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Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution

Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity toward other antibiotics, offers treatment opportunities to constrain or reverse the evolution of antibiotic resistance. The applicability of CS-informed treatments remains uncertain, in part because we...

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Autores principales: Liakopoulos, Apostolos, Aulin, Linda B. S., Buffoni, Matteo, Fragkiskou, Efthymia, Coen van Hasselt, J. G., Rozen, Daniel E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170170/
https://www.ncbi.nlm.nih.gov/pubmed/35476512
http://dx.doi.org/10.1073/pnas.2121768119
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author Liakopoulos, Apostolos
Aulin, Linda B. S.
Buffoni, Matteo
Fragkiskou, Efthymia
Coen van Hasselt, J. G.
Rozen, Daniel E.
author_facet Liakopoulos, Apostolos
Aulin, Linda B. S.
Buffoni, Matteo
Fragkiskou, Efthymia
Coen van Hasselt, J. G.
Rozen, Daniel E.
author_sort Liakopoulos, Apostolos
collection PubMed
description Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity toward other antibiotics, offers treatment opportunities to constrain or reverse the evolution of antibiotic resistance. The applicability of CS-informed treatments remains uncertain, in part because we lack an understanding of the generality of CS effects for different resistance mutations, singly or in combination. Here, we address this issue in the gram-positive pathogen Streptococcus pneumoniae by measuring collateral and fitness effects of clinically relevant gyrA and parC alleles and their combinations that confer resistance to fluoroquinolones. We integrated these results in a mathematical model that allowed us to evaluate how different in silico combination treatments impact the dynamics of resistance evolution. We identified common and conserved CS effects of different gyrA and parC alleles; however, the spectrum of collateral effects was unique for each allele or allelic pair. This indicated that allelic identity can impact the evolutionary dynamics of resistance evolution during monotreatment and combination treatment. Our model simulations, which included the experimentally derived antibiotic susceptibilities and fitness effects, and antibiotic-specific pharmacodynamics revealed that both collateral and fitness effects impact the population dynamics of resistance evolution. Overall, we provide evidence that allelic identity and interactions can have a pronounced impact on collateral effects to different antibiotics and suggest that these need to be considered in models examining CS-based therapies.
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spelling pubmed-91701702022-06-07 Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution Liakopoulos, Apostolos Aulin, Linda B. S. Buffoni, Matteo Fragkiskou, Efthymia Coen van Hasselt, J. G. Rozen, Daniel E. Proc Natl Acad Sci U S A Biological Sciences Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity toward other antibiotics, offers treatment opportunities to constrain or reverse the evolution of antibiotic resistance. The applicability of CS-informed treatments remains uncertain, in part because we lack an understanding of the generality of CS effects for different resistance mutations, singly or in combination. Here, we address this issue in the gram-positive pathogen Streptococcus pneumoniae by measuring collateral and fitness effects of clinically relevant gyrA and parC alleles and their combinations that confer resistance to fluoroquinolones. We integrated these results in a mathematical model that allowed us to evaluate how different in silico combination treatments impact the dynamics of resistance evolution. We identified common and conserved CS effects of different gyrA and parC alleles; however, the spectrum of collateral effects was unique for each allele or allelic pair. This indicated that allelic identity can impact the evolutionary dynamics of resistance evolution during monotreatment and combination treatment. Our model simulations, which included the experimentally derived antibiotic susceptibilities and fitness effects, and antibiotic-specific pharmacodynamics revealed that both collateral and fitness effects impact the population dynamics of resistance evolution. Overall, we provide evidence that allelic identity and interactions can have a pronounced impact on collateral effects to different antibiotics and suggest that these need to be considered in models examining CS-based therapies. National Academy of Sciences 2022-04-27 2022-05-03 /pmc/articles/PMC9170170/ /pubmed/35476512 http://dx.doi.org/10.1073/pnas.2121768119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Liakopoulos, Apostolos
Aulin, Linda B. S.
Buffoni, Matteo
Fragkiskou, Efthymia
Coen van Hasselt, J. G.
Rozen, Daniel E.
Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution
title Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution
title_full Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution
title_fullStr Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution
title_full_unstemmed Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution
title_short Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution
title_sort allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170170/
https://www.ncbi.nlm.nih.gov/pubmed/35476512
http://dx.doi.org/10.1073/pnas.2121768119
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