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RESTAMP – Rate estimates by sequence-tag analysis of microbial populations

Microbial division rates determine the speed of mutation accumulation and thus the emergence of antimicrobial resistance. Microbial death rates are affected by antibiotic action and the immune system. Therefore, measuring these rates has advanced our understanding of host-pathogen interactions and a...

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Autores principales: Mahmutovic, Anel, Gillman, Aaron Nicholas, Lauksund, Silje, Robson Moe, Natasha-Anne, Manzi, Aime, Storflor, Merete, Abel zur Wiesch, Pia, Abel, Sören
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7878984/
https://www.ncbi.nlm.nih.gov/pubmed/33613869
http://dx.doi.org/10.1016/j.csbj.2021.01.017
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author Mahmutovic, Anel
Gillman, Aaron Nicholas
Lauksund, Silje
Robson Moe, Natasha-Anne
Manzi, Aime
Storflor, Merete
Abel zur Wiesch, Pia
Abel, Sören
author_facet Mahmutovic, Anel
Gillman, Aaron Nicholas
Lauksund, Silje
Robson Moe, Natasha-Anne
Manzi, Aime
Storflor, Merete
Abel zur Wiesch, Pia
Abel, Sören
author_sort Mahmutovic, Anel
collection PubMed
description Microbial division rates determine the speed of mutation accumulation and thus the emergence of antimicrobial resistance. Microbial death rates are affected by antibiotic action and the immune system. Therefore, measuring these rates has advanced our understanding of host-pathogen interactions and antibiotic action. Several methods based on marker-loss or few inheritable neutral markers exist that allow estimating microbial division and death rates, each of which has advantages and limitations. Technical bottlenecks, i.e., experimental sampling events, during the experiment can distort the rate estimates and are typically unaccounted for or require additional calibration experiments. In this work, we introduce RESTAMP (Rate Estimates by Sequence Tag Analysis of Microbial Populations) as a method for determining bacterial division and death rates. This method uses hundreds of fitness neutral sequence barcodes to measure the rates and account for experimental bottlenecks at the same time. We experimentally validate RESTAMP and compare it to established plasmid loss methods. We find that RESTAMP has a number of advantages over plasmid loss or previous marker based techniques. (i) It enables to correct the distortion of rate estimates by technical bottlenecks. (ii) Rate estimates are independent of the sequence tag distribution in the starting culture allowing the use of an arbitrary number of tags. (iii) It introduces a bottleneck sensitivity measure that can be used to maximize the accuracy of the experiment. RESTAMP allows studying microbial population dynamics with great resolution over a wide dynamic range and can thus advance our understanding of host-pathogen interactions or the mechanisms of antibiotic action.
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spelling pubmed-78789842021-02-19 RESTAMP – Rate estimates by sequence-tag analysis of microbial populations Mahmutovic, Anel Gillman, Aaron Nicholas Lauksund, Silje Robson Moe, Natasha-Anne Manzi, Aime Storflor, Merete Abel zur Wiesch, Pia Abel, Sören Comput Struct Biotechnol J Research Article Microbial division rates determine the speed of mutation accumulation and thus the emergence of antimicrobial resistance. Microbial death rates are affected by antibiotic action and the immune system. Therefore, measuring these rates has advanced our understanding of host-pathogen interactions and antibiotic action. Several methods based on marker-loss or few inheritable neutral markers exist that allow estimating microbial division and death rates, each of which has advantages and limitations. Technical bottlenecks, i.e., experimental sampling events, during the experiment can distort the rate estimates and are typically unaccounted for or require additional calibration experiments. In this work, we introduce RESTAMP (Rate Estimates by Sequence Tag Analysis of Microbial Populations) as a method for determining bacterial division and death rates. This method uses hundreds of fitness neutral sequence barcodes to measure the rates and account for experimental bottlenecks at the same time. We experimentally validate RESTAMP and compare it to established plasmid loss methods. We find that RESTAMP has a number of advantages over plasmid loss or previous marker based techniques. (i) It enables to correct the distortion of rate estimates by technical bottlenecks. (ii) Rate estimates are independent of the sequence tag distribution in the starting culture allowing the use of an arbitrary number of tags. (iii) It introduces a bottleneck sensitivity measure that can be used to maximize the accuracy of the experiment. RESTAMP allows studying microbial population dynamics with great resolution over a wide dynamic range and can thus advance our understanding of host-pathogen interactions or the mechanisms of antibiotic action. Research Network of Computational and Structural Biotechnology 2021-01-19 /pmc/articles/PMC7878984/ /pubmed/33613869 http://dx.doi.org/10.1016/j.csbj.2021.01.017 Text en © 2021 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Mahmutovic, Anel
Gillman, Aaron Nicholas
Lauksund, Silje
Robson Moe, Natasha-Anne
Manzi, Aime
Storflor, Merete
Abel zur Wiesch, Pia
Abel, Sören
RESTAMP – Rate estimates by sequence-tag analysis of microbial populations
title RESTAMP – Rate estimates by sequence-tag analysis of microbial populations
title_full RESTAMP – Rate estimates by sequence-tag analysis of microbial populations
title_fullStr RESTAMP – Rate estimates by sequence-tag analysis of microbial populations
title_full_unstemmed RESTAMP – Rate estimates by sequence-tag analysis of microbial populations
title_short RESTAMP – Rate estimates by sequence-tag analysis of microbial populations
title_sort restamp – rate estimates by sequence-tag analysis of microbial populations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7878984/
https://www.ncbi.nlm.nih.gov/pubmed/33613869
http://dx.doi.org/10.1016/j.csbj.2021.01.017
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