Transcriptome Analysis of Alcohol Drinking in Non-Dependent and Dependent Mice Following Repeated Cycles of Forced Swim Stress Exposure

Chronic stress is a known contributing factor to the development of drug and alcohol addiction. Animal models have previously shown that repeated forced swim stress promotes escalated alcohol consumption in dependent animals. To investigate the underlying molecular adaptations associated with stress and chronic alcohol exposure, RNA-sequencing and bioinformatics analyses were conducted on the prefrontal cortex (CTX) of male C57BL/6J mice that were behaviorally tested for either non-dependent alcohol consumption (CTL), chronic intermittent ethanol (CIE) vapor dependent alcohol consumption, repeated bouts of forced swim stress alone (FSS), and chronic intermittent ethanol with forced swim stress (CIE + FSS). Brain tissue from each group was collected at 0-h, 72-h, and 168-h following the final test to determine long-lasting molecular changes associated with maladaptive behavior. Our results demonstrate unique temporal patterns and persistent changes in coordinately regulated gene expression systems with respect to the tested behavioral group. For example, increased expression of genes involved in “transmitter-gated ion channel activity” was only determined for CIE + FSS. Overall, our results provide a summary of transcriptomic adaptations across time within the CTX that are relevant to understanding the neurobiology of chronic alcohol exposure and stress

Single cell transcriptome profiling of the human alcohol-dependent brain

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

The SMYD1 and skNAC transcription factors contribute to neurodegenerative diseases

SMYD1 and the skNAC isoform of the NAC transcription factor have both previously been characterized as transcription factors in hematopoiesis and cardiac/skeletal muscle. Here we report that comparative analysis of genes deregulated by SMYD1 or skNAC knockdown in differentiating C2C12 myoblasts identified transcripts characteristic of neurodegenerative diseases, including Alzheimer’s, Parkinson’s and Huntington’s Diseases (AD, PD, and HD). This led us to determine whether SMYD1 and skNAC function together or independently within the brain. Based on meta-analyses and direct experimentation, we observed SMYD1 and skNAC expression within cortical striata of human brains, mouse brains and transgenic mouse models of these diseases. We observed some of these features in mouse myoblasts induced to differentiate into neurons. Finally, several defining features of Alzheimer’s pathology, including the brain-specific, axon-enriched microtubule-associated protein, Tau, are deregulated upon SMYD1 loss

Up-regulation of microRNAs in brain of human alcoholics

Background: MicroRNAs (miRNAs) are small, noncoding oligonucleotides with an important role in posttranscriptional 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

Long-term ethanol exposure: Temporal pattern of microRNA expression and associated mRNA gene networks in mouse brain

<div><p>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.</p></div

Top IPA networks sharing common hub genes.

<p>Top IPA networks sharing common hub genes.</p

Overlap of probesets among brain regions.

<p>Data from all time points were combined for each brain region. Panel A shows overlap of all probes detected within each brain region. Panel B shows overlap of all probes DE (p ≤ 0.05) within each brain region.</p

MicroRNAs uniquely detected in each brain region (included in Fig 2A).

<p>MicroRNAs uniquely detected in each brain region (included in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190841#pone.0190841.g002" target="_blank">Fig 2A</a>).</p

Overview of procedure used to pair DE microRNAs with DE targets and analyses performed on resulting datasets.

<p>Overview of procedure used to pair DE microRNAs with DE targets and analyses performed on resulting datasets.</p