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Detecting rare gene transfer events in bacterial populations

Horizontal gene transfer (HGT) enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare e...

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Autores principales: Nielsen, Kaare M., Bøhn, Thomas, Townsend, Jeffrey P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3882822/
https://www.ncbi.nlm.nih.gov/pubmed/24432015
http://dx.doi.org/10.3389/fmicb.2013.00415
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author Nielsen, Kaare M.
Bøhn, Thomas
Townsend, Jeffrey P.
author_facet Nielsen, Kaare M.
Bøhn, Thomas
Townsend, Jeffrey P.
author_sort Nielsen, Kaare M.
collection PubMed
description Horizontal gene transfer (HGT) enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare events that lead to novel functions in the new host, and that exhibit a positive effect on host fitness. Conversely, the large majority of HGT events occurring in bacterial populations will go undetected due to lack of replication success of transformants. Moreover, other HGT events that would be highly beneficial to new hosts can fail to ensue due to lack of physical proximity to the donor organism, lack of a suitable gene transfer mechanism, genetic compatibility, and stochasticity in tempo-spatial occurrence. Experimental attempts to detect HGT events in bacterial populations have typically focused on the transformed cells or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to reach relative population sizes that will allow their immediate identification; the exception being the unusually strong positive selection conferred by antibiotics. Most HGT events are not expected to alter the likelihood of host survival to such an extreme extent, and will confer only minor changes in host fitness. Due to the large population sizes of bacteria and the time scales involved, the process and outcome of HGT are often not amenable to experimental investigation. Population genetic modeling of the growth dynamics of bacteria with differing HGT rates and resulting fitness changes is therefore necessary to guide sampling design and predict realistic time frames for detection of HGT, as it occurs in laboratory or natural settings. Here we review the key population genetic parameters, consider their complexity and highlight knowledge gaps for further research.
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spelling pubmed-38828222014-01-15 Detecting rare gene transfer events in bacterial populations Nielsen, Kaare M. Bøhn, Thomas Townsend, Jeffrey P. Front Microbiol Microbiology Horizontal gene transfer (HGT) enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare events that lead to novel functions in the new host, and that exhibit a positive effect on host fitness. Conversely, the large majority of HGT events occurring in bacterial populations will go undetected due to lack of replication success of transformants. Moreover, other HGT events that would be highly beneficial to new hosts can fail to ensue due to lack of physical proximity to the donor organism, lack of a suitable gene transfer mechanism, genetic compatibility, and stochasticity in tempo-spatial occurrence. Experimental attempts to detect HGT events in bacterial populations have typically focused on the transformed cells or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to reach relative population sizes that will allow their immediate identification; the exception being the unusually strong positive selection conferred by antibiotics. Most HGT events are not expected to alter the likelihood of host survival to such an extreme extent, and will confer only minor changes in host fitness. Due to the large population sizes of bacteria and the time scales involved, the process and outcome of HGT are often not amenable to experimental investigation. Population genetic modeling of the growth dynamics of bacteria with differing HGT rates and resulting fitness changes is therefore necessary to guide sampling design and predict realistic time frames for detection of HGT, as it occurs in laboratory or natural settings. Here we review the key population genetic parameters, consider their complexity and highlight knowledge gaps for further research. Frontiers Media S.A. 2014-01-07 /pmc/articles/PMC3882822/ /pubmed/24432015 http://dx.doi.org/10.3389/fmicb.2013.00415 Text en Copyright © 2014 Nielsen, Bøhn and Townsend. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Nielsen, Kaare M.
Bøhn, Thomas
Townsend, Jeffrey P.
Detecting rare gene transfer events in bacterial populations
title Detecting rare gene transfer events in bacterial populations
title_full Detecting rare gene transfer events in bacterial populations
title_fullStr Detecting rare gene transfer events in bacterial populations
title_full_unstemmed Detecting rare gene transfer events in bacterial populations
title_short Detecting rare gene transfer events in bacterial populations
title_sort detecting rare gene transfer events in bacterial populations
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3882822/
https://www.ncbi.nlm.nih.gov/pubmed/24432015
http://dx.doi.org/10.3389/fmicb.2013.00415
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