Research
Evolutionary Dynamics of Niche Construction
Microbes as they evolve modify the environmental conditions to which they are adapting. These modifications (or niche construction) set the selective pressures experienced by new mutations and determine the topology of fitness landscapes. We have shown that due to niche construction metabolic fitness landscapes are deformable over long adaptive trajectories (Bajic et al 2018). As part of this work we collaborated in the development of COMETS 2.0 a software platform for metabolic simulations of microbial communities (Dukovski et al 2020). Using COMETS I am now exploring the dynamics of adaptation on deformable fitness landscape. Our ultimate goal is to understand the role of niche construction in shaping evolutionary dynamics in complex communities.
Metabolic Rules of Microbial Community Assembly
Microbial communities assemble into reproducible compositions at high levels of taxonomic and metabolic organization despite adopting alternative states at the species level (Vila et al 2020, Estrela et al 2020). We have been studying the processes underlying this reproducibility across environments by combining genome scale-metabolic models, metabolomics and phylogenetic methods. By leveraging the evolutionary conservation of quantitative metabolic traits we hope to predict the assembly of complex communities across different environments(Vila et al 2023). As part of this work we have also been studying the effects of environmental complexity on community assembly (Estrela et al 2021).
Directed Evolution of Microbial Communities
Microbial communities display emergent properties that are not easily predicted by looking at individual species in isolation (e.g. Lino et al 2021). Building off earlier work on artificial ecosystem-level selection we have recently proposed a range of novel ecological methods for engineering the emergent properties of complex microbial communities (Chang et al 2021). As part of this work we developed a Python Package ecoprospector that allows us to test the efficacy of community-level selection protocols using consumer-resource model simulation. We have also recently published a review on this topic (Sanchez et al 2021). In future work I hope to explore the resilience of directly evolved communities to environmental change.