Unveiling abundance-dependent metabolic phenotypes of microbial communities.

IMPORTANCE: In nature, organisms live in communities and not as isolated species, and their interactions provide a source of resilience to environmental disturbances. Despite their importance in ecology, human health, and industry, understanding how organisms interact in different environments remains an open question. In this work, we provide a novel approach that, only using genomic information, studies the metabolic phenotype exhibited by communities, where the exploration of suboptimal growth flux distributions and the composition of a community allows to unveil its capacity to respond to environmental changes, shedding light of the degrees of metabolic plasticity inherent to the community.

Structure and co-occurrence patterns in microbial communities under acute environmental stress reveal ecological factors fostering resilience.

Understanding the factors that modulate bacterial community assembly in natural soils is a longstanding challenge in microbial community ecology. In this work, we compared two microbial co-occurrence networks representing bacterial soil communities from two different sections of a pH, temperature and humidity gradient occurring along a western slope of the Andes in the Atacama Desert. In doing so, a topological graph alignment of co-occurrence networks was used to determine the impact of a shift in environmental variables on OTUs taxonomic composition and their relationships. We observed that a fraction of association patterns identified in the co-occurrence networks are persistent despite large environmental variation. This apparent resilience seems to be due to: (1) a proportion of OTUs that persist across the gradient and maintain similar association patterns within the community and (2) bacterial community ecological rearrangements, where an important fraction of the OTUs come to fill the ecological roles of other OTUs in the other network. Actually, potential functional features suggest a fundamental role of persistent OTUs along the soil gradient involving nitrogen fixation. Our results allow identifying factors that induce changes in microbial assemblage configuration, altering specific bacterial soil functions and interactions within the microbial communities in natural environments.

Deciphering transcriptional regulations coordinating the response to environmental changes.

BACKGROUND: Gene co-expression evidenced as a response to environmental changes has shown that transcriptional activity is coordinated, which pinpoints the role of transcriptional regulatory networks (TRNs). Nevertheless, the prediction of TRNs based on the affinity of transcription factors (TFs) with binding sites (BSs) generally produces an over-estimation of the observable TF/BS relations within the network and therefore many of the predicted relations are spurious. RESULTS: We present LOMBARDE, a bioinformatics method that extracts from a TRN determined from a set of predicted TF/BS affinities a subnetwork explaining a given set of observed co-expressions by choosing the TFs and BSs most likely to be involved in the co-regulation. LOMBARDE solves an optimization problem which selects confident paths within a given TRN that join a putative common regulator with two co-expressed genes via regulatory cascades. To evaluate the method, we used public data of Escherichia coli to produce a regulatory network that explained almost all observed co-expressions while using only 19 % of the input TF/BS affinities but including about 66 % of the independent experimentally validated regulations in the input data. When all known validated TF/BS affinities were integrated into the input data the precision of LOMBARDE increased significantly. The topological characteristics of the subnetwork that was obtained were similar to the characteristics described for known validated TRNs. CONCLUSIONS: LOMBARDE provides a useful modeling scheme for deciphering the regulatory mechanisms that underlie the phenotypic responses of an organism to environmental challenges. The method can become a reliable tool for further research on genome-scale transcriptional regulation studies.

Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach.

Following the trend of studies that investigate microbial ecosystems using different metagenomic techniques, we propose a new integrative systems ecology approach that aims to decipher functional roles within a consortium through the integration of genomic and metabolic knowledge at genome scale. For the sake of application, using public genomes of five bacterial strains involved in copper bioleaching: Acidiphilium cryptum, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillum ferriphilum, and Sulfobacillus thermosulfidooxidans, we first reconstructed a global metabolic network. Next, using a parsimony assumption, we deciphered sets of genes, called Sets from Genome Segments (SGS), that (1) are close on their respective genomes, (2) take an active part in metabolic pathways and (3) whose associated metabolic reactions are also closely connected within metabolic networks. Overall, this SGS paradigm depicts genomic functional units that emphasize respective roles of bacterial strains to catalyze metabolic pathways and environmental processes. Our analysis suggested that only few functional metabolic genes are horizontally transferred within the consortium and that no single bacterial strain can accomplish by itself the whole copper bioleaching. The use of SGS pinpoints a functional compartmentalization among the investigated species and exhibits putative bacterial interactions necessary for promoting these pathways.

A shift in the archaeal nitrifier community in response to natural and anthropogenic disturbances in the northern Gulf of Mexico.

The Gulf of Mexico is affected by hurricanes and suffers seasonal hypoxia. The Deepwater Horizon oil spill impacted every trophic level in the coastal region. Despite their importance in bioremediation and biogeochemical cycles, it is difficult to predict the responses of microbial communities to physical and anthropogenic disturbances. Here, we quantify sediment ammonia-oxidizing archaeal (AOA) community diversity, resistance and resilience, and important geochemical factors after major hurricanes and the oil spill. Dominant AOA archetypes correlated with different geochemical factors, suggesting that different AOA are constrained by distinct parameters. Diversity was lowest after the hurricanes, showing weak resistance to physical disturbances. However, diversity was highest during the oil spill and coincided with a community shift, suggesting a new alternative stable state sustained for at least 1 year. The new AOA community was not significantly different from that at the spill site 1 year after the spill. This sustained shift in nitrifier community structure may be a result of oil exposure.