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5 EBI is an Outstation of the European Molecular Biology Laboratory. Master title Molecular Interactions and Pathways Sandra Orchard EMBL-EBI 19.05.2015.

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Presentation on theme: "5 EBI is an Outstation of the European Molecular Biology Laboratory. Master title Molecular Interactions and Pathways Sandra Orchard EMBL-EBI 19.05.2015."— Presentation transcript:

1 5 EBI is an Outstation of the European Molecular Biology Laboratory. Master title Molecular Interactions and Pathways Sandra Orchard EMBL-EBI 19.05.2015

2 2 Why is it useful to study PPI interactions, networks and pathways? Proteins are the workhorses of cell and all their activities are controlled through interactions with other molecules. To understand the biology of a single protein, you have to study its interacting partners Network/pathway analysis increasingly used as a tool to annotate large data sets – proteins involved in a common process tend to cluster and be present in the same pathway

3 Why are there so many issues with interaction data? 1.Wide variety of methods for demonstrating molecular interactions – all have their strengths and weaknesses 2.No single method accurately defines an interaction as being a true binary interaction observed under physiological conditions

4 Why do we need interaction databases Issues with all interaction data – true picture can only be built up by combining data derived using multiple techniques, multiple laboratories Problematic for any bench researcher to do – issues with data formats, molecular identifiers, sheer volume of data Molecular interaction databases publicly funded to collect this data and annotate in a format most useful to researchers

5 Why are data standards essential Prior to 2003, many databases= many formats. User must reformat when merging data File conversion inevitably leads to data loss Many formats compromised tool development – each tool developed tended to be database specific 5

6 6 Community standard for Molecular Interactions XML schema and detailed controlled vocabularies Jointly developed by major data providers: BIND, CellZome, DIP, GSK, HPRD, Hybrigenics, IntAct, MINT, MIPS, Serono, U. Bielefeld, U. Bordeaux, U. Cambridge, and others Version 1.0 published in February 2004 The HUPO PSI Molecular Interaction Format - A community standard for the representation of protein interaction data. Henning Hermjakob et al, Nature Biotechnology 2004, 22, 176-183. Version 2.5 published in October 2007 Broadening the Horizon – Level 2.5 of the HUPO-PSI Format for Molecular Interactions; Samuel Kerrien et al. BioMed Central. 2007. PSI-MI XML format

7 7 Collecting and combining data from different sources has become easier Standardized annotation through PSI-MI ontologies Tools from different organizations can be chained, e.g. analysis of IntAct data in Cytoscape. PSI-MI XML benefits http://www.psidev.info/MI Home page

8 www.ebi.ac.uk/ols Controlled vocabularies

9 IMEx Consortium of 9 molecular interaction databases dedicated to producing high quality, annotated data, curated to the same standards Data is curated once at a single centre then exchanged between partners Users need only go to a single site to obtain all data www.imexconsortium.org

10 10 www.imexconsortium.org

11 11 1.Publicly available repository of molecular interactions (mainly PPIs) - ~305K binary interactions taken from >6,200 publications (December 2012) 2.Data is standards-compliant and available via our website, for download at our ftp site or via PSICQUIC 3.Provide open-access versions of the software to allow installation of local IntAct nodes. IntAct goals & achievements http://www.ebi.ac.uk/intact ftp://ftp.ebi.ac.uk/pub/databases/intact www.ebi.ac.uk/Tools/webservices/psicquic/view/main.xhtml

12 Master headline “Lifecycle of an Interaction” Publication (full text) Sanity Checks (nightly) IntAct Curation CVs curator report Curation manual. reject Super curator annotate p1 p2 I exp IMEx MatrixDB Mint DIP Public web site FTP site accept check

13 13 UniProt Knowledge Base http://www.ebi.uniprot.org/ Interactions can be mapped to the canonical sequence….. to splice variants.... or to post- processed chains

14 14 Data model Support for detailed features i.e. definition of interacting interface Interacting domains Overlay of Ranges on sequence:

15 15 How to deal with Complexes Some experimental protocol do generate complex data: Eg. Tandem affinity purification (TAP) One may want to convert these complexes into sets of binary interactions, 2 algorithms are available:

16 16 IntAct – Home Page http://www.ebi.ac.uk/intact

17 Ontology search 17

18 Interaction detail 18 Choice of UniProtKB or Dasty View Details of interaction PubMed/IMEx ID

19 19 Viewing Interaction Details Additional information

20 Interaction Details 20

21 21 Visualizing - networkView

22 Master headline Visualization Applying a better graph layout…

23 Cytoscape Plugins 23

24 A Database of human biological pathways

25 Extensively cross-referenced Tools for data analysis – Pathway Analysis, Expression Overlay, Species Comparison, Biomart… Used to infer orthologous events in 20 other species Reactome is…

26 human PMID:5555PMID:4444 mouse cow Direct evidence Indirect evidence PMID:8976 PMID:1234 Using model organism data to build pathways – Inferred pathway events

27 Theory - Reactions Pathway steps = the “units” of Reactome = events in biology TRANSPORT CLASSIC BIOCHEMICAL BINDING DISSOCIATION DEGRADATION PHOSPHORYLATION DEPHOSPHORYLATION

28 Reactions Connect into Pathways OUTPUT INPUT CATALYST OUTPUT INPUT CATALYST INPUT OUTPUT CATALYST

29 Species Selection

30 Data Expansion – Projecting to Other Species A + ATP A + ADP -P B Human A + ATP A + ADP -P B Mouse B A Drosophila Reaction not inferred No orthologue - Protein not inferred + ATP

31 The Pathway Browser Species selector Diagram Key Sidebar Pathway Diagram Panel Details Panel (hidden) Zoom/move toolbar Thumbnail

32 The Details Panel

33 Pathway Analysis

34 Pathway Analysis – Overrepresentation ‘Top-level’ Reveal next level P-val

35 Species Comparison I

36 Species Comparison II Yellow = human/rat Blue = human only Grey = not relevant Black = Complex

37 Expression Analysis I

38 Expression Analysis II ‘Hot’ = high ‘Cold’ = low Step through Data columns

39 Summary Network and pathway analysis enable the researcher to: 1.Identify clusters of proteins – these may share the same function (stable complex), process or subcellular location 2.Identify proteins involved in the same pathway i.e. in the same process (only works for those proteins which can be placed in pathways) 3.Add biological meaning to a list of gene/transcript/protein identifiers. 39

40 40 http://www.ebi.ac.uk/training/online/ Interactions, Pathways and Networks Analyzing protein-protein interaction networks. Koh GC, Porras P, Aranda B, Hermjakob H, Orchard SE PMID:22385417 J Proteome Res [2012 (11) ] page info:2014-31

41 41 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?

42 42 Current IntAct support: European Commission grants PSIMEx (FP7-HEALTH-2007-223411) APO-SYS (FP7-HEALTH-2007-200767) Affinomics (241481) The development of Reactome is supported by a grant from the US National Institutes of Health (P41 HG003751), EU grant LSHG- CT-2005-518254 "ENFIN", Ontario Research Fund, and the EBI Industry Programme.


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