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Sequential mutations in exponentially growing populations
Stochastic models of sequential mutation acquisition are widely used to quantify cancer and bacterial evolution. Across manifold scenarios, recurrent research questions are: how many cells are there with n alterations, and how long will it take for these cells to appear. For exponentially growing po...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359018/ https://www.ncbi.nlm.nih.gov/pubmed/37428805 http://dx.doi.org/10.1371/journal.pcbi.1011289 |
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author | Nicholson, Michael D. Cheek, David Antal, Tibor |
author_facet | Nicholson, Michael D. Cheek, David Antal, Tibor |
author_sort | Nicholson, Michael D. |
collection | PubMed |
description | Stochastic models of sequential mutation acquisition are widely used to quantify cancer and bacterial evolution. Across manifold scenarios, recurrent research questions are: how many cells are there with n alterations, and how long will it take for these cells to appear. For exponentially growing populations, these questions have been tackled only in special cases so far. Here, within a multitype branching process framework, we consider a general mutational path where mutations may be advantageous, neutral or deleterious. In the biologically relevant limiting regimes of large times and small mutation rates, we derive probability distributions for the number, and arrival time, of cells with n mutations. Surprisingly, the two quantities respectively follow Mittag-Leffler and logistic distributions regardless of n or the mutations’ selective effects. Our results provide a rapid method to assess how altering the fundamental division, death, and mutation rates impacts the arrival time, and number, of mutant cells. We highlight consequences for mutation rate inference in fluctuation assays. |
format | Online Article Text |
id | pubmed-10359018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-103590182023-07-21 Sequential mutations in exponentially growing populations Nicholson, Michael D. Cheek, David Antal, Tibor PLoS Comput Biol Research Article Stochastic models of sequential mutation acquisition are widely used to quantify cancer and bacterial evolution. Across manifold scenarios, recurrent research questions are: how many cells are there with n alterations, and how long will it take for these cells to appear. For exponentially growing populations, these questions have been tackled only in special cases so far. Here, within a multitype branching process framework, we consider a general mutational path where mutations may be advantageous, neutral or deleterious. In the biologically relevant limiting regimes of large times and small mutation rates, we derive probability distributions for the number, and arrival time, of cells with n mutations. Surprisingly, the two quantities respectively follow Mittag-Leffler and logistic distributions regardless of n or the mutations’ selective effects. Our results provide a rapid method to assess how altering the fundamental division, death, and mutation rates impacts the arrival time, and number, of mutant cells. We highlight consequences for mutation rate inference in fluctuation assays. Public Library of Science 2023-07-10 /pmc/articles/PMC10359018/ /pubmed/37428805 http://dx.doi.org/10.1371/journal.pcbi.1011289 Text en © 2023 Nicholson et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Nicholson, Michael D. Cheek, David Antal, Tibor Sequential mutations in exponentially growing populations |
title | Sequential mutations in exponentially growing populations |
title_full | Sequential mutations in exponentially growing populations |
title_fullStr | Sequential mutations in exponentially growing populations |
title_full_unstemmed | Sequential mutations in exponentially growing populations |
title_short | Sequential mutations in exponentially growing populations |
title_sort | sequential mutations in exponentially growing populations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359018/ https://www.ncbi.nlm.nih.gov/pubmed/37428805 http://dx.doi.org/10.1371/journal.pcbi.1011289 |
work_keys_str_mv | AT nicholsonmichaeld sequentialmutationsinexponentiallygrowingpopulations AT cheekdavid sequentialmutationsinexponentiallygrowingpopulations AT antaltibor sequentialmutationsinexponentiallygrowingpopulations |