Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 May:55:102769.
doi: 10.1016/j.ebiom.2020.102769. Epub 2020 May 8.

Sex-dependent associations between addiction-related behaviors and the microbiome in outbred rats

Affiliations

Sex-dependent associations between addiction-related behaviors and the microbiome in outbred rats

Veronica L Peterson et al. EBioMedicine. 2020 May.

Abstract

Background: Multiple factors contribute to the etiology of addiction, including genetics, sex, and a number of addiction-related behavioral traits. One behavioral trait where individuals assign incentive salience to food stimuli ("sign-trackers", ST) are more impulsive compared to those that do not ("goal-trackers", GT), as well as more sensitive to drugs and drug stimuli. Furthermore, this GT/ST phenotype predicts differences in other behavioral measures. Recent studies have implicated the gut microbiota as a key regulator of brain and behavior, and have shown that many microbiota-associated changes occur in a sex-dependent manner. However, few studies have examined how the microbiome might influence addiction-related behaviors. To this end, we sought to determine if gut microbiome composition was correlated with addiction-related behaviors determined by the GT/ST phenotype.

Methods: Outbred male (N=101) and female (N=101) heterogeneous stock rats underwent a series of behavioral tests measuring impulsivity, attention, reward-learning, incentive salience, and locomotor response. Cecal microbiome composition was estimated using 16S rRNA gene amplicon sequencing. Behavior and microbiome were characterized and correlated with behavioral phenotypes. Robust sex differences were observed in both behavior and microbiome; further analyses were conducted within sex using the pre-established goal/sign-tracking (GT/ST) phenotype and partial least squares differential analysis (PLS-DA) clustered behavioral phenotype.

Results: Overall microbiome composition was not associated to the GT/ST phenotype. However, microbial alpha diversity was significantly decreased in female STs. On the other hand, a measure of impulsivity had many significant correlations to microbiome in both males and females. Several measures of impulsivity were correlated with the genus Barnesiella in females. Female STs had notable correlations between microbiome and attentional deficient. In both males and females, many measures were correlated with the bacterial families Ruminocococcaceae and Lachnospiraceae.

Conclusions: These data demonstrate correlations between several addiction-related behaviors and the microbiome specific to sex.

Keywords: Addiction; Gut-brain axis; Microbiome; Sex; Sign-tracker.

PubMed Disclaimer

Conflict of interest statement

Declaration of Competing Interest JFC & TGD are in receipt of research funding from 4D‐Pharma, Mead Johnson, Nutricia, and Cremo. Timothy Dinan has been an invited speaker at meetings organized by Servier, Lundbeck, Janssen, and AstraZeneca. John Cryan has been an invited speaker at meetings organized by Mead Johnsen, Alkermes, and Janssen.

Figures

Fig 1
Fig. 1
Flow Diagram of how behavioral measures are used to create goal/sign-tracking phenotype and behavioral cluster phenotype.
Fig 2
Fig. 2
Male behavioral phenotypes and behavioral comparisons – (A) Behavioral Phenotype Cluster visualized in principal coordinate analysis (PCA) of PLS-DA clustered behavioral measures. Each dot represents an individual rat, distance from one dot to another represents overall differences in behavioral measures.Goal-trackers (GT) colored green, intermediate (IN) blue, sign-trackers (ST) red. (B) Z score indicate increases (red) or decreases (blue) in behavioral measures by behavioral cluster group and goal/sign-tracker phenotype group compared to entire male population. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig 3
Fig. 3
Female behavioral phenotypes and behavioral comparisons – (A) Behavioral Phenotype Cluster visualized in principal coordinate analysis (PCA) of PLS-DA clustered behavioral measures. Each dot represents an individual rat, distance from one dot to another represents overall differences in behavioral measures. Goal-trackers (GT) colored green, intermediate (IN) blue, sign-trackers (ST) red. (B) Z score indicate increases (red) or decreases (blue) in behavioral measures by behavioral cluster group and goal/sign-tracker phenotype group compared to entire female population. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig 4
Fig. 4
Male alpha diversity by phenotype group – (A) Shannon index measure of alpha diversity by behavioral cluster (M.Behav.Clust.1 = orange, M.Behav.Clust.2 = purple). (B) Shannon index by goal/sign-tracking phenotype: goal-tracker (M.GT = green), intermediate (M.IN = blue), and sign-tracker (M.ST = red). (C) Simpson index measures of male alpha diversity by behavioral cluster. (D) Simpson index of male goal/sign-tracker phenotype. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig 5
Fig. 5
Female alpha diversity by phenotype group – (A) Shannon index measure of alpha diversity by behavioral cluster (F.Behav.Clust.1 = orange, F.Behav.Clust.2 = purple). (B) Shannon index by goal/sign-tracking phenotype: goal-tracker (F.GT = green), intermediate (F.IN = blue), and sign-tracker (F.ST = red). (C) Simpson index measures of female alpha diversity by behavioral cluster. (D) Simpson index of female goal/sign-tracker phenotype. Asterisks indicate significance: ‘***’ p<0.001, ‘**’ p<0.01. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig 6
Fig. 6
Correlation analysis in male and female goal/sign-tracking phenotype. (A) Correlations between OTU-level bacteria and behavior in male goal/sign-tracking phenotype. (B) Correlations between OTU-level bacteria and behavior in female goal/sign-tracking phenotype. Positive correlations indicated in red, negative correlations indicated in blue. Significance that passes FDR indicated by asterisk: ‘***’ q<0.05, ‘**’ q<0.10, ‘*’ q<0.15. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig 7
Fig. 7
Correlation analysis in male and female behavioral clusters. (A) Correlation between OTU-level bacteria and behavior in male behavioral cluster phenotype. (B) Correlation between OTU-level bacteria and behavior in female behavioral cluster phenotype. Positive correlations indicated in red, negative correlations indicated in blue. Significance that passes FDR indicated by asterisk: ‘***’ q<0.05, ‘**’ q<0.10, ‘*’ q<0.15. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig 8
Fig. 8
Correlation analysis by sex. Correlations between OTU-level bacteria and behavior in entire female and male populations. Positive correlations indicated in red, negative correlations indicated in blue. Significance that passes FDR indicated by asterisk: ‘***’ q<0.05, ‘**’ q<0.10, ‘*’ q<0.15. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Similar articles

Cited by

References

    1. Acharya C., Betrapally N.S., Gillevet P.M., Sterling R.K., Akbarali H., White M.B., Ganapathy D., Fagan A., Sikaroodi M., Bajaj J.S. Chronic opioid use is associated with altered gut microbiota and predicts readmissions in patients with cirrhosis. Aliment Pharmacol Ther. 2017;45:319–331. - PubMed
    1. Amato K.R., Leigh S.R., Kent A., Mackie R.I., Yeoman C.J., Stumpf R.M., Wilson B.A., Nelson K.E., White B.A., Garber P.A. The role of gut microbes in satisfying the nutritional demands of adult and juvenile wild, black howler monkeys (Alouatta Pigra) Am J Phys Anthropol. 2014;155:652–664. - PubMed
    1. Audet M.C. Stress-induced disturbances along the gut microbiota-immune-brain axis and implications for mental health: does sex matter? Front Neuroendocrinol. 2019;54 - PubMed
    1. Baer, M.L., Williams, H.N., 2015. Vampirovibrio, Bergey's Manual of Systematics of Archaea and Bacteria, pp. 1-2.
    1. Bailey M.T., Dowd S.E., Galley J.D., Hufnagle A.R., Allen R.G., Lyte M. Exposure to a social stressor alters the structure of the intestinal microbiota: implications for stressor-induced immunomodulation. Brain Behav Immun. 2011;25:397–407. - PMC - PubMed

MeSH terms