[Molecular Mechanisms to Optimize Gene Translation Elongation Differ Significantly in Bacteria with and without Nonribosomal Peptides].

Nonribosomal peptides play an important role in the vital activity of bacteria and have an extremely broad field of biological activity. In particular, they act as antibiotics, toxins, surfactants, siderophores, and also perform a number of other specific functions. Biosynthesis of these molecules does not occur on ribosomes but by special enzymes that form gene clusters in bacterial genomes. We hypothesized that the presence of nonribosomal peptide synthesis pathways is a specific feature of bacterial metabolism, which may affect other vital processes of the cell, including translational ones. This work was the first to show the relationship between the translation regulation mechanism of protein-coding genes in bacteria, which is largely determined by the efficiency of translation elongation, and the presence of gene clusters in the genomes for the biosynthesis of nonribosomal peptides. Bioinformatic analysis of the translation elongation efficiency of protein-coding genes was performed in 11679 bacterial genomes, some of which contained gene clusters of nonribosomal peptide biosynthesis and some of which did not. The analysis showed that bacteria whose genomes contained clusters of nonribosomal peptide biosynthetic genes and those without such gene clusters differ significantly in the molecular mechanisms that ensure translation efficiency. Thus, among microorganisms whose genomes contain gene clusters of nonribosomal peptide synthetases, a significantly smaller part of them is characterized by optimized regulation of the number of local inverted repeats, while most of them have genomes optimized by the averaged energy of inverted repeats studs in mRNA and additionally by codon composition. Our results suggest that the presence of nonribosomal peptide biosynthetic pathways in bacteria may influence the structure of the overall bacterial metabolism, which is also expressed in the specific mechanisms of ribosomal protein biosynthesis.

[Prediction of Bacterial and Archaeal Allergenicity with AllPred Program].

Nowadays, allergic disorders have become one of the most important social problems in the world. This can be related to the advent of new allergenic agents in the environment, as well as an increasing density of human contact with known allergens, including various proteins. Thus, the development of computer programs designed for the prediction of allergenic properties of proteins becomes one of the urgent tasks of mo dern bioinformatics. Previously we developed a web accessible Allpred Program (http://www-bionet.sscc.ru/ psd/cgi-bin/programs/Allpred/allpred.cgi) that allows users to assess the allergenicity of proteins by taking into account the characteristics of their spatial structure. In this paper, using AllPred, we predicted the allergenicity of proteins from 462 archaea and bacteria species for which a complete genome was available. The segregation of considered proteins on archaea and bacteria has shown that allergens are predicted more often among archaea than among bacteria. The division of these proteins into groups according to their intracellular localization has revealed that the majority of allergenic proteins were among the secreted proteins. The application of methods for predicting the level of gene expression of microorganisms based on DNA sequence analysis showed a statistically significant relationship between the expression level of the proteins and their allergenicity. This analysis has revealed that potentially allergenic proteins were more common among highly expressed proteins. Sorting microorganisms into the pathogenic and nonpathogenic groups has shown that pathogens can potentially be more allergenic because of a statistically significant greater number of allergens predicted among their proteins.

A bioinformatic search for correspondence between differentially expressed genes of domestic versus wild animals and orthologous human genes altering reproductive potential.

One of the greatest achievements of genetics in the 20th century is D.K. Belyaev's discovery of destabilizing selection during the domestication of animals and that this selection affects only gene expression regulation (not gene structure) and inf luences systems of neuroendocrine control of ontogenesis in a stressful environment. Among the experimental data generalized by Belyaev's discovery, there are also f indings about accelerated extinc tion of testes' hormonal function and disrupted seasonality of reproduction of domesticated foxes in comparison with their wild congeners. To date, Belyaev's discovery has already been repeatedly conf irmed, for example, by independent observations during deer domestication, during the use of rats as laboratory animals, after the reintroduction of endangered species such as Przewalski's horse, and during the creation of a Siberian reserve population of the Siberian grouse when it had reached an endangered status in natural habitats. A genome-wide comparison among humans, several domestic animals, and some of their wild congeners has given rise to the concept of self-domestication syndrome, which includes autism spectrum disorders. In our previous study, we created a bioinformatic model of human self-domestication syndrome using differentially expressed genes (DEGs; of domestic animals versus their wild congeners) orthologous to the human genes (mainly, nervous-system genes) whose changes in expression affect reproductive potential, i. e., growth of the number of humans in the absence of restrictions caused by limiting factors. Here, we applied this model to 68 human genes whose changes in expression alter the reproductive health of women and men and to 3080 DEGs of domestic versus wild animals. As a result, in domestic animals, we identif ied 16 and 4 DEGs, the expression changes of which are codirected with changes in the expression of the human orthologous genes decreasing and increasing human reproductive potential, respectively. The wild animals had 9 and 11 such DEGs, respectively. This difference between domestic and wild animals was signif icant according to Pearson's χ2 test (p < 0.05) and Fisher's exact test (p < 0.05). We discuss the results from the standpoint of restoration of endangered animal species whose natural habitats are subject to an anthropogenic impact.

The finding and researching algorithm for potentially oscillating enzymatic systems.

Many processes in living organisms are subject to periodic oscillations at different hierarchical levels of their organization: from molecular-genetic to population and ecological. Oscillatory processes are responsible for cell cycles in both prokaryotes and eukaryotes, for circadian rhythms, for synchronous coupling of respiration with cardiac contractions, etc. Fluctuations in the numbers of organisms in natural populations can be caused by the populations' own properties, their age structure, and ecological relationships with other species. Along with experimental approaches, mathematical and computer modeling is widely used to study oscillating biological systems. This paper presents classical mathematical models that describe oscillatory behavior in biological systems. Methods for the search for oscillatory molecular-genetic systems are presented by the example of their special case - oscillatory enzymatic systems. Factors influencing the cyclic dynamics in living systems, typical not only of the molecular-genetic level, but of higher levels of organization as well, are considered. Application of different ways to describe gene networks for modeling oscillatory molecular-genetic systems is considered, where the most important factor for the emergence of cyclic behavior is the presence of feedback. Techniques for finding potentially oscillatory enzymatic systems are presented. Using the method described in the article, we present and analyze, in a step-by-step manner, first the structural models (graphs) of gene networks and then the reconstruction of the mathematical models and computational experiments with them. Structural models are ideally suited for the tasks of an automatic search for potential oscillating contours (linked subgraphs), whose structure can correspond to the mathematical model of the molecular-genetic system that demonstrates oscillatory behavior in dynamics. At the same time, it is the numerical study of mathematical models for the selected contours that makes it possible to confirm the presence of stable limit cycles in them. As an example of application of the technology, a network of 300 metabolic reactions of the bacterium Escherichia coli was analyzed using mathematical and computer modeling tools. In particular, oscillatory behavior was shown for a loop whose reactions are part of the tryptophan biosynthesis pathway.

Translation efficiency in yeasts correlates with nucleosome formation in promoters.

Elongation efficiency index (EEI) was suggested earlier to estimate gene expression efficiency by nucleotide context of coding sequence in unicellular organisms. We have analyzed association between EEI and nucleosome formation potential (NFP) in 5' regulatory regions upstream translation initiation site (TIS) from two yeast species. Theoretical estimations of NFP based on DNA sequence were obtained by Recon method. Experimental estimation of nucleosome occupancy was obtained by high-throughput sequencing data of nucleosomal DNA in Saccharomyces cerevisiae . For the sample of all genes correlation coefficient was calculated between two vectors: vector of NFP values for fixed position relative to TIS and vector of EEI values. Profiles of correlation coefficients of NFP and EEI were counted in (-600; +600) regions relative to TIS for gene sequences extracted from GenBank. We found regions of strong negative dependence between NFP and EEI for all genes as well as for 10% highly expressed genes in Schizosaccharomyces pombe (10% of EEI-highest genes). At the same time, we found positive dependence between NFP and EEI for all genes and for low expressed genes in S. cerevisiae (10% of EEI-lowest genes). The association between NFP and EEI could be explained by evolutionary selection of context characteristics of nucleotide sequences for gene expression optimization.