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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.).