Background MicroRNAs (miRNAs) are small, non-coding oligonucleotides with an important role in post transcriptional regulation of gene expression at the level of translation and mRNA degradation. Recent studies have revealed that miRNAs play important roles in a variety of biological processes, such as cell proliferation, neuronal differentiation, developmental timing, synapse function and neurogenesis. A single miRNA can target hundreds of mRNA transcripts for either translation repression or degradation, but the function of many human miRNAs is not known. Methods MiRNA array analysis was performed on the prefrontal cortex of 27 individual human cases (14 alcoholics and 13 matched controls). Target genes for differentially expressed miRNAs were predicted using multiple target prediction algorithms and a consensus approach, and predicted targets were matched against differentially expressed mRNAs from the same samples. Over- and under-representation analysis was performed using hypergeometric probability and z-score tests. Results Approximately 35 miRNAs were significantly up-regulatedin the alcoholic group compared with controls. Target prediction showed a large degree of overlap with our published cDNA microarray data. Functional classification of the predicted target genes of the regulated miRNAs includes apoptosis, cell cycle, cell adhesion, nervous system development and cell-cell signaling. Conclusions This data suggests that the reduced expression of genes in human alcoholic cases may be due to the up-regulated miRNAs. Cellular processes fundamental to neuronal plasticity appear to represent major targets of the suggested miRNA regulation.

Repeated ethanol exposure and withdrawal in mice increases voluntary drinking and represents an animal model of physical dependence. We examined time- and brain region-dependent changes in gene coexpression networks in amygdala (AMY), nucleus accumbens (NAC), prefrontal cortex (PFC), and liver after four weekly cycles of chronic intermittent ethanol (CIE) vapor exposure in C57BL/6J mice. Microarrays were used to compare gene expression profiles at 0-, 8-, and 120-hours following the last ethanol exposure. Each brain region exhibited a large number of differentially expressed genes (2,000-3,000) at the 0- and 8-hour time points, but fewer changes were detected at the 120-hour time point (400-600). Within each region, there was little gene overlap across time (~20%). All brain regions were significantly enriched with differentially expressed immune-related genes at the 8-hour time point. Weighted gene correlation network analysis identified modules that were highly enriched with differentially expressed genes at the 0- and 8-hour time points with virtually no enrichment at 120 hours. Modules enriched for both ethanol-responsive and cell-specific genes were identified in each brain region. These results indicate that chronic alcohol exposure causes global ‘rewiring‘ of coexpression systems involving glial and immune signaling as well as neuronal genes.

Alcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models. But none of these studies have systematically investigated expression within the unique cell types present in the brain. We utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16 000 nuclei isolated from the prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes and microglia. To our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species and the first such analysis in humans for any addictive substance. These findings greatly advance the understanding of transcriptomic changes in the brain of alcohol-dependent individuals.

BackgroundAlcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models.But none of these studies have systematically investigated expression within the unique cell types present in the brain. ResultsWe utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16,000 nuclei isolated from prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes, and microglia. ConclusionsTo our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species, and the first such analysis in humans for any addictive substance. These findings greatly advance understanding of transcriptomic changes in the brain of alcohol-dependent individuals.1 Background Alcohol abuse is involved in over 200 pathologies and health conditions (e.g. alcohol dependence, liver cirrhosis, cancers, and injuries) and creates substantial social and economic burdens (1,2) . To develop more effective therapeutic strategies, we must first understand how alcohol affects the body at the cellular and molecular level. Previous studies of transcriptomic responses in human alcoholics (3-6) relied on RNA extracted from brain regions using tissue homogenates comprised of multiple cell types. This approach likely masks differences in gene expression patterns among specific cells, as well as heterogeneity from cell-to-cell variation within a given cell type.Single cell RNA sequencing (scRNA-seq) has recently gained attention in cell and molecular biology research for its ability to profile novel cell types and measure cell-to-cell variation in gene expression. To our knowledge, transcriptomic responses to chronic alcohol exposure or any other abused drug have not been studied at the cellular level in the human brain. We hypothesized that cell type-specific gene expression patterns associated with alcoholism will identify novel alcohol targets that were previously missed by bulk analysis of tissue homogenates, as has been shown for other neuropathologies (7,8) . Using single nucleus RNA-seq (snRNA-seq), a popular scRNA-seq alternative for analyzing frozen brain tissue (9-18) , we profiled the transcriptomes of 16,305 nuclei extracted from frozen prefrontal cortex (PFC) samples of 4 control and 3 alcohol dependent individuals. The PFC is involved in executive function and is an important substrate in the reward circuitry associated with development of a...

Long-term alcohol use can result in lasting changes in brain function, ultimately leading to alcohol dependence. These functional alterations arise from dysregulation of complex gene networks, and growing evidence implicates microRNAs as key regulators of these networks. We examined time- and brain region-dependent changes in microRNA expression after chronic intermittent ethanol (CIE) exposure in C57BL/6J mice. Animals were sacrificed at 0, 8, and 120h following the last exposure to four weekly cycles of CIE vapor and we measured microRNA expression in prefrontal cortex (PFC), nucleus accumbens (NAC), and amygdala (AMY). The number of detected (395–419) and differentially expressed (DE, 42–47) microRNAs was similar within each brain region. However, the DE microRNAs were distinct among brain regions and across time within each brain region. DE microRNAs were linked with their DE mRNA targets across each brain region. In all brain regions, the greatest number of DE mRNA targets occurred at the 0 or 8h time points and these changes were associated with microRNAs DE at 0 or 8h. Two separate approaches (discrete temporal association and hierarchical clustering) were combined with pathway analysis to further characterize the temporal relationships between DE microRNAs and their 120h DE targets. We focused on targets dysregulated at 120h as this time point represents a state of protracted withdrawal known to promote an increase in subsequent ethanol consumption. Discrete temporal association analysis identified networks with highly connected genes including ERK1/2 (mouse equivalent Mapk3, Mapk1), Bcl2 (in AMY networks) and Srf (in PFC networks). Similarly, the cluster-based analysis identified hub genes that include Bcl2 (in AMY networks) and Srf in PFC networks, demonstrating robust microRNA-mRNA network alterations in response to CIE exposure. In contrast, datasets utilizing targets from 0 and 8h microRNAs identified NF-kB-centered networks (in NAC and PFC), and Smad3-centered networks (in AMY). These results demonstrate that CIE exposure results in dynamic and complex temporal changes in microRNA-mRNA gene network structure.