Bork Group
Deciphering function and evolution of biological systems
Mycoplasma pneumonia. Together with other SCB groups, we overlay genomic, transcriptomic, proteomic, metabolic and structural data to establish a model organism for systems biology and discover lots of exciting biology on the way (see Kuehner et al., 2009, Guell et al., 2009 and Yus et al., 2009, all Science). The figure depicts a tomographic snapshot, a single particle EM of the ribosome (many proteins of which have unexpected links to various cellular processes indicated by lconnectors) and a metabolic reconstruction in which the correspondence to operon organisation is shown (blue).
Previous and current research
The main focus of our computational biology group is to gain insights into biological systems and their evolution by comparative analysis and integration of complex molecular data. The group currently works on three different spatial scales, but with common underlying methodological frameworks:
- genes, proteins and small molecules;
- networks and cellular processes;
- phenotypes and environments, oft en related to diseases.
We are aiming at biological discoveries and oft en develop tools and resources to make this happen. We usually work in new or emerging areas of biology; for example we have projects that integrate drugs (and other small molecules) with cellular and phenotypic information to predict new uses for old drugs (e.g. Campillos et al., 2008, Science) or find biomolecules that cause disease or side effects. We study temporal and spatial aspect of protein networks to identify biological principles that determine function and evolution (e.g. de Lichtenberg et al., 2005, Science; Jensen et al., 2006, Nature; Kuehner et al., 2009, Nature). We also trace the evolution of the animal gene repertoire (e.g. Ciccarelli et al., 2006, Science) and, for example, connect gene losses and duplications with morphological or lifestyle changes. We study environmental aspects via comparative metagenomics (Tringe et al., 2005, Science; von Mering et al., 2007, Science; Qin et al., 2010, Nature) and hope to find marker genes for various diseases like obesity and cancer, but also to understand microbial community interactions. All our projects are geared towards the bridging of genotype and phenotype through a better understanding of molecular and cellular processes.
Integration of metagenomics data with environmental factors. Using novel visualization concepts and statistical approaches we can correlate the abundance of molecular functions to external data (e.g. Gianoulis et al., 2009, PNAS; Qin et al., 2010, Nature). For example, many distant ocean samples are analysed and the abundance of some pathways significantly correlate with temperature or oxygen concentration of both. In human, we find correlations of gut genes from metagenomes with several diseases.
Future projects and goals
The main system we will study over the next years is the human gut, but we will also take part in many collaborations studying various other systems, such as the Tara Oceans project to explore the biodiversity on Earth. In the gut, we aim to understand biological processes upon drug treatment, but also using large scale perturbation data and several cellular readouts to identify drug targets. We will explore networks between proteins and chemicals such as lipids or carbohydrates and link them to phenotypic data such as drug side effects. We will also look at our 2kg or so bacterial in our intestinal system, study them as communities and explore their impact on colorectal cancer and various other diseases in the context of lifestyle and other parameters. We also want to understand how these communities evolve in us, how frequently they are transmitted parentally or horizontally, and how they communicate with each other and with our cells.
The group is partially associated with the Max Delbrück Center for Molecular Medicine in Berlin and with the Molecular Medicine Partnership Unit (MMPU) at Heidelberg University.
ERC Investigator
