Band 17, Heft 4 - Special Issue: Bioinformatics of Genome Regulation and Structure - 2020 papers collection; Guest Editors: Yuriy L. Orlov, Oxana B. Dobrovolskaya, Ming Chen, Ralf Hofestädt

The article reports the main provisions of the concept and solutions for creating the digital platform in the field of bioinformatics and the formation of the thematically oriented and industrial digital ecosystems on its basis. The composition and structure of the digital platform are discussed: information repositories, data and knowledge bases, thematically oriented software repository, task-oriented services for various target groups of users. Within the framework of the platform, it is also planned to organize a system of high-quality access to specialized data centres and high-performance computing infrastructure. Particular attention is devoted to one of the components of such platform - the project office for bioresource collections management. The project office has registered such types of collections as animal collections: wild and laboratory animals, live breeding, museum zoological animal collections, farm animals; plant collections: herbarium funds of plants biological diversity, living collections of natural flora, agricultural plants. Collection types such as collections of human biomaterials, cell culture collections, microorganism collections are important for medical research.

Prostate cancer (PC) is one of the most common and socially significant oncological diseases among men. Bioinformatic analysis of omics data allows identifying molecular genetic changes associated with the disease development, as well as markers of prognosis and response to therapy. Alterations in DNA methylation and histone modification profiles widely occur in malignant tumors. In this study, we analyzed changes in DNA methylation in three groups of PC patients based on data from The Cancer Genome Atlas project (TCGA, https://portal.gdc.cancer.gov): (1) high- and intermediate-risk of the tumor progression, (2) favorable and unfavorable prognoses within the high-risk group, and (3) TMPRSS2-ERG-positive (tumors with TMPRSS2-ERG fusion transcript) and TMPRSS2-ERG-free cases within the high-risk group. We found eight CpG sites (cg07548607, cg13533340, cg16643088, cg18467168, cg23324953, cg23753247, cg25773620, and cg27148952) hypermethylated in the high-risk group compared with the intermediate-risk group of PC. Seven differentially methylated CpG sites (cg00063748, cg06834698, cg18607127, cg25273707, cg01704198, cg02067712, and cg02157224) were associated with unfavorable prognosis within the high-risk group. Six CpG sites (cg01138171, cg14060519, cg19570244, cg24492886, cg25605277, and cg26228280) were hypomethylated in TMPRSS2-ERG-positive PC compared to TMPRSS2-ERG-negative tumors within the high-risk group. The CpG sites were localized, predominantly, in regulatory genome regions belonging to promoters of the following genes: ARHGEF4, C6orf141, C8orf86, CLASP2, CSRNP1, GDA, GSX1, IQSEC1, MYOF, OR10A3, PLCD1, PLEC1, PRDM16, PTAFR, RP11-844P9.2, SCYL3, VPS13D, WT1 , and ZSWIM2 . For these genes, analysis of differential expression and its correlation with CpG site methylation ( β -value level) was also performed. In addition, STK33 and PLCD1 had similar changes in colorectal cancer. As for the CSRNP1, the ARHGEF4, and the WT1 genes, misregulated expression levels were mentioned in lung, liver, pancreatic and androgen-independent prostate cancer. The potential impact of changed methylation on the mRNA level was determined for the CSRNP1, STK33, PLCD1, ARHGEF4, WT1, SCYL3, and VPS13D genes. The above CpG sites could be considered as potential prognostic markers of the high-risk group of PC.

Currently, a trend of decline in male fertility is observed all over the world. The study of this trend has not only of scientific, but also of socio-economic importance. Many countries conduct studies of male reproductive potential and search environmental and genetic causes of the mentioned phenomenon. Previously published studies have not included data on the Russian male population. This work presents novel database “Reproductive Potential of the Male population of Russia” (RPM), which is almost the only source of such information about Russia. RPM was created using relational database management system MariaDB and is available at www.sysbio.ru/rpm. The database includes reproductive information of 1390 male volunteers from five large cities of Russia: Arkhangelsk, Novosibirsk, Kemerovo, Ulan-Ude and Yakutsk. The important feature of the developed database is the unique data of a multifactorial measurement of male fertility: spermatogenic, hormonal, metabolic and anthropological indices. The scientists can use published information in their studies of male reproductive potential as data of some Russian regions and compare it with data from other countries. Also the published data can be used to identify markers of infertility and subfertility, as well as to study ethnic and regional trends in fertility variability and demographic risks in Russia.

The study aims to investigate the role of viscoelastic interactions between cells and extracellular matrix (ECM) in avascular tumor growth. Computer simulations of glioma multicellular tumor spheroid (MTS) growth are being carried out for various conditions. The calculations are based on a continuous model, which simulates oxygen transport into MTS; transitions between three cell phenotypes, cell transport, conditioned by hydrostatic forces in cell–ECM composite system, cell motility and cell adhesion. Visco-elastic cell aggregation and elastic ECM scaffold represent two compressible constituents of the composite. Cell–ECM interactions form a Transition Layer on the spheroid surface, where mechanical characteristics of tumor undergo rapid transition. This layer facilitates tumor progression to a great extent. The study demonstrates strong effects of ECM stiffness, mechanical deformations of the matrix and cell–cell adhesion on tumor progression. The simulations show in particular that at certain, rather high degrees of matrix stiffness a formation of distant multicellular clusters takes place, while at further increase of ECM stiffness subtumors do not form. The model also illustrates to what extent mere mechanical properties of cell–ECM system may contribute into variations of glioma invasion scenarios.

Amino acid repeats are found to play important roles in both structures and functions of the proteins. These are commonly found in all kingdoms of life, especially in eukaryotes and a larger fraction of human proteins composed of repeats. Further, the abnormal expansions of shorter repeats cause various diseases to humans. Therefore, the analysis of repeats of the entire human proteome along with functional, mutational and disease information would help to better understand their roles in proteins. To fulfill this need, we developed a web database HPREP (http://bioinfo.bdu.ac.in/hprep) for human proteome repeats using Perl and HTML programming. We identified different categories of well-characterized repeats and domain repeats that are present in the human proteome of UniProtKB/Swiss-Prot by using in-house Perl programming and novel repeats by using the repeat detection T-REKS tool as well as XSTREAM web server. Further, these proteins are annotated with functional, mutational and disease information and grouped according to specific repeat types. The developed database enables the users to search by specific repeat type in order to understand their involvement in proteins. Thus, the HPREP database is expected to be a useful resource to gain better insight regarding the different repeats in human proteome and their biological roles.

We apply a skeletal animation technique developed for general computer graphics animation to display the dynamic shape of protein molecules. Polygon-based models for macromolecules such as atomic representations, surface models, and protein ribbon models are deformed by the motion of skeletal bones that provide coarse-grained descriptions of detailed computer graphics models. Using the animation software Blender, we developed methods to generate the skeletal bones for molecules. Our example of the superposition of normal modes demonstrates the thermal fluctuating motion obtained from normal mode analysis. The method is also applied to display the motions of protein molecules using trajectory coordinates of a molecular dynamics simulation. We found that a standard motion capture file was practical and useful for describing the motion of the molecule using available computer graphics tools.