Spatiotemporal single-cell Bioinformatics

The rapid development of (RNA-)sequencing assays at unprecedented throughput and resolution enables us to capture detailed molecular profiles for millions of single cells from human tissue or body fluids, and even for single disease-causing germs. Recent experimental approaches combining methods to individually tag RNA molecules from single cells at specific tissue locations for subsequent high-throughput sequencing open a myriad of potential viewpoints to study the spatial patterns of infectious disease (Spatial Transcriptomics). For a deeper analysis of sequencing data and to discover functional relationships advanced integrative bioinformatics tools are required. Moreover, several known but also yet hidden technical factors in such experiments play an important role during data generation and influence our machine learning-driven interpretation of outcomes. Thus, we make use of different state-of-the-art technologies (e.g. Visium, STOmics) in close collaboration with leading companies in the field to test our computational approaches under varying experimental setups. Primarily we are looking for interesting and challenging applications around infection, neurodegeneration and antibiotics research as to further cartography cellular and molecular features as a basis for new drug target candidates.

Biological barriers are an essential mean of the human body to establish certain physiological conditions and play an important role for our immune system. First and foremost, they keep individual tissue compartments separated and different zonation areas sterile, i.e. free from circulating microbes. Numerous examples of human diseases exist where impaired bio-interfaces are one of the major underlying pathogenic entry points. At the same time, an on-going challenge in drug development is to transfer small or natural compounds beyond these barriers at a specified time and concentration. Thus, we are interested to uncover gene expression programs of the often very specialized cells, like epi- or endothelial cells, as well as peripheral immune cells residing at tissue gateway interfaces and how we can use them for targeted drug delivery. Furthermore, we see strong potential in a class of compounds that is able to molecularly repair dysregulated barrier cells, eventually supporting human therapy.

Bioinformatics routinely involves processing enormous amount of data of various flavors. Overall, there is a strong trend for exponentially increasing data amounts and assay complexity. Thus, among our scientific community we are in urgent need of open, flexible, and highly efficient formats for data storage and exchange. Our group follows the FAIR principle and relies on our strong experience on developing broadly used and peer-reviewed online resources like databases and web servers. We continuously share new software and experimental data sets with the scientific community and place value on providing sufficiently preprocessed and comprehensive data collections in order to be AI-ready. Finally, we commit ourselves to enable transparency and reproducibility in the field and thus also invest research into how we can improve computational tools in those nowadays essential aspects. To reach this goal we run joint collaborations with our Helmholtz colleagues from the CISPA Helmholtz Center for Information Security.