Biology subjects

Vila, J. C. C.

Publications and source records attributed to Vila, J. C. C..

10 recordsLinked to original sources

bioRxiv2023

Metabolic similarity and the predictability of microbial community assembly

AbstractWhen microbial communities form, their composition is shaped by selective pressures imposed by the environment. Can we predict which communities will assemble under different environmental conditions? Here, we hypothesize that quantitative similarities in metabolic traits across metabolically similar environments lead to predictable similarities in community composition. To that end, we measured the growth rate and by-product profile of a library of proteobacterial strains in a large number of single nutrient environments. We found that growth rates and secretion profiles were positively correlated across environments when the supplied substrate was metabolically similar. By analyzing hundreds of in-vitro communities experimentally assembled in an array of different synthetic environments, we then show that metabolically similar substrates select for taxonomically similar communities. These findings lead us to propose and then validate a comparative approach for quantitatively predicting the effects of novel substrates on the composition of complex microbial consortia.

ecology↗

bioRxiv2023

The architecture of metabolic networks constrains the evolution of microbial resource hierarchies

Microbial strategies for resource use are an essential determinant of their fitness in complex habitats. When facing environments with multiple nutrients, microbes often use them sequentially according to a preference hierarchy, resulting in well-known patterns of diauxic growth. In theory, the evolutionary diversification of metabolic hierarchies could represent a mechanism supporting coexistence and biodiversity by enabling temporal segregation of niches. Despite this ecologically critical role, the extent to which substrate preference hierarchies can evolve and diversify remains largely unexplored. Here we used genome-scale metabolic modeling to systematically explore the evolution of metabolic hierarchies across a vast space of metabolic network genotypes. We find that only a limited number of metabolic hierarchies can readily evolve, corresponding to the most commonly observed hierarchies in genome-derived models. We further show how the evolution of novel hierarchies is constrained by the architecture of central metabolism, which determines both the propensity to change ranks between pairs of substrates and the effect of specific reactions on hierarchy evolution. Our analysis sheds light on the genetic and mechanistic determinants of microbial metabolic hierarchies, opening new research avenues to understand their evolution, evolvability and ecology.

evolutionary biology↗

bioRxiv2022

Predictability of the community-function landscape in wine yeast ecosystems

Predictively linking taxonomic composition and quantitative ecosystem functions is a major aspiration in microbial ecology, which must be resolved if we wish to engineer microbial consortia. Here, we have addressed this open question for an ecological function of major biotechnological relevance: alcoholic fermentation in wine yeast communities. By exhaustively phenotyping an extensive collection of naturally occurring wine yeast strains, we find that most enologically-relevant traits exhibit a strong phylogenetic signal, indicating that the most relevant functions in wine yeast communities can be predicted from taxonomy. Further, we demonstrate that the quantitative contributions of individual wine yeast strains to the community function followed simple quantitative rules. These regularities can be integrated to quantitatively predict the function of newly assembled consortia. Besides addressing a fundamental open question in functional ecology, our results and methodologies provide a blueprint for rationally managing microbial processes of biotechnological relevance.

microbiology↗

bioRxiv2022

Emergent ecosystem functions follow simple quantitative rules

The emergence of community functions is the result of a complex web of interactions between organisms and their environment. This complexity poses a significant obstacle in quantitatively predicting ecological function from the species-level composition of a community. In this study, we demonstrate that the collective impact of interspecies interactions leads to the emergence of simple linear models that predict ecological function. These predictive models mirror the patterns of global epistasis reported in genetics, and they can be quantitatively interpreted in terms of pairwise ecological interactions between species. Our results illuminate an unexplored path to quantitatively linking the composition and function of ecological communities, bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism.

ecology↗

bioRxiv2022

Emergent coexistence in multispecies microbial communities

Microbial communities are highly diverse, and understanding the factors that promote and modulate this diversity is a major area of research in microbial ecology. Recent work has proposed a reductionist perspective to microbial coexistence, where pairwise coexistence between strains in isolation is required for their coexistence in a more complex community. In this view, species exclusion in pairwise co-culture would preclude their coexistence in a more complex community too. An alternative view is that coexistence is a more complex property of the entire community, requiring the presence of additional community members. If this view were correct, competitive exclusion in pairwise co-culture would not necessarily preclude species coexistence in more complex community contexts. Empirically testing these alternative hypotheses is complicated by the intractably high microbial diversity of most natural communities, and the challenges of reconstituting every pair of coexisting species under the exact same habitat where their community of origin was assembled. To address this challenge, we have experimentally reconstituted all possible pairwise co-cultures between stably coexisting species from 13 different, low-diversity microbial enrichment communities, which had previously been assembled in a well-controlled synthetic habitat. We find that, when isolated from the rest of their community members, most species pairs fail to coexist. This result highlights the importance of community context for microbial coexistence and indicates that pairwise exclusion may not reflect the ability of species to coexist in more complex, multispecies ecosystems.

ecology↗

bioRxiv2022

Diversity begets diversity under microbial niche construction

Microbial interactions are expected to modulate microbial diversity, but whether they inhibit or stimulate further diversity in complex microbial communities, and how, remains poorly understood. By assembling microbial communities in multiple identical habitats with a single limiting nutrient, here we provide direct evidence for the role of microbial niche construction and cross-feeding in driving a positive relationship between community diversity and focal lineage diversity in microbial communities. Combining these experiments with simulations, we show that this positive relationship is not inevitable but depends on the underlying metabolic structure of by-product secretions and uptake between different taxonomic levels.

ecology↗

bioRxiv2020

Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments

A major open question in microbial community ecology is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, we investigate whether communities assembled in pairs of nutrients can be predicted from those assembled in every single nutrient alone. We first find that although the null, naturally additive model generally predicts well the family-level community composition, there exist systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance at the family-level. Pairs of more similar nutrients (e.g. two sugars) are on average more additive than pairs of more dissimilar nutrients (one sugar-one organic acid). Second, a simple dominance rule emerges: sugars generally dominate organic acids. These findings may be explained by family-level asymmetries in nutrient benefits. Overall, our results suggest that regularities in how nutrients interact may help predict communities responses to dietary changes.

ecology↗

bioRxiv2020

Top-down engineering of complex communities by directed evolution

Directed evolution has been used for decades to engineer biological systems from the top-down. Generally, it has been applied at or below the organismal level, by iteratively sampling the mutational landscape in a guided search for genetic variants of higher function. Above the organismal level, a small number of studies have attempted to artificially select microbial communities and ecosystems, with uneven and generally modest success. Our theoretical understanding of artificial ecosystem selection is still limited, particularly for large assemblages of asexual organisms, and we know little about designing efficient methods to direct their evolution. To address this issue, we have developed a flexible modeling framework that allows us to systematically probe any arbitrary selection strategy on any arbitrary set of communities and selected functions, in a wide range of ecological conditions. By artificially selecting hundreds of in-silico microbial metacommunities under identical conditions, we examine the fundamental limits of the two main breeding methods used so far, and prescribe modifications that significantly increase their power. We identify a range of directed evolution strategies that, particularly when applied in combination, are better suited for the top-down engineering of large, diverse, and stable microbial consortia. Our results emphasize that directed evolution allows an ecological structure-function landscape to be navigated in search for dynamically stable and ecologically and functionally resilient high-functioning communities.

evolutionary biology↗

bioRxiv2020

Dissimilarity-Overlap Analysis of Replicate Enrichment Communities

The taxonomic composition of microbial communities can vary substantially between individual hosts and within the same host over time. Efforts to build quantitative and predictive models of microbial population dynamics are underway, but fundamental questions remain. How different are population dynamics in different hosts? Do communities that share the same taxa also exhibit identical dynamics? In vitro communities can help establish baseline expectations that are critical towards resolving these questions in natural communities. Here, we applied a recently developed tool, Dissimilarity-Overlap Analysis (DOA), to a set of experimental in vitro communities that differed in nutrient composition. The Dissimilarity and Overlap of these communities are negatively correlated in replicate habitats, as one would expect if microbial population dynamics were on average strongly convergent (or "universal") across these replicate habitats. However, the existence of such a negative correlation does not necessarily imply that population dynamics are always universal in all communities. Even in replicate, identical habitats, two different communities may contain the same set of taxa at different abundances in equilibrium. The formation of alternative states in community assembly is strongly associated with the presence of specific taxa in the communities. Our results benchmark DOA, providing support for some of its core assumptions, and suggest that communities sharing the same taxa and external abiotic factors generally (but not necessarily) have a negative correlation between Dissimilarity and Overlap.

ecology↗

bioRxiv2018

On the deformability of an empirical fitness landscape by microbial evolution

A fitness landscape is a map between the genotype and its reproductive success in a given environment. The topography of fitness landscapes largely governs adaptive dynamics, constraining evolutionary trajectories and the predictability of evolution. Theory suggests that this topography can be \"deformed\" by mutations that produce substantial changes to the environment. In spite of its importance, the deformability of fitness landscapes has not been systematically studied beyond abstract models, and little is known about its reach and consequences in empirical systems. Here we have systematically characterized the deformability of the genome-wide metabolic fitness landscape of the bacterium E. coli. Deformability is quantified by the non-commutativity of epistatic interactions, which we experimentally demonstrate in mutant strains on the path to an evolutionary innovation. Our analysis shows that the deformation of fitness landscapes by metabolic mutations rarely affects evolutionary trajectories in the short-range. However, mutations with large environmental effects leave these as a \"legacy\", producing long-range landscape deformations in distant regions of the genotype space that affect the fitness of later descendants. Our methods and results provide the basis for an integration between adaptive and eco-evolutionary dynamics with complex genetics and genomics.

evolutionary biology↗