Project A4

Metabolic fitness landscapes for evolutionary predictions

Martin Lercher, U Düsseldorf | web | email

We test the repeatability and predictability of the evolutionary adaptation of bacterial metabolism. This project develops an advanced modeling framework for metabolism and growth in prokaryotes, which explicitly includes metabolite concentrations and reaction kinetics. We then use this model to perform evolutionary simulations. In experiments, we follow the evolution of different E. coli strains in environments to which they are not yet optimally adapted. We measure changes in protein and metabolite concentrations, asking: How similar are the evolutionary trajectories of strains that are under the same selection pressure? Do these trajectories agree with our model predictions?

Predictability in Evolution

Collaborative Research Center 1310


Growth-mediated negative feedback shapes quantitative antibiotic response

Angermayr S.A., Pang T.Y., Chevereau G., Mitosch K., Lercher M.J., Bollenbach T., Mol Syst Biol., 20. September 2022,

On the optimality of the enzyme–substrate relationship in bacteria

Dourado H., Mori M., Hwa T., Lercher M.J. , PLOS Biol. 19(10): e3001416, 26. October 2021,

Deep learning allows genome-scale prediction of Michaelis constants from structural features

Kroll A., Engqvist M.K.M., Heckmann D., Lercher M.J., PLOS Biol. 19(10): e3001402, 19. October 2021,

The protein translation machinery is expressed for maximal efficiency in Escherichia coli

Hu X., Dourado H., Schubert P. & Lercher M. J., Nat Commun 11, 5260, 16. October 2020,

An analytical theory of balanced cellular growth

Dourado H., and Lercher M. J., Nat Commun 11, 1226, 6. March 2020,

Each of 3,323 metabolic innovations in the evolution of E. coli arose through the horizontal transfer of a single DNA segment

Pang T. J., Lercher M. J., PNAS, 18. December 2018,

Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models

Heckmann D., Lloyd C. J., Mih N., Ha Y., Zielinski D. C., Haiman Z. B., Desouki A. A., Lercher M. J., Palsson B. O., Nature Communications 9: 5252, 7. December 2018,

Alleles of a gene differ in pleiotropy, often mediated through currency metabolite production, in E. coli and yeast metabolic simulations

Alzoubi D., Desouki A. A., Lercher M. J., Scientific Reports 8: 17252, 22. November 2018,

Supra-operonic clusters of functionally related genes (SOCs) are a source of horizontal gene co-transfers

Pang T. Y., Lercher M. J., Scientific Reports 7: 40294, 9. January 2017,

Energy efficiency trade-offs drive nucleotide usage in transcribed regions

Chen W.-H., Lu G., Bork P., Hu S., and Lercher M.J., Nature Communications volume 7, 21. April 2016,

Recombinant transfer in the basic genome of Escherichia coli

Dixit P.D., Pang T.Y., Studier F.W., and Maslov S., Proc. Natl. Acad. Sci. USA 112: 9070-9075, 3. June 2015,