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DAH3.4 Protein interactions, sub – cellular locations and arrays Kathryn Lilley Cambridge Centre for Proteomics Department of Biochemistry University of.

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Presentation on theme: "DAH3.4 Protein interactions, sub – cellular locations and arrays Kathryn Lilley Cambridge Centre for Proteomics Department of Biochemistry University of."— Presentation transcript:

1 DAH3.4 Protein interactions, sub – cellular locations and arrays Kathryn Lilley Cambridge Centre for Proteomics Department of Biochemistry University of Cambridge k.s.lilley@bioc.cam.ac.uk www.bio.cam.ac.uk/proteomics/ Part III Systems Biology

2 Outline Protein-protein interactions Protein sub-cellular location Protein Arrays Limitations of proteomics and systems biology

3 Types of protein analysis Proteins presentPPISCLFunction Mass Spectrometry Western blotting GFP tagging Immuno- histochemistry Enzyme assay Arrays Abundance Quantitative Mass Spec Western blotting GFP tagging Immuno- histochemistry Enzyme assay Arrays Isoform status Mass Spectrometry Western blotting Functional arrays Y2H Tagging + Mass Spectrometry Western blotting Structural studies Protein Arrays Biophysical assays (e.g.ITC, AUC) Mass Spectrometry GFP tagging Immuno- histochemistry Enzyme assay Functional arrays Enzyme assay Genetic approaches

4 Protein-Protein Interactions PPI Y2H Tagging + Mass Spectrometry Western blotting Structural studies Protein Arrays Biophysical assays (e.g.ITC, AUC) Identification of protein binding partners

5 Methods to determine PPI Y2H (yeast two hybrid) Tagging + Mass Spectrometry Western blotting Structural studies Protein Arrays Biophysical assays (analytical ultracentrifugation)

6 Y2H BD AD Gal4 transcription factor has two domains Lac Z gene BD AD Lac z protein (can easily assayed using x-gal) BD AD Bait Prey If BD and AD are expressed separately, no transcription If BD and AD are expressed as fusion proteins with proteins that interact that are brought close together structurally and can bring about transcription of LacZ mRNA UAS

7 Two-hybrid screen for protein partners Bait and prey libraries expressed in yeast Bait and prey can come from any organisms but must be fused to yeast AD and BD Only any good for binary interactions Very high false discovery rate

8 Protein Complex Purification Methods mostly based around fusion of bait protein and selective purification of complex by immunoprecipitation Methods can be ‘dirty’

9 Pull-down Wash Elute Two potential problems: All single step purifications – many extraneous protein co-purified. Tagged proteins often over expressed. Tag bait protein and pull it and its preys out of a mixture Tag could be avidin (binds to Biotin) hexa histidine (binds to Ni-NTA) flag (small peptide epitope for which and antibody is available)

10 Tandem Affinity Purification Tagging PROTEINSPACER CBP TEV site PROTEIN A IgG beads PROTEINSPACER CBP TEV site PROTEIN A TEV protease Calmodulin beads PROTEINSPACER CBP Bind and wash Elute with Calcium Run purified complex on 1D gel Identify components by MS

11 iPAC (parallel affinity chromatography) S F FLAG M2 purification, FLAG peptide elution Strep purification, Biotin elution FLAG M2 purification, FLAG peptide elution Strep purification, Biotin elution Rees et al Mol.Cell Prot 2011 Bait with two tags Flag and Strep Negative control with no tags

12 Types of protein analysis Proteins presentPPISCLFunction Mass Spectrometry Western blotting GFP tagging Immuno- histochemistry Enzyme assay Arrays Abundance Quantitative Mass Spec Western blotting GFP tagging Immuno- histochemistry Enzyme assay Arrays Isoform status Mass Spectrometry Western blotting Functional arrays Y2H Tagging + Mass Spectrometry Western blotting Structural studies Protein Arrays Biophysical assays (e.g.ITC, AUC) Mass Spectrometry GFP tagging Immuno- histochemistry Enzyme assay Functional arrays Enzyme assay Genetic approaches

13 Sub-cellular location Mass Spectrometry GFP tagging Immuno- histochemistry Enzyme assay

14 GFP tagging of yeast proteome Huh et al, 2003 GFP tagged proteins 75% of the yeast proteome classified to 22 distinct location

15 Systems wide immuno- histochemistry Barbe et al, 2008 Antibodies to 488 proteins applied to 3 different human cell lines and images stored and publically accessible Blue = DAPI staining of nucleus

16 Gentle cell lysis Pure fraction Protein correlation profiling LOPIT Subtractive proteomics Invariant rich fraction Proteomics approaches

17 Pure Fraction Extract proteins Digest LC-MS/MS Parts list

18 Subtractive Proteomics Boisvert et al (2010) Mol. Cell Prot 9:457

19 Invariant Rich Fraction Rough microsomes Smooth microsomes Golgi Apparatus ‘enriched fractions’ RM RM + SM SM Golgi Gilchrist et al (2006) Cell 127:1265

20 2 4 6 8 10 12 14 16 18 20 1 3 5 7 9 11 13 15 17 19 Gtl-6 Golgi Cyt b5 sER Sec12 ER 2468101214161820135791113151719 Carbonate wash Tom Dunkley Distribution Profiling

21 LOPIT Protocol LC-MS/MS (SCX/RP) Localisation of organelle proteins using isotope tagging (LOPIT) Quantification Identification Dunkley et al (2006) Proc. Natl. Acad. Sciences 103:6518

22 PCA Analysis of iTRAQ Dataset Marker Predicted marker LOPIT assigned no location assigned +

23 Types of protein analysis Proteins presentPPISCLFunction Mass Spectrometry Western blotting GFP tagging Immuno- histochemistry Enzyme assay Arrays Abundance Quantitative Mass Spec Western blotting GFP tagging Immuno- histochemistry Enzyme assay Arrays Isoform status Mass Spectrometry Western blotting Functional arrays Y2H Tagging + Mass Spectrometry Western blotting Structural studies Protein Arrays Biophysical assays (e.g.ITC, AUC) Mass Spectrometry GFP tagging Immuno- histochemistry Enzyme assay Functional arrays Enzyme assay Genetic approaches

24 Function Functional arrays Enzyme assay Genetic approaches Functional genomics One-by one knock out and observe phenotype Kamath et al, 2003, used RNAi to inhibit the function of, 86% of the 19,427 predicted genes of C. elegans and identified 1,722 mutant phenotypes Karlas et al 2010, screened a genome-wide siRNA library consisting of approximately 62,000 siRNAs targeting,17,000 annotated genes and,6,000 predicted genes in conjunction with infection of a lung epithelial cell line with H1N1 virus. They found that 287 host cell genes influence infection. In silico predictions Sequence alignment Structure alignment Functional Arrays e.g. Kinase substrates.calmodulin binding, ……

25 Protein Arrays Three types: Functional Arrays Analytical/Diagnostic Arrays Tissue Arrays

26

27 How to make them Slides derivatised with the following on to which proteins can be spotting using contact printing methods Nitrocellulose Amino silane Gold coated Bifunctional cross linkers Biotin/avidin hexa-histidine/ Nickel (Ni-NTA)

28 Synthesis of a yeast protein array Mok et al, 2009 Proteins expressed with a tag which makes them easy to purify Still a major task to express and purify every proteins from an organism

29 Protein in situ arrays (PISA)

30 Nucleic Acid Programmable Protein Array (NAPPA)

31 DNA Array to Protein Array (DAPA) Protein DNA

32 New approach? He et al (2009) New Biotechnology 26:227

33 Detection Fluorescence Radioactivity Quantum dots Surface plasmon resonance Mass spectrometry

34 Functional arrays

35 Kinase Substrates For more examples see Chen and Snyder (2010) J. Proteomics 74:2147-57

36 Analytical/Diagnostic Arrays Protein Expression Profiling on Capture Arrays

37 Antibody Affinity Arrays A2M2S Affinity Arrays and MALDI Mass Spectrometry Darii et al, 2009

38 Tissue Arrays Tissues mounted to standard silanized slides. Formalin-fixed paraffin-embedded human tissues Used for immunohistochemistry, in situ hybridization, fluorescent in situ hybridisation and in situ PCR Available from different companies supplying cancerous and normal tissues

39 Human Protein Atlas Tissue arrays, 48 normal tissue types, 20 cancers. Cell line arrays – 47 different cell lines Immunohistochemitsry - Sections of tissues Immunohistochemistry of 3 cell lines Antibodies raised against expressed sequence tags, a specific epitope for each human protein PrESTs www.proteinatlas.org

40 Strengths Under represented proteins present Functional information High throughput Weaknesses Proteins need to be in correct orientation and in vivo relevant structure Unknown splicing variants not detected Mixed PTMs not detected Co-interacting partners not detected Off target interactions High cost of manufacture

41 Problems with proteomics and systems biology Tip of ice berg Combinatorial PTMs Keeping complexes together Tissue specificity Synchronisation of cells Singel cell proteomics Whole proteome is highly dynamic Often not enough samples/resources to carry out sufficient replicate experiments

42 Single Cell Proteomics Bendall et al (2011) Science ICPMS Inductively coupled plasma MS


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