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Balázs Papp

Publications and source records attributed to Balázs Papp.

13 recordsLinked to original sources
PubMed2006

Phenotypic activation to discover biological pathways and kinase substrates.

Observing the effects of gene perturbation on cells or organisms has long been a standard strategy in biological research. We developed a genome-wide gene overexpression library as a new tool for large-scale functional analysis in budding yeast. Previous large-scale genetic studies have focused on applications of the deletion mutant collection, which has arguably revolutionized the functional characterization of yeast genes. While extremely powerful, deletion mutant experiments are generally limited to the characterization of loss-of-function phenotypes. We have explored the potential for using the Synthetic Genetic Array (SGA) method, a platform for high-throughput genetic analysis, with a genome-wide "overexpression array", in which each strain on the array overexpresses a unique yeast gene. The overexpression array enables gain-of-function phenotypes to be examined on a large scale, providing a unique insight into gene function and a novel source of reagents for the global mapping of genetic networks and functional relationships amongst genes and pathways. Understanding the molecular bases of overexpression phenotypes should also shed new light on the nature of genetic dominance.

Animals↗
PubMed2006

Chance and necessity in the evolution of minimal metabolic networks.

It is possible to infer aspects of an organism's lifestyle from its gene content. Can the reverse also be done? Here we consider this issue by modelling evolution of the reduced genomes of endosymbiotic bacteria. The diversity of gene content in these bacteria may reflect both variation in selective forces and contingency-dependent loss of alternative pathways. Using an in silico representation of the metabolic network of Escherichia coli, we examine the role of contingency by repeatedly simulating the successive loss of genes while controlling for the environment. The minimal networks that result are variable in both gene content and number. Partially different metabolisms can thus evolve owing to contingency alone. The simulation outcomes do preserve a core metabolism, however, which is over-represented in strict intracellular bacteria. Moreover, differences between minimal networks based on lifestyle are predictable: by simulating their respective environmental conditions, we can model evolution of the gene content in Buchnera aphidicola and Wigglesworthia glossinidia with over 80% accuracy. We conclude that, at least for the particular cases considered here, gene content of an organism can be predicted with knowledge of its distant ancestors and its current lifestyle.

Biological Evolution↗
PubMed2006

Mapping pathways and phenotypes by systematic gene overexpression.

Many disease states result from gene overexpression, often in a specific genetic context. To explore gene overexpression phenotypes systematically, we assembled an array of 5280 yeast strains, each containing an inducible copy of an S. cerevisiae gene, covering >80% of the genome. Approximately 15% of the overexpressed genes (769) reduced growth rate. This gene set was enriched for cell cycle-regulated genes, signaling molecules, and transcription factors. Overexpression of most toxic genes resulted in phenotypes different from known deletion mutant phenotypes, suggesting that overexpression phenotypes usually reflect a specific regulatory imbalance rather than disruption of protein complex stoichiometry. Global overexpression effects were also assayed in the context of a cyclin-dependent kinase mutant (pho85Delta). The resultant gene set was enriched for Pho85p targets and identified the yeast calcineurin-responsive transcription factor Crz1p as a substrate. Large-scale application of this approach should provide a strategy for identifying target molecules regulated by specific signaling pathways.

Gene Expression Profiling↗
PubMed2006

An integrated view of protein evolution.

Why do proteins evolve at different rates? Advances in systems biology and genomics have facilitated a move from studying individual proteins to characterizing global cellular factors. Systematic surveys indicate that protein evolution is not determined exclusively by selection on protein structure and function, but is also affected by the genomic position of the encoding genes, their expression patterns, their position in biological networks and possibly their robustness to mistranslation. Recent work has allowed insights into the relative importance of these factors. We discuss the status of a much-needed coherent view that integrates studies on protein evolution with biochemistry and functional and structural genomics.

Animals↗
PubMed2005

Adaptive evolution of bacterial metabolic networks by horizontal gene transfer.

Numerous studies have considered the emergence of metabolic pathways, but the modes of recent evolution of metabolic networks are poorly understood. Here, we integrate comparative genomics with flux balance analysis to examine (i) the contribution of different genetic mechanisms to network growth in bacteria, (ii) the selective forces driving network evolution and (iii) the integration of new nodes into the network. Most changes to the metabolic network of Escherichia coli in the past 100 million years are due to horizontal gene transfer, with little contribution from gene duplicates. Networks grow by acquiring genes involved in the transport and catalysis of external nutrients, driven by adaptations to changing environments. Accordingly, horizontally transferred genes are integrated at the periphery of the network, whereas central parts remain evolutionarily stable. Genes encoding physiologically coupled reactions are often transferred together, frequently in operons. Thus, bacterial metabolic networks evolve by direct uptake of peripheral reactions in response to changed environments.

Adaptation, Physiological↗
PubMed2005

Horizontal gene transfer depends on gene content of the host.

Horizontal gene transfer is a major contributor to the evolution of bacterial genomes. We examine this process through a combination of comparative genomics and in silico analysis of the Escherichia coli metabolic network. We validate our horizontal transfer estimates by confirming the predicted gradual amelioration of GC content over time. We find that the chance of acquiring a gene by horizontal transfer is up to six times higher if an enzyme that catalyses a coupled metabolite flux is already encoded in the host genome.

Base Composition↗
PubMed2005

Genome-wide analysis of the context-dependence of regulatory networks.

Genome-wide analytical tools are now allowing the discovery of the design rules that govern regulatory networks. Two recent studies in yeast have helped reveal the relatively small number of transcription-factor control strategies that cells employ to maximize their regulatory options using only a small number of components.

Binding Sites↗
PubMed2005

Molecular chaperones as regulatory elements of cellular networks.

Molecular chaperones help hundreds of signaling molecules to keep their activation-competent state, and regulate various signaling processes ranging from signaling at the plasma membrane to transcription. Besides these specific regulatory roles, recent studies have revealed that chaperones act as genetic buffers stabilizing the phenotypes of various cells and organisms. This may be related to their low affinity for the proteins they interact with, which means that they represent weak links in protein networks. Chaperones may uncouple protein, signaling, membrane, organelle and transcriptional networks during stress, which gives the cell additional protection. The same networks are preferentially remodeled in various diseases and aging, which may help us to design novel therapeutic and anti-aging strategies.

Animals↗
PubMed2004

Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast.

Under laboratory conditions 80% of yeast genes seem not to be essential for viability. This raises the question of what the mechanistic basis for dispensability is, and whether it is the result of selection for buffering or an incidental side product. Here we analyse these issues using an in silico flux model of the yeast metabolic network. The model correctly predicts the knockout fitness effects in 88% of the genes studied and in vivo fluxes. Dispensable genes might be important, but under conditions not yet examined in the laboratory. Our model indicates that this is the dominant explanation for apparent dispensability, accounting for 37-68% of dispensable genes, whereas 15-28% of them are compensated by a duplicate, and only 4-17% are buffered by metabolic network flux reorganization. For over one-half of those not important under nutrient-rich conditions, we can predict conditions when they will be important. As expected, such condition-specific genes have a more restricted phylogenetic distribution. Gene duplicates catalysing the same reaction are not more common for indispensable reactions, suggesting that the reason for their retention is not to provide compensation. Instead their presence is better explained by selection for high enzymatic flux.

Biomass↗
PubMed2003

Dosage sensitivity and the evolution of gene families in yeast.

According to what we term the balance hypothesis, an imbalance in the concentration of the subcomponents of a protein-protein complex can be deleterious. If so, there are two consequences: first, both underexpression and overexpression of protein complex subunits should lower fitness, and second, the accuracy of transcriptional co-regulation of subunits should reflect the deleterious consequences of imbalance. Here we show that all these predictions are upheld in yeast (Saccharomyces cerevisiae). This supports the hypothesis that dominance is a by-product of physiology and metabolism rather than the result of selection to mask the deleterious effects of mutations. Beyond this, single-gene duplication of protein subunits is expected to be harmful, as this, too, leads to imbalance. As then expected, we find that members of large gene families are rarely involved in complexes. The balance hypothesis therefore provides a single theoretical framework for understanding components both of dominance and of gene family size.

Evolution, Molecular↗
PubMed2003

Evolution of cis-regulatory elements in duplicated genes of yeast.

An increasing number of studies report that functional divergence in duplicated genes is accompanied by gene expression changes, although the evolutionary mechanism behind this process remains unclear. Our genomic analysis on the yeast Saccharomyces cerevisiae shows that the number of shared regulatory motifs in the duplicates decreases with evolutionary time, whereas the total number of regulatory motifs remains unchanged. Moreover, genes with numerous paralogs in the yeast genome do not have especially low number of regulatory motifs. These findings indicate that degenerative complementation is not the sole mechanism behind expression divergence in yeast. Moreover, we found some evidence for the action of positive selection on cis-regulatory motifs after gene duplication. These results suggest that the evolution of functional novelty has a substantial role in yeast duplicate gene evolution.

Evolution, Molecular↗