A Comprehensive Pilot Study to Elucidate the Distinct Gut Microbial Composition and Its Functional Significance in Cardio-Metabolic Disease.

Cardio-metabolic disease is a significant global health challenge with increasing prevalence. Recent research underscores the disruption of gut microbial balance as a key factor in disease susceptibility. We aimed to characterize the gut microbiota composition and function in cardio-metabolic disease and healthy controls. For this purpose, we collected stool samples of 18 subjects (12 diseased, 6 healthy) and we performed metagenomics analysis and functional prediction using QIIME2 and PICRUSt. Furthermore, we carried out assessments of microbe-gene interactions, gene ontology, and microbe-disease associations. Our findings revealed distinct microbial patterns in the diseased group, particularly evident in lower taxonomic levels with significant variations in 14 microbial features. The diseased cohort exhibited an enrichment of Lachnospiraceae family, correlating with obesity, insulin resistance, and metabolic disturbances. Conversely, reduced levels of Clostridium, Gemmiger, and Ruminococcus genera indicated a potential inflammatory state, linked to compromised butyrate production and gut permeability. Functional analyses highlighted dysregulated pathways in amino acid metabolism and energy equilibrium, with perturbations correlating with elevated branch-chain amino acid levels-a known contributor to insulin resistance and type 2 diabetes. These findings were consistent across biomarker assessments, microbe-gene associations, and gene ontology analyses, emphasizing the intricate interplay between gut microbial dysbiosis and cardio-metabolic disease progression. In conclusion, our study unveils significant shifts in gut microbial composition and function in cardio-metabolic disease, emphasizing the broader implications of microbial dysregulation. Addressing gut microbial balance emerges as a crucial therapeutic target in managing cardio-metabolic disease burden.

Evaluation of HLA typing content of next-generation sequencing datasets from family trios and individuals of arab ethnicity.

Introduction: HLA typing is a critical tool in both clinical and research applications at the individual and population levels. Benchmarking studies have indicated HLA-HD as the preferred tool for accurate and comprehensive HLA allele calling. The advent of next-generation sequencing (NGS) has revolutionized genetic analysis by providing high-throughput sequencing data. This study aims to evaluate, using the HLA-HD tool, the HLA typing content of whole exome, whole genome, and HLA-targeted panel sequence data from the consanguineous population of Arab ethnicity, which has been underrepresented in prior benchmarking studies. Methods: We utilized sequence data from family trios and individuals, sequenced on one or more of the whole exome, whole genome, and HLA-targeted panel sequencing technologies. The performance and resolution across various HLA genes were evaluated. We incorporated a comparative quality control analysis, assessing the results obtained from HLA-HD by comparing them with those from the HLA-Twin tool to authenticate the accuracy of the findings. Results: Our analysis found that alleles across 29 HLA loci can be successfully and consistently typed from NGS datasets. Clinical-grade whole exome sequencing datasets achieved the highest consistency rate at three-field resolution, followed by targeted HLA panel, research-grade whole exome, and whole genome datasets. Discussion: The study catalogues HLA typing consistency across NGS datasets for a large array of HLA genes and highlights assessments regarding the feasibility of utilizing available NGS datasets in HLA allele studies. These findings underscore the reliability of HLA-HD for HLA typing in underrepresented populations and demonstrate the utility of various NGS technologies in achieving accurate HLA allele calling.

Plasma Virome of HIV-infected Subjects on Suppressive Antiretroviral Therapy Reveals Association of Differentially Abundant Viruses with Distinct T-cell Phenotypes and Inflammation.

Background: The plasma virome represents the overall composition of viral sequences present in it. Alteration in plasma virome has been reported in treatment naïve and immunocompromised (CD4 count < 200) people with HIV (PWH). However, the effect of ART on virome composition in PWH on ART with preserved CD4 counts is poorly understood. Objectives: We aimed to assess the alterations in plasma virome in PWH on ART in comparison to HIV-negative uninfected controls and to further investigate possible associations of plasma viruses with inflammation and immune dysfunction, namely, immunosenescence and immune exhaustion. Methods: Plasma viral DNA from PWH on ART and controls was used for sequencing on the Illumina Nextseq500 platform, followed by the identification of viral sequences using an automated pipeline, VIROMATCH. Multiplex cytokine assay was performed to measure the concentrations of various cytokines in plasma. Immunophenotyping was performed on PBMCs to identify T cell markers of immunosenescence and immune exhaustion. Results: In our observational, cross-sectional pilot study, chronically infected PWH on ART had significantly different viral species compositions compared to controls. The plasma virome of PWH showed a significantly high relative abundance of species Human gammaherpesvirus 4, also known as Epstein-Barr virus (EBV). Moreover, EBV emerged as a significant viral taxon differentially enriched in PWH on ART, which further correlated positively with the exhaustion phenotype of T cells and significantly increased TNF-α in PWH on ART. Additionally, a significantly increased proportion of senescent T cells and IL-8 cytokine was detected in PWH on ART. Conclusion: Altered plasma virome influenced the inflammatory response and T-cell phenotype in PWH on ART.

A bioinformatics approach to elucidate conserved genes and pathways in C. elegans as an animal model for cardiovascular research.

Cardiovascular disease (CVD) is a collective term for disorders of the heart and blood vessels. The molecular events and biochemical pathways associated with CVD are difficult to study in clinical settings on patients and in vitro conditions. Animal models play a pivotal and indispensable role in CVD research. Caenorhabditis elegans, a nematode species, has emerged as a prominent experimental organism widely utilized in various biomedical research fields. However, the specific number of CVD-related genes and pathways within the C. elegans genome remains undisclosed to date, limiting its in-depth utilization for investigations. In the present study, we conducted a comprehensive analysis of genes and pathways related to CVD within the genomes of humans and C. elegans through a systematic bioinformatic approach. A total of 1113 genes in C. elegans orthologous to the most significant CVD-related genes in humans were identified, and the GO terms and pathways were compared to study the pathways that are conserved between the two species. In order to infer the functions of CVD-related orthologous genes in C. elegans, a PPI network was constructed. Orthologous gene PPI network analysis results reveal the hubs and important KRs: pmk-1, daf-21, gpb-1, crh-1, enpl-1, eef-1G, acdh-8, hif-1, pmk-2, and aha-1 in C. elegans. Modules were identified for determining the role of the orthologous genes at various levels in the created network. We also identified 9 commonly enriched pathways between humans and C. elegans linked with CVDs that include autophagy (animal), the ErbB signaling pathway, the FoxO signaling pathway, the MAPK signaling pathway, ABC transporters, the biosynthesis of unsaturated fatty acids, fatty acid metabolism, glutathione metabolism, and metabolic pathways. This study provides the first systematic genomic approach to explore the CVD-associated genes and pathways that are present in C. elegans, supporting the use of C. elegans as a prominent animal model organism for cardiovascular diseases.

Global analysis of urinary extracellular vesicle small RNAs in autosomal dominant polycystic kidney disease.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the most prevalent monogenic renal disease progressing to end-stage renal disease. There is a pressing need for the identification of early ADPKD biomarkers to enable timely intervention and the development of effective therapeutic approaches. Here, we profiled human urinary extracellular vesicles small RNAs by small RNA sequencing in patients with ADPKD and compared their differential expression considering healthy control individuals to identify dysregulated small RNAs and analyze downstream interaction to gain insight about molecular pathophysiology. METHODS: This is a cross-sectional study where urine samples were collected from a total of 23 PKD1-ADPKD patients and 28 healthy individuals. Urinary extracellular vesicles were purified, and small RNA was isolated and sequenced. Differentially expressed Small RNA were identified and functional enrichment analysis of the critical miRNAs was performed to identify driver genes and affected pathways. RESULTS: miR-320b, miR-320c, miR-146a-5p, miR-199b-3p, miR-671-5p, miR-1246, miR-8485, miR-3656, has_piR_020497, has_piR_020496 and has_piR_016271 were significantly upregulated in ADPKD patient urine extracellular vesicles and miRNA-29c was significantly downregulated. Five 'driver' target genes (FBRS, EDC3, FMNL3, CTNNBIP1 and KMT2A) were identified. CONCLUSIONS: The findings of the present study make significant contributions to the understanding of ADPKD pathogenesis and to the identification of novel biomarkers and potential drug targets aimed at slowing disease progression in ADPKD.

Identification of potential regulatory mechanisms and therapeutic targets for lung cancer.

Lung cancer poses a significant health threat globally, especially in regions like India, with 5-year survival rates remain alarmingly low. Our study aimed to uncover key markers for effective treatment and early detection. We identified specific genes related to lung cancer using the BioXpress database and delved into their roles through DAVID enrichment analysis. By employing network theory, we explored the intricate interactions within lung cancer networks, identifying ASPM and MKI67 as crucial regulator genes. Predictions of microRNA and transcription factor interactions provided additional insights. Examining gene expression patterns using GEPIA and KM Plotter revealed the clinical relevance of these key genes. In our pursuit of targeted therapies, Drug Bank pointed to methotrexate as a potential drug for the identified key regulator genes. Confirming this, molecular docking studies through Swiss Dock showed promising binding interactions. To ensure stability, we conducted molecular dynamics simulations using the AMBER 16 suite. In summary, our study pinpoints ASPM and MKI67 as vital regulators in lung cancer networks. The identification of hub genes and functional pathways enhances our understanding of molecular processes, offering potential therapeutic targets. Importantly, methotrexate emerged as a promising drug candidate, supported by robust docking and simulation studies. These findings lay a solid foundation for further experimental validations and hold promise for advancing personalized therapeutic strategies in lung cancer.Communicated by Ramaswamy H. Sarma.

Conserved Cardiovascular Network: Bioinformatics Insights into Genes and Pathways for Establishing Caenorhabditis elegans as an Animal Model for Cardiovascular Diseases.

Cardiovascular disease (CVD) is a collective term for disorders of the heart and blood vessels. The molecular events and biochemical pathways associated with CVD are difficult to study in clinical settings on patients and in vitro conditions. Animal models play a pivotal and indispensable role in cardiovascular disease (CVD) research. Caenorhabditis elegans , a nematode species, has emerged as a prominent experimental organism widely utilised in various biomedical research fields. However, the specific number of CVD-related genes and pathways within the C. elegans genome remains undisclosed to date, limiting its in-depth utilisation for investigations. In the present study, we conducted a comprehensive analysis of genes and pathways related to CVD within the genomes of humans and C. elegans through a systematic bioinformatic approach. A total of 1113 genes in C. elegans orthologous to the most significant CVD-related genes in humans were identified, and the GO terms and pathways were compared to study the pathways that are conserved between the two species. In order to infer the functions of CVD-related orthologous genes in C. elegans, a PPI network was constructed. Orthologous gene PPI network analysis results reveal the hubs and important KRs: pmk-1, daf-21, gpb-1, crh-1, enpl-1, eef-1G, acdh-8, hif-1, pmk-2, and aha-1 in C. elegans. Modules were identified for determining the role of the orthologous genes at various levels in the created network. We also identified 9 commonly enriched pathways between humans and C. elegans linked with CVDs that include autophagy (animal), the ErbB signalling pathway, the FoxO signalling pathway, the MAPK signalling pathway, ABC transporters, the biosynthesis of unsaturated fatty acids, fatty acid metabolism, glutathione metabolism, and metabolic pathways. This study provides the first systematic genomic approach to explore the CVD-associated genes and pathways that are present in C. elegans, supporting the use of C. elegans as a prominent animal model organism for cardiovascular diseases.

A computational biology approach to identify potential protein biomarkers and drug targets for sporadic amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease caused by the loss of upper and lower motor neurons. The sporadic ALS (sALS) is a multigenic disorder and the complex mechanisms underlying its onset are still not fully delineated. Despite the recent scientific advancements, certain aspects of ALS pathogenic targets need to be yet clarified. The aim of the presented study is to identify potential genetic biomarkers and drug targets for sALS, by analysing gene expression profiles, presented in the publicly available GSE68605 dataset, of motor neurons cells obtained from sALS patients. We used different computational approaches including differential expression analysis, protein network mapping, candidate protein biomarker (CPB) identification, elucidation of the role of functional modules, and molecular docking analysis. The resultant top ten up- and downregulated genes were further used to construct protein-protein interaction network (PPIN). The PPIN analysis resulted in identifying four CPBs (namely RIOK2, AKT1, CTNNB1, and TNF) that commonly overlapped with one another in network parameters (degree, bottleneck and maximum neighbourhood component). The RIOK2 protein emerged as a potential mediator of top five functional modules that are associated with RNA binding, lipoprotein particle receptor binding in pre-ribosome, and interferon, cytokine-mediated signaling pathway. Furthermore, molecular docking analysis revealed that cyclosporine exhibited the highest binding affinity (-8.6 kJ/mol) with RIOK2, and surpassed the FDA-approved ALS drugs, such as riluzole and edaravone. This suggested that cyclosporine may serve as a promising candidate for targeting RIOK2 downregulation observed in sALS patients. In order to validate our computational results, it is suggested that in vitro and in vivo studies may be conducted in future to provide a more detailed understanding of ALS diagnosis, prognosis, and therapeutic intervention.

Disruption in the regulation of casein kinase 2 in circadian rhythm leads to pathological states: cancer, diabetes and neurodegenerative disorders.

Introduction: Circadian rhythm maintains the sleep-wake cycle in biological systems. Various biological activities are regulated and modulated by the circadian rhythm, disruption of which can result in onset of diseases. Robust rhythms of phosphorylation profiles and abundances of PERIOD (PER) proteins are thought to be the master keys that drive circadian clock functions. The role of casein kinase 2 (CK2) in circadian rhythm via its direct interactions with the PER protein has been extensively studied; however, the exact mechanism by which it affects circadian rhythms at the molecular level is not known. Methods: Here, we propose an extended circadian rhythm model in Drosophila that incorporates the crosstalk between the PER protein and CK2. We studied the regulatory role of CK2 in the dynamics of PER proteins involved in circadian rhythm using the stochastic simulation algorithm. Results: We observed that variations in the concentration of CK2 in the circadian rhythm model modulates the PER protein dynamics at different cellular states, namely, active, weakly active, and rhythmic death. These oscillatory states may correspond to distinct pathological cellular states of the living system. We find molecular noise at the expression level of CK2 to switch normal circadian rhythm to any of the three above-mentioned circadian oscillatory states. Our results suggest that the concentration levels of CK2 in the system has a strong impact on its dynamics, which is reflected in the time evolution of PER protein. Discussion: We believe that our findings can contribute towards understanding the molecular mechanisms of circadian dysregulation in pathways driven by the PER mutant genes and their pathological states, including cancer, obesity, diabetes, neurodegenerative disorders, and socio-psychological disease.

Comprehensive multiomics and in silico approach uncovers prognostic, immunological, and therapeutic roles of ANLN in lung adenocarcinoma.

The anillin actin-binding protein (ANLN) is immensely overexpressed in cancers, including lung cancer (LC). Phytocompounds have gained interest due to their broader potential and reduced unwanted effects. Screening numerous compounds presents a challenge, but in silico molecular docking is pragmatic. The present study aims to identify the role of ANLN in lung adenocarcinoma (LUAD), along with identification and interaction analysis of anticancer and ANLN inhibitory phytocompounds followed by molecular dynamics (MD) simulation. Using a systematic approach, we found that ANLN is significantly overexpressed in LUAD and mutated with a frequency of 3.73%. It is linked with advanced stages, clinicopathological parameters, worsening of relapse-free survival (RFS), and overall survival (OS), pinpointing its oncogenic and prognostic potential. High-throughput screening and molecular docking of phytocompounds revealed that kaempferol (flavonoid aglycone) interacts strongly with the active site of ANLN protein via hydrogen bonds, Vander Waals interactions, and acts as a potent inhibitor. Furthermore, we discovered that ANLN expression was found to be significantly higher (p) in LC cells compared to normal cells. This is a propitious and first study to demonstrate ANLN and kaempferol interactions, which might eventually lead to removal of rout from cell cycle regulation posed by ANLN overexpression and allow it to resume normal processes of proliferation. Overall, this approach suggested a plausible biomarker role of ANLN and the combination of molecular docking subsequently led to the identification of contemporary phytocompounds, bearing symbolic anticancer effects. The findings would be advantageous for pharmaceutics but require validation using in vitro and in vivo methods. HIGHLIGHTS: • ANLN is significantly overexpressed in LUAD. • ANLN is implicated in the infiltration of TAMs and altering plasticity of TME. • Kaempferol (potential ANLN inhibitor) shows important interactions with ANLN which could remove the alterations in cell cycle regulation, imposed by ANLN overexpression eventually leading to normal process of cell proliferation.

Investigating the link between miR-34a-5p and TLR6 signaling in sepsis-induced ARDS.

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) are lung complications diagnosed by impaired gaseous exchanges leading to mortality. From the diverse etiologies, sepsis is a prominent contributor to ALI/ARDS. In the present study, we retrieved sepsis-induced ARDS mRNA expression profile and identified 883 differentially expressed genes (DEGs). Next, we established an ARDS-specific weighted gene co-expression network (WGCN) and picked the blue module as our hub module based on highly correlated network properties. Later we subjected all hub module DEGs to form an ARDS-specific 3-node feed-forward loop (FFL) whose highest-order subnetwork motif revealed one TF (STAT6), one miRNA (miR-34a-5p), and one mRNA (TLR6). Thereafter, we screened a natural product library and identified three lead molecules that showed promising binding affinity against TLR6. We then performed molecular dynamics simulations to evaluate the stability and binding free energy of the TLR6-lead molecule complexes. Our results suggest these lead molecules may be potential therapeutic candidates for treating sepsis-induced ALI/ARDS. In-silico studies on clinical datasets for sepsis-induced ARDS indicate a possible positive interaction between miR-34a and TLR6 and an antagonizing effect on STAT6 to promote inflammation. Also, the translational study on septic mice lungs by IHC staining reveals a hike in the expression of TLR6. We report here that miR-34a actively augments the effect of sepsis on lung epithelial cell apoptosis. This study suggests that miR-34a promotes TLR6 to heighten inflammation in sepsis-induced ALI/ARDS. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03700-1.

SARS CoV-2 spike protein variants exploit DC-SIGN/DC-SIGNR receptor for evolution and severity: an in-silico insight.

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is related with the COVID-19 pandemic. Recent spike protein variations have had an effect on the transmission of the virus. In addition to ACE-2, spike proteins can employ DC-SIGN and its analogous receptor, DC-SIGNR, for host evasion. Spike variations in the DC-SIGN interaction region and role of DC-SIGN in immune evasion have not been well defined. To understand the spike protein variations and their binding mode, phylogenetic analysis of the complete GISAID (Global Initiative for Sharing Avian Influenza Data) data of the SARS-CoV-2 spike protein was considered. In addition, an in silico knockout network evaluation of the SARS-CoV-2 single-cell transcriptome was conducted to determine the key role of DC-SIGN/R in immunological dysregulation. Within the DC-SIGN-interacting region of the SARS-CoV spike protein, the spike protein of SARS-CoV-2 displayed remarkable similarity to the SARS-CoV spike protein. Surprisingly, the phylogenetic analysis revealed that the SARS-CoV-2's spike exhibited significantly diverse variants in the DC-SIGN interaction domain, which altered the frequency of these variants. The variation within the DC-SIGN-interacting domain of spike proteins affected the binding of a limited number of variants with DC-SIGN and DC-SIGNR and affected their evolution. MMGBSA binding free energies evaluation differed for variants from those of the wild type, suggesting the influence of substitution mutations on the interaction pattern. In silico knockout network analysis of the single-cell transcriptome of Bronchoalveolar Lavage and peripheral blood mononuclear cells revealed that SARS-CoV-2 altered DC-SIGN/R signaling. Early surveillance of diverse SARS-CoV-2 strains could preclude a worsening of the pandemic and facilitate the development of an optimum vaccine against variations. The spike Receptor Binding Domain genetic variants are thought to boost SARS CoV-2 immune evasion, resulting in its higher longevity. Supplementary Information: The online version contains supplementary material available at 10.1007/s13337-023-00820-3.

Potential Biomarkers for Parkinson Disease from Functional Enrichment and Bioinformatic Analysis of Global Gene Expression Patterns of Blood and Substantia Nigra Tissues.

The Parkinson disease (PD) is the second most common neurodegenerative disorder affecting the central nervous system and motor functions. The biological complexity of PD is yet to reveal potential targets for intervention or to slow the disease severity. Therefore, this study aimed to compare the fidelity of blood to substantia nigra (SN) tissue gene expression from PD patients to provide a systematic approach to predict role of the key genes of PD pathobiology. Differentially expressed genes (DEGs) from multiple microarray data sets of PD blood and SN tissue from GEO database are identified. Using the theoretical network approach and variety of bioinformatic tools, we prioritized the key genes from DEGs. A total of 540 and 1024 DEGs were identified in blood and SN tissue samples, respectively. Functional pathways closely related to PD such as ERK1 and ERK2 cascades, mitogen-activated protein kinase (MAPK) signaling, Wnt, nuclear factor-κB (NF-κB), and PI3K-Akt signaling were observed by enrichment analysis. Expression patterns of 13 DEGs were similar in both blood and SN tissues. Comprehensive network topological analysis and gene regulatory networks identified additional 10 DEGs functionally connected with molecular mechanisms of PD through the mammalian target of rapamycin (mTOR), autophagy, and AMP-activated protein kinase (AMPK) signaling pathways. Potential drug molecules were identified by chemical-protein network and drug prediction analysis. These potential candidates can be further validated in vitro/in vivo to be used as biomarkers and/or novel drug targets for the PD pathology and/or to arrest or delay the neurodegeneration over the years, respectively.

Low carbohydrate intake correlates with trends of insulin resistance and metabolic acidosis in healthy lean individuals.

Introduction: Both obesity and a poor diet are considered major risk factors for triggering insulin resistance syndrome (IRS) and the development of type 2 diabetes mellitus (T2DM). Owing to the impact of low-carbohydrate diets, such as the keto diet and the Atkins diet, on weight loss in individuals with obesity, these diets have become an effective strategy for a healthy lifestyle. However, the impact of the ketogenic diet on IRS in healthy individuals of a normal weight has been less well researched. This study presents a cross-sectional observational study that aimed to investigate the effect of low carbohydrate intake in healthy individuals of a normal weight with regard to glucose homeostasis, inflammatory, and metabolic parameters. Methods: The study included 120 participants who were healthy, had a normal weight (BMI 25 kg/m2), and had no history of a major medical condition. Self-reported dietary intake and objective physical activity measured by accelerometry were tracked for 7 days. The participants were divided into three groups according to their dietary intake of carbohydrates: the low-carbohydrate (LC) group (those consuming <45% of their daily energy intake from carbohydrates), the recommended range of carbohydrate (RC) group (those consuming 45-65% of their daily energy intake from carbohydrates), and the high-carbohydrate (HC) group (those consuming more than 65% of their daily energy intake from carbohydrates). Blood samples were collected for the analysis of metabolic markers. HOMA of insulin resistance (HOMA-IR) and HOMA of ß-cell function (HOMA-ß), as well as C-peptide levels, were used for the evaluation of glucose homeostasis. Results: Low carbohydrate intake (<45% of total energy) was found to significantly correlate with dysregulated glucose homeostasis as measured by elevations in HOMA-IR, HOMA-ß% assessment, and C-peptide levels. Low carbohydrate intake was also found to be coupled with lower serum bicarbonate and serum albumin levels, with an increased anion gap indicating metabolic acidosis. The elevation in C-peptide under low carbohydrate intake was found to be positively correlated with the secretion of IRS-related inflammatory markers, including FGF2, IP-10, IL-6, IL-17A, and MDC, but negatively correlated with IL-3. Discussion: Overall, the findings of the study showed that, for the first time, low-carbohydrate intake in healthy individuals of a normal weight might lead to dysfunctional glucose homeostasis, increased metabolic acidosis, and the possibility of triggering inflammation by C-peptide elevation in plasma.

Identification of new oxospiro chromane quinoline-carboxylate antimalarials that arrest parasite growth at ring stage.

Malaria still threatens half the globe population despite successful Artemisinin-based combination therapy. One of the reasons for our inability to eradicate malaria is the emergence of resistance to current antimalarials. Thus, there is a need to develop new antimalarials targeting Plasmodium proteins. The present study reported the design and synthesis of 4, 6 and 7-substituted quinoline-3-carboxylates 9(a-o) and carboxylic acids 10(a-b) for the inhibition of Plasmodium N-Myristoyltransferases (NMTs) using computational biology tools followed by chemical synthesis and functional analysis. The designed compounds exhibited a glide score of -9.241 to -6.960 kcal/mol for PvNMT and -7.538 kcal/mol for PfNMT model proteins. Development of the synthesized compounds was established via NMR, HRMS and single crystal X-ray diffraction study. The synthesized compounds were evaluated for their in vitro antimalarial efficacy against CQ-sensitive Pf3D7 and CQ-resistant PfINDO lines followed by cell toxicity evaluation. In silico results highlighted the compound ethyl 6-methyl-4-(naphthalen-2-yloxy)quinoline-3-carboxylate (9a) as a promising inhibitor with a glide score of -9.084 kcal/mol for PvNMT and -6.975 kcal/mol for PfNMT with IC50 values of 6.58 µM for Pf3D7 line. Furthermore, compounds 9n and 9o exhibited excellent anti-plasmodial activity (Pf3D7 IC50 = 3.96, 6.71 µM, and PfINDO IC50 = 6.38, 2.8 µM, respectively). The conformational stability of 9a with the active site of the target protein was analyzed through MD simulation and was found concordance with in vitro results. Thus, our study provides scaffolds for the development of potent antimalarials targeting both Plasmodium vivax and Plasmodium falciparum.Communicated by Ramaswamy H. Sarma.

Identification of a survival associated gene trio in chemical induced breast cancer.

Sporadic cases of breast cancer being more prevalent than the hereditary cases, can be largely attributed to environmental pollutants like polycyclic aromatic hydrocarbons (PAHs). The aim of the present study was to identify gene dysregulations and the associations in DMBA (a PAH) induced breast cancer. A breast cancer model was developed in Wistar rats (n = 40), using DMBA. Serum proteomics (2D electrophoresis and MALDI-TOF MS) followed by relative gene expression analysis in mammary glands were conducted to reach to the differential gene signatures. The candidate genes were subjected to survival analysis (by GEPIA2 and KM plotter) and infiltration analysis (by ImmuCellAI) for correlating gene expression with patient survival and immune cell infiltration respectively. Further, the regulatory network investigation (by Cytoscape) was performed to find out the transcription factors (TFs) and miRNAs of the concerned genes. A gene trio (ANXA5, MTG1, PPP2R5B), expressing differentially in early mammary carcinogenesis at 4 months (precancerous stage) till full-fledged cancerous stage (post 6 months) was identified. The altered gene expression was associated with less survival among breast cancer patients (n = 4019). The dysregulated expression also has a correlation with enhanced mammary infiltration of immune cells. Moreover, a regulatory network (comprising of 77 transcription factors and 50 miRNAs) involved in the regulation of candidate genes was also deciphered. The deregulated target genes can therefore be explored for reregulation via identified TFs and miRNAs, and survival thereby improved.

Network pharmacology and bioinformatics approach reveals the therapeutic mechanism of action of curcumin in Alzheimer disease.

Curcumin is a natural anti-inflammatory and antioxidant substance which plays a major role in reducing the amyloid plaques formation, which is the major cause of Alzheimer's disease (AD). Consequently, a methodical approach was used to select the potential protein targets of curcumin in AD through network pharmacology. In this study, through integrative methods, AD targets of curcumin through SwissTargetPrediction database, STITCH database, BindingDB, PharmMapper, Therapeutic Target Database (TTD), Online Mendelian Inheritance in Man (OMIM) database were predicted followed by gene enrichment analysis, network construction, network topology, and docking studies. Gene ontology analysis facilitated identification of a list of possible AD targets of curcumin (74 targets genes). The correlation of the obtained targets with AD was analysed by using gene ontology (GO) pathway enrichment analyses and Kyoto Encyclopaedia of Genes and Genomes (KEGG). We have incorporated the applied network pharmacological approach to identify key genes. Furthermore, we have performed molecular docking for analysing the mechanism of curcumin. In order to validate the temporospatial expression of key genes in human central nervous system (CNS), we searched the Human Brain Transcriptome (HBT) dataset. We identified top five key genes namely, PPARγ, MAPK1, STAT3, KDR and APP. Further validated the expression profiling of these key genes in publicly available brain data expression profile databases. In context to a valuable addition in the treatment of AD, this study is concluded with novel insights into the therapeutic mechanisms of curcumin, will ease the treatment of AD with the clinical application of curcumin.

Oxidative Products of Curcumin Rather Than Curcumin Bind to Helicobacter Pylori Virulence Factor VacA and Are Required to Inhibit Its Vacuolation Activity.

Curcumin is a hydrophobic polyphenol derived from turmeric with potent anti-oxidant, anti-microbial, anti-inflammatory and anti-carcinogenic effects. Curcumin is degraded into various derivatives under in vitro and in vivo conditions, and it appears that its degradation may be responsible for the pharmacological effects of curcumin. The primary risk factor for the cause of gastric cancer is Helicobacter pylori (H. pylori). A virulence factor vacuolating cytotoxic A (VacA) is secreted by H. pylori as a 88 kDa monomer (p88), which can be fragmented into a 33 kDa N-terminal domain (p33) and a 55 kDa C-terminal domain (p55). Recently it has been reported that curcumin oxidation is required to inhibit the activity of another major H.pylori toxin CagA. We performed molecular docking of curcumin and its oxidative derivatives with p33 and p55 domains of VacA. Further, we have examined the effect of the oxidation of curcumin on the vacuolation activity of VacA protein. We observed the binding of curcumin to the p55 domain of VacA at five different sites with moderate binding affinities. Curcumin did not bind to p33 domain of VacA. Remarkably, cyclobutyl cyclopentadione and dihydroxy cyclopentadione, which are oxidized products of curcumin, showed a higher binding affinity with VacA protein at all sites except one as compared to parent curcumin itself. However, cyclobutyl cyclopentadione showed a significant binding affinity for the active site 5 of the p55 protein. Active site five (312-422) of p55 domain of VacA plays a crucial role in VacA-mediated vacuole formation. Invitro experiments showed that curcumin inhibited the vacuolation activity of H. pylori in human gastric cell line AGS cells whereas acetyl and diacetyl curcumin, which cannot be oxidized, failed to inhibit the vacuolation in AGS cells after H. pylori infection. Here our data showed that oxidation is essential for the activity of curcumin in inhibiting the vacuolation activity of H. pylori. Synthesis of these oxidized curcumin derivatives could potentially provide new therapeutic drug molecules for inhibiting H. pylori-mediated pathogenesis.

Entamoeba histolytica HM-1: IMSS gene expression profiling identifies key hub genes, potential biomarkers, and pathways in Amoebiasis infection: a systematic network meta-analysis.

Entamoeba histolytica (E. histolytica) is an anaerobic parasite that causes Amoebiasis in the intestine or extraintestinal, with immunology, genetics, and environmental variables all playing a part in the disease's development, but its molecular mechanism is unknown. One of the primary obstacles in understanding the etiology of Amoebiasis will be identifying the genetics profiling that controls the Amoebiasis network. By examining the gene expression profile of Amoebiasis and comparing it with healthy controls, we could identify differentially expressed genes (DEGs). DEGs were used to build the Amoebiasis protein interaction network and calculated its network topological properties. We discovered nine key hub genes (KHGs): JUN, PTGS2, FCGR3A, MNDA, CYBB, EGR1, CCL2, TLR8, and LRRK2 genes. The genes JUN and EGR1 were transcriptional factors (TFs) and up-regulated, others down-regulated. hsa-miR-155-5p, hsa-miR-101-3p, hsa-miR-124-3p, hsa-miR-26b-5p, and hsa-miR-16-5p are also among the essential miRNAs that have been demonstrated to be targeted by KHGs. These KHGs were primarily enriched in the IL-17 signaling pathway, TNF signaling pathway, NOD-like receptor signaling pathway, and Toll-like receptor signaling pathway. miRNAs were grouped in various pathways, focusing on the TGF-ß signaling pathway, human immunodeficiency virus 1 infection, insulin signaling pathway, signaling pathways regulating pluripotency of stem cells, etc. Amoebiasis KHGs (JUN, PTGS2, CCL2, and MNDA) and their associated miRNAs are the primary targets for therapeutic methods and possible biomarkers. Furthermore, we identified drugs for genes JUN, PTGS2, FCGR3A, CCL2, and LRRK2. KHGs, on the other hand, required experimental validation to prove their efficacy.