In this episode of On AIRR, Dr. Paul Thomas, reviews advances in the field of TCR sequencing. Dr. Thomas is a faculty member in the Department of Immunology of St. Jude Children’s Research Hospital. His work has advanced our understanding of innate and adaptive immune responses and TCR specificity with a focus on responses to viral infections.

In Episode 18 of On AIRR, Dr. Thomas shares his journey from immunoparasitology to pioneering TCR repertoire sequencing. He began his scientific career studying innate immune responses to parasites during his graduate work in immunoparasitology. Motivated by a desire to use advanced molecular techniques, he moved to St. Jude for his postdoctoral research, where he contributed to the development of TCR repertoire sequencing methods. The discussion covers the evolution from single-chain TCR sequencing to the development of high-throughput paired sequencing methods, culminating in the TIRTL-seq approach. Dr. Thomas explains the technical and computational challenges in TCR pairing, the innovations that made large-scale studies possible, and the importance of data quality and curation in the field. The episode highlights the impact of these advances on understanding immune responses and the future of AIRR-based diagnostics.

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.

The episode is hosted by Dr. Ulrik Stervbo and Dr. Zhaoqing Ding.

Announcements and links

• Paul Thomas Lab https://www.stjude.org/research/labs/thomas-lab.html
• Other:
  • TIRTL-seq: Deep, quantitative, and affordable paired TCR repertoire sequencing https://doi.org/10.1101/2024.09.16.613345
  • TIRTL-seq repository: https://github.com/pogorely/TIRTL
  • Adaptive Immune Receptor Repertoire Community (AIRR-C) https://www.airr-community.org
  • The Antibody Society (TAbS) https://www.antibodysociety.org

AIRR-C Seminar Series s https://www.antibodysociety.org/the-airr-community/airr-community-seminar-series/

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 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.

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

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 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. 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

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.

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.

Dr. Charlotte Deane is Professor of Structural Bioinformatics in the Department of Statistics in University of Oxford (UK) and heads the Oxford Protein Informatics Group. Prof. Deane’s research merges statistics, immunoinformatics, protein structure and small molecule drug discovery. Her group has published several databases that are widely used by academic researchers and in pharmaceutical drug discovery pipelines. We discuss the relevance of including protein structure to study and design antibodies, and the availability of such data.

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.

Dr. Xenophon Papademetris is Professor of Radiology and Biomedical Imaging, and Biomedical Engineering at Yale University, USA. The research of Prof. Papademetris is in the area of medical image analysis with a focus in the development of medical software.

Dr. Papademetris provides an overview of the typical regulatory process for software classified as a medical device. We draw from his experience in the medical image field to design a high level route map for an imaginary company bringing to the market software to diagnose minimal residual disease.

You can learn more about Medical Software development in Dr. Papademetris’s book Introduction to Medical Software: Foundations for Digital Health, Devices and Diagnostics (Cambridge University Press, 2022) and the Yale/Coursera class Introduction to Medical Software.

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