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Mathematical Characterization of Private and Public Immune Receptor Sequences

Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are gen...

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Autores principales: Böttcher, Lucas, Wald, Sascha, Chou, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501991/
https://www.ncbi.nlm.nih.gov/pubmed/37707621
http://dx.doi.org/10.1007/s11538-023-01190-z
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author Böttcher, Lucas
Wald, Sascha
Chou, Tom
author_facet Böttcher, Lucas
Wald, Sascha
Chou, Tom
author_sort Böttcher, Lucas
collection PubMed
description Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are generated probabilistically by recombination processes, clinical studies found a high degree of sharing of TCRs and BCRs among different individuals. In this work, we use a general probabilistic model for T/B cell receptor clone abundances to define “publicness” or “privateness” and information-theoretic measures for comparing the frequency of sampled sequences observed across different individuals. We derive mathematical formulae to quantify the mean and the variances of clone richness and overlap. Our results can be used to evaluate the effect of different sampling protocols on abundances of clones within an individual as well as the commonality of clones across individuals. Using synthetic and empirical TCR amino acid sequence data, we perform simulations to study expected clonal commonalities across multiple individuals. Based on our formulae, we compare these simulated results with the analytically predicted mean and variances of the repertoire overlap. Complementing the results on simulated repertoires, we derive explicit expressions for the richness and its uncertainty for specific, single-parameter truncated power-law probability distributions. Finally, the information loss associated with grouping together certain receptor sequences, as is done in spectratyping, is also evaluated. Our approach can be, in principle, applied under more general and mechanistically realistic clone generation models.
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spelling pubmed-105019912023-09-16 Mathematical Characterization of Private and Public Immune Receptor Sequences Böttcher, Lucas Wald, Sascha Chou, Tom Bull Math Biol Original Article Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are generated probabilistically by recombination processes, clinical studies found a high degree of sharing of TCRs and BCRs among different individuals. In this work, we use a general probabilistic model for T/B cell receptor clone abundances to define “publicness” or “privateness” and information-theoretic measures for comparing the frequency of sampled sequences observed across different individuals. We derive mathematical formulae to quantify the mean and the variances of clone richness and overlap. Our results can be used to evaluate the effect of different sampling protocols on abundances of clones within an individual as well as the commonality of clones across individuals. Using synthetic and empirical TCR amino acid sequence data, we perform simulations to study expected clonal commonalities across multiple individuals. Based on our formulae, we compare these simulated results with the analytically predicted mean and variances of the repertoire overlap. Complementing the results on simulated repertoires, we derive explicit expressions for the richness and its uncertainty for specific, single-parameter truncated power-law probability distributions. Finally, the information loss associated with grouping together certain receptor sequences, as is done in spectratyping, is also evaluated. Our approach can be, in principle, applied under more general and mechanistically realistic clone generation models. Springer US 2023-09-14 2023 /pmc/articles/PMC10501991/ /pubmed/37707621 http://dx.doi.org/10.1007/s11538-023-01190-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Böttcher, Lucas
Wald, Sascha
Chou, Tom
Mathematical Characterization of Private and Public Immune Receptor Sequences
title Mathematical Characterization of Private and Public Immune Receptor Sequences
title_full Mathematical Characterization of Private and Public Immune Receptor Sequences
title_fullStr Mathematical Characterization of Private and Public Immune Receptor Sequences
title_full_unstemmed Mathematical Characterization of Private and Public Immune Receptor Sequences
title_short Mathematical Characterization of Private and Public Immune Receptor Sequences
title_sort mathematical characterization of private and public immune receptor sequences
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501991/
https://www.ncbi.nlm.nih.gov/pubmed/37707621
http://dx.doi.org/10.1007/s11538-023-01190-z
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