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Spring 2017 (BMSC-GA 4437)

Course Director

David Fenyo (
Kelly Ruggles (
Beatrix Ueberheide (

Course Times
Tuesday 5-7PM 
TRB 717

Course overview
This course will give an introduction of proteomics and mass spectrometry workflows, experimental design, and data analysis with a focus on algorithms for extracting information from experimental data. The following subjects will be covered in: (1) Protein identification (peptide sequencing, database searching, spectrum library searching, de novo sequencing, significance testing); (2) Protein characterization (protein grouping, top-down proteomics, post-translational modifications, protein processing and degradation, protein complexes); (3) Protein quantitation (metabolic labeling - SILAC, chemical labeling, label-free quantitation, spectrum counting, stoichiometry, biomarker discovery and verification). Examples will be provided throughout the course on how the different approaches can be applied to investigate biological systems. The class will be structured to include hands-on practical techniques for analyzing relevant proteomics datasets.

Learning objectives
At the conclusion of the course, the student will be able to:
Understand experimental design for mass spectrometry based proteomics;
Demonstrate detailed understanding of the possibilities and limitations of algorithms that are applied to proteomics data; and
Analyze a large proteomics data set using available algorithms.

Course Assessment
Readings and participation (30%): Students are required to attend class, to complete reading assignments and to participate in discussions and engage in healthy exchange of ideas. 
Project (70%): 

  • Choose a dataset from the Global Proteome Machine blog tagged as "Interesting Data"

  • Complete comprehensive peptide and protein identification and quantitation on this dataset (don't forget about quality control!)

  • Write up results as a paper including the methods used, analysis results, issues encountered and a comparison of your results with the associated publication.  Include all source code developed in the process. 

  • Deadlines: 

    • Tuesday March 7th 5-7PM: Project presentation part 1. Present the chosen data set and analysis plan (10 minutes)

    • Tuesday May 2nd 5-7PM: Project presentation part 2. Present final results (10 minutes)

    • Friday May 5th at 5PM: Final paper due (via email to

 General Policies
Late/missed work: You must adhere to the due dates for all required submissions. If you miss a deadline, then you will not get credit for that assignment/post.
Incompletes: No “Incompletes” will be assigned for this course unless we are at the very end of the course and you have an emergency.
Responding to Messages: We will check e-mails daily during the week, and respond to course related questions within 48 hours.
Announcements: We will make announcements throughout the semester by e-mail. 
Make sure that your email address is updated; otherwise you may miss important emails from me.
Safeguards: Always back up your work on a safe place (electronic file with a backup is recommended) and make a hard copy. Do not wait for the last minute to do your work. Allow time for deadlines.
Plagiarism: Plagiarism, the presentation of someone else's words or ideas as your own, is a serious offense and will not be tolerated in this class. The first time you plagiarize someone else's work, you will receive a zero for that assignment. The second time you plagiarize, you will fail the course with a notation of academic dishonesty on your official record.

Module 1. Overview of Proteomics and Mass Spectrometry

  • Lecturer: Fenyo

  • Tuesday January 24, 2017 5PM in TRB718

  • Tuesday January 31, 2017 5PM in TRB717

  • Reading: 

    • M.A. Gillette, S.A. Carr, "Quantitative analysis of peptides and proteins in biomedicine by targeted mass spectrometry", Nature Methods 10 (2013) 28–34.

    • A. Bensimon, A.J.R. Heck R. Aebersold, "Mass Spectrometry–Based Proteomics and Network Biology", Annual Review of Biochemistry 81 (2012) 379-405.

Module 2: Protein Identification Using Protein Databases

  • Lecturer: Fenyo

  • Tuesday February 7, 2017 5PM in TRB717

  • Tuesday February 14, 2017 5PM in TRB717

  • Reading: 

  • Lecture 1

    • Eriksson, J., Chait, B.T. & Fenyö, D. "A statistical basis for testing the significance of mass spectrometric protein identification results" Anal. Chem 72, 999-1005 (2000).

    • Fenyö, D. & Beavis, R.C. "A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes" Anal. Chem 75, 768-774 (2003).

    • Elias, J.E. & Gygi, S.P. "Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry" Nat. Methods 4, 207-214 (2007).

  • Lecture 2

    • Craig R, Cortens JP, Beavis RC, "Open source system for analyzing, validating, and storing protein identification data", J Proteome Res. 3 (2004) 1234-42

    • D. Fenyö, J. Eriksson, R. Beavis, "Mass spectrometric protein identification using the global proteome machine", Methods Mol Biol 673 (2010) 189-202.

    • CF Taylor, NW Paton, KS Lilley, P-A Binz, RK Julian Jr, AR Jones, W Zhu, R Apweiler, R Aebersold, EW Deutsch, MJ Dunn, AJR Heck, A Leitner, M Macht, M Mann, L Martens, TA Neubert, SD Patterson, P Ping, SL Seymour, P Souda, A Tsugita, J Vandekerckhove, TM Vondriska, JP Whitelegge, MR Wilkins, I Xenarios, JR Yates III, H Hermjakob, "The minimum information about a proteomics experiment (MIAPE)", Nat Biotechnol. 25 (2007) 887-93.

Module 3: Interpretation of Mass Spectra and de novo Sequencing

  • Lecturer: Ueberheide

  • Tuesday February 21, 2017 5PM in TRB717

  • Tuesday February 28, 2017 5PM in TRB717

  • Reading: 

  • Seidler J, Zinn N, Boehm ME, Lehmann WD, "De novo sequencing of peptides by MS/MS", Proteomics 10 (2010) 634-49.

  • Standing KG, "Peptide and protein de novo sequencing by mass spectrometry", Curr Opin Struct Biol. 13 (2003) 595-601.

Project 1 Presentations: Tuesday March 7, 2017 5PM in TRB717

Module 4: Protein Quantitation

  • Lecturer: Ruggles

  • Tuesday March 21, 2017 5PM in TRB717

  • Tuesday March 28, 2017 5PM in TRB717

  • Assignment: 

    • Due March 21:

    • General writeup of project (Project title, description of samples, search parameters and MS methods, search databases you plan to use)

    • Download search databases

    • Find search parameters/FDR used by authors

    • Download data

    • Due March 28:

  • Convert your data from RAW-> MGF and mzML files

  • Proteowizard

  • Lecture 1

    • Domon, B. & Aebersold, R. "Options and considerations when selecting a quantitative proteomics strategy", Nat. Biotechnol 28, 710-721 (2010).

    • Zhang, G. et al. "Protein quantitation using mass spectrometry" Methods Mol. Biol 673, 211-222 (2010).

  • Lecture 2

    • Shi T, Song E, Nie S, Rodland KD, Liu T, Qian WJ, Smith RD "Advances in targeted proteomics and applications to biomedical research", Proteomics 16, 2160-82 (2016)

    • Picotti P, Aebersold R "Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions", Nat Methods 9(6), 555-66 (2012)

Module 5: Proteogenomics and Molecular Markers

  • Lecturer Ruggles

  • Tuesday April 4, 2017 5PM in TRB717

  • Tuesday April 11, 2017 5PM in TRB717

  • Assignments

    • Due April 4, 2017

    • Please run at least one web-based X! Tandem run and send me a screen shot of your results

    • Make sure all of your files are uploaded to the cluster and all of your RAW files have been converted to MGF, mzXML, mzML etc

    • Set up X!Tandem run (input.xml and taxonomy.xml)

    • Try and run X!Tandem if you feel bold!  Otherwise we can go through everything during the next lecture. 

    • Due April 11, 2017

    • Run your X!Tandem on the cluster 

    • Read this paper (Elias JE and Gygi SP. Target-Decoy Search Strategy for Mass Spectrometry-Based Proteomics. Methods Mol Biol, 506:55-71 (2010)) and set up a Target Decoy Search for FDR calculations

    • Additional FDR paper: Aggarwal and Yadav. False Discovery Rate Estimation in Proteomics. Methods Mol Biol. 2016 1362:119

  • Lecture 1

    • Nesvizhskii AI "Proteogenomics: concepts, applications and computational strategies", Nat Methods 11(11), 1114-25 (2014)

    • Mertins et al. "Proteogenomics connects somatic mutations to signalling in breast cancer", Nature 534(7605):55-62 (2016)

Module 6:  Protein Characterization

  • Lecturer: Ueberheide

  • Tuesday April 18, 2017 5PM in TRB717

  • Tuesday April 25, 2017 5PM in TRB717

  • Lecture 1

    • Z Hakhverdyan, M Domanski, LE Hough, AA Oroskar, AR Oroskar, S Keegan, DJ Dilworth, KR Molloy, V Sherman, JD Aitchison, D Fenyö, BT Chait, TH Jensen, MP Rout, J LaCava, "Rapid, optimized interactomic screening", Nature Methods 2015

      • A Leitner, R Reischl, T Walzthoeni, F Herzog, S Bohn, F Förster, and R Aebersold, "Expanding the Chemical Cross-Linking Toolbox by the Use of Multiple Proteases and Enrichment by Size Exclusion Chromatography", Mol Cell Proteomics 11 (2012)

  • Lecture 2

    • Trost, M., Bridon, G., Desjardins, M. & Thibault, P. "Subcellular phosphoproteomics", Mass Spectrom. Rev. 29, 962-990 (2010)

Project 2 Presentations: Tuesday May 2, 2017 5PM in TRB718