Biological networks

Viral and bacterial infections present a major public health concern worldwide. Many pathogens cannot be treated with present day drugs. Moreover, most of the available antiinfectives target gene products of the parasite and they can be rendered ineffective by adaptive changes of the pathogen through mutation. An alternative therapeutic strategy is to interfere with host proteins that are essential for viral entry or bacterial uptake. In this project, we aim to understand the signaling cascades that are triggered in host cells upon infection. Our goal is to construct models of the cellular network responsible for pathogen sensing and inflammation and to identify host proteins as new potential drug targets.

We investigate the infection of human epithelial cells by bacteria using RNA interference (RNAi). These intervention experiments shed light on the set of host proteins involved in the signaling pathway and on epistatic interactions among them. Thus, RNAi screens offer indirect evidence on the structure of the underlying signaling network. We develop statistical methods for the analysis of RNAi data, including the ranking of genes to identify hits, and for the reconstruction of signaling pathways.

We are also concerned with the analysis of biological networks. Specifically, we aim to quantitatively assess redundancy in intracellular networks. To this end, we are developing a computational method to predict redundancy partners based on the topology of the biochemical network that carries out a particular cellular function. With this approach and eventually through experimental validation, we want to identify and characterize the redundancy partners of given proteins.

Selected references

• Beerenwinkel N, Pachter L, Sturmfels B (2007) Epistasis and shapes of fitness landscapes. Statistica Sinica 17:1317-1342.
• Beerenwinkel N, Pachter L, Sturmfels B, Elena S, Lenski R (2007) Analysis of epistatic interactions and fitness landscapes using a new geometric approach. BMC Evolutionary Biology 7:60.