(727b) Integrative Analysis of Gene Co-Expression and Metabolic Networks in Microbial Communities: Organizational Properties of a Unicyanobacterial Consortium Conference: AIChE Annual MeetingYear: 2015Proceeding: 2015 AIChE Annual MeetingGroup: Food, Pharmaceutical & Bioengineering DivisionSession: Cell Culture II: Metabolic Flux Analysis and Modeling Time: Thursday, November 12, 2015 - 3:37pm-3:59pm Authors: Song, H. S., Pacific Northwest National Laboratory McClure, R. S., Pacific Northwest National Laboratory Overall, C. C., Pacific Northwest National Laboratory Bernstein, H. C., Pacific Northwest National Laboratory Beliaev, A. S., Pacific Northwest National Laboratory Taylor, R. C., Pacific Northwest National Laboratory Henry, C. S., Argonne National Laboratory Lindemann, S. R., Pacific Northwest National Laboratory Wiley, H. S., Pacific Northwest National Laboratory Fredrickson, J. K., Pacific Northwest National Laboratory Biological networks often show remarkable robustness by preserving their functionalities against perturbations. Robust networks are known to possess specific topological characteristics such as being scale-free, meaning that they can tolerate random disruption of genes (nodes), but are vulnerable to targeted removal of highly connected genes (hubs). Case studies in the literature have reported such topological signatures in gene regulatory, protein-protein interaction, and metabolic networks of single organisms, but, as yet, little is known regarding general organizational principles of microbial communities. The main reason for this is the lack of reliable network models for complex communities. Here, we set out to identify the structural properties of a unicyanobacterial consortium by viewing it as a network of genes. For this purpose, we collect a compendium of gene expression data of this consortium across multiple time points and conditions and reconstruct a compartmentalized gene co-expression network. Using a platform previously developed by our group, we then combine the reconstructed gene co-expression network with a community-scale metabolic network. This integrative analysis offers an opportunity to reveal the interrelationship between topological and functional roles of genes across multiple interacting organisms.