Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection.

Hepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSystem. Gene expression regulation was statistically significant. Gene network analysis identified four out of 70 HCC marker genes whose expression regulation by viral proteins may be associated with HCC: DNA-binding protein inhibitor ID - 1 (ID1), flap endonuclease 1 (FEN1), cyclin-dependent kinase inhibitor 2A (CDKN2A), and telomerase reverse transcriptase (TERT). It suggested the following viral protein effects in HCV/human protein heterocomplexes: HCV NS3(p70) protein activates human STAT3 and NOTC1; NS2-3(p23), NS5B(p68), NS1(E2), and core(p21) activate SETD2; NS5A inhibits SMYD3; and NS3 inhibits CCN2. Interestingly, NS3 and E1(gp32) activate c-Jun when it positively regulates CDKN2A and inhibit it when it represses TERT. The discovered regulatory mechanisms might be key areas of focus for creating medications and preventative therapies to decrease the likelihood of HCC development during HCV infection.

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder.

Bacillus strains are ubiquitous in the environment and are widely used in the microbiological industry as valuable enzyme sources, as well as in agriculture to stimulate plant growth. The Bacillus genus comprises several closely related groups of species. The rapid classification of these remains challenging using existing methods. Techniques based on MALDI-TOF MS data analysis hold significant promise for fast and precise microbial strains classification at both the genus and species levels. In previous work, we proposed a geometric approach to Bacillus strain classification based on mass spectra analysis via the centroid method (CM). One limitation of such methods is the noise in MS spectra. In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI-TOF MS data.

Integrating omics databases for enhanced crop breeding.

Crop plant breeding involves selecting and developing new plant varieties with desirable traits such as increased yield, improved disease resistance, and enhanced nutritional value. With the development of high-throughput technologies, such as genomics, transcriptomics, and metabolomics, crop breeding has entered a new era. However, to effectively use these technologies, integration of multi-omics data from different databases is required. Integration of omics data provides a comprehensive understanding of the biological processes underlying plant traits and their interactions. This review highlights the importance of integrating omics databases in crop plant breeding, discusses available omics data and databases, describes integration challenges, and highlights recent developments and potential benefits. Taken together, the integration of omics databases is a critical step towards enhancing crop plant breeding and improving global food security.

Apoptosis Genes as a Key to Identification of Inverse Comorbidity of Huntington's Disease and Cancer.

Cancer and neurodegenerative disorders present overwhelming challenges for healthcare worldwide. Epidemiological studies showed a decrease in cancer rates in patients with neurodegenerative disorders, including the Huntington disease (HD). Apoptosis is one of the most important processes for both cancer and neurodegeneration. We suggest that genes closely connected with apoptosis and associated with HD may affect carcinogenesis. We applied reconstruction and analysis of gene networks associated with HD and apoptosis and identified potentially important genes for inverse comorbidity of cancer and HD. The top 10 high-priority candidate genes included APOE, PSEN1, INS, IL6, SQSTM1, SP1, HTT, LEP, HSPA4, and BDNF. Functional analysis of these genes was carried out using gene ontology and KEGG pathways. By exploring genome-wide association study results, we identified genes associated with neurodegenerative and oncological disorders, as well as their endophenotypes and risk factors. We used publicly available datasets of HD and breast and prostate cancers to analyze the expression of the identified genes. Functional modules of these genes were characterized according to disease-specific tissues. This integrative approach revealed that these genes predominantly exert similar functions in different tissues. Apoptosis along with lipid metabolism dysregulation and cell homeostasis maintenance in the response to environmental stimulus and drugs are likely key processes in inverse comorbidity of cancer in patients with HD. Overall, the identified genes represent the promising targets for studying molecular relations of cancer and HD.

Candidate SNP Markers Significantly Altering the Affinity of TATA-Binding Protein for the Promoters of Human Hub Genes for Atherogenesis, Atherosclerosis and Atheroprotection.

Atherosclerosis is a systemic disease in which focal lesions in arteries promote the build-up of lipoproteins and cholesterol they are transporting. The development of atheroma (atherogenesis) narrows blood vessels, reduces the blood supply and leads to cardiovascular diseases. According to the World Health Organization (WHO), cardiovascular diseases are the leading cause of death, which has been especially boosted since the COVID-19 pandemic. There is a variety of contributors to atherosclerosis, including lifestyle factors and genetic predisposition. Antioxidant diets and recreational exercises act as atheroprotectors and can retard atherogenesis. The search for molecular markers of atherogenesis and atheroprotection for predictive, preventive and personalized medicine appears to be the most promising direction for the study of atherosclerosis. In this work, we have analyzed 1068 human genes associated with atherogenesis, atherosclerosis and atheroprotection. The hub genes regulating these processes have been found to be the most ancient. In silico analysis of all 5112 SNPs in their promoters has revealed 330 candidate SNP markers, which statistically significantly change the affinity of the TATA-binding protein (TBP) for these promoters. These molecular markers have made us confident that natural selection acts against underexpression of the hub genes for atherogenesis, atherosclerosis and atheroprotection. At the same time, upregulation of the one for atheroprotection promotes human health.

Differentially Expressed Genes and Molecular Susceptibility to Human Age-Related Diseases.

Mainstream transcriptome profiling of susceptibility versus resistance to age-related diseases (ARDs) is focused on differentially expressed genes (DEGs) specific to gender, age, and pathogeneses. This approach fits in well with predictive, preventive, personalized, participatory medicine and helps understand how, why, when, and what ARDs one can develop depending on their genetic background. Within this mainstream paradigm, we wanted to find out whether the known ARD-linked DEGs available in PubMed can reveal a molecular marker that will serve the purpose in anyone's any tissue at any time. We sequenced the periaqueductal gray (PAG) transcriptome of tame versus aggressive rats, identified rat-behavior-related DEGs, and compared them with their known homologous animal ARD-linked DEGs. This analysis yielded statistically significant correlations between behavior-related and ARD-susceptibility-related fold changes (log2 values) in the expression of these DEG homologs. We found principal components, PC1 and PC2, corresponding to the half-sum and the half-difference of these log2 values, respectively. With the DEGs linked to ARD susceptibility and ARD resistance in humans used as controls, we verified these principal components. This yielded only one statistically significant common molecular marker for ARDs: an excess of Fcγ receptor IIb suppressing immune cell hyperactivation.

The New Version of the ANDDigest Tool with Improved AI-Based Short Names Recognition.

The body of scientific literature continues to grow annually. Over 1.5 million abstracts of biomedical publications were added to the PubMed database in 2021. Therefore, developing cognitive systems that provide a specialized search for information in scientific publications based on subject area ontology and modern artificial intelligence methods is urgently needed. We previously developed a web-based information retrieval system, ANDDigest, designed to search and analyze information in the PubMed database using a customized domain ontology. This paper presents an improved ANDDigest version that uses fine-tuned PubMedBERT classifiers to enhance the quality of short name recognition for molecular-genetics entities in PubMed abstracts on eight biological object types: cell components, diseases, side effects, genes, proteins, pathways, drugs, and metabolites. This approach increased average short name recognition accuracy by 13%.

Plant Biology and Biotechnology: Focus on Genomics and Bioinformatics.

The study of molecular mechanisms of plant stress response is important for agrobiotechnology applications as it was discussed at series of recent bioinformatics conferences [...].

Computer analysis of the relation between hydrogen bond stability in SOD1 mutants and the survival time of amyotrophic lateral sclerosis patients.

BACKGROUND AND OBJECTIVE: Mutations in the SOD1 protein can lead to the death of motor neurons, which, in turn, causes an incurable disease called amyotrophic lateral sclerosis (ALS). At the same time, the mechanism of the onset and development of this disease is not fully understood and is often contradictory. METHODS: Accelerated Molecular Dynamics as implemented in the OpenMM library, principal component analysis, regression analysis, random forest method. RESULTS: The stability of hydrogen bonds in 72 mutants of the SOD1 protein was calculated. Principal component analysis was carried out. Based on ten principal components acting as predictors, a multiple linear regression model was constructed. An analysis of the correlation of these ten principal components with the initial values of the stability of hydrogen bonds made it possible to characterize the contribution of known structurally and functionally important sites in the SOD1 to the scatter of ALS patients' survival time. CONCLUSION: Such an analysis made it possible to put forward hypotheses about the relationship between the stabilizing and destabilizing effects of mutations in different structurally and functionally important regions of SOD1 with the patients's survival time.

Pharmacological targeting of c-FLIPL and Bcl-2 family members promotes apoptosis in CD95L-resistant cells.

The development of efficient combinatorial treatments is one of the key tasks in modern anti-cancer therapies. An apoptotic signal can either be induced by activation of death receptors (DR) (extrinsic pathway) or via the mitochondria (intrinsic pathway). Cancer cells are characterized by deregulation of both pathways. Procaspase-8 activation in extrinsic apoptosis is controlled by c-FLIP proteins. We have recently reported the small molecules FLIPinB/FLIPinBγ targeting c-FLIPL in the caspase-8/c-FLIPL heterodimer. These small molecules enhanced caspase-8 activity in the death-inducing signaling complex (DISC), CD95L/TRAIL-induced caspase-3/7 activation and subsequent apoptosis. In this study to increase the pro-apoptotic effects of FLIPinB/FLIPinBγ and enhance its therapeutic potential we investigated costimulatory effects of FLIPinB/FLIPinBγ in combination with the pharmacological inhibitors of the anti-apoptotic Bcl-2 family members such as ABT-263 and S63845. The combination of these inhibitors together with FLIPinB/FLIPinBγ increased CD95L-induced cell viability loss, caspase activation and apoptosis. Taken together, our study suggests new approaches for the development of combinatorial anti-cancer therapies specifically targeting both intrinsic and extrinsic apoptosis pathways.

Young «oil site¼ of the Uzon Caldera as a habitat for unique microbial life.

BACKGROUND: The Uzon Caldera is one of the places on our planet with unique geological, ecological, and microbiological characteristics. Uzon oil is the youngest on Earth. Uzon oil has unique composition, with low proportion of heavy fractions and relatively high content of saturated hydrocarbons. Microbial communities of the «oil site¼ have a diverse composition and live at high temperatures (up to 97 °C), significant oscillations of Eh and pH, and high content of sulfur, sulfides, arsenic, antimony, and mercury in water and rocks. RESULTS: The study analyzed the composition, structure and unique genetics characteristics of the microbial communities of the oil site, analyzed the metabolic pathways in the communities. Metabolic pathways of hydrocarbon degradation by microorganisms have been found. The study found statistically significant relationships between geochemical parameters, taxonomic composition and the completeness of metabolic pathways. It was demonstrated that geochemical parameters determine the structure and metabolic potential of microbial communities. CONCLUSIONS: There were statistically significant relationships between geochemical parameters, taxonomic composition, and the completeness of metabolic pathways. It was demonstrated that geochemical parameters define the structure and metabolic potential of microbial communities. Metabolic pathways of hydrocarbon oxidation was found to prevail in the studied communities, which corroborates the hypothesis on abiogenic synthesis of Uzon hydrothermal petroleum.

The role of death domain proteins in host response upon SARS-CoV-2 infection: modulation of programmed cell death and translational applications.

The current pandemic of novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) poses a significant global public health threat. While urgent regulatory measures in control of the rapid spread of this virus are essential, scientists around the world have quickly engaged in this battle by studying the molecular mechanisms and searching for effective therapeutic strategies against this deadly disease. At present, the exact mechanisms of programmed cell death upon SARS-CoV-2 infection remain to be elucidated, though there is increasing evidence suggesting that cell death pathways play a key role in SARS-CoV-2 infection. There are several types of programmed cell death, including apoptosis, pyroptosis, and necroptosis. These distinct programs are largely controlled by the proteins of the death domain (DD) superfamily, which play an important role in viral pathogenesis and host antiviral response. Many viruses have acquired the capability to subvert the program of cell death and evade the host immune response, mainly by virally encoded gene products that control cell signaling networks. In this mini-review, we will focus on SARS-CoV-2, and discuss the implication of restraining the DD-mediated signaling network to potentially suppress viral replication and reduce tissue damage.

The story of the lost twins: decoding the genetic identities of the Kumhar and Kurcha populations from the Indian subcontinent.

BACKGROUND: The population structure of the Indian subcontinent is a tapestry of extraordinary diversity characterized by the amalgamation of autochthonous and immigrant ancestries and rigid enforcement of sociocultural stratification. Here we investigated the genetic origin and population history of the Kumhars, a group of people who inhabit large parts of northern India. We compared 27 previously published Kumhar SNP genotype data sampled from Uttar Pradesh in north India to various modern day and ancient populations. RESULTS: Various approaches such as Principal Component Analysis (PCA), Admixture, TreeMix concurred that Kumhars have high ASI ancestry, minimal Steppe component and high genomic proximity to the Kurchas, a small and relatively little-known population found ~ 2500 km away in Kerala, south India. Given the same, biogeographical mapping using Geographic Population Structure (GPS) assigned most Kumhar samples in areas neighboring to those where Kurchas are found in south India. CONCLUSIONS: We hypothesize that the significant genomic similarity between two apparently distinct modern-day Indian populations that inhabit well separated geographical areas with no known overlapping history or links, likely alludes to their common origin during or post the decline of the Indus Valley Civilization (estimated by ALDER). Thereafter, while they dispersed towards opposite ends of the Indian subcontinent, their genomic integrity and likeness remained preserved due to endogamous social practices. Our findings illuminate the genomic history of two Indian populations, allowing a glimpse into one or few of numerous of human migrations that likely occurred across the Indian subcontinent and contributed to shape its varied and vibrant evolutionary past.

ANDDigest: a new web-based module of ANDSystem for the search of knowledge in the scientific literature.

BACKGROUND: The rapid growth of scientific literature has rendered the task of finding relevant information one of the critical problems in almost any research. Search engines, like Google Scholar, Web of Knowledge, PubMed, Scopus, and others, are highly effective in document search; however, they do not allow knowledge extraction. In contrast to the search engines, text-mining systems provide extraction of knowledge with representations in the form of semantic networks. Of particular interest are tools performing a full cycle of knowledge management and engineering, including automated retrieval, integration, and representation of knowledge in the form of semantic networks, their visualization, and analysis. STRING, Pathway Studio, MetaCore, and others are well-known examples of such products. Previously, we developed the Associative Network Discovery System (ANDSystem), which also implements such a cycle. However, the drawback of these systems is dependence on the employed ontologies describing the subject area, which limits their functionality in searching information based on user-specified queries. RESULTS: The ANDDigest system is a new web-based module of the ANDSystem tool, permitting searching within PubMed by using dictionaries from the ANDSystem tool and sets of user-defined keywords. ANDDigest allows performing the search based on complex queries simultaneously, taking into account many types of objects from the ANDSystem's ontology. The system has a user-friendly interface, providing sorting, visualization, and filtering of the found information, including mapping of mentioned objects in text, linking to external databases, sorting of data by publication date, citations number, journal H-indices, etc. The system provides data on trends for identified entities based on dynamics of interest according to the frequency of their mentions in PubMed by years. CONCLUSIONS: The main feature of ANDDigest is its functionality, serving as a specialized search for information about multiple associative relationships of objects from the ANDSystem's ontology vocabularies, taking into account user-specified keywords. The tool can be applied to the interpretation of experimental genetics data, the search for associations between molecular genetics objects, and the preparation of scientific and analytical reviews. It is presently available at https://anddigest.sysbio.ru/ .

Learning the changes of barnase mutants thermostability from structural fluctuations obtained using anisotropic network modeling.

In biotechnology applications, rational design of new proteins with improved physico-chemical properties includes a number of important tasks. One of the greatest practical and fundamental challenges is the design of highly thermostable protein enzymes that maintain catalytic activity at high temperatures. This problem may be solved by introducing mutations into the wild-type enzyme protein. In this work, to predict the impact of such mutations in barnase protein we applied the anisotropic network modeling approach, revealing atomic fluctuations in structural regions that are changed in mutants compared to the wild-type protein. A regression model was constructed based on these structural features that can allow one to predict the thermal stability of new barnase mutants. Moreover, the analysis of regression model provides a mechanistic explanation of how the structural features can contribute to the thermal stability of barnase mutants.

Dissecting DISC regulation via pharmacological targeting of caspase-8/c-FLIPL heterodimer.

Pharmacological targeting via small molecule-based chemical probes has recently acquired an emerging importance as a valuable tool to delineate molecular mechanisms. Induction of apoptosis via CD95/Fas and TRAIL-R1/2 is triggered by the formation of the death-inducing signaling complex (DISC). Caspase-8 activation at the DISC is largely controlled by c-FLIP proteins. However molecular mechanisms of this control have just started to be uncovered. In this study we report the first-in-class chemical probe targeting c-FLIPL in the heterodimer caspase-8/c-FLIPL. This rationally designed small molecule was aimed to imitate the closed conformation of the caspase-8 L2' loop and thereby increase caspase-8 activity after initial processing of the heterodimer. In accordance with in silico predictions, this small molecule enhanced caspase-8 activity at the DISC, CD95L/TRAIL-induced caspase activation, and subsequent apoptosis. The generated computational model provided further evidence for the proposed effects of the small molecule on the heterodimer caspase-8/c-FLIPL. In particular, the model has demonstrated that boosting caspase-8 activity by the small molecule at the early time points after DISC assembly is crucial for promoting apoptosis induction. Taken together, our study allowed to target the heterodimer caspase-8/c-FLIPL and get new insights into molecular mechanisms of its activation.

Long and short isoforms of c-FLIP act as control checkpoints of DED filament assembly.

The assembly of the death-inducing signaling complex (DISC) and death effector domain (DED) filaments at CD95/Fas initiates extrinsic apoptosis. Procaspase-8 activation at the DED filaments is controlled by short and long c-FLIP isoforms. Despite apparent progress in understanding the assembly of CD95-activated platforms and DED filaments, the detailed molecular mechanism of c-FLIP action remains elusive. Here, we further addressed the mechanisms of c-FLIP action at the DISC using biochemical assays, quantitative mass spectrometry, and structural modeling. Our data strongly indicate that c-FLIP can bind to both FADD and procaspase-8 at the DED filament. Moreover, the constructed in silico model shows that c-FLIP proteins can lead to the formation of the DISCs comprising short DED filaments as well as serve as bridging motifs for building a cooperative DISC network, in which adjacent CD95 DISCs are connected by DED filaments. This network is based on selective interactions of FADD with both c-FLIP and procaspase-8. Hence, c-FLIP proteins at the DISC control initiation, elongation, and composition of DED filaments, playing the role of control checkpoints. These findings provide new insights into DISC and DED filament regulation and open innovative possibilities for targeting the extrinsic apoptosis pathway.

Delineating the role of c-FLIP/NEMO interaction in the CD95 network via rational design of molecular probes.

BACKGROUND: Structural homology modeling supported by bioinformatics analysis plays a key role in uncovering new molecular interactions within gene regulatory networks. Here, we have applied this powerful approach to analyze the molecular interactions orchestrating death receptor signaling networks. In particular, we focused on the molecular mechanisms of CD95-mediated NF-κB activation and the role of c-FLIP/NEMO interaction in the induction of this pathway. RESULTS: To this end, we have created the homology model of the c-FLIP/NEMO complex using the reported structure of the v-FLIP/NEMO complex, and rationally designed peptides targeting this complex. The designed peptides were based on the NEMO structure. Strikingly, the experimental in vitro validation demonstrated that the best inhibitory effects on CD95-mediated NF-κB activation are exhibited by the NEMO-derived peptides with the substitution D242Y of NEMO. Furthermore, we have assumed that the c-FLIP/NEMO complex is recruited to the DED filaments formed upon CD95 activation and validated this assumption in silico. Further insight into the function of c-FLIP/NEMO complex was provided by the analysis of evolutionary conservation of interacting regions which demonstrated that this interaction is common in distinct mammalian species. CONCLUSIONS: Taken together, using a combination of bioinformatics and experimental approaches we obtained new insights into CD95-mediated NF-κB activation, providing manifold possibilities for targeting the death receptor network.

Comorbidity of asthma and hypertension may be mediated by shared genetic dysregulation and drug side effects.

Asthma and hypertension are complex diseases coinciding more frequently than expected by chance. Unraveling the mechanisms of comorbidity of asthma and hypertension is necessary for choosing the most appropriate treatment plan for patients with this comorbidity. Since both diseases have a strong genetic component in this article we aimed to find and study genes simultaneously associated with asthma and hypertension. We identified 330 shared genes and found that they form six modules on the interaction network. A strong overlap between genes associated with asthma and hypertension was found on the level of eQTL regulated genes and between targets of drugs relevant for asthma and hypertension. This suggests that the phenomenon of comorbidity of asthma and hypertension may be explained by altered genetic regulation or result from drug side effects. In this work we also demonstrate that not only drug indications but also contraindications provide an important source of molecular evidence helpful to uncover disease mechanisms. These findings give a clue to the possible mechanisms of comorbidity and highlight the direction for future research.

Web-Based Computational Tools for the Prediction and Analysis of Posttranslational Modifications of Proteins.

The increase in the number of Web-based resources on posttranslational modification sites (PTMSs) in proteins is accelerating. This chapter presents a set of computational protocols describing how to work with the Internet resources when dealing with PTMSs. The protocols are intended for querying in PTMS-related databases, search of the PTMSs in the protein sequences and structures, and calculating the pI and molecular mass of the PTM isoforms. Thus, the modern bioinformatics prediction tools make it feasible to express protein modification in broader quantitative terms.