Bjoern Peters La Jolla Institute for Allergy and Immunology Buenos Aires, Oct 31, 2012

Transcription

1 Bjoern Peters La Jolla Institute for Allergy and Immunology Buenos Aires, Oct 31, 2012

2 Overview 1. Introduction to the IEDB 2. Application: 2009 Swine-origin influenza virus 3. IEDB 2012+

3 What is the IEDB? NIH-sponsored free online resource 1. Database: repository of all published experimentally-derived epitope information Infectious disease Allergy Autoimmunity Transplantion/alloantigens Over 14,000 curated articles and direct submissions Over 90,000 unique epitopes Over 500,000 assays 2. Analysis Resource: tools to predict and model immune responses

4 Data Sources and Structure Literature curation Epitope discovery contract submission IEDB

5 Assay-Centric Data Representation IEDB captures the actual experimental assays relating to T cell responses B cell responses MHC Ligand Elution MHC Binding This allows searching in a variety of different ways By Epitope By Epitope Source By Immune Response By Host Organism By Assay

6 Example query: All TB epitopes recognized by T cells restricted by MHC class II in humans

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13 Advanced query Only MTB epitopes recognized in chronically infected humans and detectable without in vitro restimulation 13

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18 IEDB applications Meta-Analyses Prediction tool development

19 IEDB Analysis Resource Epitope prediction tools Machine learning algorithms that generalize the data contained in the IEDB to predict new epitopes MHC class I & II binding and processing B cell epitope predictions Epitope analysis tools Conservancy analysis Population coverage Homology mapping Cluster analysis

20 Epitope Analysis Tools: Add value to epitope datasets Conservation of swine flu (S-OIV) epitopes as an example 20

21 Swine flu project Initiated in spring 2009 High mortality estimates based on first affected population (Mexico) Novel combination of Swine and human influenza strains Lack of neutralizing antibodies fear of a global deadly pandemic

22 Swine flu project Question: Are there targets of pre-existing immunity in S-OIV? How different is the pandemic virus from recent seasonal flu viruses for the immune system? Query IEDB for all epitopes from influenza A Assemble sequences from recently circulating influenza strains (=in the past 20 years), Epitopes contained in recently circulating strains are likely targets of pre-existing immune responses Examine conservation of epitopes with likely pre-existing immunity in seasonal flu strains vs. pandemic flu Follow up experimentally

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25 50 B cell epitopes from recent seasonal influenza strains 55 sequences of pandemic influenza (10 antigens in each)

26 What does X number of conserved epitopes in S-OIV mean? Comparison to seasonal flu 2008

27 Analysis of Conservation in S-OIV of Known (pre-existing) Influenza Responses The Number of Epitopes Described in the Literature in Pre-2007 Years and Conserved in Specific Strains Influenza Strains B Cell T Cell CD8 + T Cell CD4 + Seasonal /S-OIV Hypothesis: Significant levels of preexisting immunity might exist in the general population against S-OIV. Greenbaum et al, PNAS, 2009

28 Preexisting T Cell Immunity Against S-OIV in the General Population Greenbaum et al, PNAS, 2009

29 Conclusions: Swine Flu epitope conservation The conservancy tool predicted that pre-existing immunity exists in the general population at the T cell (but less at the B cell) level Experimentally measured T cell responses confirmed that preexisting memory against S-OIV epitopes were similar in magnitude compared to new seasonal influenza

30 Analysis tools available in the IEDB-AR Conservancy analysis Analyze if epitopes are found conserved across different protein sequences Population coverage Analyze how many T cell epitopes with known HLA restriction will be recognized in a human population based on HLA frequencies Homology mapping Analyze the structure of an epitope in its source antigen based on homology mapping Cluster analysis Analyze how many epitopes in a set have significant sequence homology 30

31 Summary IEDB Introduction + S-OIV meta-analysis The IEDB catalogs all experiments characterizing epitopes Multiple query mechanisms allow definition of custom epitope sets IEDB epitope data is used to develop prediction algorithms and perform Meta-Analysis IEDB Analysis tools help to examine existing sets of epitopes and gain new knowledge Without the IEDB such meta-analysis would cost much more time and effort 31

32 IEDB First funding period Renewal awarded for 7 more years Update on priorities in the second funding period Populating the IEDB Query enhancements Reporting enhancements

33 Populating the IEDB PubMed Query Epitope References Automatic Abstract scans Relevant References Over 21 Million 171,639 29,559 Domain Classification Curation Infectious Disease Allergy Autoimmunity Transplantation Cancer HIV Others 18,104

34 We finally caught up!

35 Curation from now on Reduced effort allows to cut expense and refocus on other areas Implementation of biweekly update process data will appear faster You will be able to rely on the IEDB as a source of current in addition to historical information

36 The IEDB 2012+: Hierarchical queries using ontologies

37 Example: Hierarchical query tree for proteins

38 Queries for non-peptidic molecules and diseases

39 Finders require replacing IEDB controlled vocabularies with ontology classes Where available, re-use existing ontologies As necessary, contribute to building ontologies Benefits: Increase consistency in data curation Avoid duplicates Improve documentation to external users Enhance search capabilities

40 The IEDB 2012+: Aggregate reporting using Immunome Browser

41 Problem: Existing ways of displaying immune epitope data have limitations Query: T cell epitopes in TB 41

42 Solution: Immunome Browser A web application, integrated into the IEDB Maps epitopes onto antigens from a reference genome minimize redundancy, consistent use of antigen names 42

43 Mapping epitopes onto antigens Epitope #1: AEFLENFVRSSNLKFQDA from antigen Antigen 85-B precursor of M.bovis BCG strain Epitope #2: VFNFPPNGTHSWEYWGAQ from antigen alpha-antigen of M.tuberculosis H37Rv strain >gi A85B_MYCTU Antigen 85-B precursor M.bovine MTDVSRKIRAWGRRLMIGTAAAVVLPGLVGLAGGAATAGAFSRPGLPVEYLQVPSPSM GRDIKVQFQSGGNNSPAVYLLDGLRAQDDYNGWDINTPAFEWYYQSGLSIVMPVGGQS SFYSDWYSPACGKAGCQTYKWETFLTSELPQWLSANRAVKPTGSAAIGLSMAGSSAMI LAAYHPQQFIYAGSLSALLDPSQGMGPSLIGLAMGDAGGYKAADMWGPSSDPAWERND PTQQIPKLVANNTRLWVYCGNGTPNELGGANIPAEFLENFVRSSNLKFQDAYNAAGGH NAVFNFPPNGTHSWEYWGAQLNAMKGDLQSSLGAG 43

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46 Identification of 'antigenic regions' in TB 46

47 IEDB Conclusions IEDB has established a versatile database structure and curation processes to capture diverse immune epitopes Literature curation is current in all categories and new articles are typically curated within 4 weeks from entry in PubMed Focus of renewal period is on improving the query and reporting mechanisms, coming online in the next months

48 La Jolla Institute for Allergy & Immunology Acknowledgments San Diego Supercomputer Center Phil Bourne Julia Ponomarenko Consultants Laura Zarebski (Buenos Aires) David Nemazee (Scripps) Ralph Kubo (KKC) Chemical Entities of Biological Interest (ChEBI) Science Applications International Corporation CBS / UC team

49 La Jolla Institute for Allergy and Immunology non-profit research institute focused exclusively on immune system research 21 faculty (20 experimental, 1 bioinformatic) >100 postdoctoral employees Always open positions for bright + enthusiastic students / postdocs / visiting scholars