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Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes

Bacterial pathogens evolve during the infection of their human hosts(1-8), but separating adaptive and neutral mutations remains challenging(9-11). Here, we identify bacterial genes under adaptive evolution by tracking recurrent patterns of mutations in the same pathogenic strain during the infectio...

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Autores principales: Lieberman, Tami D., Michel, Jean-Baptiste, Aingaran, Mythili, Potter-Bynoe, Gail, Roux, Damien, Davis, Michael R., Skurnik, David, Leiby, Nicholas, LiPuma, John J., Goldberg, Joanna B., McAdam, Alexander J., Priebe, Gregory P., Kishony, Roy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245322/
https://www.ncbi.nlm.nih.gov/pubmed/22081229
http://dx.doi.org/10.1038/ng.997
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author Lieberman, Tami D.
Michel, Jean-Baptiste
Aingaran, Mythili
Potter-Bynoe, Gail
Roux, Damien
Davis, Michael R.
Skurnik, David
Leiby, Nicholas
LiPuma, John J.
Goldberg, Joanna B.
McAdam, Alexander J.
Priebe, Gregory P.
Kishony, Roy
author_facet Lieberman, Tami D.
Michel, Jean-Baptiste
Aingaran, Mythili
Potter-Bynoe, Gail
Roux, Damien
Davis, Michael R.
Skurnik, David
Leiby, Nicholas
LiPuma, John J.
Goldberg, Joanna B.
McAdam, Alexander J.
Priebe, Gregory P.
Kishony, Roy
author_sort Lieberman, Tami D.
collection PubMed
description Bacterial pathogens evolve during the infection of their human hosts(1-8), but separating adaptive and neutral mutations remains challenging(9-11). Here, we identify bacterial genes under adaptive evolution by tracking recurrent patterns of mutations in the same pathogenic strain during the infection of multiple patients. We conducted a retrospective study of a Burkholderia dolosa outbreak among people with cystic fibrosis, sequencing the genomes of 112 isolates collected from 14 individuals over 16 years. We find that 17 bacterial genes acquired non-synonymous mutations in multiple individuals, which indicates parallel adaptive evolution. Mutations in these genes illuminate the genetic basis of important pathogenic phenotypes, including antibiotic resistance and bacterial membrane composition, and implicate oxygen-dependent gene regulation as paramount in lung infections. Several genes have not been previously implicated in pathogenesis, suggesting new therapeutic targets. The identification of parallel molecular evolution suggests key selection forces acting on pathogens within humans and can help predict and prepare for their future evolutionary course.
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spelling pubmed-32453222012-06-01 Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes Lieberman, Tami D. Michel, Jean-Baptiste Aingaran, Mythili Potter-Bynoe, Gail Roux, Damien Davis, Michael R. Skurnik, David Leiby, Nicholas LiPuma, John J. Goldberg, Joanna B. McAdam, Alexander J. Priebe, Gregory P. Kishony, Roy Nat Genet Article Bacterial pathogens evolve during the infection of their human hosts(1-8), but separating adaptive and neutral mutations remains challenging(9-11). Here, we identify bacterial genes under adaptive evolution by tracking recurrent patterns of mutations in the same pathogenic strain during the infection of multiple patients. We conducted a retrospective study of a Burkholderia dolosa outbreak among people with cystic fibrosis, sequencing the genomes of 112 isolates collected from 14 individuals over 16 years. We find that 17 bacterial genes acquired non-synonymous mutations in multiple individuals, which indicates parallel adaptive evolution. Mutations in these genes illuminate the genetic basis of important pathogenic phenotypes, including antibiotic resistance and bacterial membrane composition, and implicate oxygen-dependent gene regulation as paramount in lung infections. Several genes have not been previously implicated in pathogenesis, suggesting new therapeutic targets. The identification of parallel molecular evolution suggests key selection forces acting on pathogens within humans and can help predict and prepare for their future evolutionary course. 2011-11-13 /pmc/articles/PMC3245322/ /pubmed/22081229 http://dx.doi.org/10.1038/ng.997 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Lieberman, Tami D.
Michel, Jean-Baptiste
Aingaran, Mythili
Potter-Bynoe, Gail
Roux, Damien
Davis, Michael R.
Skurnik, David
Leiby, Nicholas
LiPuma, John J.
Goldberg, Joanna B.
McAdam, Alexander J.
Priebe, Gregory P.
Kishony, Roy
Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes
title Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes
title_full Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes
title_fullStr Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes
title_full_unstemmed Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes
title_short Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes
title_sort parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245322/
https://www.ncbi.nlm.nih.gov/pubmed/22081229
http://dx.doi.org/10.1038/ng.997
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