On AIRR - Immune receptors in the clinic

Available Episodes

5 of 17

On AIRR 17: Data over algorithms: key lessons from the Immune Epitope Database with Bjoern Peters
In this episode of On AIRR, Dr. Bjoern Peters, Professor at the La Jolla Institute for Immunology (LJI), explores how high-quality data serves as the foundation for advancing AI-based immunological predictions and diagnostics. Originally from Germany, Dr. Peters began his academic journey in theoretical physics at Hamburg, focusing on quantum optics, before pivoting to biophysics during his PhD at Humboldt University. This shift was inspired by the challenge of understanding epitope presentation pathways and the limitations of epitope-prediction algorithms, which led him to work with Dr. Alessandro Sette at LJI to develop the Immune Epitope Database (IEDB) — the world’s largest resource for immune epitope data. Throughout the conversation, Dr. Peters traces the evolution of epitope research, starting with his work on MHC-peptide binding predictions and expanding into broader immunological data collection. He emphasizes that high-quality datasets often outcompete algorithmic improvements and shares the story of how the IEDB was established to consolidate immune epitope data. The conversation explores the status of data standardization and use of ontologies in structuring biomedical data, particularly in immunology. Dr. Peters highlights how work done by the IEDB and the Adaptive Immune Receptor Repertoire Community (AIRR-C) in these areas is critical for advancing immunology and enabling prediction and diagnostics. Finally, the discussion covers challenges of predicting epitopes from immune repertoires, the growing interest in using AIRR sequencing for diagnostics, and the importance of rigorous, unbiased validation of prediction models for clinical applications. Comments are welcome to the inbox of [email protected] or on social media under the tag #onAIRR. Further information can be found here: https://www.antibodysociety.org/the-airr-community/airr-c-podcast. The episode is hosted by Dr. Ulrik Stervbo and Dr. Zhaoqing Ding. Announcements and links Peters Lab https://www.lji.org/labs/peters-lab Tools mentioned: Immune Epitope Database (IEDB) https://www.iedb.org Ontology for Biomedical Investigations (OBI) https://obi-ontology.org Other: Adaptive Immune Receptor Repertoire Community (AIRR-C) https://www.airr-community.org The Antibody Society (TAbS) https://www.antibodysociety.org Antibody News Podcast, by TAbS https://www.antibodysociety.org/antibody-news-podcast Sette Lab https://www.lji.org/labs/sette-lab
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On AIRR 16: Deciphering the grammar of immune repertoires with Thierry Mora and Aleksandra Walczak
Dr. Thierry Mora and Dr. Aleksandra Walczak co-lead the Statistical biophysics group within Laboratoire de physique de l'ENS (LPENS) at the Ecole normale supérieure (Paris, France). Physicists by training, Dr. Mora and Dr. Walczak entered the field of the analysis of the immune system in a time when the first AIRR-seq datasets were becoming available. They have applied biophysics, neuroscience, and information theory perspectives to understand V(D)J recombination and quantify diversity. The group has published many software tools for the analysis of immune repertoires, including IGoR (to infer V(D)J recombination related processes from sequencing data), Sonia (infer selection pressures on features of amino acid CDR3 sequences), ALICE (detect TCR involved in immune responses from single RepSeq datasets), and PUBLIC (for analyzing sharing of TCRs, and predict public clones). In this episode of On AIRR, Dr. Mora and Dr. Walczak discuss the relevance and challenges of quantifying diversity and the questions that remain unanswered. They think of immune repertoire diversity in the same way as one could think of English language sentences, and try to learn the grammar of the combinations and quantify it. They also provide an overview of some of the software tools developed by their group. Comments are welcome to the inbox of [email protected] or on social media under the tag #onAIRR. Further information can be found here: https://www.antibodysociety.org/the-airr-community/airr-c-podcast. The episode is hosted by Dr. Ulrik Stervbo and Dr. Zhaoqing Ding. Announcements and links Statistical biophysics @ ENS. The website of the group. https://sites.google.com/view/statbiophysens/home Tools mentioned: IGoR: https://github.com/statbiophys/IGoR Sonia: https://github.com/statbiophys/SONIA SoNNia: https://github.com/statbiophys/sonnia ALICE: https://github.com/pogorely/ALICE PUBLIC: https://github.com/yuvalel/PUBLIC
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On AIRR 15: Germline databases or adventures into the allelic underworld with Dr. Corey Watson and Dr. William Lees
Dr. Corey Watson is an Associate Professor at the University of Louisville. His work focuses on characterising and cataloguing antibody genetic diversity in human and mouse to better understand disease susceptibility and clinical health outcomes. Dr. William Lees is a researcher at University of London. His work focuses on developing Adaptive Immune Receptor (AIR) reference sets for diverse species and the annotation of experimental sequence data. In this episode we talk about the recent work by the Germline Database Working Group of the AIRR-Community. The accuracy of V and J gene segment assignment improves with the quality of the reference germline set. The accurate assignment is critical for characterization of somatic hypermutation. We discuss the challenges in creating a database to hold all relevant and potentially relevant germline information, especially in the light of increased discovery rate through technological advances and improved analysis pipelines. We also reflect on the complexity in handling personalised germline reference sets. The episode is hosted by Dr. Ulrik Stervbo and Dr. Zhaoqing Ding. Comments are welcome to the inbox of [email protected] or on social media under the tag #onAIRR. Further information can be found here: https://www.antibodysociety.org/the-airr-community/airr-c-podcast. Website of the AIRR-C Germline Database Working Group https://www.antibodysociety.org/the-airr-community/airr-working-groups/germline_database/ Papers mentioned Collins, Andrew M., Mats Ohlin, Martin Corcoran, James M. Heather, Duncan Ralph, Mansun Law, Jesus Martínez-Barnetche, et al. 2023. “AIRR-C Human IG Reference Sets: Curated Sets of Immunoglobulin Heavy and Light Chain Germline Genes.” BioRxiv. https://doi.org/10.1101/2023.09.01.555348 Rodriguez, Oscar L., Yana Safonova, Catherine A. Silver, Kaitlyn Shields, William S. Gibson, Justin T. Kos, David Tieri, et al. 2023. “Genetic Variation in the Immunoglobulin Heavy Chain Locus Shapes the Human Antibody Repertoire.” Nature Communications 14 (1). https://doi.org/10.1038/s41467-023-40070-x Lees, William D., Scott Christley, Ayelet Peres, Justin T. Kos, Brian Corrie, Duncan Ralph, Felix Breden, et al. 2023. “AIRR Community Curation and Standardised Representation for Immunoglobulin and T Cell Receptor Germline Sets.” Immunoinformatics (Amsterdam, Netherlands) 10 (100025): 100025. https://doi.org/10.1016/j.immuno.2023.100025 Jackson, Katherine J. L., Justin T. Kos, William Lees, William S. Gibson, Melissa Laird Smith, Ayelet Peres, Gur Yaari, et al. 2022. “A BALB/c IGHV Reference Set, Defined by Haplotype Analysis of Long-Read VDJ-C Sequences From F1 (BALB/c x C57BL/6) Mice.” Frontiers in Immunology 13. https://doi.org/10.3389/fimmu.2022.888555 Ford, Easton E., David Tieri, Oscar L. Rodriguez, Nancy J. Francoeur, Juan Soto, Justin T. Kos, Ayelet Peres, et al. 2023. “FLAIRR-Seq: A Method for Single-Molecule Resolution of near Full-Length Antibody H Chain Repertoires.” The Journal of Immunology 210 (10): 1607–19. https://doi.org/10.4049/jimmunol.2200825 Omer, Aviv, Ayelet Peres, Oscar L. Rodriguez, Corey T. Watson, William Lees, Pazit Polak, Andrew M. Collins, and Gur Yaari. 2022. “T Cell Receptor Beta Germline Variability Is Revealed by Inference from Repertoire Data.” Genome Medicine 14 (1). https://doi.org/10.1186/s13073-021-01008-4 Rodriguez, Oscar L., Catherine A. Silver, Kaitlyn Shields, Melissa L. Smith, and Corey T. Watson. 2022. “Targeted Long-Read Sequencing Facilitates Phased Diploid Assembly and Genotyping of the Human T Cell Receptor Alpha, Delta, and Beta Loci.” Cell Genomics 2 (12): 100228. https://doi.org/10.1016/j.xgen.2022.100228 Tools mentioned TIgGER (Immcantation) https://tigger.readthedocs.io/en/stable IgDiscover https://github.com/NBISweden/IgDiscover Partis https://github.com/psathyrella/partis MiXCR https://mixcr.com
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On AIRR 14: Data protection and data sharing with Alexander Bernier
Alexander Bernier BCL, JD, LLM, SJD (Candidate) is a Montreal-based lawyer, and a doctoral candidate at the University of Toronto Faculty of Law. His work aims to give scientists a range of compliant data sharing designs that scientists can implement in different situations. In this episode, we discuss the risk of identifying individuals in a biological data set, how this is approached differently in different countries, and possible strategies to ensure data privacy. The episode is hosted by Dr. Ulrik Stervbo and Dr. Zhaoqing Ding. Comments are welcome to the inbox of [email protected] or on social media under the tag #onAIRR. Further information can be found here: https://www.antibodysociety.org/the-airr-community/airr-c-podcast.
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On AIRR 13: Disease diagnostics using machine learning with Maxim Zaslavsky and Dr. Scott D. Boyd
Maxim Zaslavsky is a computer scientist using machine learning to address problems in immunology. He is currently PhD student at Stanford University. Scott D. Boyd is a physician-scientist and Professor of Pathology and of Food Allergy and Immunology at Stanford University. His group is focused on using high-throughput DNA sequencing and single-cell experiments to analyse human immune responses to infection and vaccination. We discuss the preprint “Disease diagnostics using machine learning of immune receptors”, available at BioRxiv: https://doi.org/10.1101/2022.04.26.489314. The work is led by Maxim Zaslavsky with Scott Boyd the corresponding author. In the manuscript, the authors demonstrate how AIRR-seq and machine learning can be used in disease diagnostics. The episode is hosted by Dr. Ulrik Stervbo and Dr. Zhaoqing Ding. Comments are welcome to the inbox of [email protected] or on social media under the tag #onAIRR. Further information can be found here: https://www.antibodysociety.org/the-airr-community/airr-c-podcast.
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