC separation times, abundances determined Peptide identification Set of AMT tags providing a “look-up” table of peptides identified by their accurate masses and LC separation times

  14. The application of peptide AMT tags Single LC-FTICR analysis Locations of peptides identified from multiple “shotgun” LC-MS/MS analyses Peptides identified using AMT tags

  15. Treated Non-Treated IMAC IMAC 1:1 Label heavy Label light Monoisotopic mass Monoisotopic mass 4.05 Da 4.05 Da AR ~1 (Light ÷ Heavy) AR ~8 (Light ÷ Heavy) Scan number Scan number Quantitation using stable-isotope labeling with nanoLC-FTICR AMT tag approach • Ability to quantify modified peptides independent of unmodified species • Ability to accurately detect and quantify at low stoichiometric ratios IMAC selected phosphopeptides

  16. A path forward • Technology improvements for the masses: • - New metal free high resolution nanoLC system optimized for phosphoproteomics • - Improved characterization of modifications (using ECD/ETD, intact protein “top-down” approaches) • - Much higher throughput e.g. for time course studies and “fishing with an adjustable net” • Deliniation of phosphorylation sites, and abundances, for all known alpha pathway players (in progress) • Characterization of other modifications and other possible (fringe?) players • Studies of selected perturbations, time courses, etc……

  17. Acknowledgements Robert Maxwell Orna Resnekov Kirsten Benjamin David Pincus Roger Brent PNNL Proteomics Team David Camp Mary Lipton Joshua Adkins Sample processing and automation Eric Livesay Kim Hixson Heather Mottaz Carrie Goddard Marina Gritsenko Therese Clauss Dave Prior Data processing, software development and statistics Gordon Anderson Matt Monroe Mary Powers Dave Clark Angela Norbeck Nikola Tolic Gary Kiebel Eric Strittmater Ken Auberry Sam Purvine Kerry Steele Steve Callister Deep Jaitly Niksa Blonder Separations Yufeng Shen Kostas Petritis Rui Zhao David Simpson Alex Shvartsburg Quanzhou Luo Mass spectrometry Ljiljana Pasa-Tolic Keqi Tang Harold Udseth Anil Shukla Tom Metz Tao Liu Ron Moore David Anderson Aleksey Tolmachev Rui Zhang Fumin Li Jon Jacobs Charley Langley Feng Yang Jason Page Weijun Qian Hyak Kang

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