iReceptor: Bioinformatic Platform for Storing and Sharing
Next Generation Sequencing (NGS) Data from Immune Repertoires
iReceptor
Felix Breden1,2, Nishanth Marthanda1,3, Bojan Zimonja1, Jerome Jaglale1, Jamie K. Scott1,3,4, and Brian Corrie1
1The
IRAMCS Centre, 2Dept. of Biological Sciences, 3Dept. Molecular Biology and Biochemistry, and 4Faculty of Health Sciences,
Simon Fraser University, Burnaby, British Columbia, V5A 1S6 Canada
I. Human Adaptive Immune System Depends on Staggering Levels of Diversity in Antibody/B-Cell and
T-cell Receptor Diversity
•  The human adaptive immune system must produce a vast array of molecules to recognize a vast
array of pathogens (bacteria, viruses, newly emerging infections, etc.)
•  Recombination of V, D and J segments, nucleotide insertions and deletions at V-D and D-J
junctions, and somatic hypermutation in B-cells produces up to 1013 possible antibody or T-cell
receptor sequences (see Fig. 1)
III. iReceptor is the First Bioinformatic Platform Integrating Distributed Immune Repertoire “Big” Data Sets
At present there is no way to easily share or compare these huge data sets being produced by
academics, biomedical research institutes, clinics and pharmaceutical companies. iReceptor is the first
system that will facilitate this by storing these data at distributed sites, in a common data base format,
including patient demographic data, treatment and clinical outcome. The ability to share and compare
these data will greatly increase their utility for biomedical research and patient care.
•  The human body can have as many as 1011 lymphocytes (antibody/B-cell or T-cell receptor
producing cells)
•  Next Generation Sequencing (NGS) of immune repertoire profiles typically comprise 106-107
antibody or T-cell receptor sequences derived from circulating blood (PBMCs), B- and T-cell
subsets within blood, and tissue-associated cells (such as spleens or tumors)
•  Application of NGS to Immune Repertoire profiling is recent, starting in 2009 (Quake et al.,
Weinstein et al.)
Fig 1. Immune Repertoire Diversification - Multiple
different gene segments encode the beginning (V),
middle (D) and end (J) of an antibody or T-cell
receptor gene. Once a B cell is selected by antigen,
that clone expands, and its expressed antibody
genes undergo somatic hypermutation, producing a
clonal lineage of mutants (Papavasiliou and Schatz,
2002).
II. 
Next Generation Sequencing of Immune Repertoires is Critical to Development of Vaccines and
Therapeutic Antibodies, Treatment of Autoimmune Diseases, and Cancer Immunotherapy
NGS sequencing of immune repertoires is being applied to:
Leukemias and Lymphomas - Screening for Mixed Residual Disease (MRD)
Autoimmune Diseases – Follow disease-associated B-cells or T-cells (see Fig 2A).
Vaccine Research – Phylogenetic reconstruction of the evolution of neutralizing antibodies in
vivo (see Fig 2B).
Antibody Design – Screen natural repertoires and engineered libraries (e.g., phage- and yeastdisplayed antibody libraries) for therapeutic antibody leads
Fig. 3. Proposed configuration of iReceptor environment. Data migration services facilitate input of data into nodes of
receptor databases (e.g., VDJServer data commons, BC Genome Sciences Centre, SFU, etc.). iReceptor database service
authenticates access at 3 levels: public data “commons”; sharing within consortia (common consent, MTA, etc.); and within
laboratory. Agave (TACC) iReceptor Gateway webservice queries sequences across nodes (e.g., give me all sequences
from anti-HIV antibodies using IGHV1-69 gene), and packages these for analysis by offsite immune repertoire tools.
VI. Community Initiative to Solve Technical, Bioinformatic, Legal, Ethical, and IP Issues:
Community meeting May 29-June 1 2015 Vancouver – you are invited!
Community Meeting:
Analysis, Storage and Sharing of NGS Data from B-cell
Receptor/Antibody and T-cell Receptor Repertoires
May 29 - June 1, 2015 Vancouver, BC, Canada
Cancer Immunotherapy – Monitor level of therapeutics in adoptive T-cell transfer (e.g.,
neuroblastoma) and track tumor-specific tumor infiltrating lymphocytes (TILs) in response to
therapeutics (e.g., ovarian cancer)
Vaccine Research – Phylogenetic
Autoimmune Diseases - Where do disease-associated Breconstruction of the evolution of an HIVor T-cells originate and where do they mature? For
neutralizing antibody in Vivo.
example, in multiple sclerosis (MS), do B cells mature in
Purpose: To bring together researchers producing immune repertoires, legal
and ethics experts, funding agencies, human-subject advocates, journal
representatives, and others, who will:
the Central Nervous System(CNS)-draining lymph nodes
or in CNS lesions?
(i) Production of immune&repertoire&sequence&data&and&associated&metadata&
Recommend protocol/standards and "best practices” for:
(ii) Data analysis and sharing (including software and platforms)
(iii) Ethical, legal, and lP considerations
Meeting Facilitators: Tom Kepler (Boston University), Jamie Scott and Felix
Breden (Simon Fraser University)
Contact: [email protected]
Fig 2A. Lineages of antibody sequences related by progresssive
somatic hypermutations show that most antigenic stimulation occurs
outside of the central nervous system, and that there is significant
"crosstalk" between CNS lesions (X) and the CNS-draining lymph
nodes (L) (Sterm et al., 2014).
Fig 2B. Vaccine strategy based on phylogenetic
reconstruction of antibody lineage would attempt to
recapitulate development of broadly-neutralizing
antibodies in naïve persons by applying series of
immunogens designed to induce intermediate
“ancestral” antibodies (Liao et al., 2013)
N.B. Biomedical researchers, clinicians, and pharmaceutical companies are producing increasing
amounts of these data for an increasing number of research and clinical applications!
Supported by CIHR, NIH, The Antibody Society, Simon Fraser University,
GenMab&
References
1
Papavasaliou, F. N., et al., Somatic hypermutation of immunoglobulin genes: merging mechanisms for genetic diversity. Cell 109:S35-S44.
Weinstein, J. A. et al., 2009. High-throughput sequencing of the zebrafish antibody. Science 324: 807-810.
Freeman, et al., 2009. Profiling the T-cell receptor beta-chain repertoire by massively parallel sequencing. Genome Research 19:1817-1824.
Stern, N.H.L., 2014. B cells populating the multiple sclerosis brain mature in the draining cervical lymph nodes. Sci Transl. Med 6, 248ra107.
Liao, H-X., et al., 2013. Co-evolution of a broadly neutralizing HIV-1 antibody and founder virus. Nature doi:10.1038/nature12053.
Acknowledgements
This work was supported by CANARIE NEP-131 (F.B. and J.K.S.).