Project description:This study examines the transcriptomic response of biofilms of the PAH-degrading Sphingomonas sp. LH128 on solute stress when actively degrading and growing on the PAH compound. To address the effect of solute stress on bacterial physiology and transcriptomic response, NaCl was used as osmolyte. Both acute and chronic solute stress was invoked to assess differences in short-term and long-term responses.
Project description:This study examines the transcriptomic response of biofilms of the PAH-degrading Sphingomonas sp. LH128 on solute stress when actively degrading and growing on the PAH compound. To address the effect of solute stress on bacterial physiology and transcriptomic response, NaCl was used as osmolyte. Both acute and chronic solute stress was invoked to assess differences in short-term and long-term responses. Transcriptomic response of phenanthrene degrading Sphingomonas sp. LH128 biofilms as a response to short-term and long-term solute (NaCl) stress was studied using genome-wide gene expression analysis. For this purpose, the strain was grown in customized continuous glass flow chambers that contain solid phenanthrene as a sole carbon source and that allow easy recovery of biofilm cells for transcriptomic and physiological analysis. A NaCl stress of 450 mM was imposed on LH128 biofilms growing on phenanthrene crystals coated on glass slides either for 4 hours (acute stress) or for 3 days (chronic stress). RNA was extracted from the biofilm and cDNA was synthesized and labeled with Cy3. Transcriptomic response in the stressed biofilms of three replicates per conditions were analyzed and compared with non-stressed
Project description:We constructed a comprehensive multi-omics map of the molecular effects of fluoxetine (an SSRI antidepressant), in 27 rat brain regions. We profiled gene expression (bulk RNA-seq, 210 datasets) and chromatin state (bulk chromatin immunoprecipitation sequencing (ChIP-seq) for the histone marker H3K27ac, 100 datasets) in a broad, unbiased panel of 27 brain regions across the entire rodent brain, in naive and fluoxetine-treated animals. We complemented this approach with single-cell RNA-seq (scRNA-seq) analysis of two brain regions. Using diverse integrative data analysis techniques we characterized the complex and multifaceted effects of fluoxetine on region-specific and cell-type-specific gene regulatory networks and pathways. Remarkably, we observed profound molecular changes across the brain (>4,000 differentially expressed genes and differentially acetylated ChIP-seq peaks each) that were highly region-dependent. We leveraged this atlas to identify fluoxetine-moduated genes and gene-regulatory loci, predict enriched motifs that suggest potential upstream regulators, and validate global mechanisms of fluoxetine action.
Project description:To determine fluoxetine-induced transcriptional signatures in GBM cancer cells, we performed RNA-sequencing analysis of three GBM patient-derived neurosphere cancer cell lines after fluoxetine or DMSO treatment. Genes with differential expression and associated transcriptional signatures were analyzed and identified in three cancer cell lines.
Project description:Here, we performed a high-throughput drug screening and identified fluoxetine, originally an FDA-approved antidepressant, as candidate therapeutic agent for NEPC. In vitro experiments revealed that fluoxetine effectively curbed the neuroendocrine differentiation and inhibited the cell viability by targeting the AKT pathway. Altogether, this work repurposed fluoxetine for antitumor application, and supported its clinical development for NEPC therapy, which may provide a promising therapeutic strategy.
Project description:We constructed a comprehensive multi-omics map of the molecular effects of fluoxetine (an SSRI antidepressant), in 27 rat brain regions. We profiled gene expression (bulk RNA-seq, 210 datasets) and chromatin state (bulk chromatin immunoprecipitation sequencing (ChIP-seq) for the histone marker H3K27ac, 100 datasets) in a broad, unbiased panel of 27 brain regions across the entire rodent brain, in naive and fluoxetine-treated animals. We complemented this approach with single-cell RNA-seq (scRNA-seq) analysis of two brain regions. Using diverse integrative data analysis techniques we characterized the complex and multifaceted effects of fluoxetine on region-specific and cell-type-specific gene regulatory networks and pathways. Remarkably, we observed profound molecular changes across the brain (>4,000 differentially expressed genes and differentially acetylated ChIP-seq peaks each) that were highly region-dependent. We leveraged this atlas to identify fluoxetine-moduated genes and gene-regulatory loci, predict enriched motifs that suggest potential upstream regulators, and validate global mechanisms of fluoxetine action.