Introduction to Proteomics 1.0



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Introduction to Proteomics 1.0 CMSP Workshop Tim Griffin Associate Professor, BMBB Faculty Director, CMSP

Objectives Why are we here? For participants: Learn basics of MS-based proteomics Learn what s necessary for success using MS-based proteomics Designing experiments; sample preparation; data analysis For CMSP staff: Prepare users so they are equipped to have success working with CMSP Manage expectations what can these technologies do and not do

Alien language made understandable CMSP Participants

Terminology made sensible Stage-tip Ion trap b-ion MS/MS itraq TOF NanoLC HCD quadrupole Precursor ion monoisotopic MALDI ESI Right??? on! Participants CMSP

Who we are Center for Mass Spectrometry and Proteomics Operated through the Department of Biochemistry, Molecular Biology and Biophysics Serving biological MS-related research needs across UofM campus and external institutions/private companies Fee-for-service Internal Service Organization (ISO) Supported by all Colleges at UofM using CMSP and Office of Vice President for Research (plus variety of granting sources) Extensive collaboration with Minnesota Supercomputing Institute Primary mission to support research efforts at the University of Minnesota, but also train others in the use of advanced technologies and research approaches

Who we are 150+ collective years of experience in biological MS; hundreds of scientific publications Diverse expertise design, sample preparation, instrumentation, data analysis Experience with MANY sample types and research studies Fish.gophers.periodontal bacteria snake venom

Omic technologies and the molecular biology paradigm

Why proteomics and direct protein analysis? (Genomic sequencing is cheaper, faster, more comprehensive why proteomics?) DNA/RNA characterization cannot predict post-transcriptional events

Proteomics: A definition Proteomics includes not only the identification and quantification of proteins, but also the determination of their localization, modifications, interactions, activities, and, ultimately, their function. -Stan Fields in Science, 2001. Alternatively: proteomics = high-throughput biochemistry

Proteomics as a complement to genomics measurement of protein response, which is not always indicated by mrna response post-translational modifications macromolecular interactions sub-cellular location high-resolution structural and molecular characterization integration with genomic/transcriptomic data to comprehensively characterize biological systems

Proteomic technologies and approaches two-dimensional gel electrophoresis mass spectrometry protein chips yeast 2-hybrid phage display antibody engineering high-throughput protein expression high-throughput X-ray crystallography cell imaging

Enabling MS-based proteomics: soft ionization Making large, non-volatile biomolecules fly Electrospray ionization (ESI) Matrix-assisted laser desorption/ionization (MALDI)

Nuts and bolts of mass spectrometry + - - ionization + - + - + MALDI Electrospray: liquid chromatography nanospray separation by m/z* + + quadrupole ion trap time-of-flight *m/z = mass-to-charge detection mass analysis of proteins, peptides

Many instruments, same underlying process Image from : http://www.medwow.com Image from: https://www.sdstate.edu/chem/mass-spec Image from: http://planetorbitrap.com Image from: http://planetorbitrap.com

Example of technology progress: more sensitive MS Image from ASMS 2014 workshop (Speaker: Haas)

The information currency of MS Relative Abundance 200 400 600 800 1000 1200 m/z

The guts of a mass spectrometer m/z separation and detection m/z separation m/z separation and detection ionization

Doing protein and proteomic analysis via MS Biological inquiry Hypothesis Experimental design Sample preparation MS analysis Data analysis Workshop structured to follow this ordering All aspects are important: each must be done well for success Challenge: technologies within each component always changing interdisciplinary

The importance of sample preparation Garbage in, garbage out Protein mixtures isolated from biological sources are complex (hundreds to thousands of components) Mass spectrometers have limited peak capacities requiring separation and fractionation of protein and peptide mixtures prior to analysis Separation methods include: gels liquid chromatography affinity chromatography immunochromatography selective enrichment by covalent chemistry

Protein chemistry: a challenge Proteins offer unique challenges compared to other biomolecules (e.g. nucleic acids): Solubility Abundance (no PCR!) Chemical heterogeneity Each protein is a unique character!

The workhorse: LC-MS Separating molecular mixtures prior to introduction into MS base peak intensity organic concentration in mobile phase time

Some example applications: from simple to complex The simple : identifying a gel separated protein 2D gel electrophoresis: the original proteomics technology but how to ID proteins? Gygi, et. al. 1999, Molecular and Cellular Biology 19:1720

Even the simple still requires care.. Process of identifying a gel-separated protein In-gel digestion Gygi, et. al. 1999, Molecular and Cellular Biology 19:1720 Peptide purification LC-MS/MS Sequence Database Searching

A bit more complicated: Identifying PTMs on a protein Phosphorylation Glycosylation Oxidations Acetylation Methylation Lipid anchors Ubiquitinylation/sumoylation etc BUT.PTM analysis is not necessarily routine or easy!! (abundance, enrichment, ionization, fragmentation.)

Still more complicated: identification of proteins in complex mixtures More complicated sample preparation (fractionation)

A bit more complicated: Quantitative proteomics S. cerevisiae cell cycle (compliments of J.A. Huberman) Protein abundance is dynamic in response to environmental, genetic, biochemical, pathological perturbations.

Quantitative proteomics: many methods available Labeled versus un-labeled

Systems biology: integrating omics data

Dealing with the data: the rate-limiting step? Data acquisition Raw data processing (Database searching) Analysis of processed data (Statistical filtering, quantitative analysis) Data organization and interpretation Archiving and databasing

Workflow for protein identification

Bioinformatic interpretation and hypothesis generation KEGG pathways

Thank you Good luck May all your ions fly well!