A comparison of the sexually dimorphic dexamethasone transcriptome in mouse cerebral cortical and hypothalamic embryonic neural stem cells

Genomic glucocorticoid action in embryonic mouse neural stem cells

Prenatal exposure to synthetic glucocorticoids (sGCs) reprograms brain development and predisposes the developing fetus towards potential adverse neurodevelopmental outcomes. Using a mouse model of sGC administration, previous studies show that these changes are accompanied by sexually dimorphic alterations in the transcriptome of neural stem and progenitor cells (NSPCs) derived from the embryonic telencephalon. Because cell type-specific gene expression profiles tightly regulate cell fate decisions and are controlled by a flexible landscape of chromatin domains upon which transcription factors and enhancer elements act, we multiplexed data from four genome-wide assays: RNA-seq, ATAC-seq (assay for transposase accessible chromatin followed by genome wide sequencing), dual cross-linking ChIP-seq (chromatin immunoprecipitation followed by genome wide sequencing), and microarray gene expression to identify novel relationships between gene regulation, chromatin structure, and genomic glucocorticoid receptor (GR) action in NSPCs. These data reveal that GR binds preferentially to predetermined regions of accessible chromatin to influence gene programming and cell fate decisions. In addition, we identify SOX2 as a transcription factor that impacts the genomic response of select GR target genes to sGCs (i.e., dexamethasone) in NSPCs.

Early transcriptomic response of mouse adrenal gland and Y-1 cells to dexamethasone

Glucocorticoids have short- and long-term effects on adrenal gland function and development. RNA sequencing (RNA-seq) was performed to identify early transcriptomic responses to the synthetic glucocorticoid, dexamethasone (Dex), in vitro and in vivo. In total, 1711 genes were differentially expressed in the adrenal glands of the 1-h Dex-treated mice. Among them, only 113 were also considered differentially expressed genes (DEGs) in murine adrenocortical Y-1 cells treated with Dex for 1 h. Gene ontology analysis showed that the upregulated DEGs in the adrenal gland of the 1-h Dex-treated mice were highly associated with the development of neuronal cells, suggesting the adrenal medulla had a rapid response to Dex. Interestingly, only 4.3% of Dex-responsive genes in the Y-1 cell line under Dex treatment for 1 h were differentially expressed under Dex treatment for 24 h. The heatmaps revealed that most early responsive DEGs in Y-1 cells during 1 h of treatment exhibited a transient response. The expression of these genes under treatment for 24 h returned to basal levels similar to that during control treatment. In summary, this research compared the rapid transcriptomic effects of Dex stimulation in vivo and in vitro. Notably, adrenocortical Y-1 cells had a transient early response to Dex treatment. Furthermore, the DEGs had a minimal overlap in the 1-h Dex-treated group in vivo and in vitro.

Metabolic Biomarkers Assessed with PET/CT Predict Sex-Specific Longitudinal Outcomes in Patients with Diffuse Large B-Cell Lymphoma

In many cancers, including lymphoma, males have higher incidence and mortality than females. Emerging evidence demonstrates that one mechanism underlying this phenomenon is sex differences in metabolism, both with respect to tumor nutrient consumption and systemic alterations in metabolism, i.e., obesity. We wanted to determine if visceral fat and tumor glucose uptake with fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) could predict sex-dependent outcomes in patients with diffuse large B-cell lymphoma (DLBCL). We conducted a retrospective analysis of 160 patients (84 males; 76 females) with DLBCL who had imaging at initial staging and after completion of therapy. CT-based relative visceral fat area (rVFA), PET-based SUVmax normalized to lean body mass (SULmax), and end-of-treatment FDG-PET 5PS score were calculated. Increased rVFA at initial staging was an independent predictor of poor OS only in females. At the end of therapy, increase in visceral fat was a significant predictor of poor survival only in females. Combining the change in rVFA and 5PS scores identified a subgroup of females with visceral fat gain and high 5PS with exceptionally poor outcomes. These data suggest that visceral fat and tumor FDG uptake can predict outcomes in DLBCL patients in a sex-specific fashion.

Exploring the Genetic Associations Between the Use of Statins and Alzheimer's Disease

Objective

Alzheimer's disease (AD) is the most common cause of dementia. The statins have shown beneficial effects on cognitive functions and reduced the risk of dementia development. However, the exact mechanisms of statin effects in AD are not yet fully understood. In this study, we aimed to explore the underlying mechanisms of statin on AD.

Methods

We downloaded AD blood dataset (GSE63060) and statin-related blood gene expression dataset (GSE86216). Then we performed gene expression analysis of each dataset and compared blood gene expressions between AD patients and statin-treated patients. Then, we downloaded mouse embryonic neural stem cell dataset (GSE111945) and performed gene expression analysis.

Results

From the human blood dataset, we identified upregulated/downregulated genes in AD patients and statin-treated patients. Some of the upregulated genes (AEN, MBTPS1, ABCG1) in the blood of AD patients are downregulated in statin-treated patients. Several downregulated genes (FGL2, HMGCS1, PSME2, SRSF3, and ATG3) are upregulated in statin-treated patients. Gene set enrichment analysis using mouse stem cell dataset revealed a significant relationship of Kyoto Encyclopedia of Genes and Genomes-defined pathway of AD in statin-treated neural stem cells compared to vehicle-treated neural stem cells (normalized enrichment score: −2.24 in male and −1.6 in female).

Conclusion

These gene expression analyses from human blood and mouse neural stem cell demonstrate the important clues on the molecular mechanisms of impacts of statin on AD disease. Further studies are needed to investigate the exact role of candidate genes and pathways suggested in our AD pathogenesis study.

3D RNA-seq: a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists

RNA-sequencing (RNA-seq) analysis of gene expression and alternative splicing should be routine and robust but is often a bottleneck for biologists because of different and complex analysis programs and reliance on specialized bioinformatics skills. We have developed the '3D RNA-seq' App, an R shiny App and web-based pipeline for the comprehensive analysis of RNA-seq data from any organism. It represents an easy-to-use, flexible and powerful tool for analysis of both gene and transcript-level gene expression to identify differential gene/transcript expression, differential alternative splicing and differential transcript usage (3D) as well as isoform switching from RNA-seq data. 3D RNA-seq integrates state-of-the-art differential expression analysis tools and adopts best practice for RNA-seq analysis. The program is designed to be run by biologists with minimal bioinformatics experience (or by bioinformaticians) allowing lab scientists to analyse their RNA-seq data. It achieves this by operating through a user-friendly graphical interface which automates the data flow through the programs in the pipeline. The comprehensive analysis performed by 3D RNA-seq is extremely rapid and accurate, can handle complex experimental designs, allows user setting of statistical parameters, visualizes the results through graphics and tables, and generates publication quality figures such as heat-maps, expression profiles and GO enrichment plots. The utility of 3D RNA-seq is illustrated by analysis of data from a time-series of cold-treated Arabidopsis plants and from dexamethasone-treated male and female mouse cortex and hypothalamus data identifying dexamethasone-induced sex- and brain region-specific differential gene expression and alternative splicing.

3D RNA-seq: a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists

RNA-sequencing (RNA-seq) analysis of gene expression and alternative splicing should be routine and robust but is often a bottleneck for biologists because of different and complex analysis programs and reliance on specialized bioinformatics skills. We have developed the '3D RNA-seq' App, an R shiny App and web-based pipeline for the comprehensive analysis of RNA-seq data from any organism. It represents an easy-to-use, flexible and powerful tool for analysis of both gene and transcript-level gene expression to identify differential gene/transcript expression, differential alternative splicing and differential transcript usage (3D) as well as isoform switching from RNA-seq data. 3D RNA-seq integrates state-of-the-art differential expression analysis tools and adopts best practice for RNA-seq analysis. The program is designed to be run by biologists with minimal bioinformatics experience (or by bioinformaticians) allowing lab scientists to analyse their RNA-seq data. It achieves this by operating through a user-friendly graphical interface which automates the data flow through the programs in the pipeline. The comprehensive analysis performed by 3D RNA-seq is extremely rapid and accurate, can handle complex experimental designs, allows user setting of statistical parameters, visualizes the results through graphics and tables, and generates publication quality figures such as heat-maps, expression profiles and GO enrichment plots. The utility of 3D RNA-seq is illustrated by analysis of data from a time-series of cold-treated Arabidopsis plants and from dexamethasone-treated male and female mouse cortex and hypothalamus data identifying dexamethasone-induced sex- and brain region-specific differential gene expression and alternative splicing.

A Novel Methodology Using Dexamethasone to Induce Neuronal Differentiation in the CNS-Derived Catecholaminergic CAD Cells

The Cath.a-differentiated (CAD) cell line is a central nervous system-derived catecholaminergic cell line originating from tyrosine hydroxylase (TH)-producing neurons located around the locus coeruleus area of the mouse brain. CAD cells have been used as an in vitro model for cellular and molecular studies due to their ability to differentiate under serum-free media conditions. However, the lack of serum-derived survival factors, limits the longevity for differentiated CAD cells to be maintained in healthy conditions; thereby, limiting their use in long-term culture studies. Here, we present a novel differentiation method that utilizes dexamethasone (Dex), a synthetic glucocorticoid receptor agonist. Specifically, we discovered that the addition of 100 µM of Dex into the 1% fetal bovine serum (FBS)-supplemented media effectively induced neuronal differentiation of CAD cells, as characterized by neurite formation and elongation. Dex-differentiated CAD cells exited the cell cycle, stopped proliferating, extended the neurites, and expressed neuronal markers. These effects were dependent on the glucocorticoid receptors (GR) as they were abolished by GR knockdown. Importantly, Dex-differentiated CAD cells showed longer survival duration than serum-free differentiated CAD cells. In addition, RNA-sequencing and qPCR data demonstrate that several genes involved in proliferation, neuronal differentiation, and survival pathways were differentially expressed in the Dex-differentiated cells. This is the first study to reveal Dex as a novel differentiation methodology used to generate postmitotic neuronal CAD cells, which may be utilized as an in vitro neuronal model for cellular and molecular neurobiology research.

Antenatal Dexamethasone Treatment Induces Sex-dependent Upregulation of NTPDase1/CD39 and Ecto-5'-nucleotidase/CD73 in the Rat Fetal Brain

Dexamethasone (DEX) is frequently used to treat women at risk of preterm delivery, but although indispensable for the completion of organ maturation in the fetus, antenatal DEX treatment may exert adverse sex-dimorphic neurodevelopmental effects. Literature findings implicated oxidative stress in adverse effects of DEX treatment. Purinergic signaling is involved in neurodevelopment and controlled by ectonucleotidases, among which in the brain the most abundant are ectonucleoside triphosphate diphosphohydrolase 1 (NTPDase1/CD39) and ecto-5'-nucleotidase (e5'NT/CD73), which jointly dephosphorylate ATP to adenosine. They are also involved in cell adhesion and migration, processes integral to brain development. Upregulation of CD39 and CD73 after DEX treatment was reported in adult rat hippocampus. We investigated the effects of maternal DEX treatment on CD39 and CD73 expression and enzymatic activity in the rat fetal brain of both sexes, in the context of oxidative status of the brain tissue. Fetuses were obtained at embryonic day (ED) 21, from Wistar rat dams treated with 0.5 mg DEX/kg/day, at ED 16, 17, and 18, and brains were processed and used for further analysis. Sex-specific increase in CD39 and CD73 expression and in the corresponding enzyme activities was induced in the brain of antenatally DEX-treated fetuses, more prominently in males. The oxidative stress induction after antenatal DEX treatment was confirmed in both sexes, although showing a slight bias in males. Due to the involvement of purinergic system in crucial neurodevelopmental processes, future investigations are needed to determine the role of these observed changes in the adverse effects of antenatal DEX treatment.

Prenatal drug exposure and neurodevelopmental programming of glucocorticoid signalling

Prenatal neurodevelopment is dependent on precise functioning of multiple signalling pathways in the brain, including those mobilised by glucocorticoids (GC) and endocannabinoids (eCBs). Prenatal exposure to drugs of abuse, including opioids, alcohol, cocaine and cannabis, has been shown to not only impact GC signalling, but also alter functioning of the hypothalamic-pituitary-adrenal (HPA) axis. Such exposures can have long-lasting neurobehavioural consequences, including alterations in the stress response in the offspring. Furthermore, cannabis contains cannabinoids that signal via the eCB pathway, which is linked to some components of GC signalling in the adult brain. Given that GCs are frequently used in pregnancy to prevent complications of prematurity, and also that rates of cannabis use in pregnancy are increasing, the likelihood of foetal co-exposure to these compounds is high and may have additional implications for long-term neurodevelopment. Here, we present a discussion of GC signalling and the HPA axis, as well as the effects of prenatal drug exposure on these pathways and the stress response, and we explore the interactions between GC and EC signalling in the developing brain and potential for neurodevelopmental consequences.

Expression and glucocorticoid-dependent regulation of the stress-inducible protein DRR1 in the mouse adult brain

Identifying molecular targets that are able to buffer the consequences of stress and therefore restore brain homeostasis is essential to develop treatments for stress-related disorders. Down-regulated in renal cell carcinoma 1 (DRR1) is a unique stress-induced protein in the brain and has been recently proposed to modulate stress resilience. Interestingly, DRR1 shows a prominent expression in the limbic system of the adult mouse. Here, we analyzed the neuroanatomical and cellular expression patterns of DRR1 in the adult mouse brain using in situ hybridization, immunofluorescence and Western blot. Abundant expression of DRR1 mRNA and protein was confirmed in the adult mouse brain with pronounced differences between distinct brain regions. The strongest DRR1 signal was detected in the neocortex, the CA3 region of the hippocampus, the lateral septum and the cerebellum. DRR1 was also present in circumventricular organs and its connecting regions. Additionally, DRR1 was present in non-neuronal tissues like the choroid plexus and ependyma. Within cells, DRR1 protein was distributed in a punctate pattern in several subcellular compartments including cytosol, nucleus as well as some pre- and postsynaptic specializations. Glucocorticoid receptor activation (dexamethasone 10 mg/kg s.c.) induced DRR1 expression throughout the brain, with particularly strong induction in white matter and fiber tracts and in membrane-rich structures. This specific expression pattern and stress modulation of DRR1 point to a role of DRR1 in regulating how cells sense and integrate signals from the environment and thus in restoring brain homeostasis after stressful challenges.

Gene-level differential analysis at transcript-level resolution

Compared to RNA-sequencing transcript differential analysis, gene-level differential expression analysis is more robust and experimentally actionable. However, the use of gene counts for statistical analysis can mask transcript-level dynamics. We demonstrate that ‘analysis first, aggregation second,’ where the p values derived from transcript analysis are aggregated to obtain gene-level results, increase sensitivity and accuracy. The method we propose can also be applied to transcript compatibility counts obtained from pseudoalignment of reads, which circumvents the need for quantification and is fast, accurate, and model-free. The method generalizes to various levels of biology and we showcase an application to gene ontologies.