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Mass spectrometry and proteomics

Mass spectrometry and proteomics. Mass spectrometry and proteomics. Eva Dimitrova and Jessica Connor. Genomics. DNA (Gene). Transcription. Transcriptomics. RNA. Translation. Functional Genomics. PROTEIN. Proteomics. Enzymatic reaction. METABOLITE. Metabolomics.

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Mass spectrometry and proteomics

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  1. Mass spectrometry and proteomics Mass spectrometry and proteomics Eva Dimitrova and Jessica Connor

  2. Genomics DNA (Gene) Transcription Transcriptomics RNA Translation Functional Genomics PROTEIN Proteomics Enzymatic reaction METABOLITE Metabolomics The “omics” nomenclature…

  3. Proteomics definition “Proteomics is a science that focuses on the study of proteins : their roles, their structures, their localization, their interactions, and other factors.” www.lexicon-biology.com

  4. 3 Kinds of Proteomics • Functional Proteomics The identification of protein functions, activities or interactions at a global or organismwide scale • Expressional Proteomics The analysis of global or organismwide changes in protein expression • Structural Proteomics The high throughput, or high volume expression and structure determination of proteins by Xray, NMR or computerbased methods

  5. Components of Expressional Proteomics Protein Separation Mass Spectroscopy Bioinformatics

  6. Pathway Step 1: Sample prep Step 2: Separation Step 3: Mass spectrometry

  7. Movie

  8. General overview Aebersold, R & Mann, M. (2003, March). Mass spectrometry based proteomics. Nature. 422, 198-207

  9. Sample preparation

  10. Sample preparation Sample preparation involves everything that lies between the sample and 1st dimension of the 2D SDS gel • Cells and cell cultures – multiply • Homogenation and protein isolation • Contaminant removal/ cleanup • Fractionation

  11. Cleanup and fractionation • General Purpose Cleanup • Improve Resolution • Improve Reproducibility • Fractionation • Reduce Complexity • Improve Range of Detection • Enrich low-abundance proteins www.expressionproteomics.com

  12. Separation

  13. 2D-SDS PAGE gel The first dimension (separation by isoelectric focusing) - gel with an immobilised pH gradient - electric current causes charged proteins to move until it reaches the isoelectric point The second dimension (separation by mass) -pH gel strip is loaded onto a SDS gel -SDS denatures the protein (to make movement solely dependent on mass, not shape) and eliminates charge. Can Resolve: ~1500-2500 proteins

  14. Staining Technology • Staining • Silver • Coomassie blue • Fluorescent dyes • Sypro Ruby-$$$ • Radioisotopic labeling

  15. Trypsin digestion Trypsin • Serine protease • Claves at the carboxyl end of lysine and arginine (except when either is followed by proline)

  16. Mass Spectrometry

  17. Ionization method MALDI Electrospray (Proteins must be charged and dry) Mass analyzer MALDI-TOF Quadrapole MALDI-QqTOF AA seq and MW QqTOF AA seq and protein modif. How does a mass spectrometer work? Create ions Separate ions Detect ions • Mass spectrum • Database analysis

  18. Definitions ESI- Electron Spray Ionization is a technique used in mass spectrometry to produce ions. It is especially useful in producing ions from macromolecules because it overcomes the propensity of these molecules to fragment when ionized MALDI- Matrix-assisted laser desorption/ionization is a soft ionization technique used in mass spectrometry, allowing the analysis of biomolecules and large organic molecules, which tend to be fragile and fragment when ionized by more conventional ionization methods.

  19. Mass analyser • TOF – time of flight • Ion trap • Quadropole • Fourier transform ion cyclotron

  20. Mass Spec Principles Sample + _ Detector Ionizer Mass Analyzer

  21. Typical Mass Spectrum Relative Abundance aspirin m/z ratio: Molecular weight divided by the charge on this protein 120 m/z-for singly charged ion this is the mass

  22. ESI and MALDI Aebersold, R & Mann, M. (2003, March). Mass spectrometry based proteomics. Nature. 422, 198-207

  23. Peptide sample

  24. Stable isotope protein labeling Aebersold, R & Mann, M. (2003, March). Mass spectrometry based proteomics. Nature. 422, 198-207

  25. Artificially trypsinated Fragmented using trypsin Artificial spectra built Spot removed from gel Peptide Mass Identification Spectrum of fragments generated MATCH Library Database of sequences (i.e. SwissProt)

  26. How MS sequencing works • Peptide mass and database matching • Further f ragmentation of the peptides occur in a predictable fashion, mainly at the peptide bonds • The resulting daughter ions have masses that are consistent with KNOWN molecular weights of di-peptides, tri-peptides, tetra-peptides… Ser-Glu-Leu-Ile-Arg-Trp Collision Cell Ser-Glu-Leu-Ile-Arg Ser-Glu-Leu-Ile Ser-Glu-Leu Etc…

  27. Peptide sample

  28. Peptide Hits

  29. Data Analysis Limitations -You are dependent on well annotated genome databases -Data is noisy. The spectra are not always perfect. Often requires manual determination. -Database searches only give scores. So if you have a false positive, you will have to manually validate them

  30. Proteomics Applications

  31. Why Proteomics? • Proteins are the active biological agents in cells • DNA sequences don’t show how proteins function or how biological processes occur • Proteins undergo post transcriptional modifications • 3D structures affect protein function • Alternative splicing

  32. The Human Proteome Initiative. (2007) http://ca.expasy.org/sprot/hpi/hpi_desc.html Retrieved March 24, 2009.

  33. Challenges • Analyses of complex mixtures are not comprehensive • Difficult to prepare a pure sample • Protein expression is very sensitive to environmental conditions • Difficult to use ion currents to determine peptide abundance

  34. Protein Profiling • Generate large scale proteome maps • Annotate and correct genomic sequences • Analyze protein expression as a function of cellular state

  35. Analysis of Plasmodium falciparum(malaria parasite)proteome Figure 1: Proteins identified in each stage are plotted as a function of their broad functional classification. To avoid redundancy, only one class was assigned per protein. Florens, L. et al. (2002) A proteomic view of the Plasmodium falciparum life cycle. Nature. 419, 520-526.

  36. Analysis of Myconcogene proteome Fig. 3. Summary of functionally related expression changes in Myc(+) cells. The proteins reduced or induced in Myc(+) cells are shown in green or red, respectively. The numbers denote fold expression change. The arrows denote activation and the blocked lines denote inhibition. Shiio, Y. et al. (2002) Quantitative proteomic analysis of Myc oncoprotein function. EMBO J. 21, 5088–5096.

  37. Protein Interactions • When analyzing a new protein, first question to ask is – to what proteins does it bind? • Method: Use new protein as an affinity agent to isolate its binding partners • Will not detect low affinity, transient, or cellular environment specific interactions

  38. Protein Interaction Experiments • Steps 1. Bait presentation using endogenous proteins 2. Affinity purification of complex 3. Analysis of bound proteins

  39. Studies of Large Protein Complexes • Spliceosome in yeast and human cells • Nuclear pore complex in yeast • Nucleolus in human cells • Largest organelle mapped • Found over 400 nucleolar proteins • Still not complete

  40. Analyzing Protein Modifications • Finding all modifications on a single protein • Identified by examining the measured mass and fragmentation spectra • Proteome wide scanning of modifications • Not complete

  41. Additional Challenges • Experimental design • Large amounts of data, absence of hypotheses • Must take advantage of statistical methods • Data collection • High throughput collection • High quality data • Data analysis, visualization, and storage • Data Publication

  42. Future Directions • Influence on clinical diagnostics and therapy • Analysis of whole proteins • Tissue imaging • Using mass tags for high throughput protein identification

  43. Other Applications of Mass Spectrometry • Isotope dating and tracking • Trace gas analysis • Mapping the location of individual atoms • Pharmacokinetics • Space exploration • Respiratory gas analysis

  44. Conclusion Proteomics is extremely valuable for understanding biological processes and advancing the field of systems biology. “The ultimate goal of systems biology is the integration of data from these observations into models that might, eventually, represent and simulate the physiology of the cell.”

  45. Proteomics Websites

  46. Uniprot http://www.uniprot.org/

  47. Interprohttp://www.ebi.ac.uk/interpro/

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