Biology subjects

Hilau, S.

Publications and source records attributed to Hilau, S..

3 recordsLinked to original sources

bioRxiv2022

Population level genetic memory of prior metabolic adaptation in E. coli

Bacteria must often survive following the exhaustion of their external growth resources. Fitting with this need, many bacterial species that cannot sporulate, can enter a state known as long term stationary phase (LTSP) in which they can persist for years within spent media. Several recent studies have revealed the dynamics of genetic adaptation of Escherichia coli under LTSP. Yet, the metabolic consequences of such genetic adaptation were not addressed. Here, we characterized the metabolic changes LTSP populations experience and link them to their genetic adaptation. We observed that during growth within fresh resources E. coli produces the short chain fatty acid butyrate, which wildtype E. coli cannot consume. Once resources are otherwise exhausted, E. coli adapts genetically to consume butyrate through the convergent, temporally precise emergence of mutation combinations within genes that regulate fatty acid metabolism. These mutations appear to negatively affect bacterial fitness when butyrate is not available, and hence rapidly decrease in frequency, once all butyrate is consumed. Yet despite this, E. coli populations show a remarkable capability of maintaining a population-level genetic memory of prior adaptation to consume butyrate. The maintenance of such a memory allows bacteria to rapidly re-adapt, at an ecological, rather than an evolutionary timeframe, to re-consume previously encountered metabolites.

evolutionary biology↗

bioRxiv2021

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

Although closely related genetically, bacterial strains belonging to the same species show significant variability in their growth and death dynamics. However, our understanding of the underlying processes that lead to this variability is still lacking. Here, we measured the growth and death dynamics of 11 strains of E. coli originating from different hosts and developed a mathematical model that captures their growth and death dynamics. Our model considers two environmental factors that determine growth dynamics: resource utilization efficiency and density-dependent growth inhibition. Here we show that both factors are required to capture the measured dynamics. Interestingly, our model results indicate that the main process that determines the major differences between the strains is the critical density at which they slow down their growth, rather than maximal growth rate or death rate. Finally, we found that bacterial growth and death dynamics can be reduced to only two dimensions and described by death rates and density-dependent growth inhibition alone. ImportanceUnderstanding the dynamics of bacterial growth has been an area of intense study. However, these dynamics have often been characterized through the narrow prism of describing growth rates, without considering parameters that may modulate these rates. Here, we generate a model that describes bacterial growth and death dynamics, incorporating two essential, growth-modulating factors: density-dependent reductions in growth rates and resource utilization efficiency. This model allows us to demonstrate that variation in the growth curves of closely related bacterial strains can be reduced to two dimensions and explained almost entirely by variation in the cellular density at which bacteria slow down their growth, combined with their death rates.

microbiology↗

bioRxiv2020

Dynamics of mutation accumulation and adaptation during three years of evolution under long-term stationary phase

Many bacterial species that cannot sporulate, such as the model bacterium Escherichia coli, can nevertheless survive for years under resource exhaustion, in a state termed long-term stationary phase (LTSP). Here we describe the dynamics of E. coli adaptation during the first three years spent under LTSP. We show that during this time E. coli continuously adapts genetically, through the accumulation of mutations. For non-mutator clones, the majority of mutations accumulated appear to be adaptive under LTSP, reflected in an extremely convergent pattern of mutation accumulation. Despite the rapid and convergent manner in which populations adapt under LTSP, they continue to harbor extensive genetic variation. The dynamics of evolution of mutation rates under LTSP are particularly interesting. The emergence of mutators, affects overall mutation accumulation rates as well as the mutational spectra and the ultimate spectrum of adaptive alleles acquired under LTSP. With time, mutators can evolve even higher mutation rates, through the acquisition of additional mutation-rate enhancing mutations. Different mutator and non-mutator clones within a single population and time point can display extreme variation in their mutation rates, resulting in differences in both the dynamics of adaptation and their associated deleterious burdens. Despite these differences, clones that vary greatly in their mutation rates tend to co-exist within their populations for many years, under LTSP.

evolutionary biology↗