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Mapping the human interactome: a update the genomic revolution in numbers from gene sequence to protein function large-scale protein interaction mapping yeast two-hybrid AP/MS binary protein interactions transient protein complexes stable different network topology >> complementary different interactome subspace interrogated similar high quality from Yu et al. High-quality binary protein interaction map of the yeast interactome network. Science 2008 MAPPIT validation of Y2H protein network maps yeast two-hybrid x y DB AD x y DB AD Pol reporter gene other two-hybrid methods x y F F’ x y F F’ other two-hybrid methods x y F F’ x y F F’ MAPPIT cytokine P P Jak Jak P P STAT P STAT P y x x P P STAT STAT y Pol reporter gene • operates in mammalian cells • ligand-inducible > extra level of control • simple readout > automation MAPPIT validation of Y2H protein network maps >> CCSB-YI1: 1.809 interactions between 1.278 proteins (estimated interactome size 18.000 +/- 4.500) MAPPIT validation of Y2H protein network maps WI-2007: 1.816 interactions between 1.496 proteins (estimated interactome size 115.600 +- 26.400) MAPPIT validation of Y2H protein network maps ~700 full length (bait) x ~700 fragments (prey) 40 fragments per ORF >> 755 interactions between 522 proteins (only 92 previously identified by Y2H !) MAPPIT validation of Y2H protein network maps framework for large-scale Y2H human interactome mapping -validation of available HT-YTH interactome maps: (Vidal & Wanker groups) >> high quality (> literature curated) -estimation of interactome size: ~130.000 interactions MAPPIT validation of Y2H protein network maps framework for large-scale Y2H human interactome mapping -validation of available HT-YTH interactome maps: (Vidal & Wanker groups) >> high quality (> literature curated) -estimation of interactome size: ~130.000 interactions -standardized confidence scoring method empirical confidence score from Braun et al. An experimentally derived confidence score for binary protein-protein interactions. Nature Methods 2009 empirical confidence score from Braun et al. An experimentally derived confidence score for binary protein-protein interactions. Nature Methods 2009 mapping the human interactome • 3 year NIH grant • Y2H: 16.000 x 16.000 full lenght human ORFs (~ 50% of total matrix of 22.000 x 22.000) • interaction toolkit re-test: ~25-30.000 interactions (~10.000/year; ~20% of the map) what did we learn ? benchmarking binary interaction mapping methods >> MAPPIT performance is similar to that of the other tested methods from Braun et al. An experimentally derived confidence score for binary protein-protein interactions. Nature Methods 2009 benchmarking binary interaction mapping methods >> the interaction mapping methods are highly complementary from Braun et al. An experimentally derived confidence score for binary protein-protein interactions. Nature Methods 2009 the ORFeome collection • 15.483 full length human ORFs • derived from Mammalian Gene Collection (MGC) • cloned in Gateway vectors from http://horfdb.dfci.harvard.edu/ MAPPIT for large-scale interactome analysis ? • high quality assay • access to a large collection of easily transferred cDNAs • different and complementary network subspace probed > screening for novel interactions towards an efficient screening format: reverse transfection nucleic acid spot transfection reagent add cells incubate ArrayMAPPIT screening human ORFeome collection prey (+reporter) plasmid transfection reagent reverse transfection mix -/+ ligand MAPPIT prey collection MAPPIT bait cell line MAPPIT prey array (stable for months !) luciferase read-out current screening setup • prey collection: 2.000 human ORF preys (GO annotation “signal transduction”) • assay format: 96well > 384well • automation: – Tecan EVO150 (DNA preps) – Tecan EVO200/Perkin-Elmer Envision (array production array + assay read-out) screening for interaction partners of E3 ligase complex adaptors “Specificity module”: SCF – Skp1 + F-box protein ECS – ElonginB/C + SOCS-box protein SKP1 screen 100 FBXO46 FBXL8 FBXW11 FBXW9 FBXW11 FBXW9 BTRC FBXO46 FBXL8 unstimulated 0,01 BTRC 10 1 0,1 1 10 0,01 stimulated 0,1 • 10-fold cut-off >> 5 hits: 3 known (blue), 3 novel (green); all F-box proteins • no other known Skp1 interaction partners in the array 100 Elongin C screen 100 SOCS2 SPSB2 RAB40B ASB9 ASB1 TCEB2 10 ASB6 ASB8 SPSB1 WSB1 ASB2 SPSB4 unstimulated 0,01 1 0,1 1 10 0,01 • • • • stimulated 0,1 10-fold cut-off >> 5 hits: 4 known and 1 novel (all SOCS-box proteins) 5-fold cut-off >> 8 additional hits: 4 known interactors (all SOCS-box proteins) 3-fold cut-off >> 14 additional hits: 2 known and 1 novel interactor (all SOCS-box proteins) 6 false negatives 100 Co-IP confirmation SPSB4 SPSB2 mock SOCS2 Elongin C FBXO46 FBXW9 FBXW11 mock SKP1 WB anti-E lysate WB anti-Elongin C WB anti-E IP anti-Flag WB anti-Elongin C WB anti-Flag IP anti-Flag WB anti-Flag MAPPIT cDNA library screening MACS enrichment anti-mIgG-PE anti-hIL5R hIL5R mEcoR 5’LTR CMV LR-F3 bait CD90 CMV gp130 rPAP1 prey hIL5RαΔcyt FACS sort anti-PE magnetobead hIL5R retroviral prey cDNA library SKP1 screen Symbol Description FBXL8 FBXL15 FBXW5 FBX044 FBXO2 CDCA3 FBXL6 FBXW9 F-box and leucine-rich repeat protein 8 F-box and leucine-rich repeat protein 15 F-box and WD domain protein 5 F-box protein 44 F-box protein 2 cell division cycle associated 3 F-box and leucine-rich repeat protein 6 F-box and WD-40 domain protein 9 • 6 known SKP1 interacting proteins • 2 novel interaction partners (both F-box proteins) Number of clones (fusions) 9 (5) 1 (1) 12 (5) 9 (7) 1 (1) 1 (1) 3 (1) 5 (3) Array versus cDNA library screening cDNA library screening array screening ‘open’: large & diverse prey pool ‘closed’: fixed set of preys labour intensive fast prey identification is tedious position in array determines prey identity MAPPIT for large-scale interactome analysis ? • high quality assay • access to a large collection of easily transferred cDNAs • different and complementary network subspace probed > > screening for novel interactions • mammalian background yeast two-hybrid interaction maps are static • the human interactome is not static but dynamic – many protein-protein interactions are conditional or context-dependent – require post-translational modifications and/or structural alterations – require co-factors, adaptors or regulatory proteins • yeast cell doesn’t provide the normal cellular environment for human proteins – no accessory proteins – no modifications – no context-dependent interactions MAPPIT for large-scale interactome analysis ? • high quality assay • access to a large collection of easily transferred cDNAs • different and complementary network subspace probed > > screening for novel interactions • mammalian background > > mapping protein network dynamics mapping dynamic aspects of protein networks ? treatment B -/+ ligand treatment A MAPPIT bait cell line treatment C mapping dynamic aspects of protein interactions: GR signalling cytoplasm nucleus NFkB monomer dimer p53 MAPPIT can detect these changes in protein interactions luciferase activity (fold induction) 30 25 unstimulated stimulated unstimulated + DEX stimulated + DEX 20 15 10 5 0 GR bait + NS4A prey GR bait + p53 prey GR bait + Hsp90 prey screening for DEX-dependent GR interactions - DEX -/+ ligand GR-bait expressing cells + DEX screening for DEX-dependent GR interactions 40 - dexamethasone + dexamethasone luciferase values (fold induction) 35 30 25 20 15 10 5 0 GR bait STOP p53 Hsp90 FBXW9 HBP1 STAT4 SOCS3 NRIP1 FASTK LPXN NCOA4 SHC4 DOK3 PPP5C STOP p53 Hsp90 FBXW9 HBP1 STAT4 SOCS3 NRIP1 FASTK LPXN NCOA4 SHC4 DOK3 PPP5C 100 90 luciferase values (fold induction) 80 70 60 50 40 30 20 10 0 Skp1 bait screening for DEX-dependent GR interactions + STAT3 – STAT5A – HGMB2 40 - dexamethasone + dexamethasone 35 luciferase values (fold induction) 6 stably interacting proteins: STAT3, STAT5A, HGMB2 (known) HBP1, STAT4, SOCS3 30 25 20 15 10 5 0 GR bait STOP p53 Hsp90 FBXW9 HBP1 STAT4 SOCS3 NRIP1 FASTK LPXN NCOA4 SHC4 DOK3 PPP5C STOP p53 Hsp90 FBXW9 HBP1 STAT4 SOCS3 NRIP1 FASTK LPXN NCOA4 SHC4 DOK3 PPP5C 100 90 luciferase values (fold induction) 80 70 60 50 40 30 20 10 0 Skp1 bait screening for DEX-dependent GR interactions + STAT3 – STAT5A – HGMB2 40 - dexamethasone + dexamethasone 35 luciferase values (fold induction) 6 DEX-inducible interactions: NRIP1 (known interactor) NCOA4 (AR interactor) FASTK, LPXN, SHC4, DOK3 30 25 20 15 10 5 0 GR bait STOP p53 Hsp90 FBXW9 HBP1 STAT4 SOCS3 NRIP1 FASTK LPXN NCOA4 SHC4 DOK3 PPP5C STOP p53 Hsp90 FBXW9 HBP1 STAT4 SOCS3 NRIP1 FASTK LPXN NCOA4 SHC4 DOK3 PPP5C 100 90 luciferase values (fold induction) 80 70 60 50 40 30 20 10 0 Skp1 bait screening for DEX-dependent GR interactions + STAT3 – STAT5A – HGMB2 40 - dexamethasone + dexamethasone 35 luciferase values (fold induction) 1 DEX-repressible interaction: PPP5C (known interactor) 30 25 20 15 10 5 0 GR bait STOP p53 Hsp90 FBXW9 HBP1 STAT4 SOCS3 NRIP1 FASTK LPXN NCOA4 SHC4 DOK3 PPP5C STOP p53 Hsp90 FBXW9 HBP1 STAT4 SOCS3 NRIP1 FASTK LPXN NCOA4 SHC4 DOK3 PPP5C 100 90 luciferase values (fold induction) 80 70 60 50 40 30 20 10 0 Skp1 bait screening for DEX-dependent GR interactions ArrayMAPPIT - further development • prey collection: 2.000 human ORF preys > 10.000 (end 09) • assay format: 384well > glass slides (?) • increase assay sensitivity – decrease assay variability • data-management, optimized experimental setup, objective scoring and quality control tracking (StatGent) CRL CCSB Jan Tavernier Marc Vidal Dominiek Catteeuw Els Pattyn Delphine Lavens Leentje De Ceuninck Isabel Uyttendaele Celia Bovijn Laura Icardi Margarida Maia Sylvie Seeuws Lennart Zabeau Irma Lemmens Anne-Sophie De Smet Elien Ruyssinck Viola Gesellchen Tim Van Acker Frank Peelman Julie Piessevaux Peter Ulrichts Annick Verhee Joris Wauman José Van der Heyden Nele Vanderroost Dieter Defever & co