Proteomics Informatics (BMSC-GA 4437) Instructor David Fenyö Contact information

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Presentation transcript:

Proteomics Informatics (BMSC-GA 4437) Instructor David Fenyö Contact information

Proteomics Informatics – Learning Objectives Be able analyze a proteomics data set and understand the limitations of the results.

Proteomics Informatics – Overview of Proteomics (Week 1) Why proteomics? Bioinformatics Overview of the course

Motivating Example: Protein Regulation Geiger et al., “Proteomic changes resulting from gene copy number variations in cancer cells”, PLoS Genet Sep 2;6(9). pii: e

Motivating Example: Protein Complexes Alber et al., Nature 2007

Motivating Example: Signaling Choudhary & Mann, Nature Reviews Molecular Cell Biology 2010

Bioinformatics Biological System Samples Measurements Experimental Design Raw Data Information Data Analysis

Mass Spectrometry Based Proteomics Mass spectrometry Lysis Fractionation MS Digestion Identified and Quantified Proteins Peak Finding Charge determination De-isotoping Integrating Peaks Searching

Proteomics Informatics – Overview of Mass spectrometry (Week 2) Ion Source Mass Analyzer Detector mass/charge intensity

Mass Analyzer 1 Frag- mentation DetectorIon Source Mass Analyzer 2 b y Proteomics Informatics – Overview of Mass spectrometry (Week 2)

Proteomics Informatics – Overview of Mass spectrometry (Week 2) Mass Analyzer 1 Frag- mentation Detector intensity mass/charge Ion Source Mass Analyzer 2 LC intensity mass/charge intensity mass/charge intensity mass/charge intensity mass/charge intensity mass/charge Time intensity mass/charge intensity mass/charge intensity mass/charge intensity mass/charge intensity mass/charge intensity mass/charge intensity mass/charge intensity mass/charge intensity mass/charge

Proteomics Informatics – Analysis of mass spectra: signal processing, peak finding, and isotope clusters (Week 3) m/z Intensity

Proteomics Informatics – Protein identification I: searching protein sequence collections and significance testing (Week 4)

Proteomics Informatics – Protein identification II: search engines and protein sequence databases (Week 5)

Proteomics Informatics – Protein identification III: de novo sequencing (Week 6) m/z % Relative Abundance [M+2H] Mass Differences Amino acid masses Sequences consistent with spectrum

Proteomics Informatics – Protein identification IV: spectrum library searching (Week 7) Lysis Fractionation Digestion LC-MS/MS MS/MS Spectrum Library Pick Spectrum Compare, Score, Test Significance Repeat for all spectra Identified Proteins

Proteomics Informatics – Protein quantitation I: metabolic labeling (SILAC), chemical labeling, label-free quantitation, spectrum counting (Week 8)

Proteomics Informatics – Protein quantitation I: metabolic labeling (SILAC), chemical labeling, label-free quantitation, spectrum counting (Week 8)

Proteomics Informatics – Protein quantitation II: software (Week 9) Skyline MaxQuant

Proteomics Informatics – Protein characterization I: post-translational modifications (Week 10) Peptide with two possible modification sites MS/MS spectrum m/z Intensity Matching Which assignment does the data support? 1, 1 or 2, or 1 and 2?

Proteomics Informatics – Protein Characterization II: protein-protein interactions, cross-linking, top-down, non-covalent complexes (Week 11) A B A C D Protein identification

Proteomics Informatics – Molecular Signatures (Week 12)

Proteomics Informatics – Molecular Signatures (Week 12)

Proteomics Informatics – Presentations of projects (Week 13) Select a published data set that has been made public and reanalyze it. Highlighted data sets: 10 min presentations

Proteomics Informatics (BMSC-GA 4437) Instructor David Fenyö Contact information