Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Introduction to Proteomics Phil Charles CCMP Overview of Talk • Overview of proteomics as a concept • Techniques discussion • 2D Gels and experimental design paradigms • Proteomics mass spectrometry • Identification • Quantitation Proteomics is the study of the overall state of an organism’s temporal protein composition The biological state of the proteome is encoded in • The relative abundance of currently expressed proteins (and their isoform) • Their localisation relative to cellular (or extracellular) structures • Their interaction partner molecules and substrates • Their current post-translational modification state • Their folded structures • … A Different View on Life Genome Transcriptome Proteome Phenotype • Different levels of biological complexity • More layers of regulation and control • Increased heterogeneity of samples Why consider Proteomics? • Orthogonal verification of gene activity. • Observe biological state after more levels of regulation and control – closer to phenotypic outcome. • Observe proteomes of extracellular locations – blood plasma/serum, urine etc. Proteomics • • • • Classical biochemistry Two-dimensional gels (2DGE) Mass spectrometry Computational analysis Methods in Proteomics • Separation – Gels – Immunochemistry – Chromatography • Identification – Immunochemistry – Mass spectrometry • Quantitation – All of the above Identification vs Quantitation • • • • What’s there? How much of it is there? How sure are you about the ID? How sure are you about the abundance? Not there versus not detectable 2DGE • Separate proteins by isoelectric point, then by mass • Visualise with silver staining or coomassie • Use CyDyes to label samples so they can be run together on the same gel Appl Microbiol Biotechnol. 2007 October; 76(6): 1223–1243. Quantitation Experimental Paradigm Labelling • Label samples in such a way as to not affect subsequent processing but allow differentiation in final analysis. Examples: – Fluorescent dyes (2DGE) – SILAC amino acid labels (MS) – Isobaric mass tags (MS/ MS) • Process multiple samples simultaneously, differentiate only in final analysis on basis of label. – Avoid some proportion of technical variance – Best to worst (for avoiding technical variance): • Labelling in vivo • Labelling protein mixture • Labelling peptide digestion mixture Aline Chrétien, Edouard Delaive, Marc Dieu, Catherine Demazy, Noëlle Ninane, Martine Raes, Olivier Toussaint Upregulation of annexin A2 in H2O2-induced premature senescence as evidenced by 2DDIGE proteome analysis Experimental Gerontology, Volume 43, Issue 4, April 2008, Pages 353–359 Quantitation Experimental Paradigm – Normalising to standard • Combine each sample (labelled with one label) with a representative standard (labelled with another label). • Perform analysis • For each protein in each run, normalise observed abundance in labelled sample to observed abundance in labelled standard. Normalised Abundance Normalised Abundance Statistical Analysis Normalised Abundance Mass Spectrometry • Mass Spectrometry is a technique for the detection and resolution of a sample of ions by their mass-to-charge ratio represented by m/z where m is the mass in Daltons and z is the charge. ’ Proteomic Mass Spectrometry • Classical biochemistry techniques and 2DGE are, in general, ‘topdown proteomics’ – identify and quantify whole proteins. • Most modern proteomic MS is ‘bottom-up’ Shotgun/’bottom-up’ proteomics LNDLEEALQQAKEDLAR NKLNDLEEALQQAK NVQDAIADAEQR SKEEAEALYHSK SLVGLGGTK TAAENDFVTLK TAAENDFVTLKK TSQNSELNNMQDLVEDYK TSQNSELNNMQDLVEDYKK VDLLNQEIEFLK YEELQVTVGR YLDGLTAER ADLEMQIESLTEELAYLK ADLEMQIESLTEELAYLKK AETECQNTEYQQLLDIK LNDL EEAL QQAC EDLA R N KLND LEEAL QQAK Proteins Separation Digestion Peptides Separation SDS-PAGE SCX Antibody-based High pH RP LC approaches Low pH RP LC Analysis MS-MS/ Tandem MS Peptide IDs + Quantitation IPI:IPI00000073.2 IPI:IPI00217963.3 IPI:IPI00031065.1 IPI:IPI00376379.4 IPI:IPI00397801.4 IPI:IPI00009950.1 IPI:IPI00395488.2 IPI:IPI00295414.7 IPI:IPI00554711.3 IPI:IPI00009867.3 IPI:IPI00019449.1 IPI:IPI00016915.1 IPI:IPI00060800.5 IPI:IPI00013885.1 IPI:IPI00221224.6 Observed Proteins + Quantitation Mass Spectrum m/z Tandem Mass Spectrum MS/MS spectrum Mass Analyser + Detector Intensity Sample Mass Analyser + Detector Intensity Tandem Mass Spectrometry m/z Identification by MS/MS m/z ? Intensity • Search fragment spectrum against a database of protein sequences. For each sequence, digest into peptides, generate an expected fragment ion spectrum, and match to observed spectrum Intensity Mass Analyser + Detector m/z IITHPNFNGNTLDNDIMLIK Identification by MS/MS • There are multiple commonly used MS/MS fragment spectra search engines, including: – – – – – – – Mascot Sequest OMSSA X!Tandem MS Amanda Andromeda ProteinPilot A brief overview of Mass Spectrometric quantitation Please feel free to stop me and ask questions! Mass Spectrum m/z Tandem Mass Spectrum MS/MS spectrum Mass Analyser + Detector Intensity Sample Mass Analyser + Detector Intensity Tandem Mass Spectrometry m/z Select Peptide Ions Fragmentation Low pH Reverse Phase LC ‘Survey Scan’/ ‘MS1’/ ‘MS Scan’ CID Also ETD, PQD,HCD ‘Fragment Ions Scan’/ ‘MS2’/ ‘MS/MS Scan’ Data-Dependent Acquisition (DDA) time Intensity Retention Time m/z Intensity Intensity Retention Time m/z m/z Peptide Isotopomer Distribution This is all 1 peptide Intensity Think of it as a frequency distribution based on a probability function. The relative intensity of each peak is the relative chance of a single peptide molecule having that m/z m/z 1/charge (z) Intensity Intensity Retention Time m/z m/z Intensity Intensity Intensity m/z Retention Time m/z IITHPNFNGNTLDNDIMLIK m/z Quantitation Labelling Strategies • MS-based strategies – In-vivo labelling (compare peak pairs) • SILAC, 15N, 18O, 2H • MS/MS-based strategies – Isobaric Tags • iTRAQ, TMT Intensity Intensity Intensity m/z Retention Time m/z m/z Intensity Intensity Intensity m/z Retention Time m/z m/z Isobaric Tag Labels e.g. iTRAQ, TMT Intensity Intensity Intensity m/z Retention Time m/z IITHPNFNGNTLDNDIMLIK m/z Intensity Intensity Intensity m/z Retention Time m/z m/z Intensity Retention Time m/z MS quantitation - peak pair comparison Intensity Retention Time m/z Intensity Retention Time m/z Intensity Retention Time m/z Intensity Retention Time m/z Identification vs Quantitation • • • • What’s there? How much of it is there? How sure are you about the ID? How sure are you about the abundance? Not there versus not detectable Quantitation Software • • • • • MaxQuant Progenesis LC-MS ABI Peaks Thermo ProteomeDiscoverer + bespoke and specific tools The Oxford Central Proteomics Facility • CCMP/CPF – Kessler Lab – WTCHG • CPF - Ben Thomas – Dunn School • Computational Biology Research group WIMM Thank you for your attention Please feel free to ask questions