Understanding Environment-Microbiome-Host metabolic interactions in Hydra

• Applicant: Dr. Jan Taubenheim
• Subject Area: Microbial Ecology and Applied Microbiology ; Bioinformatics and Theoretical Biology ; Ecology and Biodiversity of Animals and Ecosystems, Organismic Interactions
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 525705073

The human microbiome strongly impacts the physiology and health of its host, and a dysbiosis might have a huge impact on several medical conditions. Therefore, it is highly relevant to understand how a microbiome assembles, reacts to changing environments, and how it can be shaped to ameliorate the effect of dysbiotic bacterial communities. However, the human microbiome is diverse across different individuals and strikingly complex, harboring countless potential higher-order interactions with its host and between bacterial members. It is thus desirable to study the host-associated microbiome in a less complex setup to better track these interactions and identify general mechanisms, which can be transferred to more diverse microbial communities. Here, I propose to use the freshwater polyp Hydra as a model system to study the metabolic interactions between bacteria of its associated microbiome and the host under changing nutritional conditions. The Hydra microbiome is much simpler than the human one consisting of only 8-15 taxa. Major parts of it have been isolated and can be studied separately, while protocols exist to recolonize the Hydra polyp with specific parts of its microbiome, rendering the model system extremely valuable for studying bacterium-bacterium and bacteria-host interactions in a multicellular host. I will use the genetic information of Hydra and its associated bacteria to reconstruct metabolic models of all community members. With these models, I will predict metabolic bacteria-bacteria and bacteria-host interactions. Further, I will simulate changes in the nutrient availability in the environment and assess how this affects these interactions. Finally, the results will be related to changes in 16S sequencing data after an experimental alteration of nutrient availability to identify the variations in the bacterial community, which are caused by the changes in the metabolic interactions. In the first part I will focus specifically on pairwise bacterium-bacterium as well as bacterium-host interactions and their ability to predict community dynamics. Secondly, I will take a closer look at bacterium-community interactions to assess the contribution of one-to-many interactions to community dynamics. The proposed research is highly interdisciplinary, combining computational tools such as metabolic modeling, genomics, and metagenomics to investigate the host-microbiome interactions and describe ecological functions of the microbiome, eventually providing a more comprehensive understanding of the system. Overall, the proposed study offers a unique window into the complex relationships between the host, microbiome, and the environment, with the potential to inform about general mechanisms that are also relevant in human health and disease.

• DFG Programme: Research Grants