Biomedical subjects

Trupti Joshi

Publications and source records attributed to Trupti Joshi.

7 recordsLinked to original sources

PubMed2026

Monocarboxylate Transporter 2 (MCT2) Reduction Is Associated with Increased Lung Tumor Growth and Alterations in the Immune Microenvironment in a Subcutaneous Tumor Model.

Monocarboxylate transporter 2 (MCT2; SLC16A7) is a high-affinity pyruvate transporter implicated in cancer metabolism. However, its role in lung cancer progression and the tumor microenvironment remains unclear. This study examined the effects of MCT2 reduction on tumor growth and cell-type-specific transcriptional changes within the tumor microenvironment. MCT2 loxP/loxP mice were crossed with mCre-Tg mice, and MCT2 deletion was induced by tamoxifen. Control (CO) mice received vehicle treatment. TC1 cells (100,000 cells/mouse) were injected subcutaneously, and tumors were harvested after 24 days. Single-nucleus RNA sequencing (snRNA-seq) was performed on isolated tumor nuclei (4000 nuclei/sample; n = 3 per group) using the 10x Genomics Chromium platform. Data were processed with Cell Ranger v3.0.2 and Seurat v5.2.1, followed by differential expression and pathway enrichment analyses integrated with macrophage bulk RNA-seq data. Tumors in mice with systemic MCT2 reduction grew significantly faster than those in control mice, demonstrating an association between host MCT2 reduction and increased tumor growth. Transcriptomic analysis generated high-quality profiles from 6864 CO and 10,055 KO nuclei. Clustering identified 12 cellular populations and cell types. MCT2 reduction altered pathways involved in glycolysis, the tricarboxylic acid cycle, oxidative phosphorylation, and fatty acid metabolism across multiple populations. Macrophages showed prominent transcriptional changes, including enrichment of MAPK, PI3K-Akt, IgSF-CAM, ECM, and cytokine-cytokine signaling pathways. These findings were supported by macrophage bulk RNA-seq data. Systemic MCT2 reduction was associated with increased tumor growth and broad transcriptional alterations within the tumor micro-environment. Differences in metabolic and immune-related transcriptional programs, particularly in macrophages, identify potential mechanisms associated with tumor progression that warrant further functional investigation.

Animals↗

PubMed2025

Factors underlying a latitudinal gradient in the S/G lignin monomer ratio in natural poplar variants.

The chemical composition of wood plays a pivotal role in the adaptability and structural integrity of trees. However, few studies have investigated the environmental factors that determine lignin composition and its biological significance in plants. Here, we examined the lignin syringyl-to-guaiacyl (S/G) ratio in members of a Populus trichocarpa population sourced from their native habitat and conducted a genome wide association study to identify genes linked to lignin formation. Our results revealed many significant associations, suggesting that lignin biosynthesis is a complex polygenic trait. Additionally, we found an increase in the S/G ratio from northern to southern geographic origin of the trees sampled, along with a corresponding metabolic and transcriptional reprogramming of xylem cell wall biosynthesis. Further molecular analysis identified a mutation in a cell wall laccase genetically associated with higher S/G ratios that predominate in trees from warmer lower latitudes. Collectively, our findings suggest that lignin heterogeneity arises from an evolutionary process enabling poplar adaptation to different climatic challenges.

Populus↗

PubMed2006

Inferring gene regulatory networks from multiple microarray datasets.

MOTIVATION: Microarray gene expression data has increasingly become the common data source that can provide insights into biological processes at a system-wide level. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to a large number of genes, which makes the problem of inferring gene regulatory network an ill-posed one. On the other hand, gene expression data generated by different groups worldwide are increasingly accumulated on many species and can be accessed from public databases or individual websites, although each experiment has only a limited number of time-points. RESULTS: This paper proposes a novel method to combine multiple time-course microarray datasets from different conditions for inferring gene regulatory networks. The proposed method is called GNR (Gene Network Reconstruction tool) which is based on linear programming and a decomposition procedure. The method theoretically ensures the derivation of the most consistent network structure with respect to all of the datasets, thereby not only significantly alleviating the problem of data scarcity but also remarkably improving the prediction reliability. We tested GNR using both simulated data and experimental data in yeast and Arabidopsis. The result demonstrates the effectiveness of GNR in terms of predicting new gene regulatory relationship in yeast and Arabidopsis. AVAILABILITY: The software is available from http://zhangorup.aporc.org/bioinfo/grninfer/, http://digbio.missouri.edu/grninfer/ and http://intelligent.eic.osaka-sandai.ac.jp or upon request from the authors.

Algorithms↗

PubMed2006

FcgammaR-induced production of superoxide and inflammatory cytokines is differentially regulated by SHIP through its influence on PI3K and/or Ras/Erk pathways.

Phagocytosis of IgG-coated particles via FcgammaR is accompanied by the generation of superoxide and inflammatory cytokines, which can cause collateral tissue damage in the absence of regulation. Molecular mechanisms regulating these phagocytosis-associated events are not known. SHIP is an inositol phosphatase that downregulates PI3K-mediated activation events. Here, we have examined the role of SHIP in FcgammaR-induced production of superoxide and inflammatory cytokines. We report that primary SHIP-deficient bone marrow macrophages produce elevated levels of superoxide upon FcgammaR clustering. Analysis of the molecular mechanism revealed that SHIP regulates upstream Rac-GTP binding, an obligatory event for superoxide production. Likewise, SHIP-deficient macrophages displayed enhanced IL-1beta and IL-6 production in response to FcgammaR clustering. Interestingly, whereas IL-6 production required activation of both PI3K and Ras/Erk pathways, IL-1beta production was dependent only on Ras/Erk activation, suggesting that SHIP may also regulate the Ras/Erk pathway in macrophages. Consistently, SHIP-deficient macrophages displayed enhanced activation of Erk upon FcgammaR clustering. Inhibition of Ras/Erk or PI3K suppressed the enhanced production of IL-6 in SHIP-deficient macrophages. In contrast, inhibition of Ras/Erk, but not PI3K, suppressed IL-1beta production in these cells. Together, these data demonstrate that SHIP regulates phagocytosis-associated events through the inhibition of PI3K and Ras/Erk pathways.

Animals↗

PubMed2006

Fcgamma receptor signaling in phagocytes.

Fcgamma receptors are among the best-studied phagocytic receptors. The key features of Fcgamma receptor-mediated phagocytosis include phagocytic cup formation by extensive actin cytoskeletal rearrangements, particle engulfment, and the release of proinflammatory mediators such as cytokines and reactive oxygen species. These events are elegantly regulated by the simultaneous engagement of activating and inhibitory Fcgamma receptors and by intracellular signaling molecules. Extensive studies in the past several years have defined the molecular mechanisms of the phagocytic process. The purpose of this review is to revisit some of the well-established signaling pathways as well as to summarize the new findings in this field.

Adaptor Proteins, Signal Transducing↗

PubMed2005

Molecular analysis of expression and function of hFcgammaRIIbl and b2 isoforms in myeloid cells.

The inhibitory receptor FcgammaRIIb becomes tyrosine phosphorylated and associates with the inositol phosphatase SHIP to downregulate phagocytosis. The two splice variants of FcgammaRIIb, b1 and b2, are differentially expressed in hematopoetic cells. Both isoforms of FcgammaRIIb are expressed in human myeloid cells although FcgammaRIIb2 predominates. In murine B cells FcgammaRIIb2 associates with clathrin-coated pits and undergoes endocytosis, whereas FcgammaRIIbl is excluded from the coated pits, indicating that the two isoforms serve partially differing functions. In humans, there are conflicting reports with regard to the ability of FcgammaRIIb2 to become tyrosine phosphorylated, and the functional capacities of the two isoforms are poorly understood. We, and others, have previously reported that the expression of FcgammaRIIb is upregulated in human monocytes by the anti-inflammatory cytokine IL-4. Here, we extend these findings to demonstrate that the IL-4-induced upregulation of FcgammaRIIb is synergistically enhanced by the addition of IL-10, both at the protein and the mRNA level. The upregulated receptors are functional as assessed by their ability to become tyrosine phosphorylated and to downregulate phagocytosis. Interestingly, both b1 and b2 isoforms are upregulated by anti-inflammatory cytokines. Transfection experiments expressing human FcgammaRIIbl or b2 in Raw 264.7 murine macrophage cells revealed that both isoforms are tyrosine phosphorylated and promote SHIP phosphorylation. Finally, both b1 and b2 isoforms of FcgammaRIIb downregulate phagocytosis to a similar extent. Thus we conclude that FcgammaRIIbl and b2 are both functional inhibitory receptors in the phagocytic process.

Animals↗

PubMed2004

Genome-scale gene function prediction using multiple sources of high-throughput data in yeast Saccharomyces cerevisiae.

Characterizing gene function is one of the major challenging tasks in the post-genomic era. To address this challenge, we have developed GeneFAS (Gene Function Annotation System), a new integrated probabilistic method for cellular function prediction by combining information from protein-protein interactions, protein complexes, microarray gene expression profiles, and annotations of known proteins through an integrative statistical model. Our approach is based on a novel assessment for the relationship between (1) the interaction/correlation of two proteins' high-throughput data and (2) their functional relationship in terms of their Gene Ontology (GO) hierarchy. We have developed a Web server for the predictions. We have applied our method to yeast Saccharomyces cerevisiae and predicted functions for 1548 out of 2472 unannotated proteins.

Automation↗