Petra Lutter

In Miller-like experiments the first organic building blocks like amino acids are produced - the input for this primordial soup is only inorganic material. It is our target to move beyond the original setup in order to pave the way for more complex molecules as, e.g., sugars. Experimental runs with varying atmospheres shall help to better understand how the first biomolecules were formed on our primordial Earth. Additionally, chemical reactions are triggered by carrier substances in the reaction vessel.

When the receptors of a plant cell detect so-called elicitors, internal calcium stores release their ions into the cytosol. As a consequence, plants may synthesize, e.g., hydrogen peroxide to defend themselves against intruders. We have set up a mathematical model to describe the calcium reaction in a tobacco cell via differential equations. It is our target not only to find out more about the functionality of the defense process, but also to understand the observed refractory behavior. The model predicts that only after a certain time interval the plant cell is ready for the next stimulus. Microscopic life cell experiments accompany the modeling process.

Raman spectroscopy is used to provide a structural fingerprint of a molecule. We want to establish objective criteria to describe the differences in Raman spectra that might even be similar at first sight. The spectra should undergo various processing steps, until the fundamental underlying information becomes visible. With this technique it shall, e.g., be possible to tell by which bacterial strain a certain polysaccharide has been produced.

Far too often it is difficult to estimate the correct dose of prescribed drugs. Via mathematical modeling we want to predict in which organs an applied substance, e.g., tyrosine, accumulates. As too much tyrosine is toxic for the human body, it is essential to carefully balance the involved processes. With the help of a detailed micro-model we look at the reactions in a single cell. The outcome of this simulation is later on used as input for a macro-model that predicts the tyrosine concentration in each organ. Different model scenarios can mimic a variety of tyrosine-related diseases.

It is fascinating how the behavior of a bacterial strain can suddenly change. At a certain time point, e.g., Xanthomonas slows down its growth in order to enhance its exopolysaccharide production. To find more about at which level this information is encoded we combine lab as well as simulation experiments. While a detailed mathematical network shall help to follow up the behavior of, e.g., specific enzymes, GC-MS analysis delivers information on the metabolic profile. Additionally, 13C-flux experiments can show which pathway is favored in which phase of the bacterial life.