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Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics
Changes in an organism’s environment, genome, or gene expression patterns can lead to changes in its metabolism. The metabolic phenotype can be under selection and contributes to adaptation. However, the networked and convoluted nature of an organism’s metabolism makes relating mutations, metabolic...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665018/ https://www.ncbi.nlm.nih.gov/pubmed/37991493 http://dx.doi.org/10.7554/eLife.87039 |
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author | Favate, John S Skalenko, Kyle S Chiles, Eric Su, Xiaoyang Yadavalli, Srujana Samhita Shah, Premal |
author_facet | Favate, John S Skalenko, Kyle S Chiles, Eric Su, Xiaoyang Yadavalli, Srujana Samhita Shah, Premal |
author_sort | Favate, John S |
collection | PubMed |
description | Changes in an organism’s environment, genome, or gene expression patterns can lead to changes in its metabolism. The metabolic phenotype can be under selection and contributes to adaptation. However, the networked and convoluted nature of an organism’s metabolism makes relating mutations, metabolic changes, and effects on fitness challenging. To overcome this challenge, we use the long-term evolution experiment (LTEE) with E. coli as a model to understand how mutations can eventually affect metabolism and perhaps fitness. We used mass spectrometry to broadly survey the metabolomes of the ancestral strains and all 12 evolved lines. We combined this metabolic data with mutation and expression data to suggest how mutations that alter specific reaction pathways, such as the biosynthesis of nicotinamide adenine dinucleotide, might increase fitness in the system. Our work provides a better understanding of how mutations might affect fitness through the metabolic changes in the LTEE and thus provides a major step in developing a complete genotype–phenotype map for this experimental system. |
format | Online Article Text |
id | pubmed-10665018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-106650182023-11-22 Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics Favate, John S Skalenko, Kyle S Chiles, Eric Su, Xiaoyang Yadavalli, Srujana Samhita Shah, Premal eLife Evolutionary Biology Changes in an organism’s environment, genome, or gene expression patterns can lead to changes in its metabolism. The metabolic phenotype can be under selection and contributes to adaptation. However, the networked and convoluted nature of an organism’s metabolism makes relating mutations, metabolic changes, and effects on fitness challenging. To overcome this challenge, we use the long-term evolution experiment (LTEE) with E. coli as a model to understand how mutations can eventually affect metabolism and perhaps fitness. We used mass spectrometry to broadly survey the metabolomes of the ancestral strains and all 12 evolved lines. We combined this metabolic data with mutation and expression data to suggest how mutations that alter specific reaction pathways, such as the biosynthesis of nicotinamide adenine dinucleotide, might increase fitness in the system. Our work provides a better understanding of how mutations might affect fitness through the metabolic changes in the LTEE and thus provides a major step in developing a complete genotype–phenotype map for this experimental system. eLife Sciences Publications, Ltd 2023-11-22 /pmc/articles/PMC10665018/ /pubmed/37991493 http://dx.doi.org/10.7554/eLife.87039 Text en © 2023, Favate et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Evolutionary Biology Favate, John S Skalenko, Kyle S Chiles, Eric Su, Xiaoyang Yadavalli, Srujana Samhita Shah, Premal Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics |
title | Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics |
title_full | Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics |
title_fullStr | Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics |
title_full_unstemmed | Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics |
title_short | Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics |
title_sort | linking genotypic and phenotypic changes in the e. coli long-term evolution experiment using metabolomics |
topic | Evolutionary Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665018/ https://www.ncbi.nlm.nih.gov/pubmed/37991493 http://dx.doi.org/10.7554/eLife.87039 |
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