Pecha Kucha:
Integrating immune repertoire data
for biomedical research and patient care
Jamie K. Scott, MD, PhD
Professor, MBB & FHS
Simon Fraser University
10 April 2015
IRMACS Theatre
B and T cells develop from hematopoietic stemcell 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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Antibodies and T-cell receptors bind specifically
to the antigens that initially selected them.
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Combinatorial diversity plus imprecise joining
create the vast genetic diversity within the
antibody and T-cell receptor repertoires
Front-end GFs
Back-end GFs
Gene fragments (GFs) encoding the front-end
and back-end of a gene.
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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Different recombination and joining events
create clonal diversity among T and B cells
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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 differentiation
Into 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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B-cell and T-cell repertoires are now being
characterized by massive parallel sequencing.
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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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Vaccine Discovery: Reconstruction of the
Evolution of an HIV-Neutralizing Antibody
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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)
Protocols for obtaining tissue samples
Sort Cellular Subsets
Protocols for sorting cellular subsets
mRNA -> cDNA -> PCR amplify
Prepare immune receptor library
Protocols for library preparation
Sequence immune receptor library
Standard primer sets
Sequencing platforms and parameters
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Steps in Immune Repertoire Analysis (cont.):
Analysing the data
Sequence quality control filters
Minimum sequence length
FASTQ quality score cutoffs
Annotate germline V, D, J genes,
junctions, somatic mutations
(IMGT, IgBlast, SODA, JoinSolver,
iHMMmune-Align, pRESTO, etc.)
Germline gene reference set
Ontology of gene regions
Assignment of somatic mutations
Infererence of new germline alleles
Statistical uncertainty
Analyze V-gene usage, clonal lineage
frequency and expansion
(VDJFasta, AbMining, Change-O, etc)
Comparison to other immune
repertoire data bases
Definition and determination of clonal
lineage
Need for a common data-base format
Bioinformatic platforms
(iReceptor, VDJServer, GigaGen)
Ethical/Privacy considerations
Legal/IP considerations
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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
Data Federation
Data Exploration
Analysis Results
IReceptor
Data Base
Simon Fraser University
IReceptor
Data Base
University of Toronto
...
Annotation Tools
IMGT V-Quest
IgBlast ...
IReceptor
Public Data Base
Common Repository
Compute Canada
Analysis Pipeline Tools
VDJFasta
AbMining ...
(Compute Canada Resources)
VDJServer
Public Data Base
Common Repository
UT 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.
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Thank you!
Happy Anniversaries to
The IRMACS Center
and SFU!