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Pecha Kucha:
Integrating immune repertoire data for biomedical research and patient care
Jamie K. Scott, MD, PhDProfessor, MBB & FHS
Simon Fraser University
10 April 2015
IRMACS Theatre
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B and T cells develop from hematopoietic stem-cell precursors in the bone marrow
“naïve” B cells and T cells differentiate into antibody-secreting plasma cells and effector T cells after stimulation by antigen/pathogen
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B and T cells circulate among lymph nodes, scanning them for antigens.
Fluids and cells from peripheral tissues drain into lymph nodes, bringing antigens/pathogens with them
B and T cells circulate through lymph nodes scanning for antigens/pathogens to recognize and respond to.
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B-cell and T-cell immune repertoires comprise cell-surface antibodies and T-cell receptors.
Antibodies on different B cells and T-cell receptors on different T cells differ from each other in their antigen-binding sites.
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Combinatorial diversity plus imprecise joining create the vast genetic diversity within the antibody and T-cell receptor repertoires
Gene fragments (GFs) encoding the front-end and back-end of a gene.
Front-end GFs Back-end GFs
In the developing B or T cell, different combinations of front- and back-end GFs pair up at random, with intervening DNA being excised.
The final joint is also altered by “imprecise joining” in forming a full antibody or T-cell receptor gene.
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Antigen “selects” a B-cell or T-cell clone from an immune repertoire by binding to its antibody or T-cell receptor.
A “naïve” immune repertoire of B or T cells.
Clonal selection by pathogen/antigen.
Clonal amplification and differentiationInto memory and effector cells.(Mutation of antibody genes)
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Memory B and T cells produced after initial contact with antigen will respond to a new introduction of antigen.
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The reason for booster shots: Clonal expansion of memory B and T cells leads to larger, faster responses on second exposure.
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Lymph nodes collect antigens, while naïve and memory B and T cells circulate among them, scanning for antigens that bind their Ab &TcRs
Once a B or T cell finds antigen, it will stay in the lymph node to differentiate into effector and memory cells.
Effectors will leave and migrate to peripheral tissues where they will act, while memory cells will continue to scan the lymph nodes for antigen.
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Cancer treatment: Immune receptor deep sequencing is more sensitive than flow
cytometry in detecting residual leukemia
Red dots indicate leukemic T-cells
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Autoimmune Disease: Phylogenetic reconstruction identifies “cross-talk” between CNS lesions and draining lymph nodes in MS
Stern et al. Science Transl. Med. 2014
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Steps in Immune Repertoire Sequencing & Analysis:Getting the Data
Obtain tissue (e.g., white blood cells)
Sort Cellular Subsets
mRNA -> cDNA -> PCR amplifyPrepare immune receptor library
Sequence immune receptor library
Protocols for sorting cellular subsets
Protocols for library preparation
Standard primer setsSequencing platforms and parameters
Protocols for obtaining tissue samples
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Steps in Immune Repertoire Analysis (cont.):Analysing the data
Analyze V-gene usage, clonal lineage frequency and expansion (VDJFasta, AbMining, Change-O, etc)
Need for a common data-base formatBioinformatic platforms(iReceptor, VDJServer, GigaGen)Ethical/Privacy considerationsLegal/IP considerations
Annotate germline V, D, J genes, junctions, somatic mutations(IMGT, IgBlast, SODA, JoinSolver, iHMMmune-Align, pRESTO, etc.)
Germline gene reference setOntology of gene regionsAssignment of somatic mutationsInfererence of new germline allelesStatistical uncertainty
Definition and determination of clonal lineage
Comparison to other immune repertoire data bases
Sequence quality control filters Minimum sequence lengthFASTQ quality score cutoffs
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iReceptor - A Distributed Data Management System for Storing and Comparing Immune Repertoires
iReceptor is:
A platform for integrating immune receptor data bases
Distinguished by two main characteristics:- Distributed data base system- Enriched data sets associated with immune repertoire sequence
data bases
Based on iPlant – TACC Texas Advanced Computing Centre
Uses Agave, a open-source scientific gateway webservice architecture.
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iReceptor Architecture
iReceptor Gateway
Annotation ToolsIMGT V-Quest
IgBlast ...
Analysis Pipeline ToolsVDJFasta
AbMining ... (Compute Canada Resources)
...
...
Data FederationData ExplorationAnalysis Results
IReceptor Data BaseSimon Fraser University
IReceptor Data BaseUniversity of Toronto
IReceptor Public Data Base Common RepositoryCompute Canada
VDJServer Public Data BaseCommon RepositoryUT Southwest Medical Center
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Community Meeting: Analysis, Storage and Sharing of NGS Data
from Antibody and T-cell Receptor Repertoires
Purpose: Bring together the researchers producing immune repertoires, legal and ethics experts, funding agencies, human-subject advocates, journal representatives, and others.
Goal: Develop recommendations for standards and best practices for:
(i) Production of immune repertoire NGS data and associated metadata;
(ii) Data analysis and sharing (including software and platforms);
(iii) Ethical, legal, and intellectual property considerations.
Supported by: Canadian Institutes of Health Research (CIHR), US National Institutes of Health (NIH), The Antibody Society, International Society for Vaccines. SFU, the IRMACS Centre, SFU’s Faculty of Science, Dept. of Molecular Biology & Biochemistry, and Dept. of Biological Sciences, and GenMab.