Predictive Modeling of Microbial Partnerships


Many biogeochemical processes involved in the global carbon cycle are not performed by individual organisms, but rather by collaborative partnerships between two or more microbes. Referred to as “syntrophy,” these partnerships often involve consumption of carbon compounds that cannot be used by any individual organism, but yield sufficient energy for growth when paired organisms couple their metabolic capabilities. These associations are critical to carbon decomposition processes and are particularly important in oxygen-limited environments such as wetlands, sediments, and subsurface aquifers. In a new study funded by the Department of Energy’s Genomic Science Program, a team of researchers has developed a novel genome-scale, multi-omics based modeling approach to investigate the systems biology of syntrophic microbial partnerships. The team focused on Geobacter metallireducens and Geobacter sulfurreducens, two microbes that are capable of syntrophically consuming ethanol and formate (two major products of carbon decomposition). By examining the flow of metabolites within and between the partners, and coupling this information to genome-wide analysis of shifts in gene expression, a new model was developed that enabled the team to test the hypothesis that direct transfer of electrons between the two species permits this mode of metabolism. The study’s results shed new light on a poorly understood aspect of carbon cycle processes. They also represent a significant advance in our ability to extend genome scale systems biology modeling approaches to multispecies microbial consortia. This publication was selected as a research highlight in the January 2014 issue of the journal Nature Reviews Microbiology.


Nagarajan, H., M. Embree, A.-E. Rotaru, P. M. Shrestha, A. M. Feist, B. Ø. Palsson, D. R. Lovley, and K. Zengler. 2013. “Characterization and Modelling of Interspecies Electron Transfer Mechanisms and Microbial Community Dynamics of a Syntrophic Association,” Nature Communications 4, 2809. DOI:10.1038/ncomms3809.

Molloy, S. 2013. “Disentangling Syntrophy,” Nature Reviews Microbiology 12, 7. DOI:10.1038/nrmicro3194.