Microbial population dynamics and evolutionary outcomes under extreme energy limitation

Abstract

Microorganisms commonly inhabit energy-limited ecosystems where cellular maintenance and reproduction is highly constrained. To gain insight into how individuals persist under such conditions, we derived demographic parameters from a collection of 21 heterotrophic bacterial taxa by censusing 100 populations in an effectively closed system for 1,000 d. All but one taxon survived prolonged resource scarcity, yielding estimated times to extinction ranging over four orders of magnitude from 100 to 105 y. Our findings corroborate reports of long-lived bacteria recovered from ancient environmental samples, while providing insight into mechanisms of persistence. As death rates declined over time, lifespan was extended through the scavenging of dead cells. Although reproduction was suppressed in the absence of exogenous resources, populations continued to evolve. Hundreds of mutations were acquired, contributing to genome-wide signatures of purifying selection as well as molecular signals of adaptation. Consistent ecological and evolutionary dynamics indicate that distantly related bacteria respond to energy limitation in a similar and predictable manner, which likely contributes to the stability and robustness of microbial life.

The role of sigma factor competition in bacterial adaptation under prolonged starvation

“…Recently the competition between two E. coli sigma factors controlling growth and stress response were identified as a strategy to gain a transient competitive advantage in LTSP [30]. In LTSP, the genotypic and phenotypic variation of the founding population increases, generating subpopulations that compete to survive [50,118] by recycling the debris left by the death of the previous subpopulations [119]. Similarly, persistor subpopulations that can endure antibiotic regimes and drive chronic diseases are formed by pathogens in nutrient-limited host niches [27,120].…”

Phototroph-heterotroph interactions during growth and long-term starvation across Prochlorococcus and Alteromonas diversity

“…Given that the most striking effect of co-culture was on the decline phase of the co-cultures, we asked whether we could quantify this effect, and whether we could identify an appropriate model for mathematically describing culture decline. Importantly, while the growth of bacteria has been extensively studied and modelled, the decline of bacterial cultures, representing bacterial mortality, is much less studied, and mortality is rarely represented in ecological or biogeochemical models of microbial dynamics (Shoemaker et al, 2021). Bacterial mortality has, however, often been modelled in the context of food safety and genome evolution, using either mechanistic or descriptive approaches (Brouwer et al, 2017;Crane & Moore, 1986;Finkel & Kolter, 1999;Patra & Klumpp, 2013;Shoemaker et al, 2021) We chose to focus on four previously-described models which are relatively simple and have a clear biological interpretation (Fig 4a, Table 1).…”

“…The Biexponential model is slightly more complex, representing two separate subpopulations in the community, each with its own death rate (Crane & Moore, 1986). Weibull model is a probabilistic model, modeling heterogeneous population with a diverse stress tolerance (Shoemaker et al, 2021;Van Boekel, 2002) and finally the Harmonic model employs a quadratic rate of decline which is often associated with predator-prey interaction or encounter rate (Pruitt & Kamau, 1993). When fitting each of these models to the decline phase of the growth curves, the Weibull model stands out as it has a low error for both axenic and co-cultures (Table 1, Fig 4b).…”

The Interactions among Isolates of Lactiplantibacillus plantarum and Dairy Yeast Contaminants: Towards Biocontrol Applications

“…Index values were first log-transformed and presented as the mean with standard error of the means (s.e.m.) because of discrepancy of sample's means [17,36]. Significant differences among the tested groups were determined using Tukey's HSD test at significance p ≤ 0.05.…”

“…Besides problems associated with chemical elimination and yeast resistance in dairy, the market demand for clean label products requires the testing and utilisation of bioprotective agent generally recognized as safe (GRAS) in Europe's qualified presumption as safety list (QPS) [15], including Lactiplantibacillus plantarum. The application of verified L. plantarum strains with functional properties, including antifungal activity against yeast spoilers, is the desired step approaching the sustainable production of fermented dairy products [16,17].…”