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Prediction of antibiotic resistance by gene expression profiles

Although many mutations contributing to antibiotic resistance have been identified, the relationship between the mutations and the related phenotypic changes responsible for the resistance has yet to be fully elucidated. To better characterize phenotype–genotype mapping for drug resistance, here we...

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Detalles Bibliográficos
Autores principales: Suzuki, Shingo, Horinouchi, Takaaki, Furusawa, Chikara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Pub. Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4351646/
https://www.ncbi.nlm.nih.gov/pubmed/25517437
http://dx.doi.org/10.1038/ncomms6792
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author Suzuki, Shingo
Horinouchi, Takaaki
Furusawa, Chikara
author_facet Suzuki, Shingo
Horinouchi, Takaaki
Furusawa, Chikara
author_sort Suzuki, Shingo
collection PubMed
description Although many mutations contributing to antibiotic resistance have been identified, the relationship between the mutations and the related phenotypic changes responsible for the resistance has yet to be fully elucidated. To better characterize phenotype–genotype mapping for drug resistance, here we analyse phenotypic and genotypic changes of antibiotic-resistant Escherichia coli strains obtained by laboratory evolution. We demonstrate that the resistances can be quantitatively predicted by the expression changes of a small number of genes. Several candidate mutations contributing to the resistances are identified, while phenotype–genotype mapping is suggested to be complex and includes various mutations that cause similar phenotypic changes. The integration of transcriptome and genome data enables us to extract essential phenotypic changes for drug resistances.
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spelling pubmed-43516462015-03-19 Prediction of antibiotic resistance by gene expression profiles Suzuki, Shingo Horinouchi, Takaaki Furusawa, Chikara Nat Commun Article Although many mutations contributing to antibiotic resistance have been identified, the relationship between the mutations and the related phenotypic changes responsible for the resistance has yet to be fully elucidated. To better characterize phenotype–genotype mapping for drug resistance, here we analyse phenotypic and genotypic changes of antibiotic-resistant Escherichia coli strains obtained by laboratory evolution. We demonstrate that the resistances can be quantitatively predicted by the expression changes of a small number of genes. Several candidate mutations contributing to the resistances are identified, while phenotype–genotype mapping is suggested to be complex and includes various mutations that cause similar phenotypic changes. The integration of transcriptome and genome data enables us to extract essential phenotypic changes for drug resistances. Nature Pub. Group 2014-12-17 /pmc/articles/PMC4351646/ /pubmed/25517437 http://dx.doi.org/10.1038/ncomms6792 Text en Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Suzuki, Shingo
Horinouchi, Takaaki
Furusawa, Chikara
Prediction of antibiotic resistance by gene expression profiles
title Prediction of antibiotic resistance by gene expression profiles
title_full Prediction of antibiotic resistance by gene expression profiles
title_fullStr Prediction of antibiotic resistance by gene expression profiles
title_full_unstemmed Prediction of antibiotic resistance by gene expression profiles
title_short Prediction of antibiotic resistance by gene expression profiles
title_sort prediction of antibiotic resistance by gene expression profiles
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4351646/
https://www.ncbi.nlm.nih.gov/pubmed/25517437
http://dx.doi.org/10.1038/ncomms6792
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