Microbes are everywhere and make up most of the biomass on earth. They occur in assemblages or microbial communities (MCs) and conduct complex, collective functions that are of highest importance for biogeochemical cycles on earth and human well being alike. For example the microbiome in the human gut can be actively health promoting or causative for chronic diseases or cancer. These emergent community functions are driven by microbial interactions. Despite their relevance, microbial interactions have only recently become subject of scientific research. In the proposed research I will study how divers environments and the predictability of perturbation in these habitats shape microbial interactions and collective functions.

Based on my prior studies I hypothesize that distinct perturbation levels in natural habitats give rise to different organization of interactions - these types can be detected in sequence data and used for establishing mechanistic understanding of community function. I will use an integrative systems biology approach to study the environmental impact: I will setup a mathematical model that allows the simulation of MCs in predictable and unpredictable environments. I will associate environmental perturbation levels with signatures in community structure and temporal dynamics in the simulated data. Based on the model outcome I will develop a generic concept of environmental predictability that is applicable to seemingly far-apart cases like the human microbiome or microbiota in soil or wastewater treatment plants. This concept will be used for the analysis of natural MCs from distinct habitats with the aim of predicting community behaviour. The proposed research will have direct applications in medicine, industrial biotech and global climate regulation.