Lead: PD Dr. Luisa F. Jiménez-Soto
Bacterial toxins are known to help bacteria escape the immune system and, therefore, considered pathogenicity mechanisms of bacteria causing diseases. But what if we would look at them in another light, another point of view? We might be able to discover new methods to deal better with bacterial infections or even find new medical treatments at the cellular level using bacterial toxins.
Bacterial toxins have possibly helped bacteria to survive by escaping their natural predators: unicellular microorganisms classified as protists. Several predatory capabilities from some protists have been conserved during evolution and are used by human immune cells, like macrophages and dendritic cells. One example is the similarity in phagocytosis pathways between both groups. As a consequence, all methods bacteria have evolved to escape protists, like exotoxins, have a very good chance to work in immune cells, leading to higher chances of disease.
After more that 100 years of research in bacterial toxins, we have a pretty good idea of their mechanisms of action at the molecular level. It is so clear that today cell biologists use several of them as molecular tools to manipulate and research cellular pathways. Today Bioinformatics has open the option of expanding bacterial toxin research to novel areas that had been difficult in traditional microbiological studies, where culture of bacteria is required, by combining the previous accumulated knowledge and the growing sequencing data with Data Science tools.
Our research will address novel bacterial toxins, their origins and their effects on immune cells using as models the natural predators of bacteria using Data science and molecular biology techniques . This will be achieved in a research environment where in-silico (Bioinformatics) and wet-lab (microbiology, molecular biology and immunological techniques) go hand-in-hand and are applied by all lab members.
The development of our research strategy, combining data science and wet-lab, will be quite limited if it wasn’t because of our collaboration partner, Prof. Burkhard Rost and his wonderful team (www.rostlab.org) from the TUM. Their knowledge and research in State-of-the-Art machine learning methods allow us to apply the newest techniques in Natural Language Processing to our bacterial toxin research.
@Students: If you are interested in applying your data science skills combined with laboratory work, feel free to contact me. As a starting lab, our capacity is limited. However we enjoy having new students who are curious about nature, medicine, and willing to apply their studies knowledge, independently of their discipline and experience. You shall feel motivated to learn and work with in-silico and wet-lab techniques. We work in an international team with English as standard language. For our in-silico work, we use R and Python languages for statistics, visualization, data analysis and Machine Learning, and in the wet-lab we work with Biosafety level 1 and 2 organisms.
The pandemic has limited our capacity of having students in the lab, but we managed to welcome internship students from the biology faculty in the second semester of 2021. With 2022 starting, we are now welcoming students from chemistry and medicine. We are looking forward to integrate students from Bioinformatics, Computer Science, Mathematics and Statistics in our team.