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Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes

Genotype-fitness maps of evolution have been well characterized for biological components, such as RNA and proteins, but remain less clear for systems-level properties, such as those of metabolic and transcriptional regulatory networks. Here, we take multi-omics measurements of 6 different E. coli s...

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Autores principales: Kavvas, Erol S., Long, Christopher P., Sastry, Anand, Poudel, Saugat, Antoniewicz, Maciek R., Ding, Yang, Mohamed, Elsayed T., Szubin, Richard, Monk, Jonathan M., Feist, Adam M., Palsson, Bernhard O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9765567/
https://www.ncbi.nlm.nih.gov/pubmed/36226969
http://dx.doi.org/10.1128/msystems.00165-22
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author Kavvas, Erol S.
Long, Christopher P.
Sastry, Anand
Poudel, Saugat
Antoniewicz, Maciek R.
Ding, Yang
Mohamed, Elsayed T.
Szubin, Richard
Monk, Jonathan M.
Feist, Adam M.
Palsson, Bernhard O.
author_facet Kavvas, Erol S.
Long, Christopher P.
Sastry, Anand
Poudel, Saugat
Antoniewicz, Maciek R.
Ding, Yang
Mohamed, Elsayed T.
Szubin, Richard
Monk, Jonathan M.
Feist, Adam M.
Palsson, Bernhard O.
author_sort Kavvas, Erol S.
collection PubMed
description Genotype-fitness maps of evolution have been well characterized for biological components, such as RNA and proteins, but remain less clear for systems-level properties, such as those of metabolic and transcriptional regulatory networks. Here, we take multi-omics measurements of 6 different E. coli strains throughout adaptive laboratory evolution (ALE) to maximal growth fitness. The results show the following: (i) convergence in most overall phenotypic measures across all strains, with the notable exception of divergence in NADPH production mechanisms; (ii) conserved transcriptomic adaptations, describing increased expression of growth promoting genes but decreased expression of stress response and structural components; (iii) four groups of regulatory trade-offs underlying the adjustment of transcriptome composition; and (iv) correlates that link causal mutations to systems-level adaptations, including mutation-pathway flux correlates and mutation-transcriptome composition correlates. We thus show that fitness landscapes for ALE can be described with two layers of causation: one based on system-level properties (continuous variables) and the other based on mutations (discrete variables). IMPORTANCE Understanding the mechanisms of microbial adaptation will help combat the evolution of drug-resistant microbes and enable predictive genome design. Although experimental evolution allows us to identify the causal mutations underlying microbial adaptation, it remains unclear how causal mutations enable increased fitness and is often explained in terms of individual components (i.e., enzyme rate) as opposed to biological systems (i.e., pathways). Here, we find that causal mutations in E. coli are linked to systems-level changes in NADPH balance and expression of stress response genes. These systems-level adaptation patterns are conserved across diverse E. coli strains and thus identify cofactor balance and proteome reallocation as dominant constraints governing microbial adaptation.
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spelling pubmed-97655672022-12-21 Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes Kavvas, Erol S. Long, Christopher P. Sastry, Anand Poudel, Saugat Antoniewicz, Maciek R. Ding, Yang Mohamed, Elsayed T. Szubin, Richard Monk, Jonathan M. Feist, Adam M. Palsson, Bernhard O. mSystems Research Article Genotype-fitness maps of evolution have been well characterized for biological components, such as RNA and proteins, but remain less clear for systems-level properties, such as those of metabolic and transcriptional regulatory networks. Here, we take multi-omics measurements of 6 different E. coli strains throughout adaptive laboratory evolution (ALE) to maximal growth fitness. The results show the following: (i) convergence in most overall phenotypic measures across all strains, with the notable exception of divergence in NADPH production mechanisms; (ii) conserved transcriptomic adaptations, describing increased expression of growth promoting genes but decreased expression of stress response and structural components; (iii) four groups of regulatory trade-offs underlying the adjustment of transcriptome composition; and (iv) correlates that link causal mutations to systems-level adaptations, including mutation-pathway flux correlates and mutation-transcriptome composition correlates. We thus show that fitness landscapes for ALE can be described with two layers of causation: one based on system-level properties (continuous variables) and the other based on mutations (discrete variables). IMPORTANCE Understanding the mechanisms of microbial adaptation will help combat the evolution of drug-resistant microbes and enable predictive genome design. Although experimental evolution allows us to identify the causal mutations underlying microbial adaptation, it remains unclear how causal mutations enable increased fitness and is often explained in terms of individual components (i.e., enzyme rate) as opposed to biological systems (i.e., pathways). Here, we find that causal mutations in E. coli are linked to systems-level changes in NADPH balance and expression of stress response genes. These systems-level adaptation patterns are conserved across diverse E. coli strains and thus identify cofactor balance and proteome reallocation as dominant constraints governing microbial adaptation. American Society for Microbiology 2022-10-13 /pmc/articles/PMC9765567/ /pubmed/36226969 http://dx.doi.org/10.1128/msystems.00165-22 Text en Copyright © 2022 Kavvas et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Kavvas, Erol S.
Long, Christopher P.
Sastry, Anand
Poudel, Saugat
Antoniewicz, Maciek R.
Ding, Yang
Mohamed, Elsayed T.
Szubin, Richard
Monk, Jonathan M.
Feist, Adam M.
Palsson, Bernhard O.
Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes
title Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes
title_full Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes
title_fullStr Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes
title_full_unstemmed Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes
title_short Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes
title_sort experimental evolution reveals unifying systems-level adaptations but diversity in driving genotypes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9765567/
https://www.ncbi.nlm.nih.gov/pubmed/36226969
http://dx.doi.org/10.1128/msystems.00165-22
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