Mathematical modeling of interactions in evolving metaorganisms
Why do individuals from different taxonomic groups and even kingdoms of life interact with each other within a metaorganism in a generally beneficial way and thereby form a unit of selection? This question is one of the most fascinating, unresolved mysteries in current evolutionary biology. The reason is that selection at the individual level should usually be strongest for an evolving population, because at this level phenotypic variation directly translates into fitness differences among the individuals. At the level of the entire community, the same variations merge into an average value of fitness, possibly slowing down the response to selection at the community level.
Mathematical models can help us understand the selective conditions that favour beneficial interactions within the metaorganism. This project aims at establishing mathematical models based on empirical data obtained from two simple experimental systems, the Hydra and the C. elegans metaorganisms, which both serve to describe the interaction between different microbe types (bacteria, bacteriophages) and between these microbes and their host. The models will be used to understand the dynamics of the microbial interactions, i.e. the change in relative and absolute abundances of microbes over time, and also the resulting effects on fitness and other life-history functions of the metaorganism.
The project will rely on a close collaboration between experimental and theoretical groups. During the development of the mathematical models, which will be an abstraction and simplification of the biological reality, we will test important basic model assumptions and thereafter further expand the model in an iterative procedure between theory and experiments. The proposed project will prepare the ground for applying similar theoretical approaches to other research projects of the CRC 1182.
Spontaneous body contractions are modulated by the microbiome of Hydra.
Murillo-Rincon A P, Klimovich A, Pemöller E, Taubenheim J, Mortzfeld B, Augustin R, Bosch T C G (2017); Scientific Reports, 7(15937). doi:10.1038/s41598-017-16191-x
FeaturedA secreted antibacterial neuropeptide shapes the microbiome of Hydra.
Augustin R, Schröder K, Murillo Rincón A P, Fraune S, Anton-Erxleben F, Herbst E M, Wittlieb J, Schwentner M, Grötzinger J, Wassenaar T M, Bosch T C G (2017); Nat Commun., 8(1):698. doi: 10.1038/s41467-017-00625-1
The Natural Biotic Environment of Caenorhabditis elegans.
Schulenburg H, Félix M A (2017); Genetics., 206(1):55-86. doi: 10.1534/genetics.116.195511
Caenorhabditis elegans as a model for microbiome research.
Zhang F, Berg M, Dierking K, Félix M A, Shapira M, Samuel B, Schulenburg H (2017); Front. Microbiol., 8:485. doi: 10.3389/fmicb.2017.00485
Emerging Sponge Models of Animal-Microbe Symbioses.
Pita L, Fraune S, Hentschel U (2016); Front Microbiol., 7:2102. doi: 10.3389/fmicb.2016.02102
The Origin of Mucosal Immunity: Lessons from the Holobiont Hydra.
Schröder K, Bosch T C (2016); MBio., 7(6):e01184-16. doi: 10.1128/mBio.01184-16
Using Nematostella vectensis to Study the Interactions between Genome, Epigenome, and Bacteria in a Changing Environment.
Fraune S, Forêt S, Reitzel A M (2016); Front. Mar. Sci., 3:148. doi: 10.3389/fmars.2016.00148
Antimicrobial effectors in the nematode C. elegans – an outgroup to the Arthropoda.
Dierking K, Yang W, Schulenburg H (2016); Phil Trans R Soc Lond B., 371. doi:
The native microbiome of the nematode Caenorhabditis elegans: Gateway to a new host-microbiome model.
Dirksen P, Marsh SA, Braker I, Heitland N, Wagner S, Nakad R, Mader S, Petersen C, Kowallik V, Rosenstiel P C, Felix M A, Schulenburg H (2016); BMC Biology, 14:38. doi:10.1186/s12915-016-0258-1