Biology subjects

Mazumder, M.

Publications and source records attributed to Mazumder, M..

13 recordsLinked to original sources

bioRxiv2026

Genome-wide computational prediction of miRNAs encoded by influenza A virus (H3N2) predicts target genes involved in pulmonary and antiviral innate immunity

Influenza A virus (IAV) causes significant morbidity and mortality worldwide. Understanding how viral RNAs may regulate host genes through microRNA-like mechanisms can clarify pathogenesis and reveal therapeutic targets. In this study, we screened all eight IAV H3N2 RNA segments (PB2, PB1, PA, HA, NP, NA, M, and NS) using an ab initio computational pipeline; five segments (PB2, PB1, PA, HA, and M) met the VMir scoring threshold for further analysis, while NP, NA, and NS were excluded due to low pre-miRNA scores. Mature miRNAs were identified using MatureBayes, and target genes in the human genome were predicted with the miRDB server. From these targets, we selected two genes per qualifying segment (10 genes total) based on their functional relevance to influenza infection and supporting literature; all selected genes are unique to their respective segment. We identified 10 segment-specific target genes (IFNL1, DDX60, SAMHD1, MAVS, IRF4, BIRC2, AGO1, MAP3K1, NOD1, and TNFAIP1) and one common target across all five analyzed segments (CADM2). Gene Ontology and pathway analyses showed enrichment in interferon signaling, RIG-I-like receptor pathways, antiviral restriction, RNA interference, and inflammatory responses. Literature supports roles for these genes in pulmonary and antiviral innate immunity. Our findings provide a basis for experimental validation and may help the research community better understand influenza virus pathogenesis and identify novel therapeutic candidates. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/725090v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@2b14adorg.highwire.dtl.DTLVardef@5a9b2eorg.highwire.dtl.DTLVardef@81ffc1org.highwire.dtl.DTLVardef@be119b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Decoding the Tumor-Suppressive Landscape of SCARA5: A Network-Based Analysis Linking Lipid Metabolism and Immune Regulation in Breast Cancer

BackgroundThe tumor microenvironment (TME) significantly impacts breast cancer progression, with stromal and immune components influencing tumor behavior. The scavenger receptor SCARA5 is recognized as a tumor suppressor in various cancers, but its role in breast cancer remains uncertain. MethodsWe performed integrative transcriptomic analyses of bulk RNA-seq data from TCGA-BRCA, validated with GTEx, to investigate SCARA5 expression and its clinical significance. Differential expression, PAM50 subtype classification, PCA/t-SNE clustering, and ROC analyses were used to assess diagnostic potential. Functional enrichment (GO, KEGG, Reactome), PPI networks, and co-expression analyses explored pathways related to SCARA5. Single-cell transcriptomic datasets (TISCH2, Broad Portal) and spatial profiling (Human Protein Atlas) were employed to examine cellular and spatial localization. The prognostic importance was assessed using GEPIA2 survival analysis. ResultsSCARA5 was significantly downregulated in breast tumors, especially in Her2-enriched and Luminal B subtypes, with ROC curves confirming its diagnostic importance. Enrichment and PPI analyses linked SCARA5 to lipid metabolism, immune regulation, and scavenger receptor pathways. Co-expression studies showed associations with lipid metabolism genes (FABP4, ADIPOQ, CD36) and immune-related genes (CLEC3B, LYVE1). Single-cell data indicated SCARA5 expression was limited to fibroblasts, endothelial cells, and immune subsets, with rare expression in malignant epithelial cells. Spatial analysis confirmed stromal enrichment, mainly in areas rich in fibroblasts and endothelial cells. Survival analysis demonstrated worse outcomes in patients with HER2+ and Luminal B breast cancers who had low SCARA5 expression. ConclusionSCARA5 is a stromal-enriched gene with potential tumor-suppressive and immunometabolic regulatory roles in breast cancer. Its diagnostic and prognostic significance, especially in aggressive subtypes, highlights its potential as a biomarker and therapeutic target within the tumor stroma.

bioinformatics↗

bioRxiv2025

Distinct Transcriptomic Biomarkers and Pathways Associated with Cardiovascular and Neurovascular Dysregulation in Long COVID-19 Brain Fog

BackgroundLong COVID-19 often manifests as persistent cognitive impairments, commonly referred to as brain fog, with poorly understood biological mechanisms. Previous studies highlighted neuroinflammation and blood-brain barrier disruption. Here, we identify distinct biomarkers and dysregulated pathways, with a focus on cardiovascular and neurovascular involvement. MethodsWe analyzed public RNA-sequencing data (GEO: GSE251849) comparing long COVID-19 patients with brain fog, long COVID-19 patients without cognitive symptoms, convalescent patients, and healthy controls. Differential gene expression, principal component analysis, and pathway enrichment analyses were performed using DESeq2, KEGG, GO, and Enrichr tools. ResultsOur analysis revealed a distinct gene expression profile in patients with brain fog, identifying exclusive biomarkers such as NRCAM, GRIN2C, NOS2, and EDNRB. Pathway analysis revealed significant dysregulation in cardiovascular, calcium signaling, and relaxin signaling pathways, suggesting novel biological mechanisms that contribute to cognitive impairment. These findings expand beyond neuroinflammation and highlight potential cardiovascular involvement in long COVID-related cognitive dysfunction. ConclusionOur study reveals novel transcriptomic signatures that highlight cardiovascular and neurovascular dysregulation, providing promising diagnostic biomarkers and therapeutic targets. Future research should validate these findings and investigate therapeutic interventions addressing these unique pathways.

bioinformatics↗

bioRxiv2025

Live-Exudation Assisted Phytobiome Cultromics System (LEAP-CS): A High-Throughput Cultromics System for Studying Plant-Microbiome Interactions through Non-Contact Metabolic Exchange.

This study introduces an innovative methodology for co-cultivating plants and microbes, employing a membrane-based structure to facilitate their physical separation. The Live-Exudation Assisted Phytobiome Cultromics System (LEAP-CS) has the capability to investigate the complex interaction of plant and soil microbiome under in vitro conditions, offering potential benefits. Subsequent validation and testing can be performed through pot, greenhouse, and field trials. The system can efficiently function as a high-throughput screening tool for assessing plant-microbiome interactions and their associated metabolic signatures. Our phytobiome culturing technique harnesses root exudation from live plants, capitalizing on the membranes selective separation to prevent direct physical interaction between plant and microbiome components. Consequently, the interaction is solely through chemical-mediated signalling. By employing this method, we can intricately dissect complex plant-microbiome interactions while faithfully maintaining and emulating the contact independent inherent associations prevalent within these phytobiomes. In conclusion, this user-friendly and reproducible in-vitro model holds immense potential for shedding light on the intricate community and metabolic exchange dynamics of plant-microbiome interactions, thus significantly advancing our understanding in this area.

plant biology↗

bioRxiv2025

A cell-free bacterial signal orchestrates trans-kingdom fitness tradeoff to enhance sulfur deficiency tolerance in plants

Plant-associated microorganisms interact with each other and host plants via intricate chemical signals, offering multiple benefits, including plant nutrition. We report such a mechanism through which the rhizosphere microbiome improves plant growth under sulfur (S) deficiency. Disruption of plant S homeostasis resulted in a coordinated shift in composition and S-metabolism of the rhizosphere microbiome. Using this insight, we developed an 18-membered synthetic rhizosphere bacterial community (SynCom) that rescued growth of Arabidopsis and a leafy Brassicaceae vegetable under S-deficiency. This beneficial trait is taxonomically widespread among SynCom members, with bacterial pairs predominantly providing synergistic benefits to host plants. Notably, stronger competitive interactions among SynCom members conferred greater fitness benefits to the host, suggesting a trans-kingdom fitness tradeoff. Finally, guided chemical screening, deletion knockout mutant, and targeted metabolomics identified and validated microbially released glutathione (GSH) as the necessary bioactive signal that orchestrates plant-microbe (trans-kingdom) fitness tradeoff and improves plant growth under sulfur limitation. HighlightsO_LIAlteration in plant sulfur (S) homeostasis leads to coordinated shifts in the composition and S-metabolism of the rhizosphere microbiome. C_LIO_LITaxonomically divergent bacterial members within the rhizosphere microbiome improve plant growth under S-deficiency. C_LIO_LIStronger competitive interactions within rhizosphere bacterial members provide greater fitness benefit to the host plant under S-deficiency, suggesting a trans-kingdom fitness tradeoff. C_LIO_LIMicrobially released glutathione (GSH) is a necessary bioactive signal that improves plant growth under sulfur limitation and orchestrates plant-microbe (trans-kingdom) fitness tradeoff. C_LI

microbiology↗

bioRxiv2024

Transcriptomic-Based Identification of FCRL6 as a Novel Diagnostic Biomarker in Diabetic Nephropathy

Diabetic nephropathy (DN) is a microvascular complication that arises in a sizable portion of individuals with diabetes mellitus, representing a growing public health issue given its progressive injury of the kidney. DN is primarily driven by the upregulation of pro-inflammatory markers and pathways, which cause hyperfiltration and significant physiological changes to the renal structure. To further understand the molecular mechanisms by which DN progresses, we used bioinformatics and meta-analysis techniques to analyze two datasets from the Gene Expression Omnibus (GEO) database: GSE142025 and GSE142153. Differential gene expressions (DGEs) were identified using the Bioconductor DESeq2 library and further used in functional enrichment analysis. DGEs were also constructed into protein-protein interaction networks and used to find regulatory hub genes. In total, 911 DGEs were found, and enrichment using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) revealed strong correlations with immunoreactive responses and cascades. In our analysis, we discovered 12 protein-coding genes novel with regards to DN; we further identified Fc Receptor-Like 6 - FCRL6 - as a potential biomarker in nephropathy and described its involvement in the suppression of natural killer cell-mediated toxicity as a mechanism of poor immunoregulation in the diabetic kidney. The current study presents comparative analyses of the DN transcriptome and a possible diagnostic marker with applications in immunotherapy treatments of nephropathy.

bioinformatics↗

bioRxiv2024

Deep skin fibroblast-mediated macrophage recruitment supports acute wound healing

Epithelial and immune cells have long been appreciated for their contribution to the early immune response after injury; however, much less is known about the role of mesenchymal cells. Using single nuclei RNA-sequencing, we defined changes in gene expression associated with inflammation at 1-day post-wounding (dpw) in mouse skin. Compared to keratinocytes and myeloid cells, we detected enriched expression of pro-inflammatory genes in fibroblasts associated with deeper layers of the skin. In particular, SCA1+ fibroblasts were enriched for numerous chemokines, including CCL2, CCL7, and IL33 compared to SCA1-fibroblasts. Genetic deletion of Ccl2 in fibroblasts resulted in fewer wound bed macrophages and monocytes during injury-induced inflammation with reduced revascularization and re-epithelialization during the proliferation phase of healing. These findings highlight the important contribution of deep skin fibroblast-derived factors to injury-induced inflammation and the impact of immune cell dysregulation on subsequent tissue repair.

cell biology↗

bioRxiv2021

Machine learning-based modulation of Ca2+-binding affinity in EFhand proteins and comparative structural insights into site-specific cooperative binding

Ca2+-binding proteins are present in almost all living organisms and different types display different levels of binding affinities for the cation. Here, we applied two new scoring schemes enabling the user to manipulate the binding affinities of such proteins. We specifically designed a unique EF-hand loop capable of binding calcium with high affinity by altering five residues of the loop based on the scoring scheme. We worked on the N-terminal domain of Entamoeba histolytica calcium-binding protein1 (NtEhCaBP1), and used site-directed mutagenesis to incorporate the designed loop sequence into the second EF hand motif of this protein. The binding isotherms calculated using ITC calorimetry showed a [~]500-fold greater association constant (Ka) for the mutant. The crystal structure of the mutant was also determined, and displayed more compact Ca2+-coordination spheres in both of its EF loops than did the structure of the wildtype protein, consistent with the greater calcium-binding affinities of the mutant. The NtEhCaBP1 mutant was also shown to form a hexamer rather than just a trimer, and this hexamer formation was attributed to the position of the last helix of the mutant having been changed as a result of the strong calcium coordination. Further dynamic correlation analysis revealed that the mutation in the second EF loop changed the entire residue network of the monomer, resulting in a stronger coordination of Ca2+ even in other EF hand loop.

biophysics↗

bioRxiv2021

In silico Analysis of Transcriptomic Profiling and Affected Biological pathways in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic autoimmune, inflammatory neurological disease that is widely associated with Grey and white matter degradation due to the demyelination of axons. Thus exposing the underlying causes of this condition can lead to a novel treatment approach for Multiple Sclerosis. The total RNA microarray processed data from GEO for Multiple sclerotic patients was comprehensively analyzed to find out underlying differences between Grey Matter lesions (GML), Normal appearing Grey Matter (NAGM), and Control Grey matter at the transcriptomics level. Thus, in the current study, we performed various bioinformatics analyses on transcriptional profiles of 184 samples including 105 NAGM, 37 GML, and 42 Controls obtained from the NCBI-Bio project (PRJNA543111). First, exploratory data analysis based on gene expression data using principal component analysis (PCA) depicted distinct patterns between GML and CG samples. Subsequently, the Welchs T-test differential gene expression analysis identified 15,525 significantly differentially expressed genes (p.adj value <0.05, Fold change(>=+/-1.5) between these conditions. This study reveals the genes like CREB3L2, KIF5B, WIPI1, EP300, NDUFA1, ATG101, AND TAF4 as the key features that may substantially contribute to loss of cognitive functions in Multiple sclerosis and several other neurodegenerative disorders. Further, this study also proposes genes associated with Huntingtons disease in Multiple sclerotic patients. Eventually, the results presented here reveal new insights into MS and how it affects the development of male primary sexual characteristics.

neuroscience↗

bioRxiv2021

Analysis of Gene Expression Profiles to study Malaria Vaccine Dose Efficacy & Immune Response Modulation.

Malaria is a life-threatening disease, and the Africa is still one of the most affected endemic regions despite years of policy to limit infection and transmission rates. Further, studies into the variable efficacy of the vaccine are needed to provide a better understanding of protective immunity. Thus, the current study is designed to delineate the effect of the different vaccination doses on the transcriptional profiles of subjects to determine its efficacy and understand the molecular mechanisms underlying the protection this vaccine provides. Here, we used gene expression profiles of pre and post-vaccination patients after various doses of RTS,S based on 275 and 583 samples collected from the GEO datasets. At first, exploratory data analysis based Principal component analysis (PCA) shown the distinct pattern of different doses. Subsequently, differential gene expression analysis using edgeR revealed the significantly (FDR <0.005) 158 down-regulated and 61 upregulated genes between control vs. Controlled Human Malaria Infection (CHMI) samples. Further, enrichment analysis of significant genes using Annotation and GAGE tools delineate the involvement of CCL8, CXCL10, CXCL11, XCR1, CSF3, IFNB1, IFNE, IL12B, IL22, IL6, IL27, etc.,genes which found to be upregulated after earlier doses but downregulated after the 3rd dose in cytokine-chemokine pathways. Notably, we identified 13 cytokine genes whose expression significantly varied during three doses. Eventually, these findings give insight to the dual role of cytokine responses in malaria pathogenesis and variations in their expression patterns after various doses of vaccination involved in protection.

bioinformatics↗

bioRxiv2021

In Silico Analysis and Characterization of Differentially Expressed Genes to Distinguish Glioma Stem Cells from Normal Neural Stem Cells

Glioblastoma multiforme (GBM) is a heterogeneous, invasive primary brain tumor that develops chemoresistance post therapy. Theories regarding the aetiology of GBM focus on transformation of normal neural stem cells (NSCs) to a cancerous phenotype or tumorigenesis driven via glioma stem cells (GSCs). Comparative RNA-Seq analysis of GSCs and NSCs can provide a better understanding of the origin of GBM. Thus, in the current study, we performed various bioinformatics analyses on transcriptional profiles of a total 40 RNA-seq samples including 20 NSC and 20 GSC, that were obtained from the NCBI-SRA (SRP200400). First, differential gene expression (DGE) analysis using DESeq2 revealed 348 significantly differentially expressed genes between GSCs and NSCs (padj. value <0.05, log2fold change [≥] 3.0 (for GSCs) and [≤] -3.0 (for NSCs)) with 192 upregulated and 156 downregulated genes in GSCs in comparison to NSCs. Subsequently, exploratory data analysis using principal component analysis (PCA) based on key significant genes depicted the clear separation between both the groups. Further, Hierarchical clustering confirmed the distinct clusters of GSC and NSC samples. Eventually, the biological enrichment analysis of the significant genes showed their enrichment in tumorigenesis pathways such as Wnt-signalling, VEGF-signalling and TGF-{beta}-signalling pathways. Conclusively, our study depicted significant differences in the gene expression patterns between NSCs and GSCs. Besides, we also identified novel genes and genes previously unassociated with gliomagenesis that may prove to be valuable in establishing diagnostic, prognostic biomarkers and therapeutic targets for GBM.

cancer biology↗

bioRxiv2021

Radiation Threats to Humans in Space and an alternative approach with Probiotics

Space type radiation is an important factor to consider for scientists on International Space Stations, especially high linear transfer energy (LET) since it has imminent effects on microorganisms. The abundances of bacteria are a good indicator of how radiation influences the gut microbiome. The current study is an attempt towards this; thus, we have employed a public dataset (Bioproject code PRJNA368790) of 80 mice samples treated with a range of doses from 0Gy to 1Gy and feces samples were collected at different time points of post radiation treatment. Metagenomic analysis was performed on this data to understand the effect of radiation doses on the abundance of microbial species or microbial diversity implementing the DADA2 and Phyloseq pipelines. Our analyses have shown that 0.1Gy high LET radiation had the significant effect on the species of bacteria. There is a significant decrease in four types of bacteria, i.e., Bifidobacterium longum, Bifidobacterium castoris, Lactobacillus gasseri and Lactobacillus johnsonii, with p-value of 7.05x10-5, 0.020, 0.057and 0.020, respectively. Additionally, pathway analysis indicates the protein coding products of these bacteria are involved in the GABAergic synaptic pathway. Further, our study has shown the significant difference between post radiation time points, i.e., 10 days vs.30 days and suggested the acclimatization period could be around 10 days for these bacteria.

microbiology↗

bioRxiv2017

Presence of WH2 like domain in VgrG-1 toxin of Vibrio cholerae reveals the molecular mechanism of actin cross-linking

Type VI secretion systems (T6SS) plays a crucial role in Vibrio cholerae mediated pathogenicity and predation. Tip of T6SS is homologous to gp27/gp5 complex or tail spike of T4 bacteriophage. VgrG-1 of V. cholerae T6SS is unusual among other VgrG because its effector domain is trans-located into the cytosol of eukaryotic cells with an additional actin cross-linking domain (ACD) at its C terminal end. ACD of VgrG-1 (VgrG-1-ACD) causes T6SS dependent host cell cytotoxicity through actin cytoskeleton disruption to prevent bacterial engulfment by macrophages. ACD mediated actin cross-linking promotes survival of the bacteria in the small intestine of humans, along with other virulence factors; establishes successful infection with the onset of diarrhoea in humans. Our studies demonstrated VgrG-1-ACD can bind to actin besides actin cross-linking activity. Computational analysis of ACD revealed the presence of WH2 domain through which it binds actin. Mutations in WH2 domain lead to loss of actin binding in vitro. VgrG-1-ACD having the mutated WH2 domain cannot cross-link actin efficiently in vitro and manifests less actin cytoskeleton disruption when transfected in HeLa cells.\n\nSummary statementActin cross-linking (ACD) domain of VgrG-1 toxin of Type VI secretion in Vibrio cholera has WASP Homology domain 2 (WH2) domain. ACD interact with actin through WH2 domain, WH2 is essential for ACD mediated cross-linking and disruption of actin cytoskeleton in the host cell.

biochemistry↗