Marsh, S. A. | Search bioRxiv

bioRxiv2021

Opioid withdrawal produces sex-specific effects on fentanyl-vs.-food choice and mesolimbic transcription

BackgroundOpioid withdrawal is a key driver of opioid addiction and an obstacle to recovery. However, withdrawal effects on opioid reinforcement and mesolimbic neuroadaptation are understudied and the role of sex is largely unknown. MethodsMale (n=10) and female (n=9) rats responded under a fentanyl-vs.-food "choice" procedure during daily 2h sessions. In addition to the daily choice sessions, rats were provided extended access to fentanyl during 12h sessions. After two weeks of this self-administration regimen, the nucleus accumbens (NAc) and ventral tegmental area (VTA) of a subset of rats were subjected to RNA sequencing. In the remaining rats, a third week of this self-administration regimen was conducted, during which methadone effects on fentanyl-vs.-food choice were determined. ResultsPrior to opioid dependence, male and female rats similarly allocated responding between fentanyl and food. Abstinence from extended fentanyl access elicited a similar increase in somatic withdrawal signs in both sexes. Despite similar withdrawal signs and extended access fentanyl intake, opioid withdrawal was accompanied by a maladaptive increase in fentanyl choice in males, but not females. Behavioral sex differences corresponded with transcriptional hyperfunction in the NAc and VTA of opioid-withdrawn females relative to males. Methadone blocked withdrawal-associated increases in fentanyl choice in males, but failed to further decrease fentanyl choice in females. ConclusionsThese results provide foundational evidence of sex-specific neuroadaptations to opioid withdrawal, which may be relevant to the female-specific resilience to withdrawal-associated increases in opioid choice and aid in the identification of novel therapeutic targets.

neuroscience↗

bioRxiv2020

CeMbio - The C. elegans microbiome resource

The study of microbiomes by sequencing has revealed a plethora of correlations between microbial community composition and various life-history characteristics of the corresponding host species. However, inferring causation from correlation is often hampered by the sheer compositional complexity of microbiomes, even in simple organisms. Synthetic communities offer an effective approach to infer cause-effect relationships in host-microbiome systems. Yet the available communities suffer from several drawbacks, such as artificial (thus non-natural) choice of microbes, microbe-host mismatch (e.g. human microbes in gnotobiotic mice), or hosts lacking genetic tractability. Here we introduce CeMbio, a simplified natural Caenorhabditis elegans microbiota derived from our previous meta-analysis of the natural microbiome of this nematode. The CeMbio resource is amenable to all strengths of the C. elegans model system, strains included are readily culturable, they all colonize the worm gut individually, and comprise a robust community that distinctly affects nematode life-history. Several tools have additionally been developed for the CeMbio strains, including diagnostic PCR primers, completely sequenced genomes, and metabolic network models. With CeMbio, we provide a versatile resource and toolbox for the in-depth dissection of naturally relevant host-microbiome interactions in C. elegans. Dataset accession numbersWhole genome sequencing data (PRJNA624308); microbiome sequencing [PRJEB37101 and PRJEB37035]; data supplement on the GSA Figshare Portal.

microbiology↗