Immune Epitope Database and Analysis Resource (IEDB)
Transcript of Immune Epitope Database and Analysis Resource (IEDB)
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www.IEDB.org
Bjoern Peters
La Jolla Institute for Allergy and Immunology
Buenos Aires, Oct 31, 2012
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Overview
1. Introduction to the IEDB
2. Application: 2009 Swine-origin influenza virus
3. IEDB 2012+
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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
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IEDB
www.iedb.org
Literature curation Epitope discovery
contract submission
Data Sources and Structure
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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 …
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Example query: All TB epitopes
recognized by T cells restricted
by MHC class II in humans
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Advanced query
Only MTB epitopes recognized in
chronically infected humans and
detectable without in vitro restimulation
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IEDB applications
Meta-Analyses
Prediction tool
development
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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
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Epitope Analysis Tools:
Add value to epitope datasets
Conservation of swine flu (S-OIV)
epitopes as an example
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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
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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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50 B cell epitopes from
recent seasonal
influenza strains
55 sequences of
pandemic influenza
(10 antigens in each)
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What does X number of
conserved epitopes in S-OIV
mean? Comparison to
seasonal flu 2008
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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 2008 16 68 87
2009/S-OIV 8 54 57
Analysis of Conservation in S-OIV of
Known (pre-existing) Influenza
Responses
Hypothesis: Significant levels of preexisting immunity might exist in
the general population against S-OIV.
Greenbaum et al, PNAS, 2009
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Preexisting T Cell Immunity
Against S-OIV in the General
Population
Greenbaum et al, PNAS, 2009
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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
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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
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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
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IEDB 2012+
• First funding period 2004 – 2011
• Renewal awarded for 7 more years
Update on priorities in the second funding
period
– Populating the IEDB
– Query enhancements
– Reporting enhancements
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Populating the IEDB
PubMed Epitope
References
Over 21 Million 171,639
Relevant
References
29,559
Infectious Disease Allergy
Autoimmunity Transplantation
Cancer HIV
Others
Curation
Query Automatic
Abstract scans
Domain Classification
18,104
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We finally caught up!
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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
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The IEDB 2012+:
Hierarchical queries using
ontologies
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Example: Hierarchical query tree for
proteins
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Queries for non-peptidic molecules
and diseases
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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
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The IEDB 2012+:
Aggregate reporting using Immunome
Browser
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Problem: Existing ways of displaying
immune epitope data have limitations
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Query: T cell
epitopes in TB
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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
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Mapping epitopes onto antigens
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M.bovine >gi|398979|A85B_MYCTU Antigen 85-B precursor
MTDVSRKIRAWGRRLMIGTAAAVVLPGLVGLAGGAATAGAFSRPGLPVEYLQVPSPSM
GRDIKVQFQSGGNNSPAVYLLDGLRAQDDYNGWDINTPAFEWYYQSGLSIVMPVGGQS
SFYSDWYSPACGKAGCQTYKWETFLTSELPQWLSANRAVKPTGSAAIGLSMAGSSAMI
LAAYHPQQFIYAGSLSALLDPSQGMGPSLIGLAMGDAGGYKAADMWGPSSDPAWERND
PTQQIPKLVANNTRLWVYCGNGTPNELGGANIPAEFLENFVRSSNLKFQDAYNAAGGH
NAVFNFPPNGTHSWEYWGAQLNAMKGDLQSSLGAG
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
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Identification of 'antigenic regions' in TB
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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
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Acknowledgments La Jolla Institute for Allergy & Immunology
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
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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