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Narayan, R.

Publications and source records attributed to Narayan, R..

At least 19 recordsLinked to original sources

Inhibitors of gut bacterial L-dopa decarboxylation with reduced susceptibility to host metabolism

Microorganisms in the human gut influence the efficacy and metabolism of host-targeted small molecule therapeutics, including the frontline Parkinson's disease drug levodopa (L-dopa). Previous work has identified a mechanism-based inhibitor of gut bacterial decarboxylases that degrade L-dopa, -fluoromethyltyrosine (AFMT). However, early experiments with AFMT in rodent models suggested undesirable in vivo metabolism by host tyrosine hydroxylase, producing -fluoromethyldopa, a metabolite likely to worsen Parkinson's phenotypes and prevent application as an L-dopa co-treatment. Here, we demonstrate oxidation of AFMT to -fluoromethyldopa in vitro by recombinant human tyrosine hydroxylase. We then develop AFMT analogs that retain activity against bacterial decarboxylases but have reduced susceptibility to host hydroxylation. Suitable arenes for inhibitor design were identified using assays with commercially available noncanonical amino acids, which revealed aryl difluorination as a promising modification. Difluoroaryl AFMT derivatives are less prone to degradation by tyrosine hydroxylase in vitro yet still inhibit L-dopa metabolism by bacterial decarboxylases. This work exemplifies how substrate reactivity can streamline design of mechanism-based enzyme inhibitors, as well as how constraints posed by the host can be incorporated during development of microbiome-targeted therapeutics. The compounds reported here are promising starting points for future studies in animal models and further exploration of gut bacterial effects on L-dopa treatment efficacy.

microbiology↗

Broad protection against Influenza A Viruses via an adjuvant-free mucosal microparticle vaccine with conserved CD8/CD4 bispecific peptides

Rapid antigenic evolution of Influenza A viruses (IAVs) enables their escape from strain-specific vaccine immunity and underscores the need for broadly protective strategies. Here, we describe a modular, adjuvant-free mucosal vaccine platform that elicits potent and cross-protective T cell immunity. The approach uses overlapping CD4+ and CD8+ epitope-dense regions from the consensus IAV M1 and NP proteins, identified through computational and functional screening. These peptides are delivered using polylactic-co-glycolic acid (PLGA) microparticles, engineered for selective uptake by antigen-presenting cells and enable sustained, pH-responsive antigen release. This design enhances antigen processing and MHC cross-presentation, functionally substituting for a conventional adjuvant. This formulation drives robust activation of primed human as well as murine CD4+ and CD8+ T cells and confers broad protection against homologous (H1N1, H3N2) as well as heterologous (H5N1) IAV strains in immunized mice. Overall, this adjuvant-free dose-sparing platform establishes an adaptable framework for next-generation broadly-protective vaccines against rapidly-evolving viruses. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/715080v2_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@19fafedorg.highwire.dtl.DTLVardef@d73109org.highwire.dtl.DTLVardef@1d486edorg.highwire.dtl.DTLVardef@1e663c8_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

An Oral Combination therapy against SARS-CoV-2 based on Synergistic Action of Auranofin and Remdesivir.

The combination of direct-acting and host-directed antivirals targeting SARS-CoV-2 represents an attractive treatment strategy to combat COVID-19. In our previous work, we showed that the FDA-approved anti-arthritis drug Auranofin restricts SARS-CoV-2 replication and pathology in an animal model. Here, we report that Auranofin inhibits SARS-CoV-2 by targeting viral entry and main protease (Mpro) activity without affecting viral transcription. Time-of-addition studies combined with functional assays of viral entry, protease activity, and cell-cell fusion delineated its inhibitory effects at both early and late stages of the viral life cycle. Molecular docking and isothermal titration calorimetry analyses of Auranofin and the known Mpro inhibitor Nirmatrelvir indicated competitive binding within the Mpro active-site pocket. In addition, Auranofin attenuated NF-{kappa}B-dependent signalling and suppressed proinflammatory cytokine production. Combination studies with SARS-CoV-2 targeting nucleoside analogues, revealed the strongest synergistic antiviral activity with remdesivir in vitro. Comparable synergy was observed between auranofin and GS-621763, the orally bioavailable derivative of remdesivir, and was further validated in a preclinical animal model. Collectively, these findings provide a rationale for the further development of auranofin-nucleoside analog combinations targeting SARS-CoV-2. FundingThis research has been supported by ICMR (IIRPIG-2023-0000978) and BIRAC grant (BT/CS0070/06/22) to ST. We acknowledge the infrastructure and research support provided to IISc by the Crypto Relief Fund, L&T Trust, DST-FIST program, Institute of Eminence Fund, Ministry of Education, and the DBT-IISc partnership program (Phase II). RN acknowledges DBT-RA fellowship, SK acknowledges PMRF fellowship, and RS acknowledges FICCI-PMRF fellowship. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSMultiple previous studies have provided evidence showing that auranofin is an antiviral agent targeting SARS-CoV-2 through a host-targeting mechanism, involving the inhibition of thioredoxin reductase and redox homeostasis. Mixed results have been reported regarding the effect of this drug on inhibiting virus-induced syncytia. A prior study from our lab demonstrated the drugs effectiveness in reducing SARS-CoV-2 viral loads in both cell and animal models. Added value of the studyOur study firmly establishes the synergistic use of Auranofin and Remdesivir GS 621763 in the treatment of SARS-CoV-2 infection.

microbiology↗

Differential modulation of Interferon and Cell Death Responses defines Human vs Avian Influenza A Virus Strain-Specific Virulence and guides Combination Therapy.

Influenza A virus (IAV) poses a significant global health risk, with highly pathogenic strains like H5N1 (CFR [~]52%) causing severe disease compared to less lethal but more transmissible strains like H1N1 (CFR 0.01-0.03%). Although IAV primarily infects lung epithelial cells, causing cell death and tissue damage, the molecular basis of strain-specific pathogenesis remains poorly understood. Here we show that in cell culture, H5N1 induced more rapid and extensive cell death than H1N1. Since Interferon (IFN) signaling is key to innate immunity, we examined its role in virus-induced cell death using STAT1-knockout A549 cells and JAK/STAT pathway inhibitors like Baricitinib. Both approaches reduced cell death across various IAV strains, including H1N1, H5N1, H7N9, and H3N2. However, inhibition increased viral titers, raising concerns about its clinical use in isolation. To overcome this, we tested a combination of Oseltamivir (antiviral) and Baricitinib (anti-inflammatory). Post-infection treatment in a murine model reduced lung inflammation and improved survival. Given that both drugs are FDA-approved, this approach has strong translational potential for clinical IAV treatment.

microbiology↗

The role of mitochondrial complex I in the proinflammatory response to polylactide implants

During the foreign body response, immune cells are metabolically rewired after exposure to breakdown products of various biomaterials, including polylactide (PLA) and polyethylene. Particles of polyethylene interact with Toll-like receptor 4 on macrophages, resulting in increased oxygen consumption that forms reactive oxygen species at complex I of the mitochondrial electron transport chain (mETC). However, PLA degradation products bind to monocarboxylate transporters for downstream signaling with elevated oxygen consumption rates, whose functional implication is unclear and remains inferred from cellular responses to polyethylene biomaterials. By chemically probing the function of the mETC, we show that proinflammatory macrophages activated by exposure to amorphous PLA (aPLA) breakdown products rely on mitochondrial respiration for ATP production, independent of oxygen consumption rates. In contrast, macrophages activated by semi-crystalline PLA (cPLA) breakdown products exhibit a metabolic phenotype wherein ATP levels are unaffected by changing oxygen consumption rates. In subcutaneous implants, the incorporation of metformin in aPLA or cPLA to chemically inhibit complex I did not effectively modulate the proinflammatory response to biomaterials, suggesting that PLA degradation products elicit a distinct metabolic program, thus providing an alternative perspective on the role of mitochondrial respiration in the inflammatory response to biomaterials.

bioengineering↗

Regulating the proinflammatory response to implanted composite biomaterials comprising polylactide and hydroxyapatite by targeting immunometabolism

Composite biomaterials comprising polylactide (PLA) and hydroxyapatite (HA) are applied in bone, cartilage and dental regenerative medicine, where HA confers osteoconductive properties. However, after surgical implantation, adverse immune responses to these composites can occur, which have been attributed to size and morphology of HA particles. Approaches to effectively modulate these adverse immune responses have not been described. PLA degradation products have been shown to alter immune cell metabolism, which drives the inflammatory response. Therefore, we aimed to modulate the inflammatory response to composite biomaterials by regulating glycolytic flux with small molecule inhibitors incorporated into composites comprised of amorphous PLA (aPLA) and HA (aPLA+HA). Inhibition at specific steps in glycolysis reduced proinflammatory (CD86+CD206-) and increased pro-regenerative (CD206+) immune cell populations around implanted aPLA+HA resulting in a pro-regenerative microenvironment. Notably, neutrophil and dendritic cell (DC) numbers along with proinflammatory monocyte and macrophage populations were decreased, and Arginase 1 expression among DCs was increased. Targeting immunometabolism to control the inflammatory response to biomaterial composites, and creating a pro-regenerative microenvironment, is a significant advance in tissue engineering where immunomodulation enhances osseointegration, and angiogenesis, which will lead to improved bone regeneration.

bioengineering↗

Immunometabolic cues recompose and reprogram the microenvironment around biomaterials

Circulating monocytes infiltrate and coordinate immune responses in various inflamed tissues, such as those surrounding implanted biomaterials, affecting therapeutic, diagnostic, tissue engineering and regenerative applications. Here, we show that immunometabolic cues in the biomaterial microenvironment govern CCR2- and CX3CR1-dependent trafficking of immune cells, including neutrophils and monocytes; ultimately, this affects the composition and activation states of macrophage and dendritic cell populations. Furthermore, immunometabolic cues around implants orchestrate the relative composition of proinflammatory, transitory and anti-inflammatory CCR2+, CX3CR1+ and CCR2+CX3CR1+ immune cell populations. Consequently, modifying immunometabolism by glycolytic inhibition drives a pro-regenerative microenvironment in part by myeloid cells around amorphous polylactide implants. In addition to, Arginase 1-expressing myeloid cells, T helper 2 cells and {gamma}{delta}+ T-cells producing IL-4 significantly contribute to shaping the metabolically reprogramed, pro-regenerative microenvironment around crystalline polylactide biomaterials. Taken together, we find that local metabolic states regulate inflammatory processes in the biomaterial microenvironment, with implications for translational medicine.

bioengineering↗

SARS-CoV-2 variants of concern exhibit differential gastro-intestinal tropism and pathogenesis in the Syrian golden hamster model.

Severe Acute Respiratory Syndrome Virus-2 (SARS-CoV-2) is a respiratory virus that uses angiotensin-converting enzyme 2 (ACE2) protein as an entry receptor. Thus, ACE2 expression levels in different tissues should dictate viral tropism. Notably, human ACE2 mRNA and protein levels are most abundant in the gastrointestinal tract, a pattern mirrored in Syrian golden hamsters. This prompted us to investigate the gastrointestinal tropism of SARS-CoV-2 variants of concern, including the Wuhan-like Hong Kong strain, highly pathogenic Delta, and highly transmissible but mildly pathogenic Omicron variants in hamsters. Delta was the most pathogenic in the respiratory and gastrointestinal tracts, followed by ancestral Wuhan-like and Omicron strains. In the gastrointestinal tract, viral RNA load was significant in the proximal organs such as the oesophagus and stomach, highest in the SI, and minimal to undetectable in the colon. Additionally, all three variants reduced fecal microbial diversity, with the Delta causing the highest decrease in observed features and phylogenetic diversity. Our findings highlight Deltas stronger preference for the gastrointestinal tract, suggesting a link between high virulence and gastrointestinal tropism of SARS-CoV-2 variants of concern.

pathology↗

Stereochemistry Determines Immune Cellular Responses to Polylactide Implants

Repeating L- and D-chiral configurations determine polylactide (PLA) stereochemistry which affects its thermal and physicochemical properties, including degradation profiles. Clinically, degradation of implanted PLA biomaterials promotes prolonged inflammation and excessive fibrosis, but the role of PLA stereochemistry is unclear. Additionally, although PLA of varied stereochemistries cause differential immune responses in-vivo, this observation has yet to be effectively modeled in-vitro. A bioenergetic model was applied to study immune cellular responses to PLA containing > 99% L-lactide (PLLA), > 99% D-lactide (PDLA) and a 50/50 melt-blend of PLLA and PDLA (stereocomplex PLA). Stereocomplex PLA breakdown products increased IL-1{beta}, TNF- and IL-6 protein levels but not MCP-1. Expression of these proinflammatory cytokines is mechanistically driven by increases in glycolysis in primary macrophages. In contrast, PLLA and PDLA degradation products selectively increase MCP-1 protein expression. Whereas both oxidative phosphorylation and glycolysis are increased with PDLA, only oxidative phosphorylation is increased with PLLA. For each biomaterial, glycolytic inhibition reduces proinflammatory cytokines and markedly increases anti-inflammatory (IL-10) protein levels; differential metabolic changes in fibroblasts were observed. These findings provide mechanistic explanations for the diverse immune responses to PLA of different stereochemistries, and underscore the pivotal role of immunometabolism on the biocompatibility of biomaterials applied in medicine.

bioengineering↗

Polylactide Degradation Activates Immune Cells by Metabolic Reprogramming

Polylactide (PLA) is the most widely utilized biopolymer in medicine. However, chronic inflammation and excessive fibrosis resulting from its degradation remain significant obstacles to extended clinical use. Immune cell activation has been correlated to the acidity of breakdown products, yet methods to neutralize the pH have not significantly reduced adverse responses. Using a bioenergetic model, we observed delayed cellular changes that were not apparent in the short-term. Amorphous and semi-crystalline PLA degradation products, including monomeric L-lactic acid, mechanistically remodel metabolism in cells leading to a reactive immune microenvironment characterized by elevated proinflammatory cytokines. Selective inhibition of metabolic reprogramming and altered bioenergetics both reduce these undesirable high cytokine levels and stimulate anti-inflammatory signals. Our results present a new biocompatibility paradigm by identifying metabolism as a target for immunomodulation to increase tolerance to biomaterials, ensuring safe clinical application of PLA-based implants for soft- and hard-tissue regeneration, and advancing nanomedicine and drug delivery.

bioengineering↗

ORF6 protein of SARS-CoV-2 inhibits TRIM25 mediated RIG-I ubiquitination to mitigate type I IFN induction.

Evasion and antagonism of host cellular immunity upon SARS-CoV-2 infection confers a profound replication advantage on the virus and contributes to COVID-19 pathogenesis. We explored the ability of different SARS-CoV-2 proteins to antagonize the host innate immune system and found that the ORF6 protein mitigated type-I IFN (interferon) induction and downstream IFN signaling. Our findings also corroborated previous reports that ORF6 blocks the nuclear import of IRF3 and STAT1 to inhibit IFN induction and signaling. Here we show that ORF6 directly interacts with RIG-I and blocks downstream type-I IFN induction and signaling by inhibiting K-63 linked ubiquitination of RIG-I by the E3 Ligase TRIM25. This involves ORF6-mediated targeting of TRIM25 for degradation, also observed during SARS-CoV-2 infection. The type-I IFN antagonistic activity of ORF6 was mapped to its C-terminal cytoplasmic tail, specifically to amino acid residues 52-61. Overall, we provide new insights into how the SARS-CoV-2 ORF6 protein inhibits type I-IFN induction and signaling through distinct mechanisms.

microbiology↗

A natural broad-spectrum inhibitor of enveloped virus entry, effective against SARS-CoV-2 and Influenza A Virus in preclinical animal models.

The COVID-19 pandemic has highlighted the need for novel antivirals for pandemic management and preparedness. Targeting host processes that are co-opted by viruses is an attractive strategy for developing antivirals with a high resistance barrier. Picolinic acid (PA) is a byproduct of tryptophan metabolism, endogenously produced in humans and other mammals. Here we report broad-spectrum antiviral effects of PA against enveloped viruses, including Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), Influenza A virus (IAV), Flaviviruses, Herpes Simplex Virus, and Human Parainfluenza Virus. We further demonstrate using animal models that PA is effective against SARS-CoV-2 and IAV, especially as an oral prophylactic. The mode of action studies revealed that PA inhibits viral entry of enveloped viruses, primarily by interfering with viral-cellular membrane fusion, inhibiting virus-mediated syncytia formation, and dysregulating cellular endocytosis. Overall, our data establish PA as a broad-spectrum antiviral agent, with promising preclinical efficacy against pandemic viruses SARS-CoV-2 and IAV.

microbiology↗

Drug targeting Nsp1-ribosomal complex shows antiviral activity against SARS-CoV-2

The SARS-Cov-2 non-structural protein 1 (Nsp1) contains an N-terminal domain and C-terminal helices connected by a short linker region. The C-terminal helices of Nsp1 (Nsp1-C-ter) from SARS-Cov-2 bind in the mRNA entry channel of the 40S ribosomal subunit and block the entry of mRNAs thereby shutting down host protein synthesis. Nsp1 suppresses the host immune function and is vital for viral replication. Hence, Nsp1 appears to be an attractive target for therapeutics. In this study, we have in silico screened Food and Drug Administration (FDA)-approved drugs against Nsp1-C-ter and find that montelukast sodium hydrate binds to Nsp1-C-ter with a binding affinity (KD) of 10.8{+/-}0.2 M in vitro and forms a stable complex with it in simulation runs with a binding energy of -76.71{+/-}8.95 kJ/mol. The drug also rescues the inhibitory effect of Nsp1 in host protein synthesis as demonstrated by the expression of firefly luciferase reporter gene in cells. Importantly, montelukast sodium hydrate demonstrates antiviral activity against SARS-CoV-2 with reduced viral replication in HEK cells expressing ACE2 and Vero-E6 cells. We therefore propose montelukast sodium hydrate may help in combatting SARS-CoV-2 infection.

biophysics↗

Meta-analysis of orthogonal OMICs data from COVID-19 patients unveils prognostic markers and antiviral factors.

While our battle with the COVID-19 pandemic continues, a multitude of Omics data has been generated from patient samples in various studies, which remains to be translated. We conducted a meta-analysis of published transcriptome and proteome profiles of nasal swab and bronchioalveolar lavage fluid (BALF) samples of COVID-19 patients, to shortlist high confidence upregulated host factors. Subsequently, mRNA overexpression of selected genes was validated in nasal swab/BALF samples from a cohort of COVID-19 positive/negative, symptomatic/asymptomatic individuals. Analysis of these data revealed S100 family genes (S100A6, S100A8, S100A9, and S100P) as prognostic markers of COVID-19 disease. Furthermore, Thioredoxin gene (TXN) was identified as a significant upregulated host factor in our overlap analysis. An FDA-approved drug Auranofin, which inhibits Thioredoxin reduction, was found to mitigate SARS-CoV-2 replication in vitro and in vivo in the hamster challenge model. Overall, this study translates COVID-19 host response Big Data into potential clinical interventions.

microbiology↗

Improving Deconvolution Methods in Biology through Open Innovation Competitions: An Application to the Connectivity Map

Do machine learning methods improve standard deconvolution techniques for gene expression data? This paper uses a unique new dataset combined with an open innovation competition to evaluate a wide range of gene-expression deconvolution approaches developed by 294 competitors from 20 countries. The objective of the competition was to separate the expression of individual genes from composite measures of gene pairs. Outcomes were evaluated using direct measurements of single genes from the same samples. Results indicate that the winning algorithm based on random forest regression outperformed the other methods in terms of accuracy and reproducibility. More traditional gaussian-mixture methods performed well and tended to be faster. The best deep learning approach yielded outcomes slightly inferior to the above methods. We anticipate researchers in the field will find the dataset and algorithms developed in this study to be a powerful research tool for benchmarking their deconvolution methods and a useful resource for multiple applications.

genomics↗

Non-oncology drugs are a source of previously unappreciated anti-cancer activity

Anti-cancer uses of non-oncology drugs have been found on occasion, but such discoveries have been serendipitous and rare. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. To accomplish this, we used PRISM, which involves drug treatment of molecularly barcoded cell lines in pools. Relative barcode abundance following treatment thus reflects cell line viability. We found that an unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines. Moreover, the killing activity of the majority of these drugs was predictable based on the molecular features of the cell lines. Follow-up of several of these compounds revealed novel mechanisms. For example, compounds that kill by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing is dependent on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which kills cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, whose killing is dependent on high expression of the multi-drug resistance gene ABCB1. These results illustrate the potential of the PRISM drug repurposing resource as a starting point for new oncology therapeutic development. The resource is available at https://depmap.org.

cancer biology↗

Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions

Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant performance gains over established algorithms. These include algorithms for antibody clustering, imputing gene expression data, and querying the Connectivity Map (CMap). Performance gains are evaluated quantitatively using realistic, albeit sanitized, data sets. The solutions produced through these competitions are then examined with respect to their utility and the prospects for implementation in the field. We present the decision process and competition design considerations that lead to these successful outcomes as a model for researchers who want to use competitions and non-domain crowds as collaborators to further their research.

bioinformatics↗

Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases

Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the "Disease Module Identification DREAM Challenge", an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology, and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies (GWAS). Our critical assessment of 75 contributed module identification methods reveals novel top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets and correctly prioritize candidate disease genes. This community challenge establishes benchmarks, tools and guidelines for molecular network analysis to study human disease biology (https://synapse.org/modulechallenge).

bioinformatics↗