量化抗生素耐药性的遗传决定因素对细菌谱系动力学的影响。

David Helekal, Tatum D Mortimer, Aditi Mukherjee, Gabriella Gentile, Adriana Le Van, Robert A Nicholas, Ann E Jerse, Samantha G Palace, Yonatan H Grad
{"title":"量化抗生素耐药性的遗传决定因素对细菌谱系动力学的影响。","authors":"David Helekal, Tatum D Mortimer, Aditi Mukherjee, Gabriella Gentile, Adriana Le Van, Robert A Nicholas, Ann E Jerse, Samantha G Palace, Yonatan H Grad","doi":"10.1101/2025.02.03.636319","DOIUrl":null,"url":null,"abstract":"<p><p>The dynamics of antimicrobial resistance in bacterial populations are informed by the fitness impact of genetic determinants of resistance and antibiotic pressure. However, estimates of real-world fitness impact have been lacking. To address this gap, we developed a hierarchical Bayesian phylodynamic model to quantify contributions of resistance determinants to strain success in a 20-year collection of <i>Neisseria gonorrhoeae</i> isolates. Fitness contributions varied with antibiotic use, and genetic pathways to phenotypically identical resistance conferred distinct fitness effects. These findings were supported by <i>in vitro</i> and experimental infection competition. Quantifying these fitness contributions to lineage dynamics reveals opportunities for investigation into other genetic and environmental drivers of fitness. This work thus establishes a method for linking pathogen genomics and antibiotic use to define factors shaping ecological trends.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11838577/pdf/","citationCount":"0","resultStr":"{\"title\":\"Quantifying the impact of antibiotic use and genetic determinants of resistance on bacterial lineage dynamics.\",\"authors\":\"David Helekal, Tatum D Mortimer, Aditi Mukherjee, Gabriella Gentile, Adriana Le Van, Robert A Nicholas, Ann E Jerse, Samantha G Palace, Yonatan H Grad\",\"doi\":\"10.1101/2025.02.03.636319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The dynamics of antimicrobial resistance in bacterial populations are informed by the fitness impact of genetic determinants of resistance and antibiotic pressure. However, estimates of real-world fitness impact have been lacking. To address this gap, we developed a hierarchical Bayesian phylodynamic model to quantify contributions of resistance determinants to strain success in a 20-year collection of <i>Neisseria gonorrhoeae</i> isolates. Fitness contributions varied with antibiotic use, and genetic pathways to phenotypically identical resistance conferred distinct fitness effects. These findings were supported by <i>in vitro</i> and experimental infection competition. Quantifying these fitness contributions to lineage dynamics reveals opportunities for investigation into other genetic and environmental drivers of fitness. This work thus establishes a method for linking pathogen genomics and antibiotic use to define factors shaping ecological trends.</p>\",\"PeriodicalId\":519960,\"journal\":{\"name\":\"bioRxiv : the preprint server for biology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11838577/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"bioRxiv : the preprint server for biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2025.02.03.636319\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv : the preprint server for biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2025.02.03.636319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

细菌抗菌素耐药性的动态是由存在抗生素压力时耐药性的遗传决定因素所赋予的适应度优势和没有抗生素压力时潜在的适应度成本所决定的。然而,考虑到多药耐药、多种耐药途径以及药物暴露的不确定性,缺乏对现实世界适应度影响的定量估计框架。在这里,我们通过分析20多年来从美国各地收集的淋病奈瑟菌临床分离株的基因组序列,以及国家抗生素治疗数据,解决了这些挑战。使用层次贝叶斯系统动力学模型,我们量化了抗性决定因素对菌株成功的贡献。当使用同源抗生素时,抗性突变具有适应度优势,但在其他情况下并不总是产生适应度成本。在不再使用氟喹诺酮类药物治疗后,gyrA同一部位的两个氟喹诺酮类药物耐药突变对适应度的影响不同,这一发现得到了体外竞争实验的支持。适应度成本通过损失昂贵的抗性决定因素而减轻,并通过获得新的适应度抗性决定因素来抵消。对抗性决定因素解释每个谱系动态的程度进行量化,突出了差距,并指出了研究其他遗传和环境驱动因素的机会。因此,这项工作建立了一种将病原体基因组学和抗生素使用模式联系起来的方法,以量化抗性决定因素的适应性影响和形成生态趋势的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Quantifying the impact of antibiotic use and genetic determinants of resistance on bacterial lineage dynamics.

The dynamics of antimicrobial resistance in bacterial populations are informed by the fitness impact of genetic determinants of resistance and antibiotic pressure. However, estimates of real-world fitness impact have been lacking. To address this gap, we developed a hierarchical Bayesian phylodynamic model to quantify contributions of resistance determinants to strain success in a 20-year collection of Neisseria gonorrhoeae isolates. Fitness contributions varied with antibiotic use, and genetic pathways to phenotypically identical resistance conferred distinct fitness effects. These findings were supported by in vitro and experimental infection competition. Quantifying these fitness contributions to lineage dynamics reveals opportunities for investigation into other genetic and environmental drivers of fitness. This work thus establishes a method for linking pathogen genomics and antibiotic use to define factors shaping ecological trends.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Unified imputation of missing data modalities and features in multi-omic data via shared representation learning. Frequency-dependent cerebellar circuits independently gate social vocalizations and movement. Proteome landscape of B-cell malignancies identifies mantle cell lymphoma protein signature. COMBO-RATE: An experimentally validated bioinformatic tool to identify promiscuous HLA restrictions. Meta-learning is expressed through altered prefrontal cortical dynamics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1