PLoS ONE (Jan 2017)

Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils.

  • María Camila Alvarez-Silva,
  • Astrid Catalina Álvarez-Yela,
  • Fabio Gómez-Cano,
  • María Mercedes Zambrano,
  • Johana Husserl,
  • Giovanna Danies,
  • Silvia Restrepo,
  • Andrés Fernando González-Barrios

DOI
https://doi.org/10.1371/journal.pone.0181826
Journal volume & issue
Vol. 12, no. 8
p. e0181826

Abstract

Read online

Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community.