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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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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. |
format | Online Article Text |
id | pubmed-10501991 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
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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