Biology subjects

Lele, K.

Publications and source records attributed to Lele, K..

3 recordsLinked to original sources

bioRxiv2026

Fitness landscapes for species interactions: when do population genetics and adaptive dynamics diverge?

Multiple frameworks have been developed to investigate the evolution of species interactions on fitness landscapes, each with unique strengths and weaknesses. These include adaptive dynamics, which uses linear stability analyses to predict eco-evolutionary outcomes resulting from the invasion of rare mutants into a resident population, and population genetics, which mechanistically models finite populations and stochastic processes in finite time. Though there are some known correspondences between these frameworks, it is not clear that they will always result in the same eco-evolutionary outcomes. Moreover, while adaptive dynamics is very powerful for predicting outcomes, it is not always straightforward to relate these predictions to the data generated in experimental evolution studies. Here, we use a data-driven model of microbial species interactions to compare and contrast the predictions of population genetics and adaptive dynamics. We derive expected outcomes for one-species and two-species evolutionary trajectories by using the invasion fitness landscape concept from adaptive dynamics, and then use analytical theory and forward-in-time simulations to set these predictions within the context of population genetic models. In the context of our one-species models, we show that the timescale of evolution depends on mutation supply and effect sizes, when populations are initialized both along and off a trade-off function. For two-species competition models, we show that mutation supply, effect sizes, and asymmetries between competing species result in discrepancies between adaptive dynamics and population genetics, especially in cases where adaptive dynamics predicts stable coexistence. Our study provides insight into the role of finite timescales, mutation supplies and population sizes in the evolution of species interactions, and facilitates further research that leverages the invasion fitness landscape concept within the realm of population genetics.

evolutionary biology↗

bioRxiv2024

Pairwise interactions and serial bottlenecks help explain species composition in a multi-species microbial community

Characterizing the processes that drive microbial community assembly remains a key challenge in ecology. Several recent studies have argued that pairwise interactions may be insufficient to explain co-occurrence patterns in complex microbial communities, but most such studies have focused on synthetic communities not found in nature or microbes grown in contexts that differ widely from their natural environment. Moreover, most models of pairwise interactions rely on equilibrium assumptions that are not relevant to all natural communities, such as gut microbiomes or species in fluctuating environments. Inclusion of appropriate demographic factors into models of pairwise interactions could be a potential approach to better capture patterns of community assembly. In this study, we investigated whether multi-species co-occurrence patterns can be predicted from pairwise interactions for microbes isolated from sourdough starters. Interaction parameters inferred from pairwise growth trajectories were suggestive of widespread coexistence between pairs of microbes in our species pool. In communities of up to nine species, most species presence and relative abundance could be reliably predicted based on a model of pairwise interactions. The inclusion of nonequilibrium demography in our model further improved the accuracy of our pairwise model. Our work contributes to the broader debate on the processes underlying community assembly by showing that pairwise interactions are predictive of community structure in a system of moderate species complexity.

ecology↗

bioRxiv2021

Genomic signatures of UV resistance evolution in Escherichia coli depend on the growth phase during exposure

Physiological states can determine the ability of organisms to handle stress. Does this mean that the same selection pressure will lead to different evolutionary outcomes, depending on the organisms physiological state? If yes, what will be the genomic signatures of such adaptation(s)? We used experimental evolution in Escherichia coli followed by whole-genome whole-population sequencing to investigate these questions. The sensitivity of Escherichia coli to ultraviolet (UV) radiation depends on the growth phase during which it experiences the radiation. We evolved replicate E. coli populations under two different conditions of UV exposures, namely exposure during the lag and the exponential growth phases. Initially, the UV sensitivity of the ancestor was greater during the exponential phase than the lag phase. However, at the end of 100 cycles of exposure, UV resistance evolved to similar extents in both treatments. Genome analysis showed that mutations in genes involved in DNA repair, cell membrane structure and RNA polymerase were common in both treatments. However, different functional groups were found mutated in populations experiencing lag and exponential UV treatment. In the former, genes involved in transcriptional and translational regulations and cellular transport were mutated, whereas the latter treatment showed mutations in genes involved in signal transduction and cell adhesion. Interestingly, the treatments showed no phenotypic differences in a number of novel environments. Taken together, these results suggest that selection pressures at different physiological stages can lead to differences in the genomic signatures of adaptation, which need not necessarily translate into observable phenotypic differences.

evolutionary biology↗