HIGH-PERFORMANCE SIMULATIONS OF POPULATION-GENETIC PROCESSES IN BACTERIAL COMMUNITIES USING THE HAPLOID EVOLUTIONARY CONSTRUCTOR SOFTWARE

Three high-performance versions of the Haploid Evolutionary Constructor program are presented (http://evol-constructor.bionet.nsc.ru). The software was designed for simulating the functioning and evolution of microbial communities. These high-performance versions are to be run on systems with shared and distributed memory, using CPU and/or GPU. Almost linear acceleration has been achieved on clusters and multi-core CPU. On GPU systems, the simulation time was reduced to several minutes (dozens of hours on CPU)

Phylostratigraphic analysis of gene networks of human diseases

Phylostratigraphic analysis is an approach to the study of gene evolution that makes it possible to determine the time of the origin of genes by analyzing their orthologous groups. The age of a gene belonging to an orthologous group is def ined as the age of the most recent ancestor of all species represented in that group. Such an analysis can reveal important stages in the evolution of both the organism as a whole and groups of functionally related genes, in particular gene networks. In addition to investigating the time of origin of a gene, the level of its genetic variability and what type of selection the gene is subject to in relation to the most closely related organisms is studied. Using the Orthoscape application, gene networks from the KEGG Pathway, Human Diseases database describing various human diseases were analyzed. It was shown that the majority of genes described in gene networks are under stabilizing selection and a high reliable correlation was found between the time of gene origin and the level of genetic variability: the younger the gene, the higher the level of its variability is. It was also shown that among the gene networks analyzed, the highest proportion of evolutionarily young genes was found in the networks associated with diseases of the immune system (65 %), and the highest proportion of evolutionarily ancient genes was found in the networks responsible for the formation of human dependence on substances that cause addiction to chemical compounds (88 %); gene networks responsible for the development of infectious diseases caused by parasites are signif icantly enriched for evolutionarily young genes, and gene networks responsible for the development of specif ic types of cancer are signif icantly enriched for evolutionarily ancient genes

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

A review of simulation and modeling approaches in microbiology

Bacterial communities are tightly interconnected systems consisting of numerous species making it challenging to analyze their structure and relations. There are several experimental techniques providing heterogeneous data concerning various aspects of this object. A recent avalanche of metagenomic data challenges not only biostatisticians but also biomodelers, since these data are essential to improve the modeling quality while simulation methods are useful to understand the evolution of microbial communities and their function in the ecosystem. An outlook on the existing modeling and simulation approaches based on different types of experimental data in the field of microbial ecology and environmental microbiology is presented. A number of approaches focusing on a description of such microbial community aspects as its trophic structure, metabolic and population dynamics, genetic diversity as well as spatial heterogeneity and expansion dynamics is considered. We also propose a classification of the existing software designed for simulation of microbial communities. It is shown that although the trend for using multiscale/hybrid models prevails, the integration between models concerning different levels of biological organization of communities still remains a problem to be solved. The multiaspect nature of integration approaches used to model microbial communities is based on the need to take into account heterogeneous data obtained from various sources by applying high-throughput genome investigation methods

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 influences systems of neuroendocrine control of ontogenesis in a stressful environment. Among the experimental data generalized by Belyaev’s discovery, there are also findings about accelerated extinction 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 confirmed, 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 identified 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 significant 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

SPATIALLY DISTRIBUTED MODELING OF PROKARYOTIC COMMUNITY EVOLUTION

This paper describes the development of an approach to the simulation of prokaryotic community activity and evolution and the software package «Haploid evolutionary constructor» (http://evol-constructor.bionet.nsc.ru). The initial model with ideal mixing (0D) is expanded to a spatially distributed model (1D). The 0D and 1D poisoner–prey prokaryotic community models are compared. It is shown that the community stability is influenced by the spatial distribution of substrates and prokaryotic cells

HIGH-THROUGHPUT SIMULATIONS OF PROKARYOTIC COMMUNITY EVOLUTION WITH HAPLOID EVOLUTIONARY CONSTRUCTOR

The results of the development of a high-throughput version of the software package Haploid Evolutionary Constructor (HEC), available at http://evol-constructor.bionet.nsc.ru, are presented. The software is used to simulate the functioning and evolution of prokaryotic communities. A parallel version of the software package was created using the MPI technology. The test was performed on a cluster of the Bioinformatics shared access center. The acceleration obtained was almost linear. The simulation time of complex bacterial communities was reduced from dozens of hours to several minutes

ELOE: A WEB APPLICATION FOR ESTIMATION OF GENE TRANSLATION ELONGATION EFFICIENCY

Expression efficiency is one of major characteristics of genes considered in a number of modern investigations. It is known that gene expression efficiency in an organism is regulated at many stages: transcription, translation, posttranslational protein modification, and others. In this study, a special EloE (Elongation Efficiency) web application is described. It sorts genes in an organism in the order of decreasing theoretical rate of the elongation stage of translation deduced from their nucleotide sequences. The predictions done in this way show a significant correlation with available experimental data on gene expression in various organisms, for instance, S. cerevisiae and H. pylori. In addition, the program identifies preferential codons in a genome and defines the distribution of stability of potential secondary structures in 5′ and 3′ regions of mRNA. EloE can be useful in preliminary estimation of translation elongation efficiency of genes in organisms for which experimental data are not available yet. Some results can be used, for instance, in other programs modeling artificial genetic constructs in gene engineering experiments