Microbial metabolism in aromatic-contaminated environments has important ecological implications, and obtaining a complete understanding of this process remains a relevant goal. To understand the roles of biodiversity and aromatic-mediated genetic and metabolic rearrangements, we conducted ‘OMIC’ investigations in an anthropogenically influenced and polyaromatic hydrocarbon (PAH)-contaminated soil with (Nbs) or without (N) bio-stimulation with calcium ammonia nitrate, NH4NO3 and KH2PO4 and the commercial surfactant Iveysol, plus two naphthalene-enriched communities derived from both soils (CN2 and CN1, respectively). Using a metagenomic approach, a total of 52, 53, 14 and 12 distinct species (according to operational phylogenetic units (OPU) in our work equivalent to taxonomic species) were identified in the N, Nbs, CN1 and CN2 communities, respectively. Approximately 10 out of 95 distinct species and 238 out of 3293 clusters of orthologous groups (COGs) protein families identified were clearly stimulated under the assayed conditions, whereas only two species and 1465 COGs conformed to the common set in all of the mesocosms. Results indicated distinct biodegradation capabilities for the utilisation of potential growth-supporting aromatics, which results in bio-stimulated communities being extremely fit to naphthalene utilisation and non-stimulated communities exhibiting a greater metabolic window than previously predicted. On the basis of comparing protein expression profiles and metagenome data sets, inter-alia interactions among members were hypothesised. The utilisation of curated databases is discussed and used for first time to reconstruct ‘presumptive’ degradation networks for complex microbial communities.
Herein, we provide a novel, context-specific reconstruction procedure based on metaproteomic and taxonomic data. Without previous knowledge of a high-quality, genome-scale metabolic networks for each different member in a bacterial community, we propose a meta-network approach, where the expression levels and taxonomic assignments of proteins are used as the most relevant clues for inferring an active set of reactions. Our approach was applied to draft the context-specific metabolic networks of two different naphthalene-enriched communities derived from an anthropogenically influenced, polyaromatic hydrocarbon contaminated soil, with (CN2) or without (CN1) bio-stimulation. We were able to capture the overall functional differences between the two conditions at the metabolic level and predict an important activity for the fluorobenzoate degradation pathway in CN1 and for geraniol metabolism in CN2. Experimental validation was conducted, and good agreement with our computational predictions was observed. We also hypothesize different pathway organizations at the organismal level, which is relevant to disentangle the role of each member in the communities. The approach presented here can be easily transferred to the analysis of genomic, transcriptomic and metabolomic data.
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