Genomic analysis unveils genome degradation events and gene flux in the emergence and persistence of S. Paratyphi A lineages.

Paratyphoid fever caused by S. Paratyphi A is endemic in parts of South Asia and Southeast Asia. The proportion of enteric fever cases caused by S. Paratyphi A has substantially increased, yet only limited data is available on the population structure and genetic diversity of this serovar. We examined the phylogenetic distribution and evolutionary trajectory of S. Paratyphi A isolates collected as part of the Indian enteric fever surveillance study "Surveillance of Enteric Fever in India (SEFI)." In the study period (2017-2020), S. Paratyphi A comprised 17.6% (441/2503) of total enteric fever cases in India, with the isolates highly susceptible to all the major antibiotics used for treatment except fluoroquinolones. Phylogenetic analysis clustered the global S. Paratyphi A collection into seven lineages (A-G), and the present study isolates were distributed in lineages A, C and F. Our analysis highlights that the genome degradation events and gene acquisitions or losses are key molecular events in the evolution of new S. Paratyphi A lineages/sub-lineages. A total of 10 hypothetically disrupted coding sequences (HDCS) or pseudogenes-forming mutations possibly associated with the emergence of lineages were identified. The pan-genome analysis identified the insertion of P2/PSP3 phage and acquisition of IncX1 plasmid during the selection in 2.3.2/2.3.3 and 1.2.2 genotypes, respectively. We have identified six characteristic missense mutations associated with lipopolysaccharide (LPS) biosynthesis genes of S. Paratyphi A, however, these mutations confer only a low structural impact and possibly have minimal impact on vaccine effectiveness. Since S. Paratyphi A is human-restricted, high levels of genetic drift are not expected unless these bacteria transmit to naive hosts. However, public-health investigation and monitoring by means of genomic surveillance would be constantly needed to avoid S. Paratyphi A serovar becoming a public health threat similar to the S. Typhi of today.

Gene network interaction analysis to elucidate the antimicrobial resistance mechanisms in the Clostridiumdifficile.

Antimicrobial resistance has caused chaos worldwide due to the depiction of multidrug-resistant (MDR) infective microorganisms. A thorough examination of antimicrobial resistance (AMR) genes and associated resistant mechanisms is vital to solving this problem. Clostridium difficile (C. difficile) is an opportunistic nosocomial bacterial strain that has acquired exogenous AMR genes that confer resistance to antimicrobials such as erythromycin, azithromycin, clarithromycin, rifampicin, moxifloxacin, fluoroquinolones, vancomycin, and others. A network of interactions, including 20 AMR genes, was created and analyzed. In functional enrichment analysis, Cellular components (CC), Molecular Functions (MF), and Biological Processes (BP) were discovered to have substantial involvement. Mutations in the rpl genes, which encode ribosomal proteins, confer resistance in Gram-positive bacteria. Full erythromycin and azithromycin cross-resistance can be conferred if more than one of the abovementioned genes is present. In the enriched BP, rps genes related to transcriptional regulation and biosynthesis were found. The genes belong to the rpoB gene family, which has previously been related to rifampicin resistance. The genes rpoB, gyrA, gyrB, rpoS, rpl genes, rps genes, and Van genes are thought to be the hub genes implicated in resistance in C. difficile. As a result, new medications could be developed using these genes. Overall, our observations provide a thorough understanding of C. difficile AMR mechanisms.

An integrated gene network analysis to decode the multi-drug resistance mechanism in Klebsiella pneumoniae.

Antimicrobial resistance (AMR) among microorganisms has become one of the worldwide concerns of this century and continues to challenge us. To properly understand this problem, it is essential to know the genes that cause AMR and their resistance mechanisms. Our present study focused on Klebsiella pneumoniae, which possesses AMR genes conferring resistance against multiple antibiotics. A gene interaction network of 42 functional partners was constructed and analyzed to broaden our understanding. Three closely related clusters (C1-C3) having an association with multi-drug resistance mechanisms were identified by clustering analysis. The enrichment analysis illustrated 30 genes in biological processes, 24 genes in molecular function, and 25 genes in cellular components having a significant role. The analysis of the gene interaction network revealed genes birA2, folP, pabC, folA, gyrB, glmM, gyrA, thyA_2 had maximum no. of interactions with their functional partners viz. 26, 25, 25, 24, 23, 23, 23, 23 respectively and can be considered as hub genes. Analyzing the enriched pathways and Gene Ontologies provides insight into AMR's molecular basis. In addition, the proposed study could aid the researchers in developing new treatment options to combat multi-drug resistant K. pneumoniae.

Salmonella Typhi acquires diverse plasmids from other Enterobacteriaceae to develop cephalosporin resistance.

BACKGROUND: Recent reports have established the emergence and dissemination of extensively drug resistant (XDR) H58 Salmonella Typhi clone in Pakistan. In India where typhoid fever is endemic, only sporadic cases of ceftriaxone resistant S. Typhi are reported. This study aimed at elucidating the phylogenetic evolutionary framework of ceftriaxone resistant S. Typhi isolates from India to predict their potential dissemination. METHODS: Five ceftriaxone resistant S. Typhi isolates from three tertiary care hospitals in India were sequenced on an Ion Torrent Personal Genome Machine (PGM). A core genome single-nucleotide-polymorphism (SNP) based phylogeny of the isolates in comparison to the global collection of MDR and XDR S. Typhi isolates was built. Two of five isolates were additionally sequenced using Oxford Nanopore MinION to completely characterize the plasmid and understand its transmission dynamics within Enterobacteriaceae. RESULTS: Comparative genomic analysis and detailed plasmid characterization indicate that while in Pakistan (4.3.1 lineage I) the XDR trait is associated with blaCTX-M-15 gene on IncY plasmid, in India (4.3.1 lineage II), the ceftriaxone resistance is due to short term persistence of resistance plasmids such as IncX3 (blaSHV-12) or IncN (blaTEM-1B + blaDHA-1). CONCLUSION: Considering the selection pressure exerted by the extensive use of ceftriaxone in India, there are potential risks for the occurrence of plasmid transmission events in the predominant H58 lineages. Therefore, continuous monitoring of S. Typhi lineages carrying plasmid-mediated cephalosporin resistant genes is vital not just for India but also globally.

Comparative genomics of invasive Streptococcus pneumoniae CC320/271 serotype 19F/19A before the introduction of pneumococcal vaccine in India.

The emergence of multi drug resistant clone CC320 serotype19F/19A and their capsular (cps) antigenic variants due to selective pressures such as vaccine had been reported worldwide. Hence, it is important to identify the prevalent clones, sequence types and cps variants of serotype 19F/19A in India, where PCV13 has been recently introduced. Multi-locus sequence typing (MLST) was performed for all (n = 21) invasive S. pneumoniae isolates of serotype 19A (n = 5) and 19F (n = 16) collected between the years 2012 and 2018 from children less than 5 years. The genome characterization by whole genome sequencing for the Sequence types (STs) 320 and 271(n = 7) were performed and compared with another six Indian WGSs of similar STs available from the GPS platform. The predominant STs in the serotype 19F/19A study isolates were of CC320: ST 320, 236 and 271, associated with PMEN clone Taiwan19F-14. The WGSs of CC320 study isolates showed high genomic similarity to the Taiwan19F-14 clone, and the penicillin binding protein (PBP) amino acid sequence similarity was 100% for PBP1A, 93% for PBP 2B and 2X. Whilst PBP comparison with other global MDR ST320 strains revealed that the ST320 clones in India are of low-level penicillin resistance. The presence of a few ST320/19A/19F invasive isolates with high similarity to the Taiwan clone suggests slow and gradual expansion of Taiwan19F-14 associated CC320 clones in India. Since serotype 19F/19A is covered by PCV13 vaccine, the expansion of 19F/19A cones with non-PCV13 vaccine serotype in India should be monitored.

Highly accurate-single chromosomal complete genomes using IonTorrent and MinION sequencing of clinical pathogens.

Oxford Nanopore MinION sequencing technology has been gaining immense importance in identification of pathogen and antimicrobial resistance, though with 10-15% error rate. Short read technologies generates high accurate genome but with multiple fragments of genome. This study proposes a novel workflow to reduce the indels resulted from MinION long read sequencing by overlaying short read sequences from IonTorrent in the clinical isolates. Best of both techniques were employed which generated highly accurate-single chromosomal microbial genomes with increase in completeness of genomes from 44.5%, 30% and 43% to 98.6%, 98.6% and 96.6% for P. aeruginosa, A. veronii and B. pertussis respectively. To the best of our knowledge, this is the first study to generate a hybrid of IonTorrent and MinION reads to obtain single chromosomal genomes. This would enable to precisely infer both structural arrangement of genes and SNP based analysis for phylogenetic information.

Unraveling the molecular landscape of Ataxia Telangiectasia: Insights into Neuroinflammation, immune dysfunction, and potential therapeutic target.

BACKGROUND: Ataxia Telangiectasia (AT) is a genetic disorder characterized by compromised DNA repair, cerebellar degeneration, and immune dysfunction. Understanding the molecular mechanisms driving AT pathology is crucial for developing targeted therapies. METHODS: In this study, we conducted a comprehensive analysis to elucidate the molecular mechanisms underlying AT pathology. Using publicly available RNA-seq datasets comparing control and AT samples, we employed in silico transcriptomics to identify potential genes and pathways. We performed differential gene expression analysis with DESeq2 to reveal dysregulated genes associated with AT. Additionally, we constructed a Protein-Protein Interaction (PPI) network to explore the interactions between proteins implicated in AT. RESULTS: The network analysis identified hub genes, including TYROBP and PCP2, crucial in immune regulation and cerebellar function, respectively. Furthermore, pathway enrichment analysis unveiled dysregulated pathways linked to AT pathology, providing insights into disease progression. CONCLUSION: Our integrated approach offers a holistic understanding of the complex molecular landscape of AT and identifies potential targets for therapeutic intervention. By combining transcriptomic analysis with network-based methods, we provide valuable insights into the underlying mechanisms of AT pathogenesis.

Exploring the role of estrogen and progestins in breast cancer: A genomic approach to diagnosis.

Breast cancer (BC) is the most common cancer among women and a major cause of death from cancer. The role of estrogen and progestins, including synthetic hormones like R5020, in the development of BC has been highlighted in numerous studies. In our study, we employed machine learning and advanced bioinformatics to identify genes that could serve as diagnostic markers for BC. We thoroughly analyzed the transcriptomic data of two BC cell lines, T47D and UDC4, and performed differential gene expression analysis. We also conducted functional enrichment analysis to understand the biological functions influenced by these genes. Our study identified several diagnostic genes strongly associated with BC, including MIR6728, ENO1-IT1, ENO1-AS1, RNU6-304P, HMGN2P17, RP3-477M7.5, RP3-477M7.6, and CA6. The genes MIR6728, ENO1-IT1, ENO1-AS1, and HMGN2P17 are involved in cancer control, glycolysis, and DNA-related processes, while CA6 is associated with apoptosis and cancer development. These genes could potentially serve as predictors for BC, paving the way for more precise diagnostic methods and personalized treatment plans. This research enhances our understanding of BC and offers promising avenues for improving patient care in the future.

Aspartame Causes Developmental Defects and Teratogenicity in Zebra Fish Embryo: Role of Impaired SIRT1/FOXO3a Axis in Neuron Cells.

Aspartame, a widely used artificial sweetener, is present in many food products and beverages worldwide. It has been linked to potential neurotoxicity and developmental defects. However, its teratogenic effect on embryonic development and the underlying potential mechanisms need to be elucidated. We investigated the concentration- and time-dependent effects of aspartame on zebrafish development and teratogenicity. We focused on the role of sirtuin 1 (SIRT1) and Forkhead-box transcription factor (FOXO), two proteins that play key roles in neurodevelopment. It was found that aspartame exposure reduced the formation of larvae and the development of cartilage in zebrafish. It also delayed post-fertilization development by altering the head length and locomotor behavior of zebrafish. RNA-sequencing-based DEG analysis showed that SIRT1 and FOXO3a are involved in neurodevelopment. In silico and in vitro analyses showed that aspartame could target and reduce the expression of SIRT1 and FOXO3a proteins in neuron cells. Additionally, aspartame triggered the reduction of autophagy flux by inhibiting the nuclear translocation of SIRT1 in neuronal cells. The findings suggest that aspartame can cause developmental defects and teratogenicity in zebrafish embryos and reduce autophagy by impairing the SIRT1/FOXO3a axis in neuron cells.

Rational design of a multivalent vaccine targeting arthropod-borne viruses using reverse vaccinology strategies.

Viruses transmitted by arthropods, such as Dengue, Zika, and Chikungunya, represent substantial worldwide health threats, particularly in countries like India. The lack of approved vaccines and effective antiviral therapies calls for developing innovative strategies to tackle these arboviruses. In this study, we employed immunoinformatics methodologies, incorporating reverse vaccinology, to design a multivalent vaccine targeting the predominant arboviruses. Epitopes of B and T cells were recognized within the non-structural proteins of Dengue, Zika, and Chikungunya viruses. The predicted epitopes were enhanced with adjuvants ß-defensin and RS-09 to boost the vaccine's immunogenicity. Sixteen distinct vaccine candidates were constructed, each incorporating epitopes from all three viruses. FUVAC-11 emerged as the most promising vaccine candidate through molecular docking and molecular dynamics simulations, demonstrating favorable binding interactions and stability. Its effectiveness was further evaluated using computational immunological studies confirming strong immune responses. The in silico cloning performed using the pET-28a(+) plasmid facilitates the future experimental implementation of this vaccine candidate, paving the way for potential advancements in combating these significant arboviral threats. However, further in vitro and in vivo studies are warranted to confirm the results obtained in this computational study, which highlights the effectiveness of immunoinformatics and reverse vaccinology in creating vaccines against major Arboviruses, offering a promising model for developing vaccines for other vector-borne diseases and enhancing global health security.

Exploring the effect of disease causing mutations in metal binding sites of human ARSA in metachromatic leukodystrophy.

The arylsulfatase A (ARSA) gene is observed to be deficient in patients with metachromatic leukodystrophy (MLD), a type of lysosomal storage disease. MLD is a severe neurodegenerative disorder characterized by an autosomal recessive inheritance pattern. This study aimed to map the most deleterious mutations at the metal binding sites of ARSA and the amino acids in proximity to the mutated positions. We utilized an array of computational tools, including PredictSNP, MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT, SNAP, and ConSurf, to identify the most detrimental mutations potentially implicated in MLD collected from UniProt, ClinVar, and HGMD. Two mutations, D29N and D30H, as being extremely deleterious based on assessments of pathogenicity, conservation, biophysical characteristics, and stability analysis. The D29 and D30 are located at the metal-interacting regions of ARSA and found to undergo post-translational modification, specifically phosphorylation. Henceforth, the in-depth effect of metal binding upon mutation was examined using molecular dynamics simulations (MDS) before and after phosphorylation. The MDS results exhibited high deviation for the D29N and D30H mutations in comparison to the native, and the same was confirmed by significant residue fluctuation and reduced compactness. These structural alterations suggest that such mutations may influence protein functionality, offering potential avenues for personalized therapeutic and providing a basis for potential mutation-specific treatments for severe MLD patients.

Transcriptomic analysis reveals zinc-mediated virulence and pathogenicity in multidrug-resistant Acinetobacter baumannii.

Acinetobacter baumannii is a gram-negative bacterium well known for its multidrug resistance and connection to nosocomial infections under ESKAPE pathogens. This opportunistic pathogen is ubiquitously associated with nosocomial infections, posing significant threats within healthcare environments. Its critical clinical symptoms, namely, meningitis, urinary tract infections, bloodstream infections, ventilator-associated pneumonia, and pneumonia, catalyze the imperative demand for innovative therapeutic interventions. The proposed research focuses on delineating the role of Zinc, a crucial metallo-binding protein and micronutrient integral to bacterial metabolism and virulence, to enhance understanding of the pathogenicity of A. baumannii. RNA sequencing and subsequent DESeq2 analytical methods were used to identify differential gene expressions influenced by zinc exposure. Exploiting the STRING database for functional enrichment analysis has demonstrated the complex molecular mechanisms underlying the enhancement of pathogenicity prompted by Zinc. Moreover, hub genes like gltB, ribD, AIL77834.1, sdhB, nuoI, acsA_1, acoC, accA, accD were predicted using the cytohubba tool in Cytoscape. This investigation underscores the pivotal role of Zinc in the virulence of A. baumannii elucidates the underlying molecular pathways responsible for its pathogenicity. The research further accentuates the need for innovative therapeutic strategies to combat A. baumannii infections, particularly those induced by multidrug-resistant strains.

Genomic investigation unveils colistin resistance mechanism in carbapenem-resistant Acinetobacter baumannii clinical isolates.

Colistin resistance in Acinetobacter baumannii is mediated by multiple mechanisms. Recently, mutations within pmrABC two-component system and overexpression of eptA gene due to upstream insertion of ISAba1 have been shown to play a major role. Thus, the aim of our study is to characterize colistin resistance mechanisms among the clinical isolates of A. baumannii in India. A total of 207 clinical isolates of A. baumannii collected from 2016 to 2019 were included in this study. Mutations within lipid A biosynthesis and pmrABC genes were characterized by whole-genome shotgun sequencing. Twenty-eight complete genomes were further characterized by hybrid assembly approach to study insertional inactivation of lpx genes and the association of ISAba1-eptA. Several single point mutations (SNPs), like M12I in pmrA, A138T and A444V in pmrB, and E117K in lpxD, were identified. We are the first to report two novel SNPs (T7I and V383I) in the pmrC gene. Among the five colistin-resistant A. baumannii isolates where complete genome was available, the analysis showed that three of the five isolates had ISAba1 insertion upstream of eptA. No mcr genes were identified among the isolates. We mapped the SNPs on the respective protein structures to understand the effect on the protein activity. We found that majority of the SNPs had little effect on the putative protein function; however, some SNPs might destabilize the local structure. Our study highlights the diversity of colistin resistance mechanisms occurring in A. baumannii, and ISAba1-driven eptA overexpression is responsible for colistin resistance among the Indian isolates.IMPORTANCEAcinetobacter baumannii is a Gram-negative, emerging and opportunistic bacterial pathogen that is often associated with a wide range of nosocomial infections. The treatment of these infections is hindered by increase in the occurrence of A. baumannii strains that are resistant to most of the existing antibiotics. The current drug of choice to treat the infection caused by A. baumannii is colistin, but unfortunately, the bacteria started to show resistance to the last-resort antibiotic. The loss of lipopolysaccharides and mutations in lipid A biosynthesis genes are the main reasons for the colistin resistance. The present study characterized 207 A. baumannii clinical isolates and constructed complete genomes of 28 isolates to recognize the mechanisms of colistin resistance. We showed the mutations in the colistin-resistant variants within genes essential for lipid A biosynthesis and that cause these isolates to lose the ability to produce lipopolysaccharides.

Advancements and hurdles in the development of a vaccine for triple-negative breast cancer: A comprehensive review of multi-omics and immunomics strategies.

Triple-Negative Breast Cancer (TNBC) presents a significant challenge in oncology due to its aggressive behavior and limited therapeutic options. This review explores the potential of immunotherapy, particularly vaccine-based approaches, in addressing TNBC. It delves into the role of immunoinformatics in creating effective vaccines against TNBC. The review first underscores the distinct attributes of TNBC and the importance of tumor antigens in vaccine development. It then elaborates on antigen detection techniques such as exome sequencing, HLA typing, and RNA sequencing, which are instrumental in identifying TNBC-specific antigens and selecting vaccine candidates. The discussion then shifts to the in-silico vaccine development process, encompassing antigen selection, epitope prediction, and rational vaccine design. This process merges computational simulations with immunological insights. The role of Artificial Intelligence (AI) in expediting the prediction of antigens and epitopes is also emphasized. The review concludes by encapsulating how Immunoinformatics can augment the design of TNBC vaccines, integrating tumor antigens, advanced detection methods, in-silico strategies, and AI-driven insights to advance TNBC immunotherapy. This could potentially pave the way for more targeted and efficacious treatments.

Molecular engineering of a theranostic molecule that detects Aß plaques, inhibits Iowa and Dutch mutation Aß self-aggregation and promotes lysosomal biogenesis for Alzheimer's disease.

Extracellular clustering of amyloid-ß (Aß) and an impaired autophagy lysosomal pathway (ALP) are the hallmark features in the early stages of incurable Alzheimer's disease (AD). There is a pressing need to find or develop new small molecules for diagnostics and therapeutics for the early stages of AD. Herein, we report a small molecule, namely F-SLCOOH, which can bind and detect Aß1-42, Iowa mutation Aß, Dutch mutation Aß fibrils and oligomers exhibiting enhanced emission with high affinity. Importantly, F-SLCOOH can readily pass through the blood-brain barrier and shows highly selective binding toward the extracellular Aß aggregates in real-time in live animal imaging of a 5XFAD mice model. In addition, a high concentration of F-SLCOOH in both brain and plasma of wildtype mice after intraperitoneal administration was found. The ex vivo confocal imaging of hippocampal brain slices indicated excellent colocalization of F-SLCOOH with Aß positive NU1, 4G8, 6E10 A11 antibodies and THS staining dye, affirming its excellent Aß specificity and targetability. The molecular docking studies have provided insight into the unique and specific binding of F-SLCOOH with various Aß species. Importantly, F-SLCOOH exhibits remarkable anti-fibrillation properties against toxic Aß aggregate formation of Aß1-42, Iowa mutation Aß, and Dutch mutation Aß. F-SLCOOH treatment also exerts high neuroprotective functions and promotes autophagy lysosomal biogenesis in neuronal AD cell models. In summary, the present results suggest that F-SLCOOH is a highly promising theranostic agent for diagnosis and therapeutics of AD.

Identification of key biomarkers and associated pathways of pancreatic cancer using integrated transcriptomic and gene network analysis.

Pancreatic cancer shows malignancy around the world standing in 4th position for causing death globally. This cancer is majorly divided into exocrine and neuroendocrine where exocrine pancreatic ductal adenocarcinoma is observed to be nearly 85% of cases. The lack of diagnosis of pancreatic cancer is considered to be one of the major drawbacks to the prognosis and treatment of pancreatic cancer patients. The survival rate after diagnosis is very low, due to the higher incidence of drug resistance to cancer which leads to an increase in the mortality rate. The transcriptome analysis for pancreatic cancer involves dataset collection from the ENA database, incorporating them into quality control analysis to the quantification process to get the summarized read counts present in collected samples and used for further differential gene expression analysis using the DESeq2 package. Additionally, explore the enriched pathways using GSEA software and represented them by utilizing the enrichment map finally, the gene network has been constructed by Cytoscape software. Furthermore, explored the hub genes that are present in the particular pathways and how they are interconnected from one pathway to another has been analyzed. Finally, we identified the CDKN1A, IL6, and MYC genes and their associated pathways can be better biomarker for the clinical processes to increase the survival rate of of pancreatic cancer.

Structure-based virtual screening to identify potential lipase inhibitors to reduce lipid storage in Wolman disorder.

Wolman disorder (WD) was first described in Iranian-Jewish (IJ) children, and it is caused by a deficiency of the lysosomal acid lipase (LAL). Newborns with WD are healthy and active at birth but soon develop severe malnutrition symptoms and often die before 1 year. In particular, spleens, livers, bone marrows, intestines, adrenal glands, and lymph nodes accumulate harmful amounts of lipids. G87V mutation in LIPA is responsible for Wolman disorder. Some reports suggest that δ-tocopherol can reduce lipid accumulation in cholesterol storage disorders. Hence, we used δ-tocopherol for the virtual screening process in this study. Initially, the lead compounds were docked with native and G87V mutant LIPA. Subsequently, the ADME and toxicity parameters for screened compounds were determined to ensure the safety profiles. Finally, the molecular dynamics simulations result indicated that dl-alpha-Tocopherol-13C3, a molecule obtained from the PubChem database, is identified as a potential and stable lead molecule that could be effective against the G87V mutant form of LIPA.

Elucidating the mechanism of antimicrobial resistance in Mycobacterium tuberculosis using gene interaction networks.

Antimicrobial resistance (AMR) in microorganisms is an urgent global health threat. AMR of Mycobacterium tuberculosis is associated with significant morbidity and mortality. It is of great importance to underpin the resistance pathways involved in the mechanisms of AMR and identify the genes that are directly involved in AMR. The focus of the current study was the bacteria M. tuberculosis, which carries AMR genes that give resistance that lead to multidrug resistance. We, therefore, built a network of 43 genes and examined for potential gene-gene interactions. Then we performed a clustering analysis and identified three closely related clusters that could be involved in multidrug resistance mechanisms. Through the bioinformatics pipeline, we consistently identified six-hub genes (dnaN, polA, ftsZ, alr, ftsQ, and murC) that demonstrated the highest number of interactions within the clustering analysis. This study sheds light on the multidrug resistance of MTB and provides a protocol for discovering genes that might be involved in multidrug resistance, which will improve the treatment of resistant strains of TB.

Integrated gene network analysis sheds light on understanding the progression of Osteosarcoma.

Introduction: Osteosarcoma is a rare disorder among cancer, but the most frequently occurring among sarcomas in children and adolescents. It has been reported to possess the relapsing capability as well as accompanying collateral adverse effects which hinder the development process of an effective treatment plan. Using networks of omics data to identify cancer biomarkers could revolutionize the field in understanding the cancer. Cancer biomarkers and the molecular mechanisms behind it can both be understood by studying the biological networks underpinning the etiology of the disease. Methods: In our study, we aimed to highlight the hub genes involved in gene-gene interaction network to understand their interaction and how they affect the various biological processes and signaling pathways involved in Osteosarcoma. Gene interaction network provides a comprehensive overview of functional gene analysis by providing insight into how genes cooperatively interact to elicit a response. Because gene interaction networks serve as a nexus to many biological problems, their employment of it to identify the hub genes that can serve as potential biomarkers remain widely unexplored. A dynamic framework provides a clear understanding of biological complexity and a pathway from the gene level to interaction networks. Results: Our study revealed various hub genes viz. TP53, CCND1, CDK4, STAT3, and VEGFA by analyzing various topological parameters of the network, such as highest number of interactions, average shortest path length, high cluster density, etc. Their involvement in key signaling pathways, such as the FOXM1 transcription factor network, FAK-mediated signaling events, and the ATM pathway, makes them significant candidates for studying the disease. The study also highlighted significant enrichment in GO terms (Biological Processes, Molecular Function, and Cellular Processes), such as cell cycle signal transduction, cell communication, kinase binding, transcription factor activity, nucleoplasm, PML body, nuclear body, etc. Conclusion: To develop better therapeutics, a specific approach toward the disease targeting the hub genes involved in various signaling pathways must have opted to unravel the complexity of the disease. Our study has highlighted the candidate hub genes viz. TP53, CCND1 CDK4, STAT3, VEGFA. Their involvement in the major signaling pathways of Osteosarcoma makes them potential candidates to be targeted for drug development. The highly enriched signaling pathways include FOXM1 transcription pathway, ATM signal-ling pathway, FAK mediated signaling events, Arf6 signaling events, mTOR signaling pathway, and Integrin family cell surface interactions. Targeting the hub genes and their associated functional partners which we have reported in our studies may be efficacious in developing novel therapeutic targets.