Research Area B: Bacterial Cells and Communities

Central question:

Which complex interaction networks shape mutualism or antagonism along with strain evolution and adaptation in bacterial communities?

Aim

Members of complex bacterial communities interact on multiple levels. These interactions may involve the exchange of genetic information, metabolites and molecular signals and they ultimately contribute to the dynamics and evolution of microbiomes. Scientists in Research Area B join forces to characterize the contribution of phages to the spread of genes related to antibiotic resistance, fitness and virulence within human microbiomes, using computational, biochemical and cell biology approaches.

In parallel, they will dissect the major mutualistic and antagonistic metabolic interactions of host-associated or in vitro -reconstituted microbiomes, using a combination of omics approaches. The long term goals of Research Area B are the development of targeted phage-based anti-infective strategies and the identification of microbial metabolic consortia with therapeutic potential.


Principal Investigators
Prof. Dr. Largus Angenent

University of Tübingen
Center for Applied Geoscience
Environmental Biotechnology
Website

Prof. Dr. Daniel Huson

University of Tübingen
Center for Bioinformatics
Algorithms in Bioinformatics
Website

Prof. Dr. Andreas Peschel

University of Tübingen
Interfaculty Institute of Microbiology and Infection Medicine
Infection Biology
Website

Prof. Dr. Karl Forchhammer

University of Tübingen
Interfaculty Institute of Microbiology and Infection Medicine
Organismic Interactions
Website

Prof. Dr. Andreas Kappler

University of Tübingen
Center for Applied Geoscience
Geomicrobiology
Website

 

Prof. Dr. Christiane Wolz

University of Tübingen
Interfaculty Institute of Microbiology and Infection Medicine
Website

Prof. Dr. em. Friedrich Götz

University of Tübingen
Interfaculty Institute of Microbiology and Infection Medicine
Microbial Genetics
Website

Prof. Dr. Kay Nieselt

University of Tübingen
Center for Bioinformatics
Integrative Transcriptomics
Website