Laboratory of Computational Proteomics
Proteomics Informatics Spring 2019
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Center for Health Informatics and Bioinformatics
 
High Performance Computing Facility
NYU Langone Medical Center
NIH
NCI
NIGMS
NIST
Proteomics Informatics Spring 2019 (BMSC-GA 4437)

Lecturers:
David Fenyö (David@FenyoLab.org), Professor
Beatrix Ueberheide (Beatrix.Ueberheide@nyumc.org), Assistant Professor

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 mass fingerprinting, tandem mass spectrometry, database searching, spectrum library searching, de novo sequencing, significance testing); (2) Protein char¬acterization (protein coverage, 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. Each student is required to lead at least one reading from the assigned weekly readings. This discussion lead will be graded.
    • Assignments (30%): Programming assignment will be given at the end of each class, and the solutions to these assignments should be e-mailed to Assignments@FenyoLab.org within a week.
    • Final project (40%)
    Missed Exams and Grade Appeals

    Make-up examinations (for final only) will be given under special circumstances. Documentation will be required to verify a student’s claim. If a make-up exam is permitted, a different exam will be written for that student and may have a different format than the regular examination.

    The assignments must be turned in on time and no late assignments will be accepted.

    If there is a time that you believe that there is a mistake in grading of an assignment/exam, you will have a chance to appeal your exam grade within a week after you receive your grade. If you think this is the case, you must write a note describing the error, attach it to the original exam, and give it to me within a week of the return of your exam. I will review your argument and my initial grading, and then return your exam with a decision to you in a timely manner.

    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. Try to avoid last minute submissions.
    • 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: I will check e-mails daily during the week, and I will respond to course related questions within 48 hours.
    • Announcements: I 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.



    Lecture 1 Introduction: Proteomics (February 4, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Fenyo

    Reading List

  • A. Bensimon, A.J.R. Heck R. Aebersold, "Mass Spectrometry–Based Proteomics and Network Biology", Annual Review of Biochemistry 81 (2012) 379-405.
  • Lundberg E, Borner GHH. Spatial proteomics: a powerful discovery tool for cell biology. Nat Rev Mol Cell Biol. 2019


    Lecture 2 Introduction: Mass spectrometry (February 11, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Fenyo

    Reading List
  • Roman A. Zubarev & Alexander Makarov, Orbitrap Mass Spectrometry, Anal. Chem. 2013, 85, 5288?5296.
  • J.D. Chapman, D.R. Goodlett, C.D. Masselon, Multiplexed and data-independent tandem mass spectrometry for global proteome profiling, Mass Spec Rev 33: 452–470, 2014.


    Lecture 3 Protein identification (February 25, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Fenyo

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

    Additional Reading
  • GPMDB Tutorials


    Lecture 4 Interpretation of mass spectra & denovo sequencing I (March 4, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Ueberheide

    Reading List
  • 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.


    Lecture 5 Interpretation of mass spectra & denovo sequencing II (March 11, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Ueberheide


    Lecture 6 Protein quantitation I (March 18, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Fenyo

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


    Lecture 7 Protein characterization: post-translational modifications (March 25, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Ueberheide

    Reading List
  • Protein characterization I: PTMs
  • Trost, M., Bridon, G., Desjardins, M. & Thibault, P. "Subcellular phosphoproteomics", Mass Spectrom. Rev. 29, 962-990 (2010).


    Lecture 8 Protein quantitation II: targeted and data-independent acquisition (April 1, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Fenyo

    Reading List
  • 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. Maiolica, M.A. Jünger, I. Ezkurdi, R. Aebersold, "Targeted proteome investigation via selected reaction monitoring mass spectrometry", Journal of Proteomics 75 (2012) 3495-3513.

    Additional Reading
  • Pino LK et al., The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics. Mass Spectrom Rev. 2017
  • D.R. Mani, S.E. Abbatiello, S.A. Carr, "Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics", BMC Bioinformatics 13 (2012) S9.


    Lecture 9 Proteogenomics (April 8, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Fenyo

    Reading List
  • Proteogenomics
  • Ruggles KV, Krug K, Wang X, Clauser KR, Wang J, Payne SH, Fenyö D, Zhang B, Mani DR. Methods, Tools and Current Perspectives in Proteogenomics. Mol Cell Proteomics 2017


    Lecture 10 Proteomics Tools for Characterizing Macromolecular Assemblies (April 15, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Chait

    Reading List
  • B.T. Chait, M. Cadene, P.D. Olinares, M.P. Rout, Y. Shi. “Revealing Higher Order Protein Structure Using Mass Spectrometry”, J Am Soc Mass Spectrom. 27 (2016) 952-965


    Lecture 11 Metabolomics (April 22, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Jones


    Lecture 12 Protein characterization: protein interactions (May 6, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: TBD

    Reading List
  • Protein characterization II: protein interactions
  • 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 13 Molecular Markers (May 13, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)
    Lecturer: Fenyo

    Reading List
  • Molecular Markers
  • DF Ransohoff, "Bias as a threat to the validity of cancer molecular-marker research", Nat Rev Cancer 5 (2005) 142-9.


    Lecture 14 Project Presentations (May 20, 2018 Science Building 435 E 30th Street, 9th Floor, Room 920 5:30pm)