NFX1-123: A potential therapeutic target in cervical cancer.

NFX1-123 is a splice variant isoform of the NFX1 gene. It is highly expressed in cervical cancers caused by HPV, and NFX1-123 is a protein partner with the HPV oncoprotein E6. Together, NFX1-123 and E6 affect cellular growth, longevity, and differentiation. The expression status of NFX1-123 in cancers beyond cervical and head and neck cancers, and its potential as therapeutic target, have not been investigated. TSVdb of TCGA was used to quantify NFX1-123 expression in 24 cancers compared with normal tissues. The NFX1-123 protein structure was predicted and then submitted to retrieve suitable drug molecules. The top four compounds, found to bind in silico to NFX1-123, were tested experimentally to determine their effects on NFX1-123-related cellular growth, survival, and migration. 46% of cancers (11 of 24 had significant differences in NFX1-123 expression, with nine having had greater NFX1-123 expression, when compared with adjacent normal tissues. Bioinformatics and proteomic predictive analysis modeled the three-dimensional structure of NFX1-123, and drug libraries were screened for high-binding affinity compounds using this modeled structure. Seventeen drugs with binding energies ranging from -1.3 to -10 Kcal/mol were identified. The top four compounds were used to treat HPV- and HPV+ cervical cancer cell lines, three of which (Ropitoin, R428 and Ketoconazole) reduced NFX1-123 protein levels, inhibited cellular growth, survival, and migration, and enhanced the cytotoxicity of Cisplatin. These findings highlight cancers expressing high levels of NFX1-123, and drugs that target it, may reduce cellular growth, survival, and migration, making NFX1-123 a potential novel therapeutic target.

Systems biology approach to understand the interplay between Bacillus anthracis and human host genes that leads to CVDs.

Humans infected with invasive Bacillus anthracis (B. anthracis) have a very poor prognosis and are at high risk for developing cardiovascular diseases (CVDs) and shock. Several bacterial elements probably have significant pathogenic roles in this pathogenic process of anthrax. In our current work, we have analysed the molecular level interactions between B. anthracis and human genes to understand the interplay during anthrax that leads to the CVDs. Our results have shown dense interactions between the functional partners in both host and the B. anthracis Gene interaction network (GIN). The functional enrichment analysis indicated that the clusters in the host GIN had genes related to hypoxia and autophagy in response to the lethal toxin; and genes related to adherens junction and actin cytoskeleton in response to edema toxin play a significant role in multiple stages of the disease. The B. anthracis genes BA_0530, guaA, polA, rpoB, ribD, secDF, metS, dinG and human genes ACTB, EGFR, EP300, CTNNB1, ESR1 have shown more than 50 direct interactions with the functional partners and hence they can be considered as hub genes in the network and they are observed to have important roles in CVDs. The outcome of our study will help to understand the molecular pathogenesis of CVDs in anthrax. The hub genes reported in the study can be considered potential drug targets and they can be exploited for new drug discovery.

FN1 encoding fibronectin as a pivotal signaling gene for therapeutic intervention against pancreatic cancer.

The delayed diagnosis of pancreatic cancer has resulted in rising mortality rate and low survival rate that can be circumvented using potent theranostics biomarkers. The treatment gets complicated with delayed detection resulting in lowered 5-year relative survival rate. In our present study, we employed systems biology approach to identify central genes that play crucial roles in tumor progression. Pancreatic cancer genes collected from various databases were used to construct a statistically significant interactome with 812 genes that was further analysed thoroughly using topological parameters and functional enrichment analysis. The significant genes in the network were then identified based on the maximum degree parameter. The overall survival analysis indicated through hazard ratio [HR] and gene expression [log Fold Change] across pancreatic adenocarcinoma revealed the critical role of FN1 [HR 1.4; log2(FC) 5.748], FGA [HR 0.78; log2(FC) 1.639] FGG [HR 0.9; log2(FC) 1.597], C3 [HR 1.1; log2(FC) 2.637], and QSOX1 [HR 1.4; log2(FC) 2.371]. The functional significance of the identified hub genes signified the enrichment of integrin cell surface interactions and proteoglycan syndecan-mediated cell signaling. The differential expression, low overall survival and functional significance of FN1 gene implied its possible role in controlling metastasis in pancreatic cancer. Furthermore, alternate splice variants of FN1 gene showed 10 protein coding transcripts with conserved cell attachment site and functional domains indicating the variants' potential role in pancreatic cancer. The strong association of the identified hub-genes can be better directed to design potential theranostics biomarkers for metastasized pancreatic tumor.

Organ-specific host differential gene expression analysis in systemic candidiasis: A systems biology approach.

Patients admitted to the hospital with coronavirus disease (COVID-19) are at risk for acquiring mycotic infections in particular Candidemia. Candida albicans (C. albicans) constitutes an important component of the human mycobiome and the most common cause of invasive fungal infections. Invasive yeast infections are gaining interest among the scientific community as a consequence of complications associated with severe COVID-19 infections. Early identification and surveillance for Candida infections is critical for decreasing the COVID-19 mortality. Our current study attempted to understand the molecular-level interactions between the human genes in different organs during systematic candidiasis. Our research findings have shed light on the molecular events that occur during Candidiasis in organs such as the kidney, liver, and spleen. The differentially expressed genes (up and down-regulated) in each organ will aid in designing organ-specific therapeutic protocols for systemic candidiasis. We observed organ-specific immune responses such as the development of the acute phase response in the liver; TGF-pathway and genes involved in lymphocyte activation, and leukocyte proliferation in the kidney. We have also observed that in the kidney, filament production, up-regulation of iron acquisition mechanisms, and metabolic adaptability are aided by the late initiation of innate defense mechanisms, which is likely related to the low number of resident immune cells and the sluggish recruitment of new effector cells. Our findings point to major pathways that play essential roles in specific organs during systemic candidiasis. The hub genes discovered in the study can be used to develop novel drugs for clinical management of Candidiasis.

Gene interaction network studies to decipher the multi-drug resistance mechanism in Salmonella enterica serovar Typhi CT18 reveal potential drug targets.

Salmonella enterica subsp. enterica serovar Typhi, a human enteric pathogen causing typhoid fever, developed resistance to multiple antibiotics over the years. The current study was dedicated to understand the multi-drug resistance (MDR) mechanism of S. enterica serovar Typhi CT18 and to identify potential drug targets that could be exploited for new drug discovery. We have employed gene interaction network analysis for 44 genes which had 275 interactions. Clustering analysis resulted in three highly interconnecting clusters (C1-C3). Functional enrichment analysis revealed the presence of drug target alteration and three different multi-drug efflux pumps in the bacteria that were associated with antibiotic resistance. We found seven genes (arnA,B,C,D,E,F,T) conferring resistance to Cationic Anti-Microbial Polypeptide (CAMP) molecules by membrane Lipopolysaccharide (LPS) modification, while macB was observed to be an essential controlling hub of the network and played a crucial role in MacAB-TolC efflux pump. Further, we identified five genes (mdtH, mdtM, mdtG, emrD and mdfA) which were involved in Major Facilitator Superfamily (MFS) efflux system and acrAB contributed towards AcrAB-TolC efflux pump. All three efflux pumps were seen to be highly dependent on tolC gene. The five genes, namely tolC, macB, acrA, acrB and mdfA which were involved in multiple resistance pathways, can act as potential drug targets for successful treatment strategies. Therefore, this study has provided profound insights into the MDR mechanism in S. Typhi CT18. Our results will be useful for experimental biologists to explore new leads for S. enterica.

Exploring the multi-drug resistance in Escherichia coli O157:H7 by gene interaction network: A systems biology approach.

In the present study, we have constructed an interaction network of 29 antibiotic resistant genes along with 777 interactions in E. coli O157:H7. Gene ontology analysis reveals that 94, 89 and 67 genes have roles in the cellular process, biological process and molecular function respectively. Gene complexes related to tripartite efflux pumps mdtEF-tolC and ABC family efflux pump macAB-tolC play key roles in multidrug efflux systems. It is noteworthy to mention that, 19 genes are involved in multi-efflux pumps and they play a significant role in multidrug resistance (MDR); while 18 genes are vital for fatty acid synthesis. Interestingly, we found that the four genes arnABCD are involved in both MDR and in fatty acid synthesis. Hence these genes could be targeted for new drug discovery. On the whole, our results provide a detailed understanding of the mode of MDR mechanisms in E.coli O157:H7.

Impact of bedaquiline and capreomycin on the gene expression patterns of multidrug-resistant Mycobacterium tuberculosis H37Rv strain and understanding the molecular mechanism of antibiotic resistance.

The emergence of multidrug resistance (MDR), extensively drug-resistant, and total drug-resistant Mycobacterium tuberculosis (Mtb) strains have hampered the treatment of tuberculosis (TB). Capreomycin and Bedaquiline are currently used for MDR-TB treatment. To understand the impact of these antibiotics on Mtb genes, we have curated the gene expression data where the Mtb cultures were exposed to the Bedaquiline and Capreomycin. Based on the P value cut off (<0.05) and logFC (<-0.5 and >+0.5) values, we have selected the top differentially expressed genes during the antibiotic exposures. We have observed that the top differentially expressed Mtb genes were related to universal stress genes, two-component regulatory systems, and drug efflux pumps. We have curated the Mtb gene datasets and carried out the functional over-representation analysis using the individual gene expression values. We further, constructed the gene interaction networks of antibiotic resistance genes and virulence genes of Mtb to understand the impact of the antibiotics at the molecular level and thus to understand the antimicrobial resistance and virulence patterns. Our study elucidates the impact of antibiotics on the Mtb genes at the molecular level and the positively enriched pathways, operons, and regulons data are helpful in understanding the resistance patterns in Mtb. The upregulated genes during the exposure of Bedaquiline and Capreomycin can be considered as potent drug targets for the development of new anti-TB drugs.

Systems biology studies in Pseudomonas aeruginosa PA01 to understand their role in biofilm formation and multidrug efflux pumps.

The antimicrobial resistance (AMR) exhibited against broad spectrum and new generation antibiotics used for Pseudomonas infections is a major threat and renders the treatment ineffective. In our present study, we have used a computational approach to understand various drug resistance mechanisms which contribute to Multi-Drug Resistance (MDR) in P. aeruginosa. The interaction network of 60 AMR genes along with the 337 functional interactions was analyzed. Functional enrichment analysis of AMR genes has shown that the genes in the network are mainly associated with efflux pump mechanisms, alginate biosynthesis, biofilm formation, and ampC beta-lactamase biosynthesis. Interestingly, the genes phoP, phoQ, and cat genes are observed to have roles in more than one drug-resistant mechanism. The genes phoP and phoQ apart from their role in two-component regulatory systems also play major roles in multidrug efflux pumps and alteration in drug target. The gene cat involves in alteration of drug target and enzymatic inactivation. The interaction network analysis has shown that the AMR genes oprJ, oprM, oprN, ampC, gyrA, mexA, oprD, mexB and nfxB have higher number of direct interactors and they are considered as the hub nodes in the network and these genes can be used as potential drug targets for developing new drugs. The results from our study will be helpful in better understanding of the antibiotic resistance mechanisms in P. aeruginosa. The gene targets reported, can be used for new drug discovery against Pseudomonas infections.

Cellular and molecular level host-pathogen interactions in Francisella tularensis: A microbial gene network study.

Due to the high infectivity and fatal effect on human population, Francisella tularensis (F. tularensis) is classified as a potential biological warfare agent. The interaction between host and pathogen behind the successful establishment of F. tularensis infection within the human host is largely unknown. In our present work, we have studied the molecular level interactions between the host cellular components and F. tularensis genes to understand the interplay between the host and pathogen. Interestingly, we have identified the pathways associated with the pathogen offensive strategies that help in invasion of host defensive systems. The F. tularensis genes purL, katG, proS, rpoB and fusA have displayed high number of interactions with the host genes and thus play a crucial role in vital pathogen pathways. The pathways identified were involved in adaptation to different stress conditions within the host and might be crucial for designing new therapeutic interventions against tularemia.

Datasets comprising the quality validations of simulated protein-ligand complexes and SYBYL docking scores of bioactive natural compounds as inhibitors of Mycobacterium tuberculosis protein-targets.

Docking scores and simulation parameters to study the potency of natural compounds against protein targets in Mycobacterium tuberculosis (Mtb) were retrieved through molecular docking and in-silico structural investigation. The molecular docking datasets comprised 15 natural compounds, seven conventional anti-tuberculosis (anti-TB) drugs and their seven corresponding Mtb target proteins. Mtb protein targets were actively involved in translation mechanism, nucleic acid metabolism and membrane integrity. Standard structural screening and stereochemical optimizations were adopted to generate the 3D protein structures and their corresponding ligands prior to molecular docking. Force-field integration and energy minimization were further employed to obtain the proteins in their ideal geometry. Surflex-dock algorithm using Hammerhead scoring functions were used to finally produce the docking scores between each protein and the corresponding ligand(s). The best-docked complexes selected for simulation studies were subjected to topology adjustments, charge neutralizations, solvation and equilibrations (temperature, volume and pressure). The protein-ligand complexes and molecular dynamics parameter files have been provided. The trajectories of the simulated parameters such as density, pressure and temperature were generated with integrated tools of the simulation suite. The datasets can be useful to computational and molecular medicine researchers to find therapeutic leads relevant to the chemical behaviours of a specific class of compounds against biological systems. Structural parameters and energy functions provided a set of standard values that can be utilised to design simulation experiments regarding similar macromolecular interactions.

Gene interaction network to unravel the role of gut bacterial species in cardiovascular diseases: E. coli O157:H7 host-bacterial interaction study.

BACKGROUND: Cardiovascular Disease (CVD) is one of the most common causes of mortality in humans. Presently, the role of pathogens in the initiation and progression of the CVDs is not clearly understood. Hence, it is essential to understand the molecular-level interactions between the human proteins and the microbial proteins to deduce their functional roles in the CVDs. METHOD: The host-pathogen interactions (HPI) related to CVDs in the case of E. coli str. O157:H7 colonization were curated, and also the protein-protein interactions (PPI) between humans and E. coli were collected. Gene interaction network (GIN) and functional enrichment analyses (FEA) were utilized for this. RESULTS: The GIN revealed dense interactions between the functional partners. The FEA indicated that the essential pathways played a significant role in humans as well as in E. coli. The primary responses against most of the bacterial pathogens in humans are different from that of E. coli; Terpenoid biosynthesis and production of secondary metabolite pathways aid the survival of the E. coli inside the host. Interestingly, network analysis divulged that the E. coli genes ksgA, rpsT, ispE, rpsI, ispH, and the human genes TP53, CASP3, CYCS, EP300, RHOA communicated by significant numbers in direct interactions. CONCLUSIONS: The results obtained from the present study will help researchers understand the molecular-level interactions in the CVDs between the human and the E. coli genes. The important genes with vital interactions can be considered as hub molecules and can be exploited for new drug discovery.

Role of SHV-11, a Class A ß-Lactamase, Gene in Multidrug Resistance Among Klebsiella pneumoniae Strains and Understanding Its Mechanism by Gene Network Analysis.

Aim: The rapid emergence of ß-lactam resistance in gram-negative bacteria is a major problem in the treatment of infections caused by pathogenic bacterial strains, in particular Klebsiella pneumoniae. In our study, we are presenting a systems biology approach to understand the role of SHV-11 gene in drug resistance mechanism patterns in K. pneumoniae strain. Results: From the results, we have observed that the SHV-11 gene has a role in drug resistance mechanism along with its functional partner genes gyrA, parC, glsA, osmE, yjhA, yhdT, rimL, pepB, KPN_00437, and KPN_01875. We have also observed that of 51 genes, 27 genes were enriched in various Gene Ontology terms such as DNA metabolic process, DNA repair, and response to stress. The genes gyrA, parC, gyrB, parE, recA, dnaA, polB, dnaK, mutS, and dnaN constitute >41% of the total interactions; thus, these genes can be considered as hub nodes in the network, and they can be used as the potential drug targets. Conclusions: Drug exposure leads to the DNA damage in bacterial spp. We observed that the SHV11 gene along with the functional partners help in maintaining the genomic integrity by withstanding the environmental stress by inducing DNA damage repair mechanism. Our results provide a detailed understanding on the role of SHV-11 gene in drug resistance mechanisms in K. pneumoniae, and we are of the opinion that our results will be useful for researchers exploring the antibiotic resistance mechanisms in pathogenic bacteria.

Discerning molecular interactions: A comprehensive review on biomolecular interaction databases and network analysis tools.

Computational analysis of biomolecular interaction networks is now gaining a lot of importance to understand the functions of novel genes/proteins. Gene interaction (GI) network analysis and protein-protein interaction (PPI) network analysis play a major role in predicting the functionality of interacting genes or proteins and gives an insight into the functional relationships and evolutionary conservation of interactions among the genes. An interaction network is a graphical representation of gene/protein interactome, where each gene/protein is a node, and interaction between gene/protein is an edge. In this review, we discuss the popular open source databases that serve as data repositories to search and collect protein/gene interaction data, and also tools available for the generation of interaction network, visualization and network analysis. Also, various network analysis approaches like topological approach and clustering approach to study the network properties and functional enrichment server which illustrates the functions and pathway of the genes and proteins has been discussed. Hence the distinctive attribute mentioned in this review is not only to provide an overview of tools and web servers for gene and protein-protein interaction (PPI) network analysis but also to extract useful and meaningful information from the interaction networks.

System-wide coordinates of higher order functions in host-pathogen environment upon Mycobacterium tuberculosis infection.

Molecular signatures and their interactions behind the successful establishment of infection of Mycobacterium tuberculosis (Mtb) inside macrophage are largely unknown. In this work, we present an inter-system scale atlas of the gene expression signatures, their interactions and higher order gene functions of macrophage-Mtb environment at the time of infection. We have carried out large-scale meta-analysis of previously published gene expression microarray studies andhave identified a ranked list of differentially expressed genes and their higher order functions in intracellular Mtb as well as the infected macrophage. Comparative analysis of gene expression signatures of intracellular Mtb with the in vitro dormant Mtb at different hypoxic and oxidative stress conditions led to the identification of the large number of Mtb functional groups, namely operons, regulons and pathways that were common and unique to the intracellular environment and dormancy state. Some of the functions that are specific to intracellular Mtb are cholesterol degradation and biosynthesis of immunomodulatory phenolic compounds. The molecular signatures we have identified to be involved in adaptation to different stress conditions in macrophage environment may be critical for designing therapeutic interventions against tuberculosis. And, our approach may be broadly applicable for investigating other host-pathogen interactions.

Identification and functional analysis of essential, conserved, housekeeping and duplicated genes.

Gene conservation, duplication and constitutive expression are intricately linked and strong predictors of essentiality. Here, we introduce metrics based on diversity indices to measure gene conservation, duplication and constitutive expression and validate them by measuring their performance in prediction of essential genes. Conservation and duplication were measured using the diversity indices on the bit score profile of Escherichia coli K12 orthologues, across the genomes, and paralogues, within the genome respectively. Constitutive expression was measured using expression diversity of E. coli K12 genes across different conditions. In addition, we developed a systematic method for enrichment analysis of gene-sets in a given ranked list of genes. The method was used to identify genome-wide functions of essential, conserved, constitutively expressed and duplicated genes. Furthermore, we also ranked various operons, complexes and pathways according to their essentiality, conservation, constitutive expression and duplication.