RTF II: Evolution and ecology of microbes

Coordinators: M. Groussin (CAU), S. Niemann (RCB, UzL), J. Rupp (UzL)

Many chronic inflammatory diseases are influenced by microorganisms, either by individual pathogens or by a community of numerous microorganisms (e.g. the microbiome). Evolutionary and/or ecological changes in the interaction with these microbes are often key to the emergence of a disease, but are frequently neglected in medical research. RTF II is based on the newly-created research area of evolutionary medicine. The researchers in RTF II use evolutionary approaches to improve our understanding of the ecological and evolutionary basis of microbe-induced, patient-specific inflammatory diseases such as COPD, tuberculosis and inflammatory bowel disease (IBD).

Northern Germany has become one of the hot spots in Europe for evolutionary research, and evolutionary medicine in particular. Members of PMI have developed a variety of approaches to better understand the evolutionary and ecological dynamics of disease-associated microbes or microbial communities. On the basis of these activities, several major research initiatives in evolutionary medicine have been funded, including the Leibniz ScienceCampus Evolutionary Medicine of the Lung (EvoLUNG), the Clinician Scientist Program in Evolutionary Medicine (CSEM) and the Research Training Group "Translational Evolutionary Research" (RTG TransEvo).

The primary goal of RTF II is to analyze the evolutionary and ecological dynamics which contribute towards microbe-induced chronic inflammatory diseases. As a central approach, RTF II is setting up an experimental evolution platform to assess the influence of eco-evolutionary changes in individual microbes or microbial communities on disease-specific characteristics (e.g. antibiotic resistance or virulence in COPD-related Pseudomonas aeruginosa). RTF II will also establish a patient-specific microbiome library related to IBD, to serve as the basis for further eco-evolutionary analyses and possible interventions.

Evolutionary and ecological processes are at the core of many chronic diseases, in particular those, which are characterized by individual microbes or the entire microbiome, but their importance has been largely neglected in medical research, if not ignored completely. RTF II specifically considers the evolutionary and ecological processes to gain a deeper understanding of microbe-associated diseases. The medium-term goal of this approach is to improve the sustainability of novel interventions against chronic inflammatory diseases. To this end, RTF II combines evolutionary medicine with the challenges of precision medicine.

The microbe-related eco-evolutionary processes often vary between patients, and thereby influence whether certain diseases occur at all. RTF II’s experimental approach provides insights into how such eco-evolutionary processes are connected with disease-related characteristics. With the data obtained, precision medicine therapies which target the individual microbes or the composition of the microbiome can be developed - examples of such forms of treatment are microbial/microbiome transfer, evolution-based antibiotic therapy or diet-related measures.

Characterization and validation of organisms from evolution experiments or the patient-specific microbiome are carried out in cooperation with RTF V (metabolomic analysis), RTF VI (sequence-based profiling) and RTF IV (experimental inflammation models). The results are utilized in the theoretical modeling of RTF VIII (theoretical models of inflammation) to develop a predictive precision medicine framework, which should particularly be applied in CD-3 (individualized antibiotic therapy) and TI-1 (microbiome-related therapy), but also in CD-2 (tryptophan metabolism and inflammation) and CD-5 (T-cell-oriented therapy).

What does this research area’s work build on?

What are the main research objectives?

What makes this research area special?

What does the research area contribute to precision medicine in chronic inflammation?

Cooperation with other research areas in the cluster

Members