(727b) Integrative Analysis of Gene Co-Expression and Metabolic Networks in Microbial Communities: Organizational Properties of a Unicyanobacterial Consortium | AIChE

(727b) Integrative Analysis of Gene Co-Expression and Metabolic Networks in Microbial Communities: Organizational Properties of a Unicyanobacterial Consortium

Authors 

Song, H. S. - Presenter, Pacific Northwest National Laboratory
McClure, R. S. - Presenter, Pacific Northwest National Laboratory
Overall, C. C. - Presenter, Pacific Northwest National Laboratory
Bernstein, H. C. - Presenter, Pacific Northwest National Laboratory
Beliaev, A. S. - Presenter, Pacific Northwest National Laboratory
Taylor, R. C. - Presenter, Pacific Northwest National Laboratory
Henry, C. S. - Presenter, Argonne National Laboratory
Lindemann, S. R. - Presenter, Pacific Northwest National Laboratory
Wiley, H. S. - Presenter, Pacific Northwest National Laboratory
Fredrickson, J. K. - Presenter, 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.