RT Journal Article
SR Electronic
T1 Modeling trophic dependencies and exchanges among insects’ bacterial symbionts in a host-simulated environment
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 086165
DO 10.1101/086165
A1 Itai Opatovsky
A1 Diego Santos-Garcia
A1 Tamar Lahav
A1 Shani Ofaim
A1 Laurence Mouton
A1 Valérie Barbe
A1 Einat Zchori-Fein
A1 Shiri Freilich
YR 2016
UL http://biorxiv.org/content/early/2016/11/07/086165.abstract
AB Individual organisms are linked to their communities and ecosystems via metabolic activities. Metabolic exchanges and co-dependencies have long been suggested to have a pivotal role in determining community structure. Metabolic interactions with bacteria have been key drivers in the evolution of sap-feeding insects, enabling complementation of their deprived nutrition. The sap-feeding whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) harbors an obligatory symbiotic bacterium, as well as varying combinations of facultative symbionts. We took advantage of the well-defined bacterial community in B. tabaci as a case study for a comprehensive and systematic survey of metabolic interactions within the bacterial community and their associations with documented frequency of bacterial combinations. We first reconstructed the metabolic networks of five common B. tabaci symbionts (Portiera, Rickettsia, Hamiltonella, Cardinium and Wolbachia), and then used network analysis approaches to predict: (1) species-specific metabolic capacities in a simulated bacteriocyte-like environment; (2) metabolic capacities of the corresponding species’ combinations, and (3) dependencies of each species on different media components.The automatic-based predictions for metabolic capacities of the symbionts in the host environment were in general agreement with previously reported genome analyses, each focused on the single-species level. The analysis suggested several previously un-reported routes for complementary interactions. Highly abundant symbiont combinations were found to have the potential to produce a diverse set of complementary metabolites, in comparison to un-detected combinations. No clear association was detected between metabolic codependencies and co-occurrence patterns. The findings indicate a potential key role for metabolic exchanges as key determinants shaping community structure in this system.