Biology subjects

Subedi, S.

Publications and source records attributed to Subedi, S..

13 recordsLinked to original sources

bioRxiv2026

Chemokine receptor activity is differentially regulated by membrane cholesterol

Cholesterol is a key membrane component that regulates G protein-coupled receptor (GPCR) function, yet its molecular mechanisms remain unclear. Here, we combine chemical extraction of membrane sterols with functional signaling assays and single-molecule fluorescence resonance energy transfer (smFRET) to define how cholesterol controls activation of chemokine receptors. Reduction of membrane cholesterol in mammalian cells selectively decreased constitutive and agonist-induced signaling across CXCR1, CXCR2, CXCR4, while it activated ACKR3, and did not affect CXCR3, revealing receptor-specific dependence on membrane sterols. Mechanistically, cholesterol regulation partly required the conserved class A GPCR residue Trp4.50 and shifted agonist-bound CXCR4 toward active conformational states, providing a molecular explanation for its functional effects. In contrast, replenishment with oxidized cholesterol species failed to restore receptor activity, distinguishing cholesterol from oxysterols as modulators of receptor activation. Our findings identify cholesterol as an allosteric regulator of chemokine receptors and suggest that oxysterols may reshape inflammatory signaling by selectively modulating GPCR activity.

biochemistry↗

bioRxiv2025

Cnpy1 is a candidate endoplasmic reticulum chaperone of Vomeronasal type 2 GPCRs.

Mouse vomeronasal sensory neurons are continuously generated from stem cells and differentiate to express either V1R or V2R G-protein coupled receptors (GPCRs), along with their respective Gi2 or Go G-protein subunits. We previously reported that Go-type neurons exhibit elevated expression of endoplasmic reticulum (ER) chaperones and a distinctive hypertrophic, gyroid ER architecture, suggesting specialized proteostatic demands. Here we identify a transcript for the mouse Cnpy1 gene that yields full-length Cnpy1 protein selectively expressed in and localized to the ER of Go neurons. Immunoprecipitation coupled with mass spectrometry revealed that Cnpy1 associates specifically with V2R GPCRs and multiple ER chaperones. Cnpy1 deletion resulted in mice that were deficient in Go neuronal activation upon exposure to vomeronasal stimuli and a marked reduction in male-male aggressive behavior. In the absence of Cnpy1, Go neurons develop normally till birth but undergo selective, progressive apoptosis during postnatal development. Unexpectedly, Cnpy1-null vomeronasal neurons displayed neither an obvious unfolded protein response nor defects in V2R GPCR traffic to dendritic tips, indicating that Cnpy1 is required for V2R assembly or functional maturation but dispensable for their ER export. Together, these findings identify Cnpy1 as a previously unrecognized component of an ER chaperone complex that is essential for Go neuron signaling and survival.

neuroscience↗

bioRxiv2025

EXTRACTION, ISOLATION, PURIFICATION AND OPTIMIZATION OF AMYLASE AND PROTEASE ENZYMES ISOLATED FROM Bacillus species

BackgroundAmylase and protease are two of the most demanded and widely used commercial enzymes. Amylases have many industrial uses: starch conversion (food/bakery industry), sizing agent (textile industry and paper industry), degradation of starchy residue from clothes (detergent industry), conversion of starch to fermentable sugar (fuel industry) etc. Their main source is of microbial origin. About two-third of the industrial enzymes (amylase, protease, cellulose, penicillinase, chitinase, nucleases, esterase, lipase etc.) are produced by Bacillus spp. Among bacteria, Bacillus species are specific producers of extracellular enzymes. ObjectiveThe present work comprised the identification of amylase and protease producing Bacillus spp and exposure of the producers to various parameters for the maximum yield of the enzyme. MethodsTo isolate and identify the amylase and protease producing strain, soil samples were collected from different vegetation from the altitude at 4367.35 feet above sea level. The isolates were screened and various biochemical tests and morphological observations were done to identify the isolates. The enzymes were produced by the submerged state fermentation (SmF) from the isolates and purified by dialysis. Effects of temperature, pH, and different carbon and nitrogen sources of the medium using SmF were optimized. ResultsAmong 95 isolates, 36 were identified. Among the identified isolates, Bacillus subtilis and Bacillus thuringiensis were optimized for the amylase and protease production respectively. The maximum amylase production was found at 42C temperature, in fructose as a carbon sugar, peptone as a nitrogen source and at pH 7. Similarly, the maximum protease production was found at 42C temperature, in sucrose as a carbon sugar, ammonium sulphate as a nitrogen source. The producers inhabited the soil of leguminous plant. ConclusionIn the present study, a natural polymer gelatin is used with the nutrient agar medium to help in cell immobilization for maximum production of alkaline protease by strains of Bacillus. More sophisticated process of purification might yield more enzyme compared to the dialysis in our process that yield 42U/ml/min and 52U/ml/min respectively.

microbiology↗

bioRxiv2025

Structural Insights into Allosteric Regulation of GdpP: A Conformationally Dynamic Phosphodiesterase

The phosphodiesterase GdpP is a central regulator of the bacterial second messenger c-di-AMP and a key driver of antibiotic resistance in pathogenic Firmicutes. GdpP integrates environmental signals through its sensory PAS domain to control its C-terminal catalytic domain activity, but the molecular basis for this allosteric communication has remained unknown due to the lack of structural data for the complete cytosolic region. Here, we present the first Cryo-EM structures of the cytosolic region of Streptococcus mutans GdpP (SmGdpP74) in multiple conformational states, revealing a sophisticated tetrameric architecture that enables asymmetric catalytic regulation. Our structural and functional analyses demonstrate that SmGdpP74 operates through substrate-induced conformational transition, with the DHHA1 domain interface serving as the primary determinant of asymmetric catalysis. The non-canonical GGDEF domain functions as a tetrameric scaffolding hub that positions the DHH-DHHA1 catalytic domains, representing the first detailed example of a GGDEF domain repurposed to stabilize heterologous catalytic domains. We identify a flexible GGDEF-DHH linker as a critical coupling element that transmits conformational signals between domains, with the conserved KRSR motif acting as a molecular switch for heme-mediated inhibition. Additionally, the flexibility of this linker is essential for the enzymes catalytic activity. Based on these findings, we propose a comprehensive mechanistic model where SmGdpP74 integrates substrate availability with conformational changes for efficient hydrolysis and allosteric control of its enzymatic activity through the PAS domain. These structural insights provide a foundation for rational drug design targeting allosteric regulatory mechanisms in GdpP, potentially offering new approaches to combat antibiotic resistance in pathogenic Firmicutes.

molecular biology↗

bioRxiv2024

A highly scalable approach to topic modelling in single-cell data by approximate pseudobulk projection

Probabilistic topic modelling has become essential in many types of single-cell data analysis. Based on probabilistic topic assignments in each cell, we identify the latent representation of cellular states, and topic-specific gene frequency vectors provide interpretable bases to be compared with known cell-type-specific marker genes. However, fitting a topic model on a large number of cells would require heavy computational resources-specialized computing units, computing time and memory. Here, we present a scalable approximation method customized for single-cell RNA-seq data analysis, termed ASAP, short for Annotating Single-cell data by Approximate Pseudobulk estimation. Our approach is more accurate than existing methods but requires orders of magnitude less computing time, leaving much lower memory consumption. We also show that our approach is widely applicable for atlas-scale data analysis; our method seamlessly integrates single-cell and bulk data in joint analysis, not requiring additional preprocessing or feature selection steps.

bioinformatics↗

bioRxiv2023

Computational Assessment of Aromatase: Unmasking Therapeutic Avenues for Female Hormonal Disorders

Women of reproductive age widely experience the physical, mental, and emotional effects of hormonal imbalances. The levels of two hormones, estrogen, and progesterone, were particularly high. When these two hormones are unbalanced, symptoms such as irregular menstrual cycles, pelvic pain, and uterine fibroids can appear. Statistics show that 80 percent of women have hormonal imbalances. The creation of novel disease-containing drug candidates may be facilitated by computer-aided drug design (CADD), as many drugs and surgical treatments have unique adverse effects. Achieving good data coverage requires an optimized process for protein identification and enhanced selection techniques for medicinal compounds, including their metabolic characterization. In this study, aromatase is the prioritized protein that acted as a rate-limiting enzyme in steroidogenesis. To maintain its expression and regulation to control estrogen production, natural compounds were retrieved from the ZINC15 database through ADME/TOX property filtration. Compound B, specifically designated as (1R,3S,6S,7S,10S,11R)-7-[(dimethylamino)methyl]-3,12-dimethyl-2,9-dioxatetracyclo [9.3.0.01,3.06,10] tetradec-12-en-8-one, exhibits remarkable therapeutic potential, as evidenced by its inability to inhibit S-adenosyl methionine (SAM) biosynthesis, the observed stability of molecular interactions based on Density Functional Theory (DFT), and a favorable energy gap between molecular orbital stages. This research can be employed as a utility module for fast screening of drug-like molecules and taking these leads forward to clinical trials, assessing their value as potential suitors for drug repurposing against female hormonal disorders.

bioinformatics↗

bioRxiv2023

Polygenic adaptation to overnutrition reveals a role for cholinergic signaling in longevity

Overnutrition by high-sugar (HS) feeding reduces both the lifespan and healthspan across taxa. Pressuring organisms to adapt to overnutrition can highlight genes and pathways important for the healthspan in stressful environments. We used an experimental evolution approach to adapt four replicate, outbred population pairs of Drosophila melanogaster to a HS or control diet. Sexes were separated and aged on either diet until mid-life, then mated to produce the next generation, allowing enrichment for protective alleles over time. All HS-selected populations increased their lifespan and were therefore used as a platform to compare allele frequencies and gene expression. Pathways functioning in the nervous system were overrepresented in the genomic data and showed evidence for parallel evolution, although very few genes were the same across replicates. Acetylcholine-related genes, including the muscarinic receptor mAChR-A, showed significant changes in allele frequency in multiple selected populations and differential expression on a HS diet. Using genetic and pharmacological approaches, we show that cholinergic signaling affects Drosophila feeding in a sugar-specific fashion. Together, these results suggest that adaptation produces changes in allele frequencies that benefit animals under conditions of overnutrition and that it is repeatable at the pathway level.

genetics↗

bioRxiv2022

Repurposing of Drugs against mutated strain of Eurasian Avian like H1N1 (EA H1N1) Swine flu, Genotype-4 (G4) virus

Mutation, reassortment and recombination have led to the evolution and the emergence of more pathogenic and new subtypes of influenza virus. The surge of highly mutated viruses has prompted the need of coherent solution for the so called "medical holocaust" viral outbreaks. The genotype 4 of EAH1N1 strain has been circulating in the swine population as a dominant genotype, exhibiting even human to human transmission. This has risen the possibility of causing another global health threat as a lethal viral outbreak in the future. The Computer Aided Drug Discovery (CADD) could be a prudent mechanism to develop new drug candidates against such disease for its mitigation. In this regard, the computational in silico methods had been envisaged in this research for the prediction of lead compounds against the selected proteins of EA H1N1 G4 strain, namely Haemagglutinin (HA) and Polymerase acidic protein(PA). The research focused on the selection of the target viral protein and molecular docking for the identification of putative ligands. It was followed by the identification of the probable mutations and assessment of effectiveness of identified drugs against their respective targets. Total of 3 compounds Enalapril, Enalaprilat and Ivabradine have been identified as a potential inhibitor of HA and PA protein that were prioritized on the basis of preference index parameter and binding energy of compound with the respective target. Besides, the probable mutations in each target protein in future were predicted and all these 3 top hits were found to be effective against mutated variant of these proteins. Thus, Enalapril, Enalaprilat and Ivabradine could be the lead compounds to explore further as multi target inhibiting drugs against wild and mutant variant of target proteins.

bioinformatics↗

bioRxiv2022

SPRUCE: Single-cell Pairwise Relationships Untangled by Composite Embedding model

In multi-cellular organisms, cell identity and functions are primed and refined through interactions with other surrounding cells. Here, we propose a scalable machine learning method, termed SPRUCE, which is designed to systematically ascertain common cell-cell communication patterns embedded in single-cell RNA-seq data. We applied our approach to investigate tumour microenvironments consolidating multiple breast cancer data sets and found seven frequently-observed interaction signatures and underlying gene-gene interaction networks. Our results implicate that a part of tumour heterogeneity, especially within the same subtype, is better understood by differential interaction patterns rather than the static expression of known marker genes.

bioinformatics↗

bioRxiv2021

Analysis of the ARTIC version 3 and version 4 SARS-CoV-2 primers and their impact on the detection of the G142D amino acid substitution in the spike protein

The ARTIC Network provides a common resource of PCR primer sequences and recommendations for amplifying SARS-CoV-2 genomes. The initial tiling strategy was developed with the reference genome Wuhan-01, and subsequent iterations have addressed areas of low amplification and sequence drop out. Recently, a new version (V4) was released, based on new variant genome sequences, in response to the realization that some V3 primers were located in regions with key mutations. Herein, we compare the performance of the ARTIC V3 and V4 primer sets with a matched set of 663 SARS-CoV-2 clinical samples sequenced with an Illumina NovaSeq 6000 instrument. We observe general improvements in sequencing depth and quality, and improved resolution of the SNP causing the D950N variation in the spike protein. Importantly, we also find nearly universal presence of spike protein substitution G142D in Delta-lineage samples. Due to the prior release and widespread use of the ARTIC V3 primers during the initial surge of the Delta variant, it is likely that the G142D amino acid substitution is substantially underrepresented among early Delta variant genomes deposited in public repositories. In addition to the improved performance of the ARTIC V4 primer set, this study also illustrates the importance of the primer scheme in downstream analyses. ImportanceARTIC Network primers are commonly used by laboratories worldwide to amplify and sequence SARS-CoV-2 present in clinical samples. As new variants have evolved and spread, it was found that the V3 primer set poorly amplified several key mutations. In this report, we compare the results of sequencing a matched set of samples with the V3 and V4 primer sets. We find that adoption of the ARTIC V4 primer set is critical for accurate sequencing of the SARS-CoV-2 spike region. The absence of metadata describing the primer scheme used will negatively impact the downstream use of publicly available SARS-Cov-2 sequencing reads and assembled genomes.

bioinformatics↗

bioRxiv2020

Molecular Architecture of Early Dissemination and Evolution of the SARS-CoV-2 Virus in Metropolitan Houston, Texas

We sequenced the genomes of 320 SARS-CoV-2 strains from COVID-19 patients in metropolitan Houston, Texas, an ethnically diverse region with seven million residents. These genomes were from the viruses causing infections in the earliest recognized phase of the pandemic affecting Houston. Substantial viral genomic diversity was identified, which we interpret to mean that the virus was introduced into Houston many times independently by individuals who had traveled from different parts of the country and the world. The majority of viruses are apparent progeny of strains derived from Europe and Asia. We found no significant evidence of more virulent viral types, stressing the linkage between severe disease, underlying medical conditions, and perhaps host genetics. We discovered a signal of selection acting on the spike protein, the primary target of massive vaccine efforts worldwide. The data provide a critical resource for assessing virus evolution, the origin of new outbreaks, and the effect of host immune response. SignificanceCOVID-19, the disease caused by the SARS-CoV-2 virus, is a global pandemic. To better understand the first phase of virus spread in metropolitan Houston, Texas, we sequenced the genomes of 320 SARS-CoV-2 strains recovered from COVID-19 patients early in the Houston viral arc. We identified no evidence that a particular strain or its progeny causes more severe disease, underscoring the connection between severe disease, underlying health conditions, and host genetics. Some amino acid replacements in the spike protein suggest positive immune selection is at work in shaping variation in this protein. Our analysis traces the early molecular architecture of SARS-CoV-2 in Houston, and will help us to understand the origin and trajectory of future infection spikes.

genetics↗

bioRxiv2020

Using whole-genome sequencing and a pentaplex real-time PCR to characterize third-generation cephalosporin-resistant Enterobacteriaceae from Southeast Queensland, Australia

SynopsisThird-generation cephalosporin-resistant (3GC-R) Enterobacteriaceae represent a major threat to human health. Here, we captured 288 3GC-R Enterobacteriaceae clinical isolates from 264 patients presenting at a regional Australian hospital over a 14-month period. Alongside routine mass spectrometry speciation and antibiotic sensitivity testing, isolates were examined using rapid ([~]40 min) real-time PCR assays targeting the most common extended spectrum {beta}-lactamases (ESBLs; CTX-M-1 and CTX-M-9 groups, plus TEM, SHV, and an internal 16S ribosomal DNA control). AmpC CMY {beta}-lactamase prevalence was also examined. Escherichia coli (80.2%) and Klebsiella pneumoniae (17.0%) were dominant, with Klebsiella oxytoca, Klebsiella aerogenes and Enterobacter cloacae infrequently identified. Ceftriaxone and cefoxitin resistance were identified in 97.0% and 24.5% of E. coli and K. pneumoniae isolates, respectively. Consistent with global findings in Enterobacteriaceae, most (98.3%) isolates harbored at least one {beta}-lactamase gene, with 144 (50%) encoding blaCTX-M-1 group, 92 (31.9%) blaCTX-M-9 group, 48 (16.7%) blaSHV, 133 (46.2%) blaTEM, and 34 (11.8%) blaCMY. A subset of isolates (n=98) were subjected to whole-genome sequencing (WGS) to identify the presence of cryptic resistance determinants, and to verify genotyping accuracy. WGS of {beta}-lactamase negative or carbapenem-resistant isolates identified uncommon ESBLs and carbapenemases, including blaNDM and blaIMP, and confirmed all PCR-positive genotypes. We demonstrate that our PCR assays enable the rapid and cost-effective identification of ESBLs in the hospital setting, which has important infection control and therapeutic implications.

microbiology↗

bioRxiv2020

Cell cycle-associated expression patterns predict gene function in mycobacteria

While the major events in prokaryotic cell cycle progression are likely to be coordinated with transcriptional and metabolic changes, these processes remain poorly characterized. Unlike many rapidly-growing bacteria, DNA replication and cell division are temporally-resolved in mycobacteria, making these slow-growing organisms a potentially useful system to investigate the prokaryotic cell cycle. To determine if cell-cycle dependent gene regulation occurs in mycobacteria, we characterized the temporal changes in the transcriptome of synchronously replicating populations of Mycobacterium tuberculosis (Mtb). By enriching for genes that display a sinusoidal expression pattern, we discover 485 genes that oscillate with a period consistent with the cell cycle. During cytokinesis, the timing of gene induction could be used to predict the timing of gene function, as mRNA abundance was found to correlate with the order in which proteins were recruited to the developing septum. Similarly, the expression pattern of primary metabolic genes could be used to predict the relative importance of these pathways for different cell cycle processes. Pyrimidine synthetic genes peaked during DNA replication and their depletion caused a filamentation phenotype that phenocopied defects in this process. In contrast, the IMP dehydrogenase guaB2 dedicated to guanosine synthesis displayed the opposite expression pattern and its depletion perturbed septation. Together, these data imply obligate coordination between primary metabolism and cell division, and identify periodically regulated genes that can be related to specific cell biological functions.

microbiology↗