Identification of common candidate genes and pathways for Spina Bifida and Wilm's Tumor using an integrative bioinformatics analysis.

Spina Bifida (SB) and Wilm's Tumor (WT) are conditions, both associated with children. Several studies have shown that WT later develops in SB patients, which led us to elucidate common key genes and linked pathways of both conditions, aimed at their concurrent therapeutic management. For this, integrated bioinformatics analysis was employed. A comprehensive manual curation of genes identified 133 and 139 genes associated with SB and WT, respectively, which were used to construct a single protein-protein interaction (PPI) network. Topological parameters analysis of the network showed its scale-free and hierarchical nature. Centrality-based analysis of the network identified 116 hubs, of which, 6 were called the key genes attributed to being common between SB and WT besides being the hubs. Gene enrichment analysis of the 5 most essential modules, identified important biological processes and pathways possibly linking SB to WT. Additionally, miRNA-key gene-transcription factor (TF) regulatory network elucidated a few important miRNAs and TFs that regulate our key genes. In closing, we put forward TP53, DICER1, NCAM1, PAX3, PTCH1, MTHFR; hsa-mir-107, hsa-mir-137, hsa-mir-122, hsa-let-7d; and YY1, SOX4, MYC, STAT3; key genes, miRNAs and TFs, respectively, as the key regulators. Further, MD simulation studies of wild and Glu429Ala forms of MTHFR proteins showed that there is a slight change in MTHFR protein structure due to Glu429Ala polymorphism. We anticipate that the interplay of these three entities will be an interesting area of research to explore the regulatory mechanism of SB and WT and may serve as candidate target molecules to diagnose, monitor, and treat SB and WT, parallelly.Communicated by Ramaswamy H. Sarma.

Brain-derived neurotrophic factor G196A (rs6265) gene polymorphism increases Turner syndrome susceptibility.

Brain-derived neurotrophic factor (BDNF) is a member of the nerve growth factor family. It plays a significant role in the regulation of brain metabolic activity, modification of synaptic efficacy, and enhances neuronal survival. A common naturally occurring allelic variation, i.e. G196A (Val66 Met, rs6265) of the BDNF gene is implicated in neuroplasticity. This study analyzes its expression levels and determines the frequency of BDNF G196A gene polymorphism in women with Turner syndrome (TS) compared to the controls. This case-control study comprised 14 TS patients and 8 healthy individuals. The expression levels of BDNF gene in TS patients were checked by qPCR. For BDNF gene, a dynamic expression range along with the presence of G196A polymorphism was found across all TS patients. The effects of Val66 Met mutation on BDNF protein structure and function were studied by molecular dynamics simulations of wild and mutant (Val66 Met) forms. The analysis of different trajectories generated by simulation showed that there was a significant change in the protein structure due to Val66 Met polymorphism, which might lead to functional impairment. This is first time we are reporting the association of BDNF G196A gene polymorphism with TS risk. Our study suggests that in turner patients, BDNF G196A polymorphism may be an important genetic factor predisposing to neuroplasticity risk and can be exploited as diagnostic/prognostic marker for TS. Further study on a large number of TS samples will prove this point beyond doubts or otherwise enriching the much desired repertoire of personalized medicine.

Identification of key regulators in Sarcoidosis through multidimensional systems biological approach.

Sarcoidosis is a multi-organ disorder where immunology, genetic and environmental factors play a key role in causing Sarcoidosis, but its molecular mechanism remains unclear. Identification of its genetics profiling that regulates the Sarcoidosis network will be one of the main challenges to understand its aetiology. We have identified differentially expressed genes (DEGs) by analyzing the gene expression profiling of Sarcoidosis and compared it with healthy control. Gene set enrichment analysis showed that these DEGs were mainly enriched in the inflammatory response, immune system, and pathways in cancer. Sarcoidosis protein interaction network was constructed by a total of 877 DEGs (up-down) and calculated its network topological properties, which follow hierarchical scale-free fractal nature up to six levels of the organization. We identified a large number of leading hubs that contain six key regulators (KRs) including ICOS, CTLA4, FLT3LG, CD33, GPR29 and ITGA4 are deeply rooted in the network from top to bottom, considering a backbone of the network. We identified the transcriptional factors (TFs) which are closely interacted with KRs. These genes and their TFs regulating the Sarcoidosis network are expected to be the main target for the therapeutic approaches and potential biomarkers. However, experimental validations of KRs needed to confirm their efficacy.

Deciphering key genes in cardio-renal syndrome using network analysis.

Cardio-renal syndrome (CRS) is a rapidly recognized clinical entity which refers to the inextricably connection between heart and renal impairment, whereby abnormality to one organ directly promotes deterioration of the other one. Biological markers help to gain insight into the pathological processes for early diagnosis with higher accuracy of CRS using known clinical findings. Therefore, it is of interest to identify target genes in associated pathways implicated linked to CRS. Hence, 119 CRS genes were extracted from the literature to construct the PPIN network. We used the MCODE tool to generate modules from network so as to select the top 10 modules from 23 available modules. The modules were further analyzed to identify 12 essential genes in the network. These biomarkers are potential emerging tools for understanding the pathophysiologic mechanisms for the early diagnosis of CRS. Ontological analysis shows that they are rich in MF protease binding and endo-peptidase inhibitor activity. Thus, this data help increase our knowledge on CRS to improve clinical management of the disease.

In Silico Integrative Approach Revealed Key MicroRNAs and Associated Target Genes in Cardiorenal Syndrome.

Cardiorenal syndromes constellate primary dysfunction of either heart or kidney whereby one organ dysfunction leads to the dysfunction of another. The role of several microRNAs (miRNAs) has been implicated in number of diseases, including hypertension, heart failure, and kidney diseases. Wide range of miRNAs has been identified as ideal candidate biomarkers due to their stable expression. Current study was aimed to identify crucial miRNAs and their target genes associated with cardiorenal syndrome and to explore their interaction analysis. Three differentially expressed microRNAs (DEMs), namely, hsa-miR-4476, hsa-miR-345-3p, and hsa-miR-371a-5p, were obtained from GSE89699 and GSE87885 microRNA data sets, using R/GEO2R tools. Furthermore, literature mining resulted in the retrieval of 15 miRNAs from scientific research and review articles. The miRNAs-gene networks were constructed using miRNet (a Web platform of miRNA-centric network visual analytics). CytoHubba (Cytoscape plugin) was adopted to identify the modules and the top-ranked nodes in the network based on Degree centrality, Closeness centrality, Betweenness centrality, and Stress centrality. The overlapped miRNAs were further used in pathway enrichment analysis. We found that hsa-miR-21-5p was common in 8 pathways out of the top 10. Based on the degree, 5 miRNAs, namely, hsa-mir-122-5p, hsa-mir-222-3p, hsa-mir-21-5p, hsa-mir-146a-5p, and hsa-mir-29b-3p, are considered as key influencing nodes in a network. We suggest that the identified miRNAs and their target genes may have pathological relevance in cardiorenal syndrome (CRS) and may emerge as potential diagnostic biomarkers.

Network-based analysis of key regulatory genes implicated in Type 2 Diabetes Mellitus and Recurrent Miscarriages in Turner Syndrome.

The information on the genotype-phenotype relationship in Turner Syndrome (TS) is inadequate because very few specific candidate genes are linked to its clinical features. We used the microarray data of TS to identify the key regulatory genes implicated with TS through a network approach. The causative factors of two common co-morbidities, Type 2 Diabetes Mellitus (T2DM) and Recurrent Miscarriages (RM), in the Turner population, are expected to be different from that of the general population. Through microarray analysis, we identified nine signature genes of T2DM and three signature genes of RM in TS. The power-law distribution analysis showed that the TS network carries scale-free hierarchical fractal attributes. Through local-community-paradigm (LCP) estimation we find that a strong LCP is also maintained which means that networks are dynamic and heterogeneous. We identified nine key regulators which serve as the backbone of the TS network. Furthermore, we recognized eight interologs functional in seven different organisms from lower to higher levels. Overall, these results offer few key regulators and essential genes that we envisage have potential as therapeutic targets for the TS in the future and the animal models studied here may prove useful in the validation of such targets.

Identification of the Key Regulators of Spina Bifida Through Graph-Theoretical Approach.

Spina Bifida (SB) is a congenital spinal cord malformation. Efforts to discern the key regulators (KRs) of the SB protein-protein interaction (PPI) network are requisite for developing its successful interventions. The architecture of the SB network, constructed from 117 manually curated genes was found to self-organize into a scale-free fractal state having a weak hierarchical organization. We identified three modules/motifs consisting of ten KRs, namely, TNIP1, TNF, TRAF1, TNRC6B, KMT2C, KMT2D, NCOA3, TRDMT1, DICER1, and HDAC1. These KRs serve as the backbone of the network, they propagate signals through the different hierarchical levels of the network to conserve the network's stability while maintaining low popularity in the network. We also observed that the SB network exhibits a rich-club organization, the formation of which is attributed to our key regulators also except for TNIP1 and TRDMT1. The KRs that were found to ally with each other and emerge in the same motif, open up a new dimension of research of studying these KRs together. Owing to the multiple etiology and mechanisms of SB, a combination of several biomarkers is expected to have higher diagnostic accuracy for SB as compared to using a single biomarker. So, if all the KRs present in a single module/motif are targetted together, they can serve as biomarkers for the diagnosis of SB. Our study puts forward some novel SB-related genes that need further experimental validation to be considered as reliable future biomarkers and therapeutic targets.

Structure-Guided Approach to Identify Potential Inhibitors of Large Envelope Protein to Prevent Hepatitis B Virus Infection.

Hepatitis B virus (HBV) infection is one of the major causes of liver diseases, which can lead to hepatocellular carcinoma. The role of HBV envelope proteins is crucial in viral morphogenesis, infection, and propagation. Thus, blocking the pleiotropic functions of these proteins especially the PreS1 and PreS2 domains of the large surface protein (LHBs) is a promising strategy for designing efficient antivirals against HBV infection. Unfortunately, the structure of the LHBs protein has not been elucidated yet, and it seems that any structure-based drug discovery is critically dependent on this. To find effective inhibitors of LHBs, we have modeled and validated its three-dimensional structure and subsequently performed a virtual high-throughput screening against the ZINC database using RASPD and ParDOCK tools. We have identified four compounds, ZINC11882026, ZINC19741044, ZINC00653293, and ZINC15000762, showing appreciable binding affinity with the LHBs protein. The drug likeness was further validated using ADME screening and toxicity analysis. Interestingly, three of the four compounds showed the formation of hydrogen bonds with amino acid residues lying in the capsid binding region of the PreS1 domain of LHBs, suggesting the possibility of inhibiting the viral assembly and maturation process. The identification of potential lead molecules will help to discover more potent inhibitors with significant antiviral activities.

Identification and Classification of Differentially Expressed Genes and Network Meta-Analysis Reveals Potential Molecular Signatures Associated With Tuberculosis.

Tuberculosis (TB) is one of deadly transmissible disease that causes death worldwide; however, only 10% of people infected with Mycobacterium tuberculosis develop disease, indicating that host genetic factors may play key role in determining susceptibility to TB disease. In this way, the analysis of gene expression profiling of TB infected individuals can give us a snapshot of actively expressed genes and transcripts under various conditions. In the present study, we have analyzed microarray data set and compared the gene expression profiles of patients with different datasets of healthy control, latent infection, and active TB. We observed the transition of genes from normal condition to different stages of the TB and identified and annotated those genes/pathways/processes that have important roles in TB disease during its cyclic interventions in the human body. We identified 488 genes that were differentially expressed at various stages of TB and allocated to pathways and gene set enrichment analysis. These pathways as well as GSEA's importance were evaluated according to the number of DEGs presents in both. In addition, we studied the gene regulatory networks that may help to further understand the molecular mechanism of immune response against the TB infection and provide us a new angle for future biomarker and therapeutic targets. In this study, we identified 26 leading hubs which are deeply rooted from top to bottom in the gene regulatory network and work as the backbone of the network. These leading hubs contains 31 key regulator genes, of which 14 genes were up-regulated and 17 genes were down-regulated. The proposed approach is based on gene-expression profiling, and network analysis approaches predict some unknown TB-associated genes, which can be considered (or can be tested) as reliable candidates for further (in vivo/in vitro) studies.

Assessment of the key regulatory genes and their Interologs for Turner Syndrome employing network approach.

Turner Syndrome (TS) is a condition where several genes are affected but the molecular mechanism remains unknown. Identifying the genes that regulate the TS network is one of the main challenges in understanding its aetiology. Here, we studied the regulatory network from manually curated genes reported in the literature and identified essential proteins involved in TS. The power-law distribution analysis showed that TS network carries scale-free hierarchical fractal attributes. This organization of the network maintained the self-ruled constitution of nodes at various levels without having centrality-lethality control systems. Out of twenty-seven genes culminating into leading hubs in the network, we identified two key regulators (KRs) i.e. KDM6A and BDNF. These KRs serve as the backbone for all the network activities. Removal of KRs does not cause its breakdown, rather a change in the topological properties was observed. Since essential proteins are evolutionarily conserved, the orthologs of selected interacting proteins in C. elegans, cat and macaque monkey (lower to higher level organisms) were identified. We deciphered three important interologs i.e. KDM6A-WDR5, KDM6A-ASH2L and WDR5-ASH2L that form a triangular motif. In conclusion, these KRs and identified interologs are expected to regulate the TS network signifying their biological importance.

Recent trends in ZikV research: A step away from cure.

Zika virus (ZikV) is a member of the Flaviviridae virus family, genus Flavivirus has emerged as a potential threat to human health worldwide. Consequences of vertical infections includes microcephaly with brain and eye anomalies, and adult infections includes Guillain-Barrésyndrome (GBS), brain ischemia, myelitis and meningoencephalitis. To develop a better treatment, many efforts are being made, like drug-repurposing concept for FDA-approved drugs for antiviral activity are screened against ZikV infection and emerging as a promising alternative to expedite drug development and various vaccines like DNA, ZPIV, LAIV, mRNA and AGS-v vaccines have been designed and in under clinical trial phases. Moreover, few pharmacological agents like Mycophenolicacid, Niclosamide, PHA-690509, Emricasan and Bortezomib are most potent anti-ZikV candidates and highly effective single or combining treatment with these drugs. This article reviews the ZikV illness, transmission patterns, pathophysiology of disease, global efforts, challenges and the prospects for the development of vaccines and antiviral agents.