Research - Institute of Biochemistry - Synthetic and Systems Biology Unit - Laboratory of Computational Systems Biology  - Papp Lab

Balázs PAPP
senior research associate

Gábor BOROSS junior research associate
Károly KOVÁCS research associate
Dorottya KALAPIS research associate
Charles ROCABERT research associate
Roland TENGÖLICS research associate
Balázs SZAPPANOS junior research associate
Ádám GYÖRKEI junior research associate
Gergely FEKETE scientific administrator
Orsolya LISKA scientific administrator
Zsuzsa SARKADI scientific administrator
Stefánia ERDEI laboratory assistant
Szabolcs Cselgő KOVÁCS laboratory assistant
Gábor GRÉZAL scientific administrator
Eszter ARI research associate
Joao Benhur MOKOCHINSKI research associate


Thanks to recent advances in molecular biology techniques, a vast amount of data has been accumulated on the genetic material of organisms and on the ‘molecular circuits’ (i.e. molecular constituents and their interactions) of their cells. Our rapidly increasing knowledge allows us to address some of the most fundamental questions of biology. What are the general principles governing the structure and function of molecular circuits? Is it possible to predict the cell’s behavior, such as the nutrient utilization of bacteria, based on knowledge of the wiring diagram of its molecular circuits? How do mutations and environmental changes (such as the administration of drug compounds) influence the operation of molecular circuits? Can we predict whether a mutation is harmful for the organism? How did molecular circuits arise during evolution and why do we observe the naturally occurring circuits instead of chemically possible alternative ones? Employing computational biology techniques and large-scale molecular datasets, our lab investigates these questions in the best characterized unicellular organisms, Escherichia coli and baker’s yeast. Among others, our work offers insights into the birth of metabolic pathways and into the rewiring of molecular circuits during the evolution of antibiotic resistance.

Evolution of metabolic networks

Understanding how the properties of metabolic systems evolve and how new pathways emerge are among the key issues in evolutionary and systems biology. We employ genome-scale computational modelling of metabolism and experimental approaches to study the following questions:

(i) How do complex metabolic innovations requiring multiple mutations arise through purely Darwinian evolution? As multiple specific mutations are highly unlikely to simultaneously occur, it remains challenging to explain the numerous adaptive phenotypes that rely on multiple mutations. We propose that under varying environments metabolic innovations accessible through the addition of a single biochemical reaction serve as stepping stones towards the later establishment of complex metabolic pathways in another environment.

(ii) Can we predict the genetic basis (i.e. the underlying genes) of adaptive evolution? Because metabolic evolution often capitalizes on the weak side activities of preexisting enzymes (i.e. underground reactions), we hypothesize that a detailed knowledge of an organism’s ‘underground metabolism’ may enable the computational prediction of which genes drive adaptation toward new metabolic capabilities. To test this notion, we computationally reconstruct the network of known underground enzyme activites in E. coli and analyse its evolutionary potential using both computational tools and genome-wide enzyme overexpression screens.

Systems-level analysis of antibiotic cross-resistance and collateral sensitivity

Evolution of antimicrobial drug resistance is a problem that continues to challenge the healthcare industry. It is often observed that acquired resistance to an antibiotics is accompanied by decreased or increased sensitivity to other agents (cross-resistance and collateral sensitivity, respectively). However, the general principles underlying these evolutionary interactions remain poorly understood. To what extent these interactions are predictable based on chemical and functional properties of individual antibiotics? What are the systems-level changes that accompany resistance evolution and how do these changes correlate with altered sensitivities to other agents? We combine experimental evolutionary techniques with functional genomic and computational tools to decipher the networks of cross-resistance and collateral sensitivity in Escherichia coli. The project is run in collaboration with the Pál lab (BRC, Szeged).

Network of cross resistance (black) and collateral sensitivity (red) interactions between antibiotics (from Lázár et al. 2013)

Selected publications

Pál, C. Papp B. and Hurst, L.D. (2001): Highly expressed genes in yeast evolve slowly. Genetics 158: 927-931.

Papp, B., Pál, C. and Hurst, L.D. (2003) Dosage sensitivity and the evolution of gene families in yeast. Nature 424: 194-7.

Papp, B., Pál, C. and Hurst, L.D. (2004) Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast. Nature 429: 661-4.

Pál, C., Papp B. and Lercher, M.J. (2005) Adaptive evolution of bacterial metabolic networks by horizontal gene transfer. Nature Genetics 37: 1372-5.

*Pál, C., *Papp, B., Lercher, M.J., Csermely, P., Oliver, S.G. and Hurst, L.D. (2006) Chance and necessity in the evolution of minimal metabolic networks. Nature 440: 667-70.

Szappanos, B., Kovács, K., Szamecz, B., Honti, F., Costanzo, M., Baryshnikova, A., Gelius-Dietrich, G., Lercher, M.J., Jelasity, M., Myers, C.L., Andrews, B.J., Boone, C., Oliver, S.G., Pál, C., Papp, B. (2011) An integrated approach to characterize genetic interaction networks in yeast metabolism. Nature Genetics 43: 656.

Papp, B., Notebaart, R.A., Pál, C. (2011) Systems-biology approaches for predicting genomic evolution. Nature Reviews Genetics 12: 591

Lázár, V., Singh, G. P., Spohn, R., Nagy, I., Horváth, B., Hrtyan, M., Busa-Fekete, R., Bogos, B., Méhi, O., Csörgő, B., Pósfai, G., Fekete, G., Szappanos, B., Kégl, B., Papp, B.*, Pál, C.* (2013) Bacterial evolution of antibiotic hypersensitivity. Molecular Systems Biology 9:700

Notebaart, R.A.*, Szappanos, B., Kintses, B., Pál, F., Györkei, A., Bogos, B., Lázár, V., Spohn, R., Csörgő, B., Wagner, A., Ruppin, E., Pál, C.*, Papp, B.* (2014) Network-level architecture and the evolutionary potential of underground metabolism. Proc Natl Acad Sci U S A. 111: 11762-11767.

Szappanos, B., Fritzemeier, J.C., Csörgő, B., Lázár, V., Lu, X., Fekete, G., Bálint, B., Herczeg, R., Nagy, I., Notebaart, R.A., Lercher, M.J., Pál, C.*, Papp, B.* (2016) Adaptive evolution of complex innovations through stepwise metabolic niche expansion. Nat Commun. 7:11607