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

PLoS One. 2017 Aug 2;12(8):e0181826. doi: 10.1371/journal.pone.0181826. eCollection 2017.

Abstract

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.

MeSH terms

  • Agriculture
  • Algorithms
  • Bacteria / genetics*
  • Bacteria / metabolism
  • Computer Simulation
  • DNA, Bacterial / analysis
  • Metabolic Flux Analysis
  • Metabolic Networks and Pathways*
  • Metagenomics / methods*
  • Models, Biological
  • Sequence Analysis, DNA / methods
  • Soil Microbiology*

Substances

  • DNA, Bacterial

Grants and funding

This work received funding from Colciencias (contract Nos. 573-2012 and 649-2013). The funder provided support in the form of salaries for authors MCAS and AAY but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.