Neutrophil Extracellular Traps in Colorectal Cancer Progression and Metastasis.

Neutrophils form sticky web-like structures known as neutrophil extracellular traps (NETs) as part of innate immune response. NETs are decondensed extracellular chromatin filaments comprising nuclear and cytoplasmic proteins. NETs have been implicated in many gastrointestinal diseases including colorectal cancer (CRC). However, the regulatory mechanisms of NET formation and potential pharmacological inhibitors in the context of CRC have not been thoroughly discussed. In this review, we intend to highlight roles of NETs in CRC progression and metastasis as well as the potential of targeting NETs during colon cancer therapy.

Immunoinformatics approaches to explore B and T cell epitope-based vaccine designing for SARS-CoV-2 Virus.

SARS-CoV-2, a new world coronavirus belonging to class Nidovirales of Coronaviridae family causes COVID-19 infection which is the leading cause of death worldwide. Currently there are no approved drugs and vaccines available for the prevention of COVID-19 infection, although couples of immunizations are being tested in clinical trials. However, the present efforts are focused on computational vaccination technique for evaluating candidates to design multi-epitope-based vaccine against pathogenic mechanism of novel SARS-COV-2. Based on recent published evidence, we recognized spike glycoprotein and envelope small membrane protein are the potential targets to combat the pathogenic mechanism of SARS-CoV-2. Similarly, in the present study we identified epitope of both B and T cell associated with these proteins. Extremely antigenic, conserve, immunogenic and nontoxic epitope of B and T cell of Spike protein are WPWYVWLGFI, SRVKNLNSSEGVPDLLV whereas the CWCARPTCIK and YCCNIVNVSL are associated with envelope small membrane protein were selected as potential candidate for vaccine designing. These epitopes show virtuous interaction with HLAA0201 during molecular docking analysis. Under simulation protocol the predicted vaccine candidates show stability. Collectively, this work provides novel potential candidates for epitope-based vaccine designing against COVID-19 infection.

Genome wide association study and phylogenetic analysis of novel SARS-COV-2 virus among different countries.

Corona Virus (COVID-19) outbreak has threatened the world, since it has become pandemic and spread all over the world. The causative agent SARS-COV2 has proved lethal caused serious public health concern worldwide. Our aims were to describe the SARS-COV-2 genetic connections and check for recombination of all genome. The recombination was investigated by RDP5 and conflicting phylogenetic clustering in individual genomic fragments was established by phylogenetic study by maximum likelihood and Bayesian methods. Our analysis suggests that the available sequences from currently genomes of various strain were retrieved from different countries including Japan, French Republic, Spain, Peru, China, Vietnam, Taiwan, Brazil, U.S.A., South Korea, Sweden, Australia, Nepal, India, Iran, and Italy. The phylogeny of SARS-COV-2 observed the largest number of genome is Vietnam 29891-bp, while France is the smallest member identified with 29679-bp. Using Recombination Detection program5 (RDP5) the china strains was taken as parental strain but there were no recombination in the all strains. In our study we identified the mutation in Pakistani strains in high conserved region of Corona nucleoca super family domain at the nucleotide position (394: C replace with T, Position: 858: C replace with T and Position: 997 G replace A).

Model organism life extending therapeutics modulate diverse nodes in the drug-gene-microbe tripartite human longevity interactome.

Advances in antiaging drug/lead discovery in animal models constitute a large body of literature on novel senotherapeutics and geroprotectives. However, with little direct evidence or mechanism of action in humans-these drugs are utilized as nutraceuticals or repurposed supplements without proper testing directions, appropriate biomarkers, or consistent in-vivo models. In this study, we take previously identified drug candidates that have significant evidence of prolonging lifespan and promoting healthy aging in model organisms, and simulate them in human metabolic interactome networks. Screening for drug-likeness, toxicity, and KEGG network correlation scores, we generated a library of 285 safe and bioavailable compounds. We interrogated this library to present computational modeling-derived estimations of a tripartite interaction map of animal geroprotective compounds in the human molecular interactome extracted from longevity, senescence, and dietary restriction-associated genes. Our findings reflect previous studies in aging-associated metabolic disorders, and predict 25 best-connected drug interactors including Resveratrol, EGCG, Metformin, Trichostatin A, Caffeic Acid and Quercetin as direct modulators of lifespan and healthspan-associated pathways. We further clustered these compounds and the functionally enriched subnetworks therewith to identify longevity-exclusive, senescence-exclusive, pseudo-omniregulators and omniregulators within the set of interactome hub genes. Additionally, serum markers for drug-interactions, and interactions with potentially geroprotective gut microbial species distinguish the current study and present a holistic depiction of optimum gut microbial alteration by candidate drugs. These findings provide a systems level model of animal life-extending therapeutics in human systems, and act as precursors for expediting the ongoing global effort to find effective antiaging pharmacological interventions.Communicated by Ramaswamy H. Sarma.

A Comprehensive Bioinformatics Approach to Identify Molecular Signatures and Key Pathways for the Huntington Disease.

Huntington disease (HD) is a degenerative brain disease caused by the expansion of CAG (cytosine-adenine-guanine) repeats, which is inherited as a dominant trait and progressively worsens over time possessing threat. Although HD is monogenetic, the specific pathophysiology and biomarkers are yet unknown specifically, also, complex to diagnose at an early stage, and identification is restricted in accuracy and precision. This study combined bioinformatics analysis and network-based system biology approaches to discover the biomarker, pathways, and drug targets related to molecular mechanism of HD etiology. The gene expression profile data sets GSE64810 and GSE95343 were analyzed to predict the molecular markers in HD where 162 mutual differentially expressed genes (DEGs) were detected. Ten hub genes among them (DUSP1, NKX2-5, GLI1, KLF4, SCNN1B, NPHS1, SGK2, PITX2, S100A4, and MSX1) were identified from protein-protein interaction (PPI) network which were mostly expressed as down-regulated. Following that, transcription factors (TFs)-DEGs interactions (FOXC1, GATA2, etc), TF-microRNA (miRNA) interactions (hsa-miR-340, hsa-miR-34a, etc), protein-drug interactions, and disorders associated with DEGs were predicted. Furthermore, we used gene set enrichment analysis (GSEA) to emphasize relevant gene ontology terms (eg, TF activity, sequence-specific DNA binding) linked to DEGs in HD. Disease interactions revealed the diseases that are linked to HD, and the prospective small drug molecules like cytarabine and arsenite was predicted against HD. This study reveals molecular biomarkers at the RNA and protein levels that may be beneficial to improve the understanding of molecular mechanisms, early diagnosis, as well as prospective pharmacologic targets for designing beneficial HD treatment.

Characterization and Structural Prediction of Proteins in SARS-CoV-2 Bangladeshi Variant Through Bioinformatics.

The renowned respiratory disease induced by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has become a global epidemic in just less than a year by the first half of 2020. The subsequent efficient human-to-human transmission of this virus eventually affected millions of people worldwide. The most devastating thing is that the infection rate is continuously uprising and resulting in significant mortality especially among the older age population and those with health co-morbidities. This enveloped, positive-sense RNA virus is chiefly responsible for the infection of the upper respiratory system. The virulence of the SARS-CoV-2 is mostly regulated by its proteins such as entry to the host cell through fusion mechanism, fusion of infected cells with neighboring uninfected cells to spread virus, inhibition of host gene expression, cellular differentiation, apoptosis, mitochondrial biogenesis, etc. But very little is known about the protein structures and functionalities. Therefore, the main purpose of this study is to learn more about these proteins through bioinformatics approaches. In this study, ORF10, ORF7b, ORF7a, ORF6, membrane glycoprotein, and envelope protein have been selected from a Bangladeshi Corona-virus strain G039392 and a number of bioinformatics tools (MEGA-X-V10.1.7, PONDR, ProtScale, ProtParam, SCRIBER, NetSurfP v2.0, IntFOLD, UCSF Chimera, and PyMol) and strategies were implemented for multiple sequence alignment and phylogeny analysis with 9 different variants, predicting hydropathicity, amino acid compositions, protein-binding propensity, protein disorders, and 2D and 3D protein modeling. Selected proteins were characterized as highly flexible, structurally and electrostatically extremely stable, ordered, biologically active, hydrophobic, and closely related to proteins of different variants. This detailed information regarding the characterization and structure of proteins of SARS-CoV-2 Bangladeshi variant was performed for the first time ever to unveil the deep mechanism behind the virulence features. And this robust appraisal also paves the future way for molecular docking, vaccine development targeting these characterized proteins.

Bioinformatics and network-based approaches for determining pathways, signature molecules, and drug substances connected to genetic basis of schizophrenia etiology.

Knowledge of heterogeneous etiology and pathophysiology of schizophrenia (SZP) is reasonably inadequate and non-deterministic due to its inherent complexity and underlying vast dynamics related to genetic mechanisms. The evolution of large-scale transcriptome-wide datasets and subsequent development of relevant, robust technologies for their analyses show promises toward elucidating the genetic basis of disease pathogenesis, its early risk prediction, and predicting drug molecule targets for therapeutic intervention. In this research, we have scrutinized the genetic basis of SZP through functional annotation and network-based system biology approaches. We have determined 96 overlapping differentially expressed genes (DEGs) from 2 microarray datasets and subsequently identified their interconnecting networks to reveal transcriptome signatures like hub proteins (FYN, RAD51, SOCS3, XIAP, AKAP13, PIK3C2A, CBX5, GATA3, EIF3K, and CDKN2B), transcription factors and miRNAs. In addition, we have employed gene set enrichment to highlight significant gene ontology (e.g., positive regulation of microglial cell activation) and relevant pathways (such as axon guidance and focal adhesion) interconnected to the genes associated with SZP. Finally, we have suggested candidate drug substances like Luteolin HL60 UP as a possible therapeutic target based on these key molecular signatures.

Bioinformatics and System Biology Techniques to Determine Biomolecular Signatures and Pathways of Prion Disorder.

Prion disorder (PD) is caused by misfolding and the formation of clumps of proteins in the brain, notably Prion proteins resulting in a steady decrease in brain function. Early detection of PD is difficult due to its unpredictable nature, and diagnosis is limited regarding specificity and sensitivity. Considering the uncertainties, the current study used network-based integrative system biology approaches to reveal promising molecular biomarkers and therapeutic targets for PD. In this study, brain transcriptomics gene expression microarray datasets (GSE160208 and GSE124571) of human PD were evaluated and 35 differentially expressed genes (DEGs) were identified. By employing network-based protein-protein interaction (PPI) analysis on these DEGs, 10 central hub proteins, including SPP1, FKBP5, HPRT1, CDKN1A, BAG3, HSPB1, SYK, TNFRSF1A, PTPN6, and CD44, were identified. Employing bioinformatics approaches, a variety of transcription factors (EGR1, SSRP1, POLR2A, TARDP, and NR2F1) and miRNAs (hsa-mir-8485, hsa-mir-148b-3p, hsa-mir-4295, hsa-mir-26b-5p, and hsa-mir-16-5p) were predicted. EGR1 was found as the most imperative transcription factor (TF), and hsa-mir-16-5p and hsa-mir-148b-3p were found as the most crucial miRNAs targeted in PD. Finally, resveratrol and hypochlorous acid were predicted as possible therapeutic drugs for PD. This study could be helpful in better understanding of molecular systems and prospective pharmacological targets for developing effective PD treatments.

Prognostic Value Estimation of BRIP1 in Breast Cancer by Exploiting Transcriptomics Data Through Bioinformatics Approaches.

BRIP1 (Breast Cancer 1 Interacting Helicase 1) is a tumor suppressor gene that has vital function in preserving the genetic stability by repairing DNA damage though have significant associations with the onset of breast cancer (BC) if mutated or overexpressed. In this study, the prognostic value of BRIP1 gene was evaluated and validated through bioinformatics approaches utilizing transcriptomic (mRNA expression) data from several BC databases. To determine the prognostic value, the expression level of mRNA transcript was analyzed in context of comparison between breast tumor and normal tissues regarding clinical features, breast tumor subtypes, promoter methylation status, correlation level, mutation frequency, and survival of BC patients. BRIP1 expression was found to be significantly overexpressed in various BC molecular subtypes (e.g. PAM50, Sorlie's) and clinical status (estrogen and progesterone receptor) than associated normal tissues which correlated with prognosis. Also, in promoter methylation level, its expression was observed as upregulated-hypomethylated regarding various clinicopathological features. Multiple data mining exhibited positive correlation between BRIP1 and INTS2 (Integrator Complex Subunit 2) expressions in BC. Further, mutation analysis revealed that BRIP1 gene was altered by acquiring both somatic and germline mutations. In addition, a total of 42 mutations; 24 missense, 8 fusion, 7 truncating, and 3 inframe mutations in BC patients was detected in BRIP1 protein. Moreover, higher BRIP1 expression was found to be correlated with poor disease-specific, disease metastasis-free, relapse-free, and overall survivals of BC patients. Since, overexpression of BRIP1 was identified to be associated with different clinical features, breast tumor subtypes, promoter methylation status, and survival of BC patients that may provide a risk of ensuing malignant transformation. Thus, lower expression of BRIP1 might hinder BC prognosis. We consider that this analysis will present a proof for BRIP1 gene to be a noteworthy molecular biomarker for BC prognosis.

Presence of blaCTX-M antibiotic resistance gene in Lactobacillus spp. isolated from Hirschsprung diseased infants with stoma.

INTRODUCTION: Although antibiotics have revolutionized health care by saving lives, the evolution of both pathogenic and commensal antibiotic-resistant bacteria are emerging as a threat in the health sector. As for Lactobacillus spp., it is usually a non-pathogenic bacteria. However, it can cause infection in immunocompromised condition. In this study, Lactobacillus spp. has been isolated from the faeces of infants with Hirschsprung disease (HD), which is congenital aganglionosis of intestine, where surgical approach and antibiotics are frequently used as medical intervention. The aim of this study is to assess the antibiotic resistance pattern and determine the presence of resistance genes, if any, in Lactobacillus spp. isolated from HD infants with ileostomy. METHODOLOGY: Six Lactobacillus spp. were isolated from faeces of six HD infants and confirmed using both conventional and molecular methods. Antibiotic resistance pattern was checked through disc diffusion method and was further investigated for the presence of antibiotic resistance genes (blaTEM, blaCTX-M, blaOXA-2, blaIMP, blaVIM-2, blaNDM-1 and mcr-1). RESULTS: Antibiotic susceptibility of the isolates showed high level of resistance towards cephalosporins, oxacillin, aztreonam, meropenem and polymyxin group. However, four of the isolates showed the presence of blaCTX-M gene after PCR amplification. CONCLUSIONS: To our knowledge, this is the first report on the presence of antibiotic resistance gene blaCTX-M in Lactobacillus spp. and this presence may pose a serious threat in treatment regimen. As not much is known regarding the presence of blaCTX-M in Lactobacillus spp., this finding may provide new light to research on antibiotic resistance in gut microflora.

Development of a Simple, Peripheral-Blood-Based Lateral-Flow Dipstick Assay for Accurate Detection of Patients with Enteric Fever.

Enteric fever is a systemic infection caused by typhoidal strains of Salmonella enterica and is a significant cause of mortality and morbidity in many parts of the world, especially in resource-limited areas. Unfortunately, currently available diagnostic tests for enteric fever lack sensitivity and/or specificity. No true clinically practical gold standard for diagnosing patients with enteric fever exists. Unfortunately, microbiologic culturing of blood is only 30 to 70% sensitive although 100% specific. Here, we report the development of a lateral-flow immunochromatographic dipstick assay based on the detection of Salmonella enterica serovar Typhi (S Typhi) lipopolysaccharide (LPS)-specific IgG in lymphocyte culture secretion. We tested the assay using samples from 142 clinically suspected enteric fever patients, 28 healthy individuals residing in a zone where enteric fever is endemic, and 35 patients with other febrile illnesses. In our analysis, the dipstick detected all blood culture-confirmed S Typhi cases (48/48) and 5 of 6 Salmonella enterica serovar Paratyphi A blood cultured-confirmed cases. The test was negative in all 35 individuals febrile with other illnesses and all 28 healthy controls from the zone of endemicity. The test was positive in 19 of 88 individuals with suspected enteric fever but with negative blood cultures. Thus, the dipstick had a sensitivity of 98% compared to blood culture results and a specificity that ranged from 78 to 100% (95% confidence interval [CI], 70 to 100%), depending on the definition of a true negative. These results suggest that this dipstick assay can be very useful for the detection of enteric fever patients especially in regions of endemicity.