Neutrophils display distinct post-translational modifications in response to varied pathological stimuli.

Neutrophils play a vital role in the innate immunity by perform effector functions through phagocytosis, degranulation, and forming extracellular traps. However, over-functioning of neutrophils has been associated with sterile inflammation such as Type 2 Diabetes, atherosclerosis, cancer and autoimmune disorders. Neutrophils exhibiting phenotypical and functional heterogeneity in both homeostatic and pathological conditions suggests distinct signaling pathways are activated in disease-specific stimuli and alter neutrophil functions. Hence, we examined mass spectrometry based post-translational modifications (PTM) of neutrophil proteins in response to pathologically significant stimuli, including high glucose, homocysteine and bacterial lipopolysaccharides representing diabetes-indicator, an activator of thrombosis and pathogen-associated molecule, respectively. Our data revealed that these aforesaid stimulators differentially deamidate, citrullinate, acetylate and methylate neutrophil proteins and align to distinct biological functions associated with degranulation, platelet activation, innate immune responses and metabolic alterations. The PTM patterns in response to high glucose showed an association with neutrophils extracellular traps (NETs) formation, homocysteine induced proteins PTM associated with signaling of systemic lupus erythematosus and lipopolysaccharides induced PTMs were involved in pathways related to cardiomyopathies. Our study provides novel insights into neutrophil PTM patterns and functions in response to varied pathological stimuli, which may serve as a resource to design therapeutic strategies for the management of neutrophil-centred diseases.

Potential protein kinase inhibitors that target G-quadruplex DNA structures in the human telomeric regions.

Telomeric regions contain Guanine-rich sequences arranged in a planar manner and connected by Hoogsteen hydrogen bonds that can fold into G-quadruplex (G4) DNA structures, and can be stabilized by monovalent metal cations. The presence of G4 DNA holds significance in cancer-related processes, especially due to their regulatory potential at transcriptional and translational levels of oncogene and tumor suppressor genes. The objective of this current research is to explore the evolving realm of FDA-approved protein kinase inhibitors, with a specific emphasis on their capacity to stabilize the G4 DNA structures formed at the human telomeric regions. This involves investigating the possibility of repurposing FDA-approved protein kinase inhibitors as a novel approach for targeting multiple cancer types. In this context, we have selected 16 telomeric G4 DNA structures as targets and 71 FDA-approved small-molecule protein kinase inhibitors as ligands. To investigate their binding affinities, molecular docking of human telomeric G4 DNA with nuclear protein kinase inhibitors and their corresponding co-crystalized ligands were performed. We found that Ponatinib and Lapatinib interact with all the selected G4 targets, the binding free energy calculations, and molecular dynamic simulations confirm their binding efficacy and stability. Thus, it is hypothesized that Ponatinib and Lapatinib may stabilize human telomeric G4 DNA in addition to their ability to inhibit BCR-ABL and the other members of the EGFR family. As a result, we also hypothesize that the stabilization of G4 DNA might represent an additional underlying mechanism contributing to their efficacy in exerting anti-cancer effects.

A global phosphosite-correlated network map of Thousand And One Kinase 1 (TAOK1).

Thousand and one amino acid kinase 1 (TAOK1) is a sterile 20 family Serine/Threonine kinase linked to microtubule dynamics, checkpoint signaling, DNA damage response, and neurological functions. Molecular-level alterations of TAOK1 have been associated with neurodevelopment disorders and cancers. Despite their known involvement in physiological and pathophysiological processes, and as a core member of the hippo signaling pathway, the phosphoregulatory network of TAOK1 has not been visualized. Aimed to explore this network, we first analyzed the predominantly detected and differentially regulated TAOK1 phosphosites in global phosphoproteome datasets across diverse experimental conditions. Based on 709 qualitative and 210 quantitative differential cellular phosphoproteome datasets that were systematically assembled, we identified that phosphorylation at Ser421, Ser9, Ser965, and Ser445 predominantly represented TAOK1 in almost 75% of these datasets. Surprisingly, the functional role of all these phosphosites in TAOK1 remains unexplored. Hence, we employed a robust strategy to extract the phosphosites in proteins that significantly correlated in expression with predominant TAOK1 phosphosites. This led to the first categorization of the phosphosites including those in the currently known and predicted interactors, kinases, and substrates, that positively/negatively correlated with the expression status of each predominant TAOK1 phosphosites. Subsequently, we also analyzed the phosphosites in core proteins of the hippo signaling pathway. Based on the TAOK1 phosphoregulatory network analysis, we inferred the potential role of the predominant TAOK1 phosphosites. Especially, we propose pSer9 as an autophosphorylation and TAOK1 kinase activity-associated phosphosite and pS421, the most frequently detected phosphosite in TAOK1, as a significant regulatory phosphosite involved in the maintenance of genome integrity. Considering that the impact of all phosphosites that predominantly represent each kinase is essential for the efficient interpretation of global phosphoproteome datasets, we believe that the approach undertaken in this study is suitable to be extended to other kinases for accelerated research.

Tyr352 as a Predominant Phosphosite in the Understudied Kinase and Molecular Target, HIPK1: Implications for Cancer Therapy.

Homeodomain-interacting protein kinase 1 (HIPK1) is majorly found in the nucleoplasm. HIPK1 is associated with cell proliferation, tumor necrosis factor-mediated cellular apoptosis, transcription regulation, and DNA damage response, and thought to play significant roles in health and common diseases such as cancer. Despite this, HIPK1 remains an understudied molecular target. In the present study, based on a systematic screening and mapping approach, we assembled 424 qualitative and 44 quantitative phosphoproteome datasets with 15 phosphosites in HIPK1 reported across multiple studies. These HIPK1 phosphosites were not currently attributed to any functions. Among them, Tyr352 within the kinase domain was identified as the predominant phosphosite modulated in 22 differential datasets. To analyze the functional association of HIPK1 Tyr352, we first employed a stringent criterion to derive its positively and negatively correlated protein phosphosites. Subsequently, we categorized the correlated phosphosites in known interactors, known/predicted kinases, and substrates of HIPK1, for their prioritized validation. Bioinformatics analysis identified their significant association with biological processes such as the regulation of RNA splicing, DNA-templated transcription, and cellular metabolic processes. HIPK1 Tyr352 was also identified to be upregulated in Her2+ cell lines and a subset of pancreatic and cholangiocarcinoma tissues. These data and the systems biology approach undertaken in the present study serve as a platform to explore the functional role of other phosphosites in HIPK1, and by extension, inform cancer drug discovery and oncotherapy innovation. In all, this study highlights the comprehensive phosphosite map of HIPK1 kinase and the first of its kind phosphosite-centric analysis of HIPK1 kinase based on global-level phosphoproteomics datasets derived from human cellular differential experiments across distinct experimental conditions.

Deciphering the Receptor-Mediated Signaling Pathways of Interleukin-19 and Interleukin-20.

Interleukin-19 (IL-19) and Interleukin-20 (IL-20) are inflammatory cytokines belonging to the IL-10 family with immunoregulatory properties. Emerging evidence highlights the importance of association of these cytokines with both immunological and inflammatory disorders, including chronic inflammation, cardiac dysfunction, and cancer. IL-19 and IL-20 bind to the heterodimeric receptor complex and induce multiple downstream signaling cascades by activating the signal transducer and activator of transcription 3 (STAT3), Jun N-terminal kinase (JNK), extracellular signal-regulated kinase (ERK), AKT serine/threonine kinase 1 (AKT1), and NFKB inhibitor alpha (NFKBIA), leading to proinflammatory and anti-inflammatory reactions in cancer, inflammation, tumor microenvironment, and infectious diseases. Considering the significant role of these cytokines, we integrated its cellular signaling network by combining multiomics molecular events associated with 56 molecules of induced by IL-19 and 156 molecules of by IL-20. The reactions of these signaling events are classified into enzyme catalysis/post-translational modifications, activation/inhibition events, molecular associations, gene regulations at the mRNA and protein level, and the protein translocation events. We believe that this signaling pathway map would serve as a knowledge base, that aid researchers and clinicians to understand and explore the intricate mechanisms and identify novel signaling components and therapeutic targets for diseases associated with dysregulated IL-19 and IL-20 signaling.

Incidence and prevalence of chronic pulmonary aspergillosis in patients with post-tuberculosis lung abnormality: Results from a community survey in North India.

BACKGROUND: Post-tuberculosis lung abnormality (PTLA) is the most common risk factor for developing chronic pulmonary aspergillosis (CPA). However, the prevalence and incidence of CPA in PTLA patients in India remain unknown. OBJECTIVES: We aimed to ascertain the incidence and prevalence of CPA in subjects with PTLA. METHODS: We identified a cohort of pulmonary tuberculosis who completed anti-tuberculosis therapy (ATT) before November 2019 from the records of the 12 tuberculosis treatment centers attached to the national program. We recorded the clinical and demographic details. We performed computed tomography (CT) of the chest and estimated serum A. fumigatus-specific IgG. We categorised subjects as PTLA with or without CPA using a composite of clinical, radiological, and microbiological features. We resurveyed the subjects at 6 months (or earlier) for the presence of new symptoms. We calculated the prevalence and the incidence rate (per 100-person years) of CPA. RESULTS: We included 117 subjects with PTLA, with a median of 3 years after ATT completion. Eleven subjects had CPA in the initial survey, and one additional case developed CPA during the second survey. The prevalence of CPA in PTLA subjects was 10.3% (12/117). The total observation period was 286.7 person-years. The median (interquartile range) time to develop CPA after ATT completion was 12.5 (5-36.7) months. We found the CPA incidence rate (95% confidence interval) of 4.2 (1.8-6.5) per 100-person years. CONCLUSION: Chronic pulmonary aspergillosis complicates 10% of PTLA subjects after successful outcomes with ATT. Four new CPA cases may develop per 100-persons years of observation after ATT completion. We suggest screening patients with PTLA who develop new symptoms for CPA.

Computational screening of potential anti-inflammatory leads from Jeevaneeya Rasayana plants targeting COX-2 and 5- LOX by molecular docking and dynamic simulation approaches.

Inflammation plays a pivotal role in various pathological processes, ranging from routine injuries and infections to cancer. Cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) are two major enzymes involved in the formation of lipid mediators of inflammation, such as prostaglandins and leukotrienes, through the arachidonic acid pathway. Despite the frequent use of nonsteroidal anti-inflammatory drugs for managing inflammatory disorders by inhibiting these enzymes, there is a wide spectrum of adverse effects linked to their usage. Jeevaneeya Rasayana (JR), a polyherbal formulation traditionally used in India, is renowned for its anti-inflammatory properties. The present study aimed to identify the potential phytocompounds in JR plants against COX-2 and 5-LOX, utilizing molecular docking and dynamic simulations. Among the 429 identified phytocompounds retrieved from publicly available data sources, Terrestribisamide and 1-(9Z-octadecenoyl)-sn-glycero-3-phosphoethanolamine have shown potential binding affinity and favorable interactions with COX-2 and 5-LOX arachidonic acid binding sites. The physicochemical properties and ADMET profiles of these compounds determined their drug-likeness and pharmacokinetics features. Additional validation using molecular dynamics simulations, SASA, Rg, and MM-PBSA binding energy calculations affirmed the stability of the complex formed between those compounds with target proteins. Together, the study identified the effectual binding potential of those bioactive compounds against COX-2 and 5-LOX, providing a viable approach for the development of effective anti-inflammatory medications.

Meta-analysis of the serum/plasma proteome identifies significant associations between COVID-19 with Alzheimer's/Parkinson's diseases.

In recent years, we have seen the widespread devastations and serious health complications manifested by COVID-19 globally. Although we have effectively controlled the pandemic, uncertainties persist regarding its potential long-term effects, including prolonged neurological issues. To gain comprehensive insights, we conducted a meta-analysis of mass spectrometry-based proteomics data retrieved from different studies with a total of 538 COVID-19 patients and 523 healthy controls. The meta-analysis revealed that top-enriched pathways were associated with neurological disorders, including Alzheimer's (AD) and Parkinson's disease (PD). Further analysis confirmed a direct correlation in the expression patterns of 24 proteins involved in Alzheimer's and 23 proteins in Parkinson's disease with COVID-19. Protein-protein interaction network and cluster analysis identified SNCA as a hub protein, a known biomarker for Parkinson's disease, in both AD and PD. To the best of our knowledge, this is the first meta-analysis study providing proteomic profiling evidence linking COVID-19 to neurological complications.

Epstein-Barr Virus: Human Interactome Reveals New Molecular Insights into Viral Pathogenesis for Potential Therapeutics and Antiviral Drug Discovery.

Host-virus Protein-Protein Interactions (PPIs) play pivotal roles in biological processes crucial for viral pathogenesis and by extension, inform antiviral drug discovery and therapeutics innovations. Despite efforts to develop the Epstein-Barr virus (EBV)-host PPI network, there remain significant knowledge gaps and a limited number of interacting human proteins deciphered. Furthermore, understanding the dynamics of the EBV-host PPI network in the distinct lytic and latent viral stages remains elusive. In this study, we report a comprehensive map of the EBV-human protein interactions, encompassing 1752 human and 61 EBV proteins by integrating data from the public repository HPIDB (v3.0) as well as curated high-throughput proteomic data from the literature. To address the stage-specific nature of EBV infection, we generated two detailed subset networks representing the latent and lytic stages, comprising 747 and 481 human proteins, respectively. Functional and pathway enrichment analysis of these subsets uncovered the profound impact of EBV proteins on cancer. The identification of highly connected proteins and the characterization of intrinsically disordered and cancer-related proteins provide valuable insights into potential therapeutic targets. Moreover, the exploration of drug-protein interactions revealed notable associations between hub proteins and anticancer drugs, offering novel perspectives for controlling EBV pathogenesis. This study represents, to the best of our knowledge, the first comprehensive investigation of the two distinct stages of EBV infection using high-throughput datasets. This makes a contribution to our understanding of EBV-host interactions and provides a foundation for future drug discovery and therapeutic interventions.

Cisplatin and Procaterol Combination in Gastric Cancer? Targeting Checkpoint Kinase 1 for Cancer Drug Discovery and Repurposing by an Integrated Computational and Experimental Approach.

Checkpoint kinase 1 (CHK1), a serine/threonine kinase, plays a crucial role in cell cycle arrest and is a promising therapeutic target for drug development against cancers. CHK1 coordinates cell cycle checkpoints in response to DNA damage, facilitating repair of single-strand breaks, and maintains the genome integrity in response to replication stress. In this study, we employed an integrated computational and experimental approach to drug discovery and repurposing, aiming to identify a potent CHK1 inhibitor among existing drugs. An e-pharmacophore model was developed based on the three-dimensional crystal structure of the CHK1 protein in complex with CCT245737. This model, characterized by seven key molecular features, guided the screening of a library of drugs through molecular docking. The top 10% of scored ligands were further examined, with procaterol emerging as the leading candidate. Procaterol demonstrated interaction patterns with the CHK1 active site similar to CHK1 inhibitor (CCT245737), as shown by molecular dynamics analysis. Subsequent in vitro assays, including cell proliferation, colony formation, and cell cycle analysis, were conducted on gastric adenocarcinoma cells treated with procaterol, both as a monotherapy and in combination with cisplatin. Procaterol, in synergy with cisplatin, significantly inhibited cell growth, suggesting a potentiated therapeutic effect. Thus, we propose the combined application of cisplatin and procaterol as a novel potential therapeutic strategy against human gastric cancer. The findings also highlight the relevance of CHK1 kinase as a drug target for enhancing the sensitivity of cytotoxic agents in cancer.

Integrative Placental Multi-Omics Analysis Reveals Perturbed Pathways and Potential Prognostic Biomarkers in Gestational Hypertension.

BACKGROUND: Gestational hypertension (GH) is a severe complication that occurs after 20 weeks of pregnancy; however, its molecular mechanisms are not yet fully understood. OBJECTIVE: Through this case-control discovery phase study, we aimed to find disease-specific candidate placental microRNAs (miRNAs) and metabolite markers for differentiating GH by integrating next-generation sequencing and metabolomics multi-omics analysis of placenta. Using small RNA sequencing and metabolomics of placental tissues of healthy pregnant (HP, n = 24) and GH subjects (n = 20), the transcriptome and metabolome were characterized in both groups. RESULTS: The study identified a total of 44 downregulated placental miRNAs which includes three novel, three mature and 38 precursor miRNAs. Six miRNAs including three mature (hsa-miR-181a-5p, hsa-miR-498-5p, and hsa-miR-26b-5p) and three novel (NC_000016.10_1061, NC_000005.10_475, and NC_000001.11_53) were considered for final target prediction and functional annotation. Integrative analysis of differentially expressed miRNAs and metabolites yielded five pathways such as purine, glutathione, glycerophospholipid, inositol phosphate and ß-alanine to be significantly perturbed in GH. We present fourteen genes (LPCAT1, LPCAT2, DGKH, PISD, GPAT2, PTEN, SACM1L, PGM2, AMPD3, AK7, AK3, CNDP1, IDH2, and ODC1) and eight metabolites (xanthosine, xanthine, spermine, glycine, CDP-Choline, glyceraldehyde 3-phosphate, ß-alanine, and histidine) with potential to distinguish GH and HP. CONCLUSION: The differential expression of miRNAs, their target genes, altered metabolites and metabolic pathways in GH patients were identified for the first time in our study. Further, the altered miRNAs and metabolites were integrated to build their inter-connectivity network. The findings obtained from our study may be used as a valuable source to further unravel the molecular pathways associated with GH and also for the evaluation of prognostic markers.

Hepatitis B Virus Modulated Transcriptional Regulatory Map of Hepatic Cellular MicroRNAs.

Hepatitis B virus (HBV) is an enveloped, hepatotropic, noncytopathic virus with a partially double-stranded DNA genome. It infects hepatocytes and is associated with progression to liver fibrosis and cirrhosis, culminating in hepatocellular carcinoma (HCC), accounting for 55% of total HCC cases. MicroRNAs (miRNAs) regulated by HBV play an important role in these pathologies. Mapping the miRNAs responsive to HBV and HBV-specific proteins, including HBV X protein (HBx) that harbor the majority of HBV-human protein interactions, could aid accelerate the diagnostics and therapeutics innovation against the infection and associated diseases. With this in mind, we used a unique annotation strategy whereby we first amassed 362 mature HBV responsive-human Differentially Expressed miRNAs (HBV-hDEmiRs). The core experimentally-validated messenger RNA targets of the HBV-hDEmiRs were mostly associated with viral infections and hepatic inflammation processes. Moreover, our annotation strategy enabled the characterization of HBx-dependent/independent HBV-hDEmiRs as a tool for evaluation of the impact of HBx as a therapeutic target. Bioinformatics analysis of the HBV-human protein-protein interactome revealed new insights into the transcriptional regulatory network of the HBV-hDEmiRs. We performed a comparative analysis of data on miRNAs gathered from HBV infected cell line studies and from tissue studies of fibrosis, cirrhosis, and HCC. Accordingly, we propose hsa-miR-15a-5p that is downregulated by multiple HBV proteins, including HBx, as a potential biomarker of HBV infection, and its progression to HCC. In all, this study underscores (1) the complexity of miRNA regulation in response to HBV infection and its progression into other liver pathologies and (2) provides a regulatory map of HBV-hDEmiRs and the underlying mechanisms modulating their expression through a cross talk between HBV viral proteins and human transcription factors.

Identification and stability analysis of potential ADP-ribose modification sites on vascular endothelial growth factor (VEGF) through molecular dynamics simulation.

Post-translational modifications (PTMs) are crucial covalent processes that alter protein properties, achieved through proteolytic cleavage or addition of modifying groups like acetyl, phosphoryl, glycosyl, or methyl to amino acids. ADP-ribosylation is a reversible post-translational modification, where ADP-ribose units are covalently attached to target protein side chains. Vascular endothelial growth factor (VEGF) is a potent angiogenic factor that plays a key role in physiological and pathological conditions. Studies have reported that ADP-ribosylation affects VEGF's ability to bind to VEGF receptors, impacting angiogenesis signalling. However, the specific amino acid undergoing ADP-ribosylation on VEGF remained unknown. To understand the mechanism of ADP-ribose addition to VEGF, an in silico study was designed. The study initially checked for the presence of any conserved motif where ADP-ribosylation could potentially occur and identified the presence of the EIE motif in VEGF, a probable site for ADP-ribosylation for many proteins. Subsequently, the amino acids near this motif were selected and their structural properties were analyzed. Surface-exposed amino acids were chosen, and ADP-ribose was then added to their side chains. The results revealed that the amino acids ASP (67) and GLU (70) underwent glycosidic linkage with ADP-ribose, indicating that they are the most probable modification sites. Subsequently, Molecular dynamic simulation analysis such as RMSD, RMSF, Rg, PCA, and FEL, along with MM-PBSA binding free energy calculations were performed to understand the stability of the VEGF-ADP-ribose complexes. The analysis revealed that amino acid at position 67 (ASP67) is the most probable site for ADP-ribosylation in VEGF.Communicated by Ramaswamy H. Sarma.

In-silico studies of Brassica oleracea active compounds and their role in thyroid peroxidase activity.

Cabbage, a leafy vegetable that is widely consumed across the globe, holds a significant place within the Brassica family. For almost a century, its potential anti-thyroid effects have captured attention. The presence of compounds such as thiocyanate and goitrin in cabbage has been extensively investigated for their ability to impede sodium-iodide symporter and thyroid peroxidase (TPO) activities. The present study is focused on uncovering the active constituents in cabbage that could interact with TPO, while also examining their stability under cooking temperatures. Employing molecular docking and molecular dynamic simulation techniques, we quantified the binding strength of phytochemicals present in cabbage with the target. Out of the 60 compounds identified in cabbage leaves, only 18 exhibited docking scores surpassing those of the commercially available anti-thyroid drug, methimazole. These chosen compounds were studied for binding free energy and pharmacokinetic properties. A specific compound, gamma-Terpinene, classified as a monoterpene, emerged as noteworthy due to its alignment with all criteria and the highest observed binding free energy compared to others. Furthermore, we explored the stability of gamma-Terpinene at 373.15K (cooking temperature) and observed its susceptibility to degradation. This might contribute to the relatively diminished anti-thyroid effects of cabbage when consumed in cooked form. Consequently, our findings suggest that the consumption of cooked cabbage could be more conducive to maintaining normal thyroid function, as opposed to its raw counterpart.Communicated by Ramaswamy H. Sarma.

Cluster-MLP: An Active Learning Genetic Algorithm Framework for Accelerated Discovery of Global Minimum Configurations of Pure and Alloyed Nanoclusters.

Structural characterization of nanoclusters is one of the major challenges in nanocluster modeling owing to the multitude of possible configurations of arrangement of cluster atoms. The genetic algorithm (GA), a class of evolutionary algorithms based on the principles of natural evolution, is a commonly employed search method for locating the global minimum configuration of nanoclusters. Although a GA search at the DFT level is required for the accurate description of a potential energy surface to arrive at the correct global minimum configuration of nanoclusters, computationally expensive DFT evaluation of the significantly larger number of cluster geometries limits its practicability. Recently, machine learning potentials (MLP) that are learned from DFT calculations gained significant attention as computationally cheap alternative options that provide DFT level accuracy. As the accuracy of the MLP predictions is dependent on the quality and quantity of the training DFT data, active learning (AL) strategies have gained significant momentum to bypass the need of large and representative training data. In this application note, we present Cluster-MLP, an on-the-fly active learning genetic algorithm framework that employs the Flare++ machine learning potential (MLP) for accelerating the GA search for global minima of pure and alloyed nanoclusters. We have used a modified version the Birmingham parallel genetic algorithm (BPGA) for the nanocluster GA search which is then incorporated into distributed evolutionary algorithms in Python (DEAP), an evolutionary computational framework for fast prototyping or technical experiments. We have shown that the incorporation of the AL framework in the BPGA significantly reduced the computationally expensive DFT calculations. Moreover, we have shown that both the AL-GA and DFT-GA predict the same global minima for all the clusters we tested.

Experience of "One Stop TB Diagnostic Solution" Model in Engaging a Private Laboratory for End-to-End Diagnostic Services in the National TB Elimination Program in Hisar, India.

The complete diagnostic evaluation of tuberculosis based on its drug-resistance profile is critical for appropriate treatment decisions. The TB diagnostic landscape in India has been transformed with the scaling-up of WHO-recommended diagnostics, but challenges remain with specimen transportation, completing diagnostic assessment, turnaround time (TAT), and maintaining laboratories. Private laboratories have demonstrated efficiencies for specimen collection, transportation, and the timely testing and issue of results. A one-stop TB diagnostic model was designed to assess the feasibility of providing end-to-end diagnostic services in the Hisar district of Haryana state, India. A NTEP-certified private laboratory was engaged to provide the services, complementing the existing public sector diagnostic services. A total of 10,164 specimens were collected between May 2022 and January 2023 and these were followed for the complete diagnostic assessment of Drug-Susceptible TB (DS-TB) and Drug-Resistant TB (DR-TB) and the time taken for issuing results. A total of 2152 (21%) patients were detected with TB, 1996 (93%) Rifampicin-Sensitive and 134 (6%) with Rifampicin-Resistant TB. Nearly 99% of the patients completed the evaluation of DS-TB and DR-TB within the recommended TAT. The One-Stop TB/DR-TB Diagnostic Solution model has demonstrated that diagnostic efficiencies could be enhanced through the strategic purchase of private laboratory services.

VirhostlncR: A comprehensive database to explore lncRNAs and their targets in viral infections.

Long non-coding-RNAs (lncRNAs) are an expanding set of cis-/trans-regulatory RNA genes that outnumber the protein-coding genes. Although being increasingly discovered, the functional role of the majority of lncRNAs in diverse biological conditions is undefined. Increasing evidence supports the critical role of lncRNAs in the emergence, regulation, and progression of various viral infections including influenza, hepatitis, coronavirus, and human immunodeficiency virus. Hence, the identification of signature lncRNAs would facilitate focused analysis of their functional roles accounting for their targets and regulatory mechanisms associated with infections. Towards this, we compiled 2803 lncRNAs identified to be modulated by 33 viral strains in various mammalian cell types and are provided through the resource named VirhostlncR (http://ciods.in/VirhostlncR/). The information on each of the viral strains, their multiplicity of infection, duration of infection, host cell name and cell types, fold change of lncRNA expression, and their specific identification methods are integrated into VirhostlncR. Based on the current datasets, we report 150 lncRNAs including differentiation antagonizing non-protein coding RNA (DANCR), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), maternally expressed gene 3 (MEG3), nuclear paraspeckle assembly transcript 1 (NEAT1), and plasmacytoma variant translocation 1 (PVT1) to be perturbed by two or more viruses. Analysis of viral protein interactions with human transcription factors (TFs) or TF-containing protein complexes identified that distinct viruses can transcriptionally regulate many of these lncRNAs through multiple protein complexes. Together, we believe that the current dataset will enable priority selection of lncRNAs for identification of their targets and serve as an effective platform for the analysis of noncoding RNA-mediated regulations in viral infections.

In-silico screening and identification of potential drug-like compounds for dengue-associated thrombocytopenia from Carica papaya leaf extracts.

Dengue virus is a mosquito-borne pathogen that causes a variety of illnesses ranging from mild fever to severe and fatal dengue haemorrhagic fever or dengue shock syndrome. One of the major clinical manifestations of severe dengue infection is thrombocytopenia. The dengue non-structural protein 1 (NS1) is the primary protein that stimulates immune cells via toll-like receptor 4 (TLR4), induces platelets, and promotes aggregation, which could result in thrombocytopenia. The leaf extracts of Carica papaya seem to have therapeutic benefits in managing thrombocytopenia associated with dengue. The present study focuses on understanding the underlying mechanism of the use of papaya leaf extracts in treating thrombocytopenia. We have identified 124 phytocompounds that are present in the papaya leaf extract. The pharmacokinetics, molecular docking, binding free energy calculations, and molecular dynamic simulations were performed to investigate the drug-like properties, binding affinities, and interaction of phytocompounds with NS1 protein as well as the interactions of NS1 with TLR4. Three phytocompounds were found to bind with the ASN130, a crucial amino acid residue in the active site of the NS1 protein. Thus, we conclude that Rutin, Myricetin 3-rhamnoside, or Kaempferol 3-(2''-rhamnosylrutinoside) may serve as promising molecules by ameliorating thrombocytopenia in dengue-infected patients by interfering the interaction of NS1 with TLR4. These molecules can serve as drugs in the management of dengue-associated thrombocytopenia after verifying their effectiveness and assessing the drug potency, through additional in-vitro assays.Communicated by Ramaswamy H. Sarma.

Exploring molecular dynamic indicators associated with reproductive performance of Bos indicus cattle in blood plasma samples through data-independent acquisition mass spectrometry.

Improving reproductive performance of cattle is of paramount importance for sustainable dairy farming. Poor reproduction performance (RP) hinders the genetic improvement of important Bos indicus cattle breeds. It is well known that incorporation of molecular information along with conventional breeding method is far better than use of conventional method alone for the genetic improvement of reproductive performance traits in cattle. Therefore, the present study sought to investigate the plasma proteome of the Deoni cows in cyclical (n = 6) and pregnant (n = 6) reproductive phases with varying reproductive performance (high and low). High-throughput data independent acquisition (DIA) based proteomics was performed to understand corresponding proteome. We identified a total of 430 plasma proteins. Among cyclic cows, twenty proteins were differentially regulated in low RP as compared to high RP. BARD1 and AFP proteins were observed upregulated in cyclical cows whose upregulation reported to affect reproductive performance in cattle. Among the pregnant cows, thirty-five proteins were differentially regulated, including the downregulation of FGL2 and ZNFX1 that modulates the maternal immune response mechanism which is required for successful implantation of the embryo. Also, proteins such as AHSG, CLU and SERPINA6 were upregulated in the pregnant cows whose upregulation reported to reduced reproductive performance. The results of this study will be helpful in establishing a framework for future research on the aspect of improving reproductive performance in Bos indicus cattle breeds. SIGNIFICANCE: The Indian subcontinent is the center of domestication for Bos indicus cattle breeds and they are known for their disease resistance, heat tolerance, ability to survive in low input regime and harsh climatic conditions. In recent times, population of many important Bos indicus breeds including Deoni cattle is declining due to various factors, especially due to reproductive performance. Traditional breeding methods are not sufficient enough to understand and improve the reproductive performance traits in important Bos indicus cattle breeds. Proteomics approach is a promising technology to understand the complex biological factors which leads to poor reproductive performance in cattle. The present study utilized DIA based LC- MS/MS analysis to identify the plasma proteins associated with reproductive performance in cyclical and pregnant cows. This study if improved further, can be used to develop potential protein markers associated with reproductive performance which is useful for the selection and genetic improvement of important Bos indicus breeds.

Mining proteomics data to extract post-translational modifications associated with gastric cancer.

Gastric cancers are highly heterogeneous, deep-seated tumours associated with late diagnosis and poor prognosis. Post-translational modifications (PTMs) of proteins are known to be well-associated with oncogenesis and metastasis in most cancers. Several enzymes which drive PTMs have also been used as theranostics in cancers of the breast, ovary, prostate and bladder. However, there is limited data on PTMs in gastric cancers. Considering that experimental protocols for simultaneous analysis of multiple PTMs are being explored, a data-driven approach involving reanalysis of mass spectrometry-derived data is useful in cataloguing altered PTMs. We subjected publicly available mass spectrometry data on gastric cancer to an iterative searching strategy for fetching PTMs including phosphorylation, acetylation, citrullination, methylation and crotonylation. These PTMs were catalogued and further analyzed for their functional enrichment through motif analysis. This value-added approach delivered identification of 21,710 unique modification sites on 16,364 modified peptides. Interestingly, we observed 278 peptides corresponding to 184 proteins to be differentially abundant. Using bioinformatics approaches, we observed that majority of these altered PTMs/proteins belonged to cytoskeletal and extracellular matrix proteins, which are known to be perturbed in gastric cancer. The dataset derived by this mutiPTM investigation can provide leads to further investigate the potential role of altered PTMs in gastric cancer management.