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Christina Kuttler

Publications and source records attributed to Christina Kuttler.

4 recordsLinked to original sources
PubMed2006

Cell-cell communication by quorum sensing and dimension-reduction.

Several bacterial taxa change their behavior if the population density exceeds a certain threshold. This phenomenon is the consequence of a communication system between the bacteria and is called quorum sensing (QS). Up to now, this phenomenon is mostly modeled at population level. However, new experimental techniques allow for single cell analysis. We introduce a modeling approach for the description of this QS system, including a discussion of the regulatory network and its bistable behavior. Based on this single-cell model we develop and analyze a spatially structured model for a cell population. Special attention is given to the scaling behavior w.r.t. the cell size (leading to an approximation theorem for stationary solutions) and its consequences for the interpretation of cell communication (QS versus diffusion sensing). Concluding, we apply the modeling approach to spatially structured experimental data.

4-Butyrolactone↗
PubMed2003

MAPPP: MHC class I antigenic peptide processing prediction.

MAPPP is a bioinformatics tool for the prediction of potential antigenic epitopes presented on the cell surface by major histocompatibility complex class I (MHC I) molecules to CD8 positive T lymphocytes. It combines existing predictions for proteasomal cleavage with peptide anchoring to MHC I molecules.

Algorithms↗
PubMedDate not supplied

Cleaving proteins for the immune system.

Proteasomes are enzymes in eukaryotic cells which cut proteins marked for degradation into fragments. In mammals some of these fragments are used by the immune system to detect proteins of foreign, e.g. viral, origin. Hence reproducing, predicting and possibly understanding the cleaving patterns of proteasomes is an interesting theoretical problem and its solution would be beneficial for vaccine design. The equations connecting cut probabilities, fragment frequencies and so-called cut strengths are derived. A simple model for the time course of protein digestion is used to explain the problem of fragment competition and the possible deviation of in vitro fragment frequencies from those that can be expected in vivo. A family of neural network proteasome models for the reproduction and prediction of cleavage patterns is described in detail together with the webtool PAProC. The first model is based on the experimentally observed cleavage pattern, an intermediate model on the distinction between weak and strong cuts, and the most elaborate model uses quantitative data, i.e., fragment frequencies.

Amino Acid Sequence↗