Mapping single-cell responses to population-level dynamics during antibiotic treatment

被引:4
|
作者
Kim, Kyeri [1 ,2 ]
Wang, Teng [1 ,2 ]
Ma, Helena R. [1 ,2 ]
Simsek, Emrah [1 ,2 ]
Li, Boyan [3 ]
Andreani, Virgile [4 ,5 ]
You, Lingchong [1 ,2 ,6 ,7 ]
机构
[1] Duke Univ, Dept Biomed Engn, Durham, NC 27708 USA
[2] Duke Univ, Ctr Quantitat Biodesign, Durham, NC 27708 USA
[3] Peking Univ, Yuanpei Coll, Integrated Sci Program, Beijing, Peoples R China
[4] Boston Univ, Biomed Engn Dept, Boston, MA USA
[5] Boston Univ, Biol Design Ctr, Boston, MA USA
[6] Duke Univ, Ctr Genom & Computat Biol, Durham, NC 27708 USA
[7] Duke Univ, Sch Med, Dept Mol Genet & Microbiol, Durham, NC 27708 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
antibiotic response; bacterial population dynamics; filamentation; quantitative biology; single-cell analysis; BETA-LACTAM ANTIBIOTICS; ESCHERICHIA-COLI; DIVISION; ELONGATION; BACTERIA; SHAPE; SIZE;
D O I
10.15252/msb.202211475
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Treatment of sensitive bacteria with beta-lactam antibiotics often leads to two salient population-level features: a transient increase in total population biomass before a subsequent decline, and a linear correlation between growth and killing rates. However, it remains unclear how these population-level responses emerge from collective single-cell responses. During beta-lactam treatment, it is well-recognized that individual cells often exhibit varying degrees of filamentation before lysis. We show that the cumulative probability of cell lysis increases sigmoidally with the extent of filamentation and that this dependence is characterized by unique parameters that are specific to bacterial strain, antibiotic dose, and growth condition. Modeling demonstrates how the single-cell lysis probabilities can give rise to population-level biomass dynamics, which were experimentally validated. This mapping provides insights into how the population biomass time-kill curve emerges from single cells and allows the representation of both single- and population-level responses with universal parameters.
引用
收藏
页数:13
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