Dependence-induced increase of alcohol self-administration and compulsive drinking mediated by the histone methyltransferase PRDM2

Abstract

Epigenetic processes have been implicated in the pathophysiology of alcohol dependence, but the specific molecular mechanisms mediating dependence-induced neuroadaptations remain largely unknown. Here, we found that a history of alcohol dependence persistently decreased the expression of Prdm2, a histone methyltransferase that monomethylates histone 3 at the lysine 9 residue (H3K9me1), in the rat dorsomedial prefrontal cortex (dmPFC). Downregulation of Prdm2 was associated with decreased H3K9me1, supporting that changes in Prdm2 mRNA levels affected its activity. Chromatin immunoprecipitation followed by massively parallel DNA sequencing showed that genes involved in synaptic communication are epigenetically regulated by H3K9me1 in dependent rats. In non-dependent rats, viral-vector-mediated knockdown of Prdm2 in the dmPFC resulted in expression changes similar to those observed following a history of alcohol dependence. Prdm2 knockdown resulted in increased alcohol self-administration, increased aversion-resistant alcohol intake and enhanced stress-induced relapse to alcohol seeking, a phenocopy of postdependent rats. Collectively, these results identify a novel epigenetic mechanism that contributes to the development of alcohol-seeking behavior following a history of dependence.

Prefrontal cortex expression of chromatin modifier genes in male WSP and WSR mice changes across ethanol dependence, withdrawal, and abstinence

“…Whether or not a strict “histone code” of post-translational modifications exists, the combination of several histone PTMs regulates chromatin structure and function in modulating gene expression (Gardner, Allis, and Strahl, 2011). Since alcohol does not modulate gene expression unidirectionally (Barbier et al, 2016; Bergeson et al, 2005; Liu et al, 2006; Ponomarev et al, 2012; Wilhelm, Hashimoto, Roberts, Sonmez, and Wiren, 2014), it is not surprising that alcohol does not unidirectionally alter chromatin structure toward a closed or open state, as suggested by the results of this study.…”

“…In general, the alcohol addiction cycle has been described as consisting of three stages: intoxication, withdrawal, and craving/abstinence (Koob and Volkow, 2010). Recently, the potential for involvement of changes in chromatin structure in alcohol abuse has been the focus of intensive research (Barbier et al, 2016; Finegersh et al, 2015; Gavin, Kusumo, Zhang, Guidotti, and Pandey, 2016; Mathies et al, 2015; Repunte-Canonigo et al, 2014; Schuebel, Gitik, Domschke, and Goldman, 2016). …”

“…Although there is an emerging literature on the effects of alcohol on epigenetic mediators (Barbier et al, 2015, 2016; Cervera-Juanes, Wilhelm, Park, Grant, and Ferguson, 2016; Pandey, Ugale, Zhang, Tang, and Prakash, 2008; Ponomarev, Wang, Zhang, Harris, and Mayfield, 2012; Warnault, Darcq, Levine, Barak, and Ron, 2013), no study has systematically and comprehensively examined changes in the expression of genes encoding for chromatin modifying proteins after chronic alcohol exposure, alcohol withdrawal, and protracted abstinence.…”

The prefrontal cortex as a critical gate of negative affect and motivation in alcohol use disorder

“…For example, while repeated cycles of excessive drinking and withdrawal produce an accumulation of damage in the PFC, trophic support mechanisms are also likely compromised due to decreased levels of brain-derived neurotrophic factor and nerve growth factor [46]. The emerging role of alcohol-induced neuroimmune dysregulation [47] and epigenetic modification [48] within the PFC also represents a fertile area for future research and medication development. Finally, the influence of sex on the interaction of stress, excessive drinking, and PFC function should be explored further [49], particularly given the unique relationship between PFC glucocorticoid signaling and alcohol-induced neurotoxicity in females [50].…”

Optimized functional annotation of ChIP-seq data

“…. , n th -closest genes to any given peak (or set 33 of peaks), thereby focusing on and prioritizing the biology over simply the raw numbers 34 (in base pairs). Detailed expositions of these new methods and their implications on the 35 interpretation of results from data analyses are presented as case studies in the 36 geneXtendeR package vignette.…”