Computation, prediction, and experimental tests of fitness for bacteriophage T7 mutants with permuted genomes

We created a simulation based on experimental data from bacteriophage T7 that computes the developmental cycle of the wild-type phage and also of mutants that have an altered genome order. We used the simulation to compute the fitness of more than 10(5) mutants. We tested these computations by constructing and experimentally characterizing T7 mutants in which we repositioned gene 1, coding for T7 RNA polymerase. Computed protein synthesis rates for ectopic gene 1 strains were in moderate agreement with observed rates. Computed phage-doubling rates were close to observations for two of four strains, but significantly overestimated those of the other two. Computations indicate that the genome organization of wild-type T7 is nearly optimal for growth: only 2.8% of random genome permutations were computed to grow faster, the highest 31% faster, than wild type. Specific discrepancies between computations and observations suggest that a better understanding of the translation efficiency of individual mRNAs and the functions of qualitatively "nonessential" genes will be needed to improve the T7 simulation. In silico representations of biological systems can serve to assess and advance our understanding of the underlying biology. Iteration between computation, prediction, and observation should increase the rate at which biological hypotheses are formulated and tested.

Nature, nurture and evolution of intra-species variation in mosquito arbovirus transmission competence

Mosquitoes vary in their competence or ability to transmit arthropod-borne viruses (arboviruses). Many arboviruses cause disease in humans and animals. Identifying the environmental and genetic causes of variation in mosquito competence for arboviruses is one of the great challenges in public health. Progress identifying genetic (nature) and environmental (nurture) factors influencing mosquito competence for arboviruses is reviewed. There is great complexity in the various traits that comprise mosquito competence. The complex interactions between environmental and genetic factors controlling these traits and the factors shaping variation in Nature are largely unknown. The norms of reaction of specific genes influencing competence, their distributions in natural populations and the effects of genetic polymorphism on phenotypic variation need to be determined. Mechanisms influencing competence are not likely due to natural selection because of the direct effects of the arbovirus on mosquito fitness. More likely the traits for mosquito competence for arboviruses are the effects of adaptations for other functions of these competence mechanisms. Determining these other functions is essential to understand the evolution and distributions of competence for arboviruses. This information is needed to assess risk from mosquito-borne disease, predict new mosquito-arbovirus systems, and provide novel strategies to mitigate mosquito-borne arbovirus transmission.

Evolution of human genes encoding cell surface receptors involved in the regulation of appetite: an analysis based on the phylostratigraphic age and divergence indexes

Genes encoding cell surface receptors make up a significant portion of the human genome (more than a thousand genes) and play an important role in gene networks. Cell surface receptors are transmembrane proteins that interact with molecules (ligands) located outside the cell. This interaction activates signal transduction pathways in the cell. A large number of exogenous ligands of various origins, including drugs, are known for cell surface receptors, which accounts for interest in them from biomedical researchers. Appetite (the desire of the animal organism to consume food) is one of the most primitive instincts that contribute to survival. However, when the supply of nutrients is stable, the mechanism of adaptation to adverse factors acquired in the course of evolution turned out to be excessive, and therefore obesity has become one of the most serious public health problems of the twenty-first century. Pathological human conditions characterized by appetite violations include both hyperphagia, which inevitably leads to obesity, and anorexia nervosa induced by psychosocial stimuli, as well as decreased appetite caused by neurodegeneration, inflammation or cancer. Understanding the evolutionary mechanisms of human diseases, especially those related to lifestyle changes that have occurred over the past 100-200 years, is of fundamental and applied importance. It is also very important to identify relationships between the evolutionary characteristics of genes in gene networks and the resistance of these networks to changes caused by mutations. The aim of the current study is to identify the distinctive features of human genes encoding cell surface receptors involved in appetite regulation using the phylostratigraphic age index (PAI) and divergence index (DI). The values of PAI and DI were analyzed for 64 human genes encoding cell surface receptors, the orthologs of which were involved in the regulation of appetite in model animal species. It turned out that the set of genes under consideration contains an increased number of genes with the same phylostratigraphic age (PAI = 5, the stage of vertebrate divergence), and almost all of these genes (28 out of 31) belong to the superfamily of G-protein coupled receptors. Apparently, the synchronized evolution of such a large group of genes (31 genes out of 64) is associated with the development of the brain as a separate organ in the first vertebrates. When studying the distribution of genes from the same set by DI values, a significant enrichment with genes having a low DIs was revealed: eight genes (GPR26, NPY1R, GHSR, ADIPOR1, DRD1, NPY2R, GPR171, NPBWR1) had extremely low DIs (less than 0.05). Such low DI values indicate that most likely these genes are subjected to stabilizing selection. It was also found that the group of genes with low DIs was enriched with genes that had brain-specific patterns of expression. In particular, GPR26, which had the lowest DI, is in the group of brain-specific genes. Because the endogenous ligand for the GPR26 receptor has not yet been identified, this gene seems to be an extremely interesting object for further theoretical and experimental research. We believe that the features of the genes encoding cell surface receptors we have identified using the evolutionary metrics PAI and DI can be a starting point for further evolutionary analysis of the gene network regulating appetite.