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Estimating the transfer rates of bacterial plasmids with an adapted Luria–Delbrück fluctuation analysis
To increase our basic understanding of the ecology and evolution of conjugative plasmids, we need reliable estimates of their rate of transfer between bacterial cells. Current assays to measure transfer rate are based on deterministic modeling frameworks. However, some cell numbers in these assays c...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352209/ https://www.ncbi.nlm.nih.gov/pubmed/35877684 http://dx.doi.org/10.1371/journal.pbio.3001732 |
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author | Kosterlitz, Olivia Muñiz Tirado, Adamaris Wate, Claire Elg, Clint Bozic, Ivana Top, Eva M. Kerr, Benjamin |
author_facet | Kosterlitz, Olivia Muñiz Tirado, Adamaris Wate, Claire Elg, Clint Bozic, Ivana Top, Eva M. Kerr, Benjamin |
author_sort | Kosterlitz, Olivia |
collection | PubMed |
description | To increase our basic understanding of the ecology and evolution of conjugative plasmids, we need reliable estimates of their rate of transfer between bacterial cells. Current assays to measure transfer rate are based on deterministic modeling frameworks. However, some cell numbers in these assays can be very small, making estimates that rely on these numbers prone to noise. Here, we take a different approach to estimate plasmid transfer rate, which explicitly embraces this noise. Inspired by the classic fluctuation analysis of Luria and Delbrück, our method is grounded in a stochastic modeling framework. In addition to capturing the random nature of plasmid conjugation, our new methodology, the Luria–Delbrück method (“LDM”), can be used on a diverse set of bacterial systems, including cases for which current approaches are inaccurate. A notable example involves plasmid transfer between different strains or species where the rate that one type of cell donates the plasmid is not equal to the rate at which the other cell type donates. Asymmetry in these rates has the potential to bias or constrain current transfer estimates, thereby limiting our capabilities for estimating transfer in microbial communities. In contrast, the LDM overcomes obstacles of traditional methods by avoiding restrictive assumptions about growth and transfer rates for each population within the assay. Using stochastic simulations and experiments, we show that the LDM has high accuracy and precision for estimation of transfer rates compared to the most widely used methods, which can produce estimates that differ from the LDM estimate by orders of magnitude. |
format | Online Article Text |
id | pubmed-9352209 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-93522092022-08-05 Estimating the transfer rates of bacterial plasmids with an adapted Luria–Delbrück fluctuation analysis Kosterlitz, Olivia Muñiz Tirado, Adamaris Wate, Claire Elg, Clint Bozic, Ivana Top, Eva M. Kerr, Benjamin PLoS Biol Methods and Resources To increase our basic understanding of the ecology and evolution of conjugative plasmids, we need reliable estimates of their rate of transfer between bacterial cells. Current assays to measure transfer rate are based on deterministic modeling frameworks. However, some cell numbers in these assays can be very small, making estimates that rely on these numbers prone to noise. Here, we take a different approach to estimate plasmid transfer rate, which explicitly embraces this noise. Inspired by the classic fluctuation analysis of Luria and Delbrück, our method is grounded in a stochastic modeling framework. In addition to capturing the random nature of plasmid conjugation, our new methodology, the Luria–Delbrück method (“LDM”), can be used on a diverse set of bacterial systems, including cases for which current approaches are inaccurate. A notable example involves plasmid transfer between different strains or species where the rate that one type of cell donates the plasmid is not equal to the rate at which the other cell type donates. Asymmetry in these rates has the potential to bias or constrain current transfer estimates, thereby limiting our capabilities for estimating transfer in microbial communities. In contrast, the LDM overcomes obstacles of traditional methods by avoiding restrictive assumptions about growth and transfer rates for each population within the assay. Using stochastic simulations and experiments, we show that the LDM has high accuracy and precision for estimation of transfer rates compared to the most widely used methods, which can produce estimates that differ from the LDM estimate by orders of magnitude. Public Library of Science 2022-07-25 /pmc/articles/PMC9352209/ /pubmed/35877684 http://dx.doi.org/10.1371/journal.pbio.3001732 Text en © 2022 Kosterlitz 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 | Methods and Resources Kosterlitz, Olivia Muñiz Tirado, Adamaris Wate, Claire Elg, Clint Bozic, Ivana Top, Eva M. Kerr, Benjamin Estimating the transfer rates of bacterial plasmids with an adapted Luria–Delbrück fluctuation analysis |
title | Estimating the transfer rates of bacterial plasmids with an adapted Luria–Delbrück fluctuation analysis |
title_full | Estimating the transfer rates of bacterial plasmids with an adapted Luria–Delbrück fluctuation analysis |
title_fullStr | Estimating the transfer rates of bacterial plasmids with an adapted Luria–Delbrück fluctuation analysis |
title_full_unstemmed | Estimating the transfer rates of bacterial plasmids with an adapted Luria–Delbrück fluctuation analysis |
title_short | Estimating the transfer rates of bacterial plasmids with an adapted Luria–Delbrück fluctuation analysis |
title_sort | estimating the transfer rates of bacterial plasmids with an adapted luria–delbrück fluctuation analysis |
topic | Methods and Resources |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352209/ https://www.ncbi.nlm.nih.gov/pubmed/35877684 http://dx.doi.org/10.1371/journal.pbio.3001732 |
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