Density-dependent effects are the main determinants of variation in growth dynamics between closely related bacterial strains

Although closely related, bacterial strains from the same species show significant diversity in their growth and death dynamics. Yet, our understanding of the relationship between the kinetic parameters that dictate these dynamics is still lacking. Here, we measured the growth and death dynamics of 11 strains of Escherichia coli originating from different hosts and show that the growth patterns are clustered into three major classes with typical growth rates, maximal fold change, and death rates. To infer the underlying phenotypic parameters that govern the dynamics, we developed a phenomenological mathematical model that accounts not only for growth rate and its dependence on resource availability, but also for death rates and density-dependent growth inhibition. We show that density-dependent growth is essential for capturing the variability in growth dynamics between the strains. Indeed, the main parameter determining the dynamics is the typical density at which they slow down their growth, rather than the maximal growth rate or death rate. Moreover, we show that the phenotypic landscape resides within a two-dimensional plane spanned by resource utilization efficiency, death rate, and density-dependent growth inhibition. In this phenotypic plane, we identify three clusters that correspond to the growth pattern classes. Overall, our results reveal the tradeoffs between growth parameters that constrain bacterial adaptation.Author summary: Even bacteria within the same strain have significant variability in their parameters that dictates their growth dynamics, such as maximal growth rate and death rate. The tradeoffs between these different parameters affect bacteria’s ability to adapt to different environments. Here, we analyzed strains of the bacteria Escherichia coli from different animal hosts and showed that their growth dynamics are clustered into three typical classes. To understand the underlying processes that dictate this variability, we developed a mathematical model and used it to infer the kinetic parameters of each strain. Our results show that a density-dependent growth term is crucial to explaining the experimental data. We show that the primary determinant of maximal biomass of each strain is not its maximal growth rate or death rate but rather the critical density at which growth is inhibited. We characterize the tradeoffs between the different kinetic parameters and show that the difference between the strains can be reduced to a two-dimensional plane. In this plane, the strains are divided into three main types with different kinetic parameters that define the typical growth patterns. Our results show how the tradeoffs between different growth parameters constrain growth dynamics and the ability of bacteria to adapt to different environments.