Abstract
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.
Highlights
The ecosystems behavior, as observed today by experiments, is the immediate result of microbial interactions between several organisms
We considered a chemoautotrophic microbial community related to the copper bioleaching process, one of the most extensive and complex biohydrometallurgic processes in which a series of chemical and biological reactions facilitate the oxidation of insoluble sulfide ores, releasing soluble metals such as copper
After an exhaustive description of the SGS method and omics data used for its application, this study provides an integrative view of bioleaching at both metabolic pathway and m icrobial genome levels
Summary
The ecosystems behavior, as observed today by experiments, is the immediate result of microbial interactions between several organisms. Advances in bioinformatics have improved the analysis of next-g eneration sequencing data that characterize microbial communities, addressing the question “who is there and who is not” (Raes et al 2011) This description remains insufficient to depict functional behaviors of microbial ecosystems if no other complementary knowledge is considered. Microbial cross- feedings are for instance investigated by integrating phylogenetic and environmental knowledge (see Zaneveld et al 2011 for review); omics experiments and in situ observations (Orphan 2009; Zelezniak et al 2015); or metabolic networks and diversity graphs (Tzamali et al 2011) These recent modeling approaches are all complementary and reinforce the emergence of the new subdiscipline called systems ecology (Klitgord and Segrè 2011) that aims to tackle complex ecological questions by merging heterogeneous data with new computational techniques. That should be further investigated to understand putative metabolic collaborative processes at the community level
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