A growth-survival trade-off quantitatively predicts microbial selection under periodic disinfection
AO_SCPLOWBSTRACTC_SCPLOWMicrobial populations frequently experience periodic lethal stresses from natural and anthropogenic sources, including routine disinfection in clinical, industrial, and domestic environments. However, periodic disinfection can rapidly select for tolerant strains with increased survival but reduced growth during permissive conditions, creating a trade-off that shapes competitive outcomes in microbial communities. Here, we develop a mathematical framework to quantify and predict selection between microbial strains competing for growth-limiting resources under periodic disinfection. The framework is validated through a competition experiment simulating periodic disinfection with benzalkonium chloride between a wild-type Escherichia coli strain and a tolerant mutant exhibiting increased survival but decreased growth. A minimal model incorporating growth rate during permissive conditions and disinfection survival quantitatively captures selection across different experimental scenarios, including uncertainty estimates propagated from parameter variance. We further provide analytical expressions and a web-based interface to determine selection outcomes and quantify the contributions of survival and growth rate to selection. Our framework establishes a quantitative basis for predicting when periodic disinfection shifts population composition towards tolerant strains and is generalizable to other lethal stresses, including antibiotic chemotherapy and physical inactivation, thereby contributing to our understanding of the impact of periodic selective pressures on microbial competition.