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Modeling trophic dependencies and exchanges among insects’ bacterial symbionts in a host-simulated environment

Itai Opatovsky, View ORCID ProfileDiego Santos-Garcia, Tamar Lahav, Shani Ofaim, Laurence Mouton, Valérie Barbe, Einat Zchori-Fein, Shiri Freilich
doi: https://doi.org/10.1101/086165
Itai Opatovsky
Institute of Plant Sciences, Newe Ya’ar Research Center, The Agricultural Research Organization, Ramat Yishay, IsraelRegional Agricultural Research and Development Center, Southern Branch (Besor), Israel
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Diego Santos-Garcia
Department of Entomology, Hebrew University of Jerusalem, Rehovot, Israel
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  • ORCID record for Diego Santos-Garcia
Tamar Lahav
Institute of Plant Sciences, Newe Ya’ar Research Center, The Agricultural Research Organization, Ramat Yishay, Israel
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Shani Ofaim
Institute of Plant Sciences, Newe Ya’ar Research Center, The Agricultural Research Organization, Ramat Yishay, Israel
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Laurence Mouton
Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, 69622 Villeurbanne Cedex, France
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Valérie Barbe
CEA/DSV/IG/Genoscope, Evry, France
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Einat Zchori-Fein
Newe Ya’ar Research Center, The Agricultural Research Organization, Ramat Yishay, Israel
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Shiri Freilich
Institute of Plant Sciences, Newe Ya’ar Research Center, The Agricultural Research Organization, Ramat Yishay, Israel
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  • For correspondence: shiri@volcani.agri.gov.il
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Abstract

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.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted November 07, 2016.
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Modeling trophic dependencies and exchanges among insects’ bacterial symbionts in a host-simulated environment
Itai Opatovsky, Diego Santos-Garcia, Tamar Lahav, Shani Ofaim, Laurence Mouton, Valérie Barbe, Einat Zchori-Fein, Shiri Freilich
bioRxiv 086165; doi: https://doi.org/10.1101/086165
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Modeling trophic dependencies and exchanges among insects’ bacterial symbionts in a host-simulated environment
Itai Opatovsky, Diego Santos-Garcia, Tamar Lahav, Shani Ofaim, Laurence Mouton, Valérie Barbe, Einat Zchori-Fein, Shiri Freilich
bioRxiv 086165; doi: https://doi.org/10.1101/086165

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