Biology subjects

Joshi, C.

Publications and source records attributed to Joshi, C..

At least 19 recordsLinked to original sources

bioRxiv2025

Clinical Exposure Normalization Restores Translational Predictiveness of In Vitro Drug Response

Single-agent clinical response data for widely used chemotherapies have remained difficult to analyze because they are scattered across decades of print literature. We consolidated these sources into NCI1970-Meta, a 49,002-patient dataset covering 30 drugs across 18 cancers, enabling the first quantitative comparison of clinical outcomes, laboratory potency metrics, clinical exposure, and literature-derived biomarkers. Clinical patterns were strongly lineage-driven: cancer type explained far more ORR variability than drug identity (37.3% vs 15.6%; F = 13.43 vs 3.29). FDA approvals reflected these same patterns where ORR strongly predicted indication status (F = 98.3-104.1). In contrast, laboratory efficacy metrics did not track clinical activity. Raw in vitro AUC showed no association with ORR (R2 = 0.00; 95% CI: 0.00-0.01) and was dominated by drug identity rather than cancer lineage (85.2% vs 8.6%; F = 212.2 vs 21.6). Instead, AUC correlated with clinical exposure: unbound Cmax (R2 = 0.21 [0.21-0.34]) and therapeutic minimum concentrations (R2 = 0.69 [0.64-0.73]). This indicates that standard assay ranges capture exposure requirements rather than true efficacy. Normalizing potency by exposure restored the expected clinical relationships and resolved drug-specific anomalies such as gemcitabine. Biomarkers showed consistent behavior across clinical and laboratory settings. Among 314 biomarker-drug pairs, correlation directions were significantly conserved (R2 = 0.17 [0.10-0.25]; p = 2.8x10-14). Literature-defined sensitivity and resistance annotations were enriched in vitro (OR = 3.7; p = 2.36x10-8) and in the clinic (OR = 3.9; p = 6.52x10-9), with stronger performance for correlations >0.1 (OR = 13.3 in vitro; OR = 8.4 clinically). Simple biomarker-sum models performed well across drugs, consistent with multi-pathway pseudo-first-order behavior. Overall, NCI1970-Meta provides a quantitative framework linking laboratory pharmacology to real-world clinical efficacy. Biological signal is reliably preserved within drugs, while cross-drug comparisons require explicit exposure normalization. This resource offers a statistical foundation for improving drug prioritization, biomarker development, and translational pharmacodynamic modeling.

pharmacology and toxicology↗

bioRxiv2024

Spatial distribution of poultry farms using point pattern modelling: a method to address livestock environmental impacts and disease transmission risks

The distribution of farm locations and sizes is paramount to characterize patterns of disease spread. With some regions undergoing rapid intensification of livestock production, resulting in increased clustering of farms in peri-urban areas, measuring changes in the spatial distribution of farms is crucial to design effective interventions. However, those data are not available in many countries, their generation being resource-intensive. Here, we develop a farm distribution model (FDM), which allows the prediction of locations and sizes of poultry farms in countries with scarce data. The model combines (i) a Log-Gaussian Cox process model to simulate the farm distribution as a spatial Poisson point process, and (ii) a random forest model to simulate farm sizes (i.e. the number of animals per farm). Spatial predictors were used to calibrate the FDM on intensive broiler and layer farm distributions in Bangladesh, Gujarat (Indian state) and Thailand. The FDM yielded realistic farm distributions in terms of spatial clustering, farm locations and sizes, while providing insights on the factors influencing these distributions. Finally, we illustrate the relevance of modelling realistic farm distributions in the context of epidemic spread by simulating pathogen transmission on an array of spatial distributions of farms. We found that farm distributions generated from the FDM yielded spreading patterns consistent with simulations using observed data, while random point patterns underestimated the probability of large outbreaks. Indeed, spatial clustering increases vulnerability to epidemics, highlighting the need to account for it in epidemiological modelling studies. As the FDM maintains a realistic distribution of farm location and sizes, its use to inform mathematical models of disease transmission is particularly relevant for regions where these data are not available.

bioinformatics↗

bioRxiv2023

A "through-DNA" mechanism for metal uptake-vs.-efflux regulation

Transition metals like Zn are essential for all organisms including bacteria, but fluctuations of their concentrations in the cell can be lethal. Organisms have thus evolved complex mechanisms for cellular metal homeostasis. One mechanistic paradigm involves pairs of transcription regulators sensing intracellular metal concentrations to regulate metal uptake and efflux. Here we report that Zur and ZntR, a prototypical pair of regulators for Zn uptake and efflux in E. coli, respectively, can coordinate their regulation through DNA, besides sensing cellular Zn2+ concentrations. Using a combination of live-cell single-molecule tracking and in vitro single-molecule FRET measurements, we show that unmetallated ZntR can enhance the unbinding kinetics of Zur from DNA by directly acting on Zur-DNA complexes, possibly through forming heteromeric ternary and quaternary complexes that involve both protein-DNA and protein-protein interactions. This through-DNA mechanism may functionally facilitate the switching in Zn uptake regulation when bacteria encounter changing Zn environments; it could also be relevant for regulating the uptake-vs.-efflux of various metals across different bacterial species and yeast.

biophysics↗

bioRxiv2023

Unravelling Genomic Origin of Lumpy Skin Disease Virus in Recent Outbreaks

Lumpy skin disease virus (LSDV) belongs to the genus Capripox virus and family Poxviridae. LSDV was endemic in most of Africa, Middle east and Turkey, but since 2015, several outbreaks have been reported in Asian countries. In this study we used Whole Genome Sequence (WGS) approach to investigate the origin of the outbreak and understand the genomic landscape of the virus. Our study showed that the LSDV strain of 2022 outbreak exhibited many genetic variations, compared to the Reference Neethling strain sequence and the previous field strains from India. A total of 1819 variations were found in 22 genome sequences, which includes 399 extragenic mutations, 153 insertion frameshift mutations, 234 deletion frameshift mutations, 271 Single nucleotide polymorphisms (SNPs) and 762 silent SNPs. 38 genes have more than 2 variations per gene and these genes belong to viral-core protein, viral binding proteins, replication and RNA polymerase proteins. We highlight the importance of several SNPs in various genes which may play an essential role in pathogenesis of LSDV. Phylogenetic analysis performed on all whole genome sequences of LSDV showed two types of variants in India. One group of the variant with fewer mutations was found to lie closer to the LSDV 2019 strain from Ranchi while the other group clustered with previous Russian outbreaks from 2015. Our study highlights the importance of genomic characterization of viral outbreaks to not only monitor the frequency of mutations but also address its role in pathogenesis of LSDV as the outbreak continues.

microbiology↗

bioRxiv2023

Chronic industrial perturbation and seasonal change induces shift in the bacterial community from gammaproteobacteria to betaproteobacteria at Amlakhadi canal

Escalating proportions of industrially contaminated sites are one of the major catastrophes faced at the present time due to the industrial revolution. In the outlook of the obstacles associated with culturing the microbes, the direct metagenomic analysis of various complex niches is rapidly gaining attention. In this study, metagenomic approach using next generation sequencing technologies was applied to exemplify the taxonomic abundance and metabolic potential of the microbial community residing in Amlakhadi canal, Ankleshwar at two different seasons. All the metagenomes revealed a predominance of Proteobacteria phylum. However, difference was observed within class level where Gammaproteobacteria was relatively high in polluted metagenome in Summer while in Monsoon the abundance shifted to Betaproteobacteria. Similarly, significant statistical differences were obtained while comparing the genera amongst contaminated sites where Serratia, Achromobacter, Stenotrophomonas and Pseudomonas were abundant at one season and the dominance changed to Thiobacillus, Thauera, Acidovorax, Nitrosomonas, Sulfuricurvum, Novosphingobium, Hyphomonas and Geobacter at the next season. Further upon functional characterization, the microbiomes demonstrated diverse survival mechanisms adapted by the inherent microbial community such as degradation of aromatic compounds, heavy metal resistance, oxidative stress responses and multidrug resistance efflux pumps. The results have important implications in understanding and predicting the impacts of human-induced activities on microbial communities inhabiting natural niche and their responses in coping with the fluctuating pollution load.

microbiology↗

bioRxiv2023

DNA metabarcoding using new rbcL and ITS2 metabarcodes collectively enhance detection efficiency of medicinal plants in single and polyherbal formulations

With the widespread adoption of barcoding and next-generation sequencing, metabarcoding is emerging as a potential tool for detecting labelled and unlabelled plant species in herbal products. In this study, newly designed rbcL and ITS2 metabarcode primers were validated for metabarcoding using in-house mock controls of medicinal plant gDNA pools and biomass pools. The applicability of the multi-barcode sequencing approach was evaluated on 17 single drugs and 15 polyherbal formulations procured from the Indian market. The rbcL metabarcode demonstrated detection efficiencies of 86.7% and 71.7% in gDNA plant pools and biomass mock controls, respectively, while the ITS2 metabarcode demonstrated 82.2% and 69.4%. In the gDNA plant pool and biomass pool mock controls, the cumulative detection efficiency increased by 100% and 90%, respectively. A total of 79% cumulative detection efficiency of both metabarcodes was observed in single drugs, while 76.3% was observed in polyherbal formulations. An average fidelity of 83.6% was observed for targeted plant species present within mock controls as well as in herbal formulations. Our results demonstrated the applicability of multilocus strategies in metabarcoding as a potential tool for detecting labelled and unlabelled plant species in herbal formulations.

molecular biology↗

bioRxiv2022

RNASeq as a tool to understand dysregulation of potential biomarkers in HNSC

With its rising fatality rates, oral cancer is one of the most concerning public health issues. To reduce disease-related mortality and morbidity, advancements in screening and detection are critical. Finding specific biomarkers is one of the most successful approaches for screening, diagnosing, and staging this dreadful disease. In this study differentially expressed genes associated with oral cancer were analyzed using RNASeq to find the potential biomarkers. Functional enrichment of upregulated genes found that 253 genes were present in the plasma membrane. Three clusters were formed using KMean Clustering from the PPI networks, and highly connected hub genes were identified from each cluster. Eventually, expression and survival analyses of hub genes were performed using The Cancer Genome Atlas (TCGA) database targeting Head and Neck Squamous Cell Carcinoma. Among those genes, expression levels of eight genes SLC2A1, ITGA6, LAMC2, COL1A2, COL1A1, TNC, THY1, and CD276 have significantly changed in Head and Neck Squamous cell carcinoma. There are reports that suggest these genes were significantly dysregulated in Oral Squamous cell carcinoma and can be explored further as potential biomarkers for margin clearance.

cancer biology↗

bioRxiv2022

Comprehensive analysis using DNA metabarcoding, PCR, and HPLC unveils the adulteration in Brahmi herbal products

BackgroundThe herbal products market is expanding and creating a bottleneck for raw materials. Hence, economically motivated adulteration has a high prevalence. DNA barcoding and species-specific PCR assays are now revolutionising the molecular identification of herbal products and are included in a number of pharmacopoeias for the identification of raw materials. High-throughput sequencing with barcoding advances toward metabarcoding, which enables the identification of unintentionally or intentionally unlabelled plant material present in herbal products. Brahmi is one of the most commercially significant and nootropic botanicals, with great controversy over the terms "Brahmi" being used to describe both Bacopa monneri (BM) and Centella asiatica (CA) species. PurposeThis study evaluates DNA-based methods for Brahmi herbal products with the traditional HPLC-based analytical approach in order to assess their effectiveness. MethodsWe employed a species-specific PCR assay, DNA metabarcoding using rbcL minibarcode, and HPLC to detect the presence of the Brahmi (either BM or CA) in eighteen market samples. All the methods have been validated using in-house blended formulations. ResultsComprehensive analysis of all three methods revealed the presence of 22.2%, 55.6%, and 50.0% of Brahmi by PCR assay, DNA metabarcoding, and HPLC, respectively, in Brahmi market formulations, whereas blended formulations only exhibited targeted plant species with all three methods. ConclusionSpecies-specific PCR can be used as a cost-effective and rapid method to detect the presence of the Brahmi, while in high-throughput methods, DNA metabarcoding can be used to detect the presence of widespread adulterated botanicals, and further, bioactive compounds could be detected by HPLC. These results emphasise the need for quality control of the marketed Brahmi herbal products as well as the implementation of all methodologies in accordance with fit for purpose.

molecular biology↗

bioRxiv2022

Integration of synthetic microbial consortia based bioprocessing with pyrolysis for efficient conversion of cellulose to valuables

Improved technologies are needed for sustainable conversion of cellulosic waste to valuable products. Here we demonstrate the successful integration of a synthetic microbial consortium (SynCONS) based consolidated bioprocessing with pyrolysis to produce commodity chemicals from cellulose. Promising microbial partners were rationally identified from 7626 organisms via comparative metabolic mapping which led to establishing two promising SynCONS with abilities to convert cellulose to ethanol and lactate in bioreactors. The partners in the two SynCONS were a) the mesophilic fungus Trichoderma reesei grown sequentially with the thermophilic bacterium Parageobacillus thermoglucosidasius NCIMB 11955 (TrPt) and b) a thermophilic bacterium Thermobifida fusca grown together with Parageobacillus thermoglucosidasius NCIMB 11955 (TfPt). TrPt sequential bioprocessing resulted in 39% (g/g) cellulose consumption with product yields up to 9.3% g/g (ethanol + lactate). The TfPt co-cultures demonstrated a cellulose consumption of 30% (g/g) and combined yields of ethanol and lactic acid up to 23.7% g/g of consumed cellulose. The total product yields were further enhanced (51% g/g cellulose) when commercially available cellulases were used in place of T. fusca. Furthermore, when the metabolically engineered ethanol-producing strain of P. thermoglucosidasius TM242 (TfPt242) was substituted in the thermophilic TfPt co-culture consortium, ethanol yields were substantially higher (32.7% g/g of consumed cellulose). Finally, subjecting the residual cellulose and microbial biomass to pyrolysis resulted in carbon material with physicochemical properties similar to commercially available activated carbon as analysed using Scanning Electron Microscopy, X-Ray Diffraction and Raman spectroscopy. Overall, the integration of this synthetic microbial consortia-based bioprocessing strategy with pyrolysis demonstrated a promising strategy for conversion of waste cellulose to chemicals, biofuels, and industrial carbon potentially suitable for several industrial applications.

bioengineering↗

bioRxiv2022

Targeted Sequencing of Alzheimers Disease Genes in Gujarat Cohort

Alzheimers Disease (AD) is the most common type of dementia affecting cognitive and behavioural functions. Its a complex disease that results from the modest effect of gene interaction and environmental factors, as a result of which its exact pathogenesis is still unknown. In the present study, we have performed an association study of exonic regions of 94 genes with AD using the Haloplex target enrichment method and genotyping of 4 genes NOTCH4(rs367398), NEP(rs61760379), APOE (rs121918398), and ATP7B(rs1801243) using PCR RFLP technique. In this study, we screened 32 AD cases and 11 control samples. We have identified 19 variants assigned to 16 genes that were significantly associated with AD with a p-value < 0.05. However, no variants have passed multiple test corrections except NOTCH4/rs367398 genotyped using the PCR-RFLP approach. The functional enrichment analysis of the significant genes for the disease indicates that the genes are significantly involved in AD. Also, functional enrichment analysis for biological processes using ClueGo and network analysis using the STRING database indicated that the genes are directly and indirectly playing a role in AD pathogenesis. The eQTL analysis of the variants with GTEx dataset indicate that out of 19 variants ACHE/rs1799806 and NOTCH4/rs367398 variants is showing significant eQTL for the neighbouring genes for different brain regions and whole blood. Regardless, additional studies with a large cohort are required to establish the role and prevalence of these variants in the local population of Gujarat.

genomics↗

bioRxiv2021

Comparative analysis of two NGS platforms and different databases for analysis of AMR genes

The use of antibiotics in human medicine and livestock production has contributed to the widespread occurrence of antimicrobial resistance (AMR). Recognizing the relevance of AMR to human and livestock health, it is important to assess the occurrence of genetic determinants of resistance in medical, veterinary, and public health settings in order to understand risks of transmission and treatment failure. Advances in Next Generation Sequencing (NGS) technologies have had a significant impact on research in microbial genetics and microbiome analyses. Now, strategies for high throughput sequencing from panels of PCR amplicons representing known AMR genes offer opportunities for targeted characterization of complex microbial populations. Aim of the present study was to compare the Illumina MiSeq and Ion Torrent S5 Plus sequencing platforms for use with the Ion AmpliSeq AMR Research Panel in a veterinary/public health setting. All samples were processed in parallel for the two sequencing technologies, subsequently following a common bioinformatics workflow to define the occurrence and abundance of AMR gene sequences. Regardless of sequencing platform, the results were closely comparable with minor differences. The Comprehensive Antibiotic Resistance Database (CARD), QIAGEN Microbial Insight - Antimicrobial Resistance (QMI-AR), Antimicrobial resistance database (AR), and CARD-CLC databases were compared for analysis, with the most genes identified using CARD. Drawing on these results we describe an end-to-end workflow for AMR gene analysis using NGS.

bioinformatics↗

bioRxiv2021

Electrodeformation of White Blood Cells Enriched with Gold Nanoparticles

The elasticity of white blood cells (WBCs) provides valuable insight into the condition of the cells themselves, the presence of some diseases, as well as immune system activity. In this work, we describe a novel process of refined control of WBCs elasticity through a combined use of gold nanoparticles (AuNPs) and the microelectrode array device. The capture and controlled deformation of gold nanoparticles enriched white blood cells in vitro are demonstrated and quantified. Gold nanoparticles enhance the effect of electrically induced deformation and make the DEP related processes more controllable.

biophysics↗

bioRxiv2020

In-Silico analysis reveals lower transcription efficiency of C241T variant of SARS-CoV-2 with host replication factors MADP1 and hnRNP-1

Novel severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has claimed more than 1.5 million lives worldwide and counting. As per the GISAID database, the genomics of SARS-CoV2 is extensively studied with more than 500 genome submissions per day. Out of several hotspot mutations within the SARS-CoV-2 genome, researchers have focused a lot on missense variants but the least work is done on the UTRs. One of the most frequent 5 UTR variants in the SARS-CoV-2 genome is the C241T with a global frequency of more than 0.9. In the present study, the effect of the C241T mutation has been studied with respect to change in RNA structure and its interaction with the host replication factors MADP1 Zinc finger CCHC-type and RNA-binding motif 1 (hnRNP1). The results obtained from molecular docking and molecular dynamics simulation indicated weaker interaction of C241T mutant stem loops with host transcription factor MADP1 indicating reduced replication efficiency. The results are also correlated with increased recovery rates and decreased death rates of global SARS-CoV-2 cases.

bioinformatics↗

bioRxiv2020

Identification of unique mutations in SARS-CoV-2 strains isolated from India suggests its attenuated pathotype

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which was first reported in Wuhan, China in November 2019 has developed into a pandemic since March 2020, causing substantial human casualties and economic losses. Studies on SARS-CoV-2 are being carried out at an unprecedented rate to tackle this threat. Genomics studies, in particular, are indispensable to elucidate the dynamic nature of the RNA genome of SARS-CoV-2. RNA viruses are marked by their unique ability to undergo high rates of mutation in their genome, much more frequently than their hosts, which diversifies their strengths qualifying them to elude host immune response and amplify drug resistance. In this study, we sequenced and analyzed the genomic information of the SARS-CoV-2 isolates from two infected Indian patients and explored the possible implications of point mutations in its biology. In addition to multiple point mutations, we found a remarkable similarity between relatively common mutations of 36-nucleotide deletion in ORF8 of SARS-CoV-2. Our results corroborate with the earlier reported 29-nucleotide deletion in SARS, which was frequent during the early stage of human-to-human transmission. The results will be useful to understand the biology of SARS-CoV-2 and itsattenuation for vaccine development.

microbiology↗

bioRxiv2020

What does your cell really do? Model-based assessment of mammalian cells metabolic functionalities using omics data

Large-scale omics experiments have become standard in biological studies, leading to a deluge of data. However, researchers still face the challenge of connecting changes in the omics data to changes in cell functions, due to the complex interdependencies between genes, proteins and metabolites. Here we present a novel framework that begins to overcome this problem by allowing users to infer how metabolic functions change, based on omics data. To enable this, we curated and standardized lists of metabolic tasks that mammalian cells can accomplish. We then used genome-scale metabolic networks to define gene modules responsible for each specific metabolic task. We further developed a framework to overlay omics data on these modules to predict pathway usage for each metabolic task. The proposed approach allows one to directly predict how changes in omics experiments change cell or tissue function. We further demonstrated how this new approach can be used to leverage the metabolic functions of biological entities from the single cell to their organization in tissues and organs using multiple transcriptomic datasets (human and mouse). Finally, we created a web-based CellFie module that has been integrated into the list of tools available in GenePattern (www.genepattern.org) to enable adoption of the approach.

systems biology↗

bioRxiv2020

Entner-Doudoroff pathway and Non-OxPPP bypasses glycolysis and OxPPP in Ralstonia solanacearum

In Ralstonia solanacearum, a devastating phytopathogen whose metabolism is poorly understood, we observed that Entner-Doudoroff (ED) pathway and NonOxidative pentose phosphate pathway (OxPPP) bypasses glycolysis and OxPPP under glucose oxidation. Evidences derived from 13C stable isotopes feeding and genome annotation based comparative metabolic network analysis supported the observations. Comparative metabolic network analysis derived from the currently available 53 annotated R. solanacearum strains also including the recently reported strain (F1C1), representing the four phylotypes confirmed the lack of key genes coding for phosphofructokinase (pfk-1) and phosphogluconate dehydrogenase (gnd) enzymes that are relevant for glycolysis and OxPPP respectively. R. solanacearum F1C1 cells fed with 13C Glucose (99%[1-13C]- or 99%[1,2-13C]- or 40%[13C6]-glucose) followed by GC-MS based labelling analysis of fragments from amino acids, glycerol and ribose provided clear evidence that rather than Glycolysis and OxPPP, ED pathway and NonOxPPP are the main routes sustaining metabolism in R. solanacearum. The 13C incorporation in the mass ions of alanine (m/z 260, m/z 232); valine (m/z 288, m/z 260), glycine (m/z 218), serine (m/z 390, m/z 362), histidine (m/z 440, m/z 412), tyrosine (m/z 466, m/z 438), phenylalanine (m/z 336, m/z 308), glycerol (m/z 377) and ribose (m/z 160) mapped the pathways supporting the observations. The outcomes help better defining the central carbon metabolic network of R. solanacearum that can be integrated with 13C metabolic flux analysis as well as flux balance analysis studies for defining the metabolic phenotypes. ImportanceUnderstanding the metabolic versatility of Ralstonia solanacearum is important as it regulates the tradeoff between virulence and metabolism (1, 2) in a wide range of plant hosts. Due to a lack of clear evidence until this work, several published research papers reported on potential roles of Glycolysis and Oxidative pentose phosphate pathways (OxPPP) in R. solanacearum (3, 4). This work provided evidence from 13C stable isotopes feeding and genome annotation based comparative metabolic network analysis that Entner-Doudoroff pathway and Non-OxPPP bypasses glycolysis and OxPPP during the oxidation of Glucose, one of the host xylem pool that serves as a potential carbon source (5). The outcomes help better defining the central carbon metabolic network of R. solanacearum that can be integrated with 13C metabolic flux analysis as well as flux balance analysis studies for defining the metabolic phenotypes. The study highlights the need to critically examine phytopathogens whose metabolism is poorly understood.

systems biology↗

bioRxiv2019

Investigation on the effect of sonic stimulation on Xanthomonas campestris at the whole transcriptome level

A gram-negative bacterium Xanthomonas campestris was subjected to sonic stimulation with sound pertaining to 1000 Hz at three different sound intensities. The X. campestris culture subjected to sonic stimulation at 66 dB produced 1.69 fold higher exopolysaccharide. Whole transcriptome analysis of this sonic-stimulated culture revealed a total of 115 genes expressed differentially in the sonic-stimulated culture, majority of which were coding for different proteins including enzyme. This study demonstrates the property of the test bacterium of being responsive to sonic/vibrational stimulation.

microbiology↗

bioRxiv2019

Investigating the influence of extraction methodology, and certain other experimental parameters on bacterial response to selected quorum-modulatory plant extracts

In context of the global threat of antimicrobial resistance (AMR), a large number of labs throughout the world are investigating plant extracts for their possible anti-pathogenic efficacy. Outcome of protocols employed for screening the plant extracts for such activities are influenced by multiple factors. Among them, this study has found the method used for extraction, size and volume of the assay system, to be important factors. Further we demonstrate the extracts prepared by microwave-and vacuum-assisted extraction methods to be stable with respect to their anti-pathogenic efficacy over a long period of storage.

microbiology↗