Systems Biology has four main research themes

1 – Cell Physiology and Applications

Cellular physiology is essential for our understanding of cell survival and proliferation, how cells interact with each other and how we can exploit them for biotechnological or biomedical applications. Within the research group “Cell Physiology and Applications” we are devoted to a better understanding of physiological organizing principles in cells. Model organisms include the prokaryotes E. coli and lactic acid bacteria as well as the eukaryotes yeast, African trypanosomes and liver cancer cells. While a big part of the focus is on central carbon metabolism we also investigate secondary metabolism such as the degradation and consumption of extracellular compounds or the formation of volatile metabolites.
We use advanced culturing technologies such as microdroplets, microplates and bioreactors, -omics technologies, metabolic modeling and experimental evolution to unravel underlying principles. With these tools we can predict and validate conditions for optimal yields or drug interventions. In diseased cells similar techniques can be used to identify bottlenecks that can be exploited by drugs. We have numerous collaborations with industry on topics including the optimization of growth rates, biomass- and metabolite-production or decreased lag-times.

2 – Single-cell metabolism and gene expression regulation

Deciphering the relationship between molecules and cellular phenotypes is one of the most compelling challenges in life sciences, requiring the integration of approaches that span multiple biological scales. We are still far from understanding the rules that control the interactions between biomolecules and the impact on the physiology of single cells or multicellular organisms. To close this gap, we apply and develop a wide-range of single-cell approaches that allow us to accurately measure, within individual cells, key biomolecules such as RNAs, proteins and metabolites. We use time-lapse fluorescence microscopy for single mRNA (MS2 system) and protein (Fluorescence-based FRET-sensors) detection in living cells, as well as single molecule RNA FISH (smFISH) in fixed cells, to investigate the spatial and temporal regulation of metabolism and gene expression and the consequences on cellular fitness. Methods from statistical biophysics, quantitative image analysis and machine learning are used to analyze raw data, and to predict and understand experimental outcomes.
A key biological question that we study is how cells optimize growth rates. We combine multiple single-cell model organisms such as E. coli, S. cerevisiae and S. pombe to unravel the conserved principles operating on molecular networks that coordinate gene expression regulation, metabolism and cell signaling.

3 – Modeling and Microbial communities

Our goal is to find common mechanisms behind the diverse phenotypes and behaviours of microorganisms. We use experimental and modeling tools to persue this goal. Mathematical modeling helps us to strip ideas and hypotheses to the necessary concepts that explain apparently complex phenomena like switching between different forms of metabolism. A guiding principle in such models is the idea that natural selection tends to increase the fitness of individuals and that fitness can be described as a mathematical function of the properties of an organism. Such models ideally predict properties of extant organisms and can be verified using omics and evolutionary experiments. Other classes of models that we create are of an encyclopedic nature, describing all metabolic reactions in a microorganism, or describe detailed kinetics of a part of metabolism. Such models are used in experimental cycles to interpret data and test and improve our knowledge of physiology.
The strategies that microorganisms use are also shaped by natural selection on the interactions with each other. These interactions can also be understood by their direct and indirect effects on individual fitness. We investigate them by using individual-based fitness models. At a higher system level, we try to understand the interaction between individual fitness and properties of communities and ecosystems, like their species diversity and the metabolic reactions and interactions taking place. For this we use data driven approaches like (meta)genomics and transcriptomics analyses. To generate the necessary data and to tests hypotheses we carry out experiments in our lab but also cooperate with specialists working in, for example, food, environmental and medical microbiology.

Schematic representation of the vaginal environment with either a Lactobacillus-dominated (LVM) or dysbiotic vaginal microbiota (DVM). Taken from Van der Veer, Hertzberger et al. and Kort (2019)
Schematic representation of the vaginal environment with either a Lactobacillus-dominated (LVM) or dysbiotic vaginal microbiota (DVM). Taken from Van der Veer, Hertzberger et al. and Kort (2019)

4 – Host microbe interactions

The vaginal mucosa hosts a community of commensal, symbiotic, and sometimes pathogenic microorganisms. The bacteria within this community, also referred as the vaginal microbiota, play an important role in protecting the vaginal tract from pathogenic infection, which can have far-reaching consequences on a woman’s sexual and reproductive health. Several vaginal microbiota compositions have been described, including those dominated by Lactobacillus iners, Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus jensenii, and those that are not dominated by a single bacterial species but rather consist of a highly diverse community of anaerobic bacteria, including Gardnerella vaginalis and members of the bacterial families of Lachnospiraceae, Leptotrichiaceae and Prevotellaceae. In particular, microbiota that are dominated by L. crispatus are associated with vaginal health, whereas microbiota consisting of diverse anaerobes – commonly referred to as vaginal dysbiosis – has been shown to increase a woman’s odds for developing bacterial vaginosis, acquiring sexual transmitted diseases, and having adverse pregnancy outcomes. At the lab for systems biology we characterize the vaginal microbiota and human isolates of Lactobacillus crispatus in a variety of experimental settings with the aim to identify bacterial and human genetic and phenotypic characteristics pertaining to the successful domination of these lactobacilli. Accordingly, we aim to understand the transition from adverse to beneficial bacterial communities and vice versa that colonize the epithelium of the human vagina.