Natalie Ann Lozano-Huntelman, Emoni Cook, Austin Bullivant, Nick Ida, April Zhou, Sada Boyd, Pamela J Yeh
{"title":"Interactions within higher-order antibiotic combinations do not influence the rate of adaptation in bacteria.","authors":"Natalie Ann Lozano-Huntelman, Emoni Cook, Austin Bullivant, Nick Ida, April Zhou, Sada Boyd, Pamela J Yeh","doi":"10.1093/evolut/qpaf023","DOIUrl":null,"url":null,"abstract":"<p><p>The prevalence and strength of antibiotic resistance has led to an ongoing battle between the development of new treatments and the evolution of resistance. Combining multiple drugs simultaneously is a potential solution for combating antibiotic resistance. However, this approach introduces new factors that must be considered, including the influence of drug interactions on the rate of resistance evolution. When antibiotics are used in combination, their effects can be additive, synergistic, or antagonistic. In this study, we investigated the effect of higher-order interactions involving three drugs on resistance evolution in Staphylococcus epidermidis. Previous studies have shown that synergistic interactions can increase the adaptation rate. However, the effects of higher-order interactions on rates of adaptation are unclear. We investigated the adaptation of Staphylococcus epidermidis to single-, two-, and three-drug environments to assess how interactions within drug combinations influence the rate of adaptation. We analyzed both the overall interaction and emergent interaction, the latter being a unique interaction that occurs in three-drug combinations due to the presence of all three drugs, rather than simply strong pairwise interactions. Our results show that neither the overall interactions nor the emergent interactions affect adaptation rates.</p>","PeriodicalId":12082,"journal":{"name":"Evolution","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evolution","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1093/evolut/qpaf023","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The prevalence and strength of antibiotic resistance has led to an ongoing battle between the development of new treatments and the evolution of resistance. Combining multiple drugs simultaneously is a potential solution for combating antibiotic resistance. However, this approach introduces new factors that must be considered, including the influence of drug interactions on the rate of resistance evolution. When antibiotics are used in combination, their effects can be additive, synergistic, or antagonistic. In this study, we investigated the effect of higher-order interactions involving three drugs on resistance evolution in Staphylococcus epidermidis. Previous studies have shown that synergistic interactions can increase the adaptation rate. However, the effects of higher-order interactions on rates of adaptation are unclear. We investigated the adaptation of Staphylococcus epidermidis to single-, two-, and three-drug environments to assess how interactions within drug combinations influence the rate of adaptation. We analyzed both the overall interaction and emergent interaction, the latter being a unique interaction that occurs in three-drug combinations due to the presence of all three drugs, rather than simply strong pairwise interactions. Our results show that neither the overall interactions nor the emergent interactions affect adaptation rates.
期刊介绍:
Evolution, published for the Society for the Study of Evolution, is the premier publication devoted to the study of organic evolution and the integration of the various fields of science concerned with evolution. The journal presents significant and original results that extend our understanding of evolutionary phenomena and processes.