We are interested in the molecular organization and evolution of cellular systems, in particular metabolism. Our major aim is to understand design principles that arise from the optimization of complex systems through natural selection. In our work, we frequently combine functional metabolic modelling with evolutionary simulations and compare evolutionary predictions with measured data. This allows us a mechanistic understanding of how complex systems have evolved, and how they are likely to evolve in the future.
- Hu XP, Dourado H, Schubert P, Lercher MJ (2020) The protein translation machinery is expressed for maximal efficiency in Escherichia coli. Nat Commun 11(1):5260. doi: 10.1038/s41467-020-18948-x.
- Dourado H, Lercher MJ (2020) An analytical theory of balanced cellular growth. Nat Commun 11(1):1226. doi: 10.1038/s41467-020-14751-w.
- Alvarez CE, Bovdilova A, Hoppner A, Wolff CC, Saigo M, Trajtenberg F, Zhang T, Buschiazzo A, Nagel-Steger L, Drincovich MF, Lercher MJ, Maurino VG (2019) Molecular adaptations of NADP-malic enzyme for its function in C4 photosynthesis in grasses. Nat Plants 5(7):755-765. doi: 10.1038/s41477-019-0451-7.
- Pang TY, Lercher MJ (2019) Each of 3,323 metabolic innovations in the evolution of E. coli arose through the horizontal transfer of a single DNA segment. Proc Natl Acad Sci U S A 116(1):187-192. doi: 10.1073/pnas.1718997115.
- Heckmann D, Schulze S, Denton A, Gowik U, Westhoff P, Weber AP, Lercher MJ (2013) Predicting C4 photosynthesis evolution: modular, individually adaptive steps on a Mount Fuji fitness landscape. Cell 153(7):1579-1588. doi: 10.1016/j.cell.2013.04.058.
Prof. Dr. Martin Lercher
Computational Cell Biology
Heinrich Heine University Düsseldorf