On AIRR - Immune receptors in the clinic

By: AIRR-Community
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  • Summary

  • A monthly podcast with a focus on the use and application of T and B cell receptor repertoires in diagnostics and other clinical settings.
    Copyright 2022 All rights reserved.
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Biological Sciences
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Episodes
  • On AIRR 15: Germline databases or adventures into the allelic underworld with Dr. Corey Watson and Dr. William Lees

    On AIRR 15: Germline databases or adventures into the allelic underworld with Dr. Corey Watson and Dr. William Lees
    Oct 30 2023
    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 onairr@airr-community.org 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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    1 hr and 2 mins
  • On AIRR 14: Data protection and data sharing with Alexander Bernier

    On AIRR 14: Data protection and data sharing with Alexander Bernier
    Aug 6 2023

    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 onairr@airr-community.org 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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    51 mins
  • On AIRR 13: Disease diagnostics using machine learning with Maxim Zaslavsky and Dr. Scott D. Boyd

    On AIRR 13: Disease diagnostics using machine learning with Maxim Zaslavsky and Dr. Scott D. Boyd
    Jul 2 2023

    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 onairr@airr-community.org 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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    34 mins

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