Olga V. Saik

ANDSystem: an Associative Network Discovery System for automated literature mining in the field of biology

BackgroundSufficient knowledge of molecular and genetic interactions, which comprise the entire basis of the functioning of living systems, is one of the necessary requirements for successfully answering almost any research question in the field of biology and medicine. To date, more than 24 million scientific papers can be found in PubMed, with many of them containing descriptions of a wide range of biological processes. The analysis of such tremendous amounts of data requires the use of automated text-mining approaches. Although a handful of tools have recently been developed to meet this need, none of them provide error-free extraction of highly detailed information.ResultsThe ANDSystem package was developed for the reconstruction and analysis of molecular genetic networks based on an automated text-mining technique. It provides a detailed description of the various types of interactions between genes, proteins, microRNAs, metabolites, cellular components, pathways and diseases, taking into account the specificity of cell lines and organisms. Although the accuracy of ANDSystem is comparable to other well known text-mining tools, such as Pathway Studio and STRING, it outperforms them in having the ability to identify an increased number of interaction types.ConclusionThe use of ANDSystem, in combination with Pathway Studio and STRING, can improve the quality of the automated reconstruction of molecular and genetic networks. ANDSystem should provide a useful tool for researchers working in a number of different fields, including biology, biotechnology, pharmacology and medicine.

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlincRNAs genes likely function in cis to activate nearby genes. This effect while most pronounced in closely spaced vlincRNA–gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlincRNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs.

Proton magnetic resonance spectroscopy of brain metabolic shifts induced by acute administration of 2-deoxy-d-glucose and lipopolysaccharides.

In vivo proton magnetic resonance spectroscopy (1H MRS) of outbred stock ICR male mice (originating from the Institute of Cancer Research) was used to study the brain (hippocampus) metabolic response to the pro‐inflammatory stimulus and to the acute deficiency of the available energy, which was confirmed by measuring the maximum oxygen consumption. Inhibition of glycolysis by means of an injection with 2‐deoxy‐d‐glucose (2DG) reduced the levels of gamma‐aminobutyric acid (GABA, p < 0.05, in comparison with control, least significant difference (LSD) test), N‐acetylaspartate (NAA, p < 0.05, LSD test) and choline compounds, and at the same time increased the levels of glutamate and glutamine. An opposite effect was found after injection with bacterial lipopolysaccharide (LPS) – a very common pro‐inflammatory inducer. An increase in the amounts of GABA, NAA and choline compounds in the brain occurred in mice treated with LPS. Different metabolic responses to the energy deficiency and the pro‐inflammatory stimuli can explain the contradictory results of the brain 1H MRS studies under neurodegenerative pathology, which is accompanied by both mitochondrial dysfunction and inflammation. The prevalence of the excitatory metabolites such as glutamate and glutamine in 2DG treated mice is in good agreement with excitation observed during temporary reduction of the available energy under acute hypoxia or starvation. In turn, LPS, as an inducer of the sickness behavior, which was manifested as depression, sleepiness, loss of appetite etc., shifts the brain metabolic pattern toward the prevalence of the inhibitory neurotransmitter GABA. Copyright

Molecular association of pathogenetic contributors to pre-eclampsia (pre-eclampsia associome)

BackgroundPre-eclampsia is the most common complication occurring during pregnancy. In the majority of cases, it is concurrent with other pathologies in a comorbid manner (frequent co-occurrences in patients), such as diabetes mellitus, gestational diabetes and obesity. Providing bronchial asthma, pulmonary tuberculosis, certain neurodegenerative diseases and cancers as examples, we have shown previously that pairs of inversely comorbid pathologies (rare co-occurrences in patients) are more closely related to each other at the molecular genetic level compared with randomly generated pairs of diseases. Data in the literature concerning the causes of pre-eclampsia are abundant. However, the key mechanisms triggering this disease that are initiated by other pathological processes are thus far unknown. The aim of this work was to analyse the characteristic features of genetic networks that describe interactions between comorbid diseases, using pre-eclampsia as a case in point.ResultsThe use of ANDSystem, Pathway Studio and STRING computer tools based on text-mining and database-mining approaches allowed us to reconstruct associative networks, representing molecular genetic interactions between genes, associated concurrently with comorbid disease pairs, including pre-eclampsia, diabetes mellitus, gestational diabetes and obesity. It was found that these associative networks statistically differed in the number of genes and interactions between them from those built for randomly chosen pairs of diseases. The associative network connecting all four diseases was composed of 16 genes (PLAT, ADIPOQ, ADRB3, LEPR, HP, TGFB1, TNFA, INS, CRP, CSRP1, IGFBP1, MBL2, ACE, ESR1, SHBG, ADA). Such an analysis allowed us to reveal differential gene risk factors for these diseases, and to propose certain, most probable, theoretical mechanisms of pre-eclampsia development in pregnant women. The mechanisms may include the following pathways: [TGFB1 or TNFA]-[IL1B]-[pre-eclampsia]; [TNFA or INS]-[NOS3]-[pre-eclampsia]; [INS]-[HSPA4 or CLU]-[pre-eclampsia]; [ACE]-[MTHFR]-[pre-eclampsia].ConclusionsFor pre-eclampsia, diabetes mellitus, gestational diabetes and obesity, we showed that the size and connectivity of the associative molecular genetic networks, which describe interactions between comorbid diseases, statistically exceeded the size and connectivity of those built for randomly chosen pairs of diseases. Recently, we have shown a similar result for inversely comorbid diseases. This suggests that comorbid and inversely comorbid diseases have common features concerning structural organization of associative molecular genetic networks.

A compendium of human genes regulating feeding behavior and body weight, its functional characterization and identification of GWAS genes involved in brain-specific PPI network

BackgroundObesity is heritable. It predisposes to many diseases. The objectives of this study were to create a compendium of genes relevant to feeding behavior (FB) and/or body weight (BW) regulation; to construct and to analyze networks formed by associations between genes/proteins; and to identify the most significant genes, biological processes/pathways, and tissues/organs involved in BW regulation.ResultsThe compendium of genes controlling FB or BW includes 578 human genes. Candidate genes were identified from various sources, including previously published original research and review articles, GWAS meta-analyses, and OMIM (Online Mendelian Inheritance in Man). All genes were ranked according to knowledge about their biological role in body weight regulation and classified according to expression patterns or functional characteristics. Substantial and overrepresented numbers of genes from the compendium encoded cell surface receptors, signaling molecules (hormones, neuropeptides, cytokines), transcription factors, signal transduction proteins, cilium and BBSome components, and lipid binding proteins or were present in the brain-specific list of tissue-enriched genes identified with TSEA tool. We identified 27 pathways from KEGG, REACTOME and BIOCARTA whose genes were overrepresented in the compendium. Networks formed by physical interactions or homological relationships between proteins or interactions between proteins involved in biochemical/signaling pathways were reconstructed and analyzed. Subnetworks and clusters identified by the MCODE tool included genes/proteins associated with cilium morphogenesis, signal transduction proteins (particularly, G protein–coupled receptors, kinases or proteins involved in response to insulin stimulus) and transcription regulation (particularly nuclear receptors). We ranked GWAS genes according to the number of neighbors in three networks and revealed 22 GWAS genes involved in the brain-specific PPI network. On the base of the most reliable PPIs functioning in the brain tissue, new regulatory schemes interpreting relevance to BW regulation are proposed for three GWAS genes (ETV5, LRP1B, and NDUFS3).ConclusionsA compendium comprising 578 human genes controlling FB or BW was designed, and the most significant functional groups of genes, biological processes/pathways, and tissues/organs involved in BW regulation were revealed. We ranked genes from the GWAS meta-analysis set according to the number and quality of associations in the networks and then according to their involvement in the brain-specific PPI network and proposed new regulatory schemes involving three GWAS genes (ETV5, LRP1B, and NDUFS3) in BW regulation. The compendium is expected to be useful for pathology risk estimation and for design of new pharmacological approaches in the treatment of human obesity.

Exploring Interaction of TNF and Orthopoxviral CrmB Protein by Surface Plasmon Resonance and Free Energy Calculation

Inhibition of the activity of the tumor necrosis factor (TNF) has become the main strategy for treating inflammatory diseases. The orthopoxvirus TNF-binding proteins can bind and efficiently neutralize TNF. To analyze the mechanisms of the interaction between human (hTNF) or mouse (mTNF) TNF and the cowpox virus N-terminal binding domain (TNFBD-CPXV), also the variola virus N-terminal binding domain (TNFBD-VARV) and to define the amino acids most importantly involved in the formation of complexes, computer models, derived from the X-ray structure of a homologous hTNF/TNFRII complex, were used together with experiments. The hTNF/TNFBD-CPXV, hTNF/TNFBD-VARV, mTNF/TNFBD-CPXV, and mTNF/TNFBD-VARV complexes were used in the molecular dynamics (MD) simulations and MM/GBSA free energy calculations. The complexes were ordered as hTNF/TNFBD-CPXV, hTNF/TNFBD-VARV, mTNF/TNFBD-CPXV and mTNF/TNFBD-VARV according to increase in the binding affinity. The calculations were in agreement with surface plasmon resonance (SPR) measurements of the binding constants. Key residues involved in complex formation were identified.

Novel candidate genes important for asthma and hypertension comorbidity revealed from associative gene networks

BackgroundHypertension and bronchial asthma are a major issue for people’s health. As of 2014, approximately one billion adults, or ~ 22% of the world population, have had hypertension. As of 2011, 235–330 million people globally have been affected by asthma and approximately 250,000–345,000 people have died each year from the disease. The development of the effective treatment therapies against these diseases is complicated by their comorbidity features. This is often a major problem in diagnosis and their treatment. Hence, in this study the bioinformatical methodology for the analysis of the comorbidity of these two diseases have been developed. As such, the search for candidate genes related to the comorbid conditions of asthma and hypertension can help in elucidating the molecular mechanisms underlying the comorbid condition of these two diseases, and can also be useful for genotyping and identifying new drug targets.ResultsUsing ANDSystem, the reconstruction and analysis of gene networks associated with asthma and hypertension was carried out. The gene network of asthma included 755 genes/proteins and 62,603 interactions, while the gene network of hypertension - 713 genes/proteins and 45,479 interactions. Two hundred and five genes/proteins and 9638 interactions were shared between asthma and hypertension. An approach for ranking genes implicated in the comorbid condition of two diseases was proposed. The approach is based on nine criteria for ranking genes by their importance, including standard methods of gene prioritization (Endeavor, ToppGene) as well as original criteria that take into account the characteristics of an associative gene network and the presence of known polymorphisms in the analysed genes. According to the proposed approach, the genes IL10, TLR4, and CAT had the highest priority in the development of comorbidity of these two diseases. Additionally, it was revealed that the list of top genes is enriched with apoptotic genes and genes involved in biological processes related to the functioning of central nervous system.ConclusionsThe application of methods of reconstruction and analysis of gene networks is a productive tool for studying the molecular mechanisms of comorbid conditions. The method put forth to rank genes by their importance to the comorbid condition of asthma and hypertension was employed that resulted in prediction of 10 genes, playing the key role in the development of the comorbid condition. The results can be utilised to plan experiments for identification of novel candidate genes along with searching for novel pharmacological targets.

Genome-wide profiling and differential expression of microRNA in rat pluripotent stem cells

MicroRNAs (miRNAs) constitute a class of small noncoding RNAs that plays an important role in the post-transcriptional regulation of gene expression. Much evidence has demonstrated that miRNAs are involved in regulating the human and mouse pluripotency. Nevertheless, to our knowledge, miRNAs in the pluripotent stem cells of one of the most commonly used model organisms – the Rattus norvegicus have not been studied. In the present study, we performed deep sequencing of small RNA molecules in the embryonic fibroblasts, embryonic stem cells, and induced pluripotent stem cells of laboratory rats. Bioinformatics analysis revealed 674 known miRNAs and 394 novel miRNA candidates in all of the samples. Expression of known pluripotency-associated miRNAs, such as the miR-290–295 and miR-183-96-182 clusters as well as members of the miR-200 family, was detected in rat pluripotent stem cells. Analysis of the targets of differentially expressed known and novel miRNAs showed their involvement in the regulation of pluripotency and the reprogramming process in rats. Bioinformatics and systems biology approaches identified potential pathways that are regulated by these miRNAs. This study contributes to our understanding of miRNAs in the regulation of pluripotency and cell reprogramming in the laboratory rat.

Molecular mechanisms of the interaction between the processes of the cell response to mechanical stress and neuronal apoptosis in primary open-angle glaucoma

Glaucoma is a chronic progressive disease. It involves more than 60 million people worldwide. Primary open-angle glaucoma (POAG) is one of its commonest forms. About 2.71 million people in the United States suffered from POAG in 2011. Currently, POAG is a major cause of irreversible vision loss. The risk of blindness in patients with treated open-angle glaucoma is 27%. It is known that the death of optic nerve cells can be triggered by mechanical stress caused by ocular hypertension, which induces neuronal apoptosis and occurs in patients with POAG. Many scientific publications are dedicated to proteins and genes involved in the development of POAG, including neuronal apoptosis and the cell response to mechanical stress (CRMS). However, the molecular mechanisms underlying the pathophysiology of POAG are still poorly understood. The reconstruction of associative networks describing the functional interactions between these genes/proteins, including biochemical reactions, regulatory interactions, and transport, requires automated knowledge extraction from scientific publications. This work aims to analyze the associative networks describing molecular interactions between proteins and genes involved in CRMS, neuronal apoptosis, and the development of POAG. It has been shown that genes associated with POAG are statistically significantly overrepresented among the genes involved in the interactions between CRMS and neuronal apoptosis in comparison to what is expected on a random basis. This finding may explain how POAG causes the death of the retinal ganglion cell.

NACE: A web-based tool for prediction of intercompartmental efficiency of human molecular genetic networks.

Molecular genetic processes generally involve proteins from distinct intracellular localisations. Reactions that follow the same process are distributed among various compartments within the cell. In this regard, the reaction rate and the efficiency of biological processes can depend on the subcellular localisation of proteins. Previously, the authors proposed a method of evaluating the efficiency of biological processes based on the analysis of the distribution of protein subcellular localisation (Popik et al., 2014). Here, NACE is presented, which is an open access web-oriented program that implements this method and allows the user to evaluate the intercompartmental efficiency of human molecular genetic networks. The method has been extended by a new feature that provides the evaluation of the tissue-specific efficiency of networks for more than 2800 anatomical structures. Such assessments are important in cases when molecular genetic pathways in different tissues proceed with the participation of various proteins with a number of intracellular localisations. For example, an analysis of KEGG pathways, conducted using the developed program, showed that the efficiencies of many KEGG pathways are tissue-specific. Analysis of efficiencies of regulatory pathways in the liver, linking proteins of the hepatitis C virus with human proteins involved in the KEGG apoptosis pathway, showed that intercompartmental efficiency might play an important role in host-pathogen interactions. Thus, the developed tool can be useful in the study of the effectiveness of functioning of various molecular genetic networks, including metabolic, regulatory, host-pathogen interactions and others taking into account tissue-specific gene expression. The tool is available via the following link: http://www-bionet.sscc.ru/nace/.