Biology subjects

Pascual-Garcia, A.

Publications and source records attributed to Pascual-Garcia, A..

11 recordsLinked to original sources

bioRxiv2026

Environmental sensing capacity predicts bacterial ecological strategies and environmental preferences

The ability to sense environmental variation is a prerequisite for ecological success. Sensor domains enable bacteria to detect nutrients, neighboring organisms, and physicochemical conditions, but whether variation in these sensing systems reflects ecological specialization remains unresolved. Here, we analyzed sensor domains across 51,343 bacterial genomes and 255 soil metagenomes spanning a climatic gradient to determine whether sensory repertoires encode bacterial ecological strategies and environmental preferences. Sensory repertoires exhibited strong phylogenetic conservatism and revealed signatures of genome streamlining, indicating that environmental sensing reflects trade-offs associated with maintaining sensory complexity. Taxa occupying environmentally heterogeneous habitats, particularly free-living aerobic generalists, encoded the largest sensory repertoires, consistent with selection for expanded environmental information processing. To link sensory function with ecological adaptation, we mapped experimentally-characterized ligand-binding motifs (LBMs) across genomes and metagenomes. Distinct LBM profiles discriminated host-associated and free-living taxa, aerobic and anaerobic lineages, and generalists and non-generalists, revealing a tight coupling between sensory capacity and ecological strategy. Across soil communities, motifs associated with osmoprotection and oxygen sensing were consistently enriched under increasing aridity, linking sensory function to environmental filtering in natural ecosystems. These findings identify environmental sensing as an important organizational axis of bacterial trait-based ecology that integrates evolutionary history, ecological lifestyle, and adaptation to local conditions. Environmental sensing should be considered for predicting microbial niches and responses to environmental change.

ecology↗

bioRxiv2025

misosoup: A metabolic modeling tool for identifying minimal microbial communities reveals pervasive cross-feeding-driven niche expansion

Microbial survival and function often depend on metabolic interactions within communities. Therefore, a central question in disentangling microbial organization is determining which minimal groups of species are able to thrive in a given medium - referred to as "minimal communities". Answering this question is essential for understanding microbial distribution, enhancing laboratory cultivation, and designing synthetic communities (SynComs). Here, we introduce misosoup, a Python package for identifying minimal communities (MInimal Supplying community Search). Through genome-scale constraint-based metabolic modeling, misosoup enables the systematic identification of communities that support microbial growth in environments where individual species fail to survive alone. We validate misosoup against experimentally verified minimal communities, demonstrating its ability to predict known cooperative interactions, cocultures, and consortia with biotechnological potential. We further illustrate the use of misosoup to investigate broad microbial ecology questions by applying it to a set of 60 marine microbes, finding pervasive cross-feeding-driven niche expansion, and showing how the detailed outputs provided by misosoup facilitate research on hot topics such as the identification of functional groups. In summary, misosoup provides a powerful tool for microbial ecology and community design, with potential applications in both research and biotechnological innovation. ImportanceMicrobes often rely on each other to survive, especially in environments where they cant live alone. Understanding which small groups of microbes can thrive together--called minimal communities--is key to improving lab research, designing synthetic ecosystems, and exploring how microbes spread in nature. To support this, we developed misosoup, a Python tool that identifies these communities using advanced metabolic modeling. misosoup helps scientists discover how microbes cooperate by sharing nutrients, a process known as metabolic cross-feeding. When tested on sets of species from different origins, the tool showed that species could thrive in more environments when part of a group. This highlights the importance of teamwork in microbial life. misosoup not only predicts these interactions but also provides detailed insights that can guide ecological studies and biotechnological innovation. By revealing how microbes support each other, misosoup contributes to a deeper understanding of lifes interconnectedness and offers tools for solving real-world challenges.

bioinformatics↗

bioRxiv2024

Structural stability determines evolutionary stability in mutualistic model ecosystems

Understanding the factors that influence the persistence and stability of complex ecological networks is a central focus of ecological research. Recent research into these factors has predominantly attempted to unveil the ecological processes and structural constraints that influence network stability. Comparatively little attention has been given to the consequences of evolutionary events, despite the fact that the interplay between ecology and evolution has been recognised as fundamental to understand the formation of ecological communities and predict their reaction to change. In light of current environmental challenges, there is a compelling need for a quantitative framework to predict biodiversity loss under environmental perturbations while accounting for evolutionary processes. We extend existing mutualistic population dynamical models by incorporating evolutionary adaptation events to address this critical gap. We relate ecological aspects of mutualistic community stability to the stability of persistent evolutionary pathways. Our findings highlight the significance of the structural stability of ecological systems in predicting biodiversity loss under both evolutionary and environmental changes, particularly in relation to species-level selection. Notably, our simulations reveal that the evolution of mutualistic networks tends to increase a network-dependent parameter termed critical competition, which places systems in a regime in which mutualistic interactions enhance structural stability and, consequently, biodiversity. This research emphasizes the pivotal role of natural selection in shaping ecological networks, steering them towards reduced effective competition below a critical threshold where mutualistic interactions foster stability. The outcomes of our study contribute to the development of a predictive framework for eco-evolutionary dynamics, offering insights into the interplay between ecological and evolutionary processes in the face of environmental change.

ecology↗

bioRxiv2024

A network optimisation condition uncovers the role offunctional groups in the feasibility and dynamical stability of microbial model ecosystems.

Investigating mechanisms favouring stable coexistence of complex microbial communities is central to understand their formation and maintenance in the natural environment and, eventually, controlling and designing synthetic communities. In this work, we studied microbial model ecosystems in which consumption and secretion of resources was explicit, determining ecological interactions (e.g. competition for resources, facilitation, mutualism). We found a sufficient condition for the dynamical stability of microbial model ecosystems. This condition allowed us to derive an objective function whose optimization selected specific configurations of consumption and secretion of resources. Optimized configurations stood out as a compromise between having a large parameter space in which species coexistence was feasible (dominated by systems in which microbes do not secrete any resources), and having a high rate of return to equilibrium after a perturbation (dominated by systems in which every microbe secrete all resources). We explained the behaviour observed for optimized configurations by noting that they host sets of species with differentiated niches -as defined by their consumption and secretion strategies-, termed functional groups. We speculated that, since increasing the number of functional groups increased the number of niches, competition between species should be reduced, favouring coexistence. Therefore, our results suggest that the formation of functional groups have an important role in microbial coexistence, which has ramifications for the design of complex microbial communities.

ecology↗

bioRxiv2023

Replaying the tape of ecology to domesticate wild microbiomes

Humanity has benefited from the domestication of nature and there is an increasing need to predict and control ecosystems. Domesticating bacterial communities would be particularly useful. Bacterial communities play key roles in global biogeochemical cycles, in industry (e.g. sewage treatment, fermented food and drink manufacturing), in agriculture (e.g. by fixing nitrogen and suppressing pathogens), and in human health and animal husbandry. There is therefore great interest in understanding bacterial community dynamics so that they can be controlled and engineered to optimise ecosystem services. We assessed the reproducibility and predictability of bacterial community dynamics by creating a frozen archive of hundreds of naturally-occuring bacterial communities that were repeatedly revived and tracked in a standardised, complex environment. Replicate communities followed reproducible trajectories and the community dynamics could be closely mapped to ecosystem functioning. However, even under standardised conditions, the communities exhibited tipping-points, where a small difference in initial community composition created divergent outcomes. We accurately predicted ecosystem outcomes based on initial bacterial community composition, and identified the conditions under which divergent ecosystem outcomes may be expected. In conclusion, we have shown the feasibility of our approach to reproducibly achieve predictable compositions and functions from wild communities. Nonetheless, the predictability of community trajectories, and therefore their utility in domestication, requires detailed knowledge of rugged compositional landscapes where ecosystem properties are not the inevitable result of prevailing environmental conditions but can be tilted toward different outcomes depending on the initial community composition.

microbiology↗

bioRxiv2022

Cross-biome microbial networks reveal functional redundancy and suggest genome reduction through functional complementarity

Microbial communities are complex and dynamic entities, and their structure arises from the interplay of a multitude of factors, including the interactions of microorganisms with each other and with the environment. Since each extant community has a unique eco-evolutionary history, it might appear that contingency rather than general rules govern their assembly. In spite of this, there is evidence that some general assembly principles exist, at least to a certain extent. In this work, we sought to identify those principles by performing a cross-study, cross-biome meta-analysis of microbial occurrence data in more than 5,000 samples from ten different environmental groups. We adopted a novel algorithm that allows the same taxa to aggregate with different partners in different habitats, capturing the complexity of interactions inherent to natural microbial communities. We tried to decouple function from phylogeny, the environment, and genome size, in order to provide an unbiased characterization of phylogenetic and functional redundancy in environmental microbial assemblages. We then examined the phylogenetic and functional composition of the resulting inferred communities, and searched for global patterns of assembly both at the community level and in individual metabolic pathways. Our analysis of the resulting microbial assemblages highlighted that environmental communities are more functionally redundant than expected by chance. This effect is greater for communities appearing in more than one environment, suggesting a link between functional redundancy and environmental adaptation. In spite of this, certain pathways are observed in fewer taxa than expected by chance, suggesting the presence of auxotrophy, and presumably cooperation among community members, which is supported by our analysis of amino acid biosynthesis pathways. Furthermore, this hypothetical cooperation may play a role in genome reduction, since we observed a negative relationship between the size of bacterial genomes and the number of taxa of the community they belong to. Overall, our results provide a global characterization of environmental microbial communities, and offer design principles for engineering robust bacterial communities.

microbiology↗

bioRxiv2021

Turnover in life strategies recapitulates microbial succession on synthetic marine particles

Particulate organic matter (POM) in the ocean sustains diverse communities of bacteria that mediate the remineralization of organic complex matter. However, the variability of these particles and of the environmental conditions surrounding them present a challenge to the study of the ecological processes shaping particle-associated communities and their function. In this work, we utilise data from experiments in which coastal water communities were grown on synthetic particles to ask which are the most important ecological drivers of their assembly and associated traits. Combining 16S rRNA amplicon sequencing with shotgun metagenomics, together with an analysis of the full genomes of a subset of isolated strains, we were able to identify two-to-three distinct community classes, corresponding to early vs. late colonizers. We show that these classes are shaped by environmental selection (early colonizers) and facilitation (late colonizers), and find distinctive traits associated with each class. While early colonizers have a larger proportion of genes related to uptake of nutrients, motility and environmental sensing with few pathways enriched for metabolism, late colonizers devote a higher proportion of genes for metabolism, comprising a wide array of different pathways including metabolism of carbohydrates, amino acids and xenobiotics We find evidence in selected metabolic pathways for the existence of a trophic-chain topology connecting both classes. The interpretation of these traits suggests a distinction between early and late colonizers analogous to other classifications found in the literature, and we discuss connections with the classical distinction between r- and K-strategists.

microbiology↗

bioRxiv2020

Environmental controls and habitat connectivity of phototrophic microbial mats and bacterioplankton communities in an Antarctic freshwater system

Freshwater ecosystems are considered hotspots of biodiversity in Antarctic polar deserts. Anticipated warming is expected to change the hydrology of these systems due to increased meltwater and reduction of ice cover, with implications for environmental conditions and physical connectivity between habitats. Using 16S rRNA sequencing, we evaluated the structure of microbial mat and planktonic communities within a connected watershed in the McMurdo Wright Valley, Antarctica to determine the roles of connectivity and habitat conditions in controlling microbial assemblage composition. We examined benthic and planktonic samples from glacial Lake Brownworth, the perennially ice-covered Lake Vanda, and the Onyx River, which connects the two. In Lake Vanda, we found distinct microbial assemblages occupying sub-habitats at different lake depths, while the communities from Lake Brownworth and Onyx River were structurally similar between them. Despite the higher connectivity between bacterial communities in the shallow parts of the system, environmental filtering dominated over dispersal in driving bacterial community structure. Functional metagenomics predictions identified genes related to degradation of halogenated aromatic compounds in surface microbial mats exposed to changes in water regimes, which progressively disappeared with increasing depth. Shifting environmental conditions due to increasing connectivity, rather than dispersal, may become the dominant drivers of bacterial diversity and functioning in Antarctic freshwater ecosystems.

ecology↗

bioRxiv2019

Microbial metabolically cohesive consortia and ecosystem functioning

Recent theory and experiments have reported a reproducible tendency for the coexistence of microbial species under controlled environmental conditions. This observation has been explained in the context of competition for resources and metabolic complementarity given that, in microbial communities, many excreted by-products of metabolism may also be resources. Microbial communities therefore play a key role in promoting their own stability and in shaping the niches of the constituent taxa. We suggest that an intermediate level of organisation between the species and the community level may be pervasive, where tightly-knit metabolic interactions create discrete consortia that are stably maintained. We call these units Metabolically Cohesive Consortia (MeCoCos) and we discuss the environmental context in which we expect their formation, and the ecological and evolutionary consequences of their existence. We argue that the ability to identify MeCoCos would open new avenues to link the species-, community-, and ecosystem-level properties, with consequences for our understanding of microbial ecology and evolution, and an improved ability to predict ecosystem functioning in the wild.

microbiology↗

bioRxiv2019

functionInk: An efficient method to detect functional groups in multidimensional networks reveals the hidden structure of ecological communities

O_LIComplex networks have been useful to link experimental data with mechanistic models, and have become widely used across many scientific disciplines. Recently, the increasing amount and complexity of data, particularly in biology, has prompted the development of multidimensional networks, where dimensions reflect the multiple qualitative properties of nodes, links, or both. As a consequence, traditional quantities computed in single dimensional networks should be adapted to incorporate this new information. A particularly important problem is the detection of communities, namely sets of nodes sharing certain properties, which reduces the complexity of the networks, hence facilitating its interpretation. C_LIO_LIIn this work, we propose an operative definition of "function" for the nodes in multidimensional networks, and we exploit this definition to show that it is possible to detect two types of communities: i) modules, which are communities more densely connected within their members than with nodes belonging to other communities, and ii) guilds, which are sets of nodes connected with the same neighbours, even if they are not connected themselves. We provide two quantities to optimally detect both types of communities, whose relative values reflect their importance in the network. C_LIO_LIThe flexibility of the method allowed us to analyze different ecological examples encompassing mutualistic, trophic and microbial networks. We showed that by considering both metrics we were able to obtain deeper ecological insights about how these different ecological communities were structured. The method mapped pools of species with properties that were known in advance, such as plants and pollinators. Other types of communities found, when contrasted with external data, turned out to be ecologically meaningful, allowing us to identify species with important functional roles or the influence of environmental variables. Furthermore, we found the method was sensitive to community-level topological properties like the nestedness. C_LIO_LIIn ecology there is often a need to identify groupings including trophic levels, guilds, functional groups, or ecotypes.The method is therefore important in providing an objective means of distinguishing modules and guilds. The method we developed, functionInk (functional linkage), is computationally efficient at handling large multidimensional networks since it does not require optimization procedures or tests of robustness. The method is available at: HTTPS://GITHUB.COM/APASCUALGARCIA/FUNCTIONINK. C_LI

bioinformatics↗

bioRxiv2019

Community-level signatures of ecological succession in natural bacterial communities

A central goal in microbial ecology is to simplify the extraordinary biodiversity that inhabits natural environments into ecologically coherent units. We present an integrative top-down analysis of over 700 bacterial communities sampled from water-filled beech tree-holes in the United Kingdom at distances between <5m to >100km, combining an analyses of community composition (16S rRNA sequencing) with assays of community functional capacity (exo-enzymatic activities, ATP production, CO2 dissipation and yield). The communities were grown in laboratory conditions in a complex growth medium, what allowed us to investigate the relationship between composition and function, excluding confounding environmental factors. We found a distance-decay trend in the similarity of the communities, and simulated data allowed us to reject the hypothesis that stochastic processes dominated the assembly of the communities, suggesting that niche effects prevailed. Consistent with this idea, clustering of communities lead us to identify six distinct community classes encompassing samples collected at often distant locations. Using structural equation modelling, we explored how functions were interrelated, demonstrating that a representative functional signature can be associated with each community class. We obtained a more mechanistic understanding of the classes using metagenomic predictions with PiCRUST. Notably, this approach allowed us to show that these classes contain distinct genetic repertoires reflecting community-level ecological strategies. We finally formulated an over-arching ecological hypothesis about how local conditions drive succession in these habitats. The ecological strategies resemble the classical distinction between r- and K-strategists and could be extrapolated to other systems, suggesting that a coarse grained picture of microbial ecological succession may be explained by relatively simple ecological mechanisms.

microbiology↗