Multi-component gene network design as a survival strategy in diverse environments

Background

Gene-environment interactions are often mediated though gene networks in which gene expression products interact with other network components to dictate network activity levels, which in turn determines the fitness of the host cell in specific environments. Even though a gene network is the right context for studying gene-environment interactions, we have little understanding on how systematic genetic perturbations affects fitness in the context of a gene network.

Results

Here we examine the effect of combinatorial gene dosage alterations on gene network activity and cellular fitness. Using the galactose utilization pathway as a model network in diploid yeast, we reduce the copy number of four regulatory genes (GAL2, GAL3, GAL4, GAL80) from two to one, and measure the activity of the perturbed networks. We integrate these results with competitive fitness measurements made in six different rationally-designed environments containing different galactose concentrations representing the natural induction spectrum of the galactose network. In the lowest galactose environment, we find a nonlinear relationship between gene expression and fitness while high galactose environments lead to a linear relationship between the two with a saturation regime reached at a sufficiently high galactose concentration. We further uncover environment-specific relevance of the different network components for dictating the relationship between the network activity and organismal fitness, indicating that none of the network components are redundant.

Conclusions

These results provide experimental support to the hypothesis that dynamic changes in the environment throughout natural evolution is key to structuring natural gene networks in a multi-component fashion, which robustly provides protection against population extinction in different environments.

     

Protein evolution on a human signaling network

Background  

The architectural structure of cellular networks provides a framework for innovations as well as constraints for protein evolution. This issue has previously been studied extensively by analyzing protein interaction networks. However, it is unclear how signaling networks influence and constrain protein evolution and conversely, how protein evolution modifies and shapes the functional consequences of signaling networks. In this study, we constructed a human signaling network containing more than 1,600 nodes and 5,000 links through manual curation of signaling pathways, and analyzed the d _N/d _S values of human-mouse orthologues on the network.     

Statistical tests for natural selection on regulatory regions based on the strength of transcription factor binding sites

Background  

Although cis -regulatory changes play an important role in evolution, it remains difficult to establish the contribution of natural selection to regulatory differences between species. For protein coding regions, powerful tests of natural selection have been developed based on comparisons of synonymous and non-synonymous substitutions, and analogous tests for regulatory regions would be of great utility.     

Dissecting the fission yeast regulatory network reveals phase-specific control elements of its cell cycle

Background  

Fission yeast Schizosaccharomyces pombe and budding yeast Saccharomyces cerevisiae are among the original model organisms in the study of the cell-division cycle. Unlike budding yeast, no large-scale regulatory network has been constructed for fission yeast. It has only been partially characterized. As a result, important regulatory cascades in budding yeast have no known or complete counterpart in fission yeast.     

The capacity for multistability in small gene regulatory networks

Background  

Recent years have seen a dramatic increase in the use of mathematical modeling to gain insight into gene regulatory network behavior across many different organisms. In particular, there has been considerable interest in using mathematical tools to understand how multistable regulatory networks may contribute to developmental processes such as cell fate determination. Indeed, such a network may subserve the formation of unicellular leaf hairs (trichomes) in the model plant Arabidopsis thaliana.     

Does the core circadian clock in the moss <Emphasis Type="Italic">Physcomitrella patens</Emphasis> (Bryophyta) comprise a single loop?

Background  

The endogenous circadian clock allows the organism to synchronize processes both to daily and seasonal changes. In plants, many metabolic processes such as photosynthesis, as well as photoperiodic responses, are under the control of a circadian clock. Comparative studies with the moss Physcomitrella patens provide the opportunity to study many aspects of land plant evolution. Here we present a comparative overview of clock-associated components and the circadian network in the moss P. patens.     

Network analysis of metabolic enzyme evolution in <Emphasis Type="Italic">Escherichia coli</Emphasis>

Background  

The two most common models for the evolution of metabolism are the patchwork evolution model, where enzymes are thought to diverge from broad to narrow substrate specificity, and the retrograde evolution model, according to which enzymes evolve in response to substrate depletion. Analysis of the distribution of homologous enzyme pairs in the metabolic network can shed light on the respective importance of the two models. We here investigate the evolution of the metabolism in E. coli viewed as a single network using EcoCyc.     

Single TNF<Emphasis Type="Italic">α</Emphasis> trimers mediating NF-<Emphasis Type="Italic">κ</Emphasis> B activation: stochastic robustness of NF-<Emphasis Type="Italic">κ</Emphasis> B signaling

Background  

The NF-κB regulatory network controls innate immune response by transducing variety of pathogen-derived and cytokine stimuli into well defined single-cell gene regulatory events.     

Exploration of biological network centralities with CentiBiN

Background  

The elucidation of whole-cell regulatory, metabolic, interaction and other biological networks generates the need for a meaningful ranking of network elements. Centrality analysis ranks network elements according to their importance within the network structure and different centrality measures focus on different importance concepts. Central elements of biological networks have been found to be, for example, essential for viability.     

Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium

Background  

Synechocystis sp. PCC6803 is a cyanobacterium considered as a candidate photo-biological production platform - an attractive cell factory capable of using CO₂ and light as carbon and energy source, respectively. In order to enable efficient use of metabolic potential of Synechocystis sp. PCC6803, it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the Synechocystis metabolic network.     

Phylogenomic analyses of KCNA gene clusters in vertebrates: why do gene clusters stay intact?

Background  

Gene clusters are of interest for the understanding of genome evolution since they provide insight in large-scale duplications events as well as patterns of individual gene losses. Vertebrates tend to have multiple copies of gene clusters that typically are only single clusters or are not present at all in genomes of invertebrates. We investigated the genomic architecture and conserved non-coding sequences of vertebrate KCNA gene clusters. KCNA genes encode shaker-related voltage-gated potassium channels and are arranged in two three-gene clusters in tetrapods. Teleost fish are found to possess four clusters. The two tetrapod KNCA clusters are of approximately the same age as the Hox gene clusters that arose through duplications early in vertebrate evolution. For some genes, their conserved retention and arrangement in clusters are thought to be related to regulatory elements in the intergenic regions, which might prevent rearrangements and gene loss. Interestingly, this hypothesis does not appear to apply to the KCNA clusters, as too few conserved putative regulatory elements are retained.     

A method for the generation of standardized qualitative dynamical systems of regulatory networks

Background  

Modeling of molecular networks is necessary to understand their dynamical properties. While a wealth of information on molecular connectivity is available, there are still relatively few data regarding the precise stoichiometry and kinetics of the biochemical reactions underlying most molecular networks. This imbalance has limited the development of dynamical models of biological networks to a small number of well-characterized systems. To overcome this problem, we wanted to develop a methodology that would systematically create dynamical models of regulatory networks where the flow of information is known but the biochemical reactions are not. There are already diverse methodologies for modeling regulatory networks, but we aimed to create a method that could be completely standardized, i.e. independent of the network under study, so as to use it systematically.