权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Evolutionary Tradeoffs in Antibiotic Resistance

抗生素耐药性的进化权衡

基本信息

批准号：
10622495
负责人：
Michael Baym
金额：
$ 41.87万
依托单位：
HARVARD MEDICAL SCHOOL
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-01 至 2024-05-31
项目状态：
已结题

项目摘要

Antibiotic resistance emerges when a mutation in a bacterium causes a previously inhibitory concentration of a compound to become survivable. Through the accumulation of mutations conferring varying increases in resistance, already many easy-to-treat infections have become nearly incurable, and are spreading in part anthropogenically. The classical model of resistance evolution, that a resistant mutant has a fitness advantage in the presence of antibiotic use, and so spreads in the population to near-fixation, captures the rise of antibiotic resistance, but on closer inspection fails to explain several critical features of resistance. First, antibiotic resistance rarely reaches fixation in clinical populations; more importantly, sensitivity is higher than the population-genetic models would predict. Second, antibiotic resistance was present, and likely common, in clinical infections before the human use of antibiotics even began. Third, despite the widespread prevalence of antibiotic-producing bacteria in the environment, these same bacteria remain surrounded by sensitive neighbors. For these reasons, we hypothesize that the existing model of resistance evolution is incomplete, and in particular that there exist evolutionary factors in the environment which have a potentially countervailing effect on resistance evolution of similar or greater magnitude to the human use of antibiotics. Here, we will combine evolution experiments in model systems with computational modeling and database mining of sequence data to study the constraints on the evolution of resistance, focusing on two key areas: the role of spatial structure in the evolution of resistance, and the role of selfish genetic elements including phages and parasitic plasmids. Resistance provides an almost ideal model system for the study of microbial evolution; fitness can be well defined, imposed selective pressures can be readily tuned, and can emerge either spontaneously or by horizontal gene transfer. We expect to uncover the evolutionary mechanisms behind the emergence, spread, and limitation of antibiotic resistance.

当细菌的突变导致a的先前抑制浓度时，抗生素耐药性就出现了

项目成果

期刊论文数量（9）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Efficient and Robust Search of Microbial Genomes via Phylogenetic Compression.

通过系统发育压缩对微生物基因组进行高效、稳健的搜索。

DOI：
10.1101/2023.04.15.536996
发表时间：
2023
期刊：
bioRxiv : the preprint server for biology
影响因子：
0
作者：
Břinda,Karel;Lima,Leandro;Pignotti,Simone;Quinones-Olvera,Natalia;Salikhov,Kamil;Chikhi,Rayan;Kucherov,Gregory;Iqbal,Zamin;Baym,Michael
通讯作者：
Baym,Michael

Optimal SARS-CoV-2 vaccine allocation using real-time seroprevalence estimates in Rhode Island and Massachusetts.

使用罗德岛州和马萨诸塞州的实时血清流行率估计来优化 SARS-CoV-2 疫苗分配。

DOI：
10.1101/2021.01.12.21249694
发表时间：
2021
期刊：
medRxiv : the preprint server for health sciences
影响因子：
0
作者：
Tran,ThuNguyen-Anh;Wikle,Nathan;Albert,Joseph;Inam,Haider;Strong,Emily;Brinda,Karel;Leighow,ScottM;Yang,Fuhan;Hossain,Sajid;Pritchard,JustinR;Chan,Philip;Hanage,WilliamP;Hanks,EphraimM;Boni,MaciejF
通讯作者：
Boni,MaciejF

Decreased thermal niche breadth as a trade-off of antibiotic resistance.

热生态位宽度的减少是抗生素耐药性的权衡。

DOI：
10.1038/s41396-022-01235-6
发表时间：
2022-07
期刊：
ISME JOURNAL
影响因子：
11
作者：
Herren, Cristina M.;Baym, Michael
通讯作者：
Baym, Michael

Prophages encode phage-defense systems with cognate self-immunity.

DOI：
10.1016/j.chom.2021.09.002
发表时间：
2021-11-10
期刊：
Cell host & microbe
影响因子：
30.3
作者：
Owen SV;Wenner N;Dulberger CL;Rodwell EV;Bowers-Barnard A;Quinones-Olvera N;Rigden DJ;Rubin EJ;Garner EC;Baym M;Hinton JCD
通讯作者：
Hinton JCD

Resolving Deleterious and Near-Neutral Effects Requires Different Pooled Fitness Assay Designs.

解决有害和近中性的影响需要不同的混合适应性检测设计。