Biology subjects

Sardar, R.

Publications and source records attributed to Sardar, R..

6 recordsLinked to original sources

bioRxiv2023

β Cell microRNAs Function as Molecular Hubs of Type 1 Diabetes Pathogenesis and as Biomarkers of Diabetes Risk

MicroRNAs (miRNAs) are small non-coding RNAs that play a crucial role in modulating gene expression and are enriched in cell-derived extracellular vesicles (EVs). We investigated whether miRNAs from human islets and islet-derived EVs could provide insight into {beta} cell stress pathways activated during type 1 diabetes (T1D) evolution, therefore serving as potential disease biomarkers. We treated human islets from 10 cadaveric donors with IL-1{beta} and IFN-{gamma} to model T1D ex vivo. MicroRNAs were isolated from islets and islet-derived EVs, and small RNA sequencing was performed. We found 20 and 14 differentially expressed (DE) miRNAs in cytokine-versus control-treated islets and EVs, respectively. Interestingly, the miRNAs found in EVs were mostly different from those found in islets. Only two miRNAs, miR-155-5p and miR-146a-5p, were upregulated in both islets and EVs, suggesting selective sorting of miRNAs into EVs. We used machine learning algorithms to rank DE EV-associated miRNAs, and developed custom label-free Localized Surface Plasmon Resonance-based biosensors to measure top ranked EVs in human plasma. Results from this analysis revealed that miR-155, miR-146, miR-30c, and miR-802 were upregulated and miR-124-3p was downregulated in plasma-derived EVs from children with recent-onset T1D. In addition, miR-146 and miR-30c were upregulated in plasma-derived EVs of autoantibody positive (AAb+) children compared to matched non-diabetic controls, while miR-124 was downregulated in both T1D and AAb+ groups. Furthermore, single-molecule fluorescence in situ hybridization confirmed increased expression of the most highly upregulated islet miRNA, miR-155, in pancreatic sections from organ donors with AAb+ and T1D. One Sentence SummarymiRNA expression patterns in human pancreatic islets and EVs change under inflammatory conditions and can be leveraged to inform biomarkers strategies for T1D.

physiology↗

bioRxiv2022

Gabapentin Disrupts Binding of Perlecan to the α2δ1 Voltage Sensitive Calcium Channel Subunit and Impairs Skeletal Mechanosensation

Our understanding of how osteocytes, the principal mechanosensors within bone, sense and perceive force remains unclear. Previous work identified "tethering elements" (TEs) spanning the pericellular space of osteocytes and transmitting mechanical information into biochemical signals. While we identified the heparan sulfate proteoglycan perlecan (PLN) as a component of these TEs, PLN must attach to the cell surface to induce biochemical responses. As voltage-sensitive calcium channels (VSCCs) are critical for bone mechanotransduction, we hypothesized that PLN binds the extracellular 2{delta}1 subunit of VSCCs to couple the bone matrix to the osteocyte membrane. Here, we showed co-localization of PLN and 2{delta}1 along osteocyte dendritic processes. Additionally, we quantified the molecular interactions between 2{delta}1 and PLN domains and demonstrated for the first time that 2{delta}1 strongly associates with PLN via its domain III. Furthermore, 2{delta}1 is the binding site for the commonly used pain drug, gabapentin (GBP), which is associated with adverse skeletal effects when used chronically. We found that GBP disrupts PLN::2{delta}1 binding in vitro, and GBP treatment in vivo results in impaired bone mechanosensation. Our work identified a novel mechanosensory complex within osteocytes composed of PLN and 2{delta}1, necessary for bone force transmission and sensitive to the drug GBP. This work provides insights into the mechanisms underlying mechanotransduction and will inform future studies to understand the mechanisms responsible for the negative effects of GBP on bone.

molecular biology↗

bioRxiv2021

Comparative analysis of codon usage patterns in SARS-CoV-2, its mutants and other respiratory viruses

The Coronavirus disease 2019 (COVID-19) outbreak caused by Severe Acute Respiratory Syndrome Coronavirus 2 virus (SARS-CoV-2) poses a worldwide human health crisis, causing respiratory illness with a high mortality rate. To investigate the factors governing codon usage bias in all the respiratory viruses, including SARS-CoV-2 isolates from different geographical locations (~62K), including two recently emerging strains from the United Kingdom (UK), i.e., VUI202012/01 and South Africa (SA), i.e., 501.Y.V2 codon usage bias (CUBs) analysis was performed. The analysis includes RSCU analysis, GC content calculation, ENC analysis, dinucleotide frequency and neutrality plot analysis. We were motivated to conduct the study to fulfil two primary aims: first, to identify the difference in codon usage bias amongst all SARS-CoV-2 genomes and, secondly, to compare their CUBs properties with other respiratory viruses. A biased nucleotide composition was found as most of the highly preferred codons were A/U-ending in all the respiratory viruses studied here. Compared with the human host, the RSCU analysis led to the identification of 11 over-represented codons and 9 under-represented codons in SARS-CoV-2 genomes. Correlation analysis of ENC and GC3s revealed that mutational pressure is the leading force determining the CUBs. The present study results yield a better understanding of codon usage preferences for SARS-CoV-2 genomes and discover the possible evolutionary determinants responsible for the biases found among the respiratory viruses, thus unveils a unique feature of the SARS-CoV-2 evolution and adaptation. To the best of our knowledge, this is the first attempt at comparative CUBs analysis on the worldwide genomes of SARS-CoV-2, including novel emerged strains and other respiratory viruses.

bioinformatics↗

bioRxiv2021

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↗

bioRxiv2020

Comparative analyses of SAR-CoV2 genomes from different geographical locations and other coronavirus family genomes reveals unique features potentially consequential to host-virus interaction and pathogenesis

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2). We have performed an integrated sequence-based analysis of SARS-CoV2 genomes from different geographical locations in order to identify its unique features absent in SARS-CoV and other related coronavirus family genomes, conferring unique infection, facilitation of transmission, virulence and immunogenic features to the virus. The phylogeny of the genomes yields some interesting results. Systematic gene level mutational analysis of the genomes has enabled us to identify several unique features of the SARS-CoV2 genome, which includes a unique mutation in the spike surface glycoprotein (A930V (24351C>T)) in the Indian SARS-CoV2, absent in other strains studied here. We have also predicted the impact of the mutations in the spike glycoprotein function and stability, using computational approach. To gain further insights into host responses to viral infection, we predict that antiviral host-miRNAs may be controlling the viral pathogenesis. Our analysis reveals nine host miRNAs which can potentially target SARS-CoV2 genes. Interestingly, the nine miRNAs do not have targets in SARS and MERS genomes. Also, hsa-miR-27b is the only unique miRNA which has a target gene in the Indian SARS-CoV2 genome. We also predicted immune epitopes in the genomes

bioinformatics↗

bioRxiv2019

ApicoTFdb: The comprehensive web repository of apicomplexan transcription factors and regulators.

Despite significant progress in apicomplexans genome sequencing and genomics, the current list of experimentally validated TFs in these genomes is incomplete and mainly consists of AP2 family of proteins, with only a limited number of non-AP2 family TFs and TAFs. We have performed systematic bioinformatics aided prediction of TFs and TAFs in apicomplexan genomes, and developed ApicoTFdb database which consists of experimentally validated as well as computationally predicted TFs and TAFs in 14 apicomplexan species. The predicted TFs are manually curated to complement the existing annotations. The current version of the database includes 1310 TFs, out of which 833 are novel and computationally predicted TFs, representing 22 distinct families across 14 apicomplexan species. The predictions include TFs of TUB, NAC, BSD, CCAAT, HTH, Cupin/Jumonji, winged-helix, and FHA family proteins, not reported earlier in the genomes. Apart from TFs, ApicoTFdb also classifies TAFs into three main subclasses-TRs, CRRs and RNARs, representing 3047 TAFs in 14 apicomplexan species are analyzed in this study. The database is equipped with a set of useful tools for comparative analysis of a user-defined list of the proteins. ApicoTFdb will be useful to the researchers interested in less-studied gene regulatory mechanisms mediating the complex life cycle of the apicomplexan parasites. The database will aid the discovery of novel drug targets to much needed combat the growing drug resistance in the parasites.

bioinformatics↗