Functional Modules, Structural Topology, and Optimal Activity in Metabolic Networks
Modular organization in biological networks has been suggested as a natural mechanism by which a cell coordinates its metabolic strategies for evolving and responding to environmental perturbations. To understand how this occurs, there is a need for developing computational schemes that contribute to integration of genomic-scale information and assist investigators in formulating biological hypotheses in a quantitative and systematic fashion. In this work, we combined metabolome data and constraint-based modeling to elucidate the relationships among structural modules, functional organization, and the optimal metabolic phenotype of Rhizobium etli, a bacterium that fixes nitrogen in symbiosis with Phaseolus vulgaris. To experimentally characterize the metabolic phenotype of this microorganism, we obtained the metabolic profile of 220 metabolites at two physiological stages: under free-living conditions, and during nitrogen fixation with P. vulgaris. By integrating these data into a constraint-based model, we built a refined computational platform with the capability to survey the metabolic activity underlying nitrogen fixation in R. etli. Topological analysis of the metabolic reconstruction led us to identify modular structures with functional activities. Consistent with modular activity in metabolism, we found that most of the metabolites experimentally detected in each module simultaneously increased their relative abundances during nitrogen fixation. In this work, we explore the relationships among topology, biological function, and optimal activity in the metabolism of R. etli through an integrative analysis based on modeling and metabolome data. Our findings suggest that the metabolic activity during nitrogen fixation is supported by interacting structural modules that correlate with three functional classifications: nucleic acids, peptides, and lipids. More fundamentally, we supply evidence that such modular organization during functional nitrogen fixation is a robust property under different environmental conditions. Biological networks are an inherent concept in systems biology that is useful in elucidating how biological entities—as metabolites or proteins—work together in supporting specific phenotypes in microorganisms. Notably, topological analyses carried out over these networks have shown that modular organization is a ubiquitous property at different levels of biological organization, in such a way that modular organization may serve as an organizing principle governing the metabolic activity in microorganisms. With the aim of elucidating the relationship among functional modules, network topology, and optimal metabolic activity, here we present an integrative study that combines computational modeling and metabolome data for evaluation of the metabolic activity of the soil bacterium Rhizobium etli during symbiotic nitrogen fixation with Phaseolus vulgaris. As a result, we supply experimental and computational evidence supporting the concept that the optimal metabolic activity during this biological process is guided by modular structures in the metabolic network of R. etli. Even more fundamentally, we suggest that these biochemical modules interact among each other to ensure an optimal phenotype during nitrogen fixation. Finally, through the in silico analysis on the genome scale metabolic reconstruction for R.etli, we give some examples that suggest that these modular structures supporting nitrogen fixation are robust to external physiological conditions.