Microbial Differences Accurately Identifies Global SERT KO Phenotype in Mice

Abstract

Altered serotonin signaling is a well-established contributor to depression, with the serotonin transporter gene (SERT) playing a critical role in regulating serotonin reuptake. Mice lacking SERT (SERT -/-) serve as a robust model for depression, exhibiting significant depressive-like behaviors compared to littermate wild-type (SERT +/+) controls. In this study, we aimed to determine the relationship between gut microbiota composition and depressive behaviors in SERT -/- mice. Behavioral assays, including the Forced Swim Test (FST) and Tail Suspension Test (TST), confirmed that SERT -/- mice exhibited significantly increased immobility times compared to SERT +/+ mice (FST: p = 0.004; TST: p = 0.080), consistent with a depressive phenotype. Utilizing littermate controls, shotgun metagenomic sequencing of fecal samples revealed significant differences in alpha diversity between the two groups of mice, as measured by the Shannon entropy index (p = 0.05). Additionally, our bacterial co-occurrence network analysis uncovered distinct structural differences in microbial interactions between SERT -/- and SERT +/+ mice (p = 0.001), suggesting shifts in microbiome stability and functionality between the groups. We created a microbial depression score utilizing the top five bacteria taxa that were differentially abundant between SERT -/- and SERT +/+ mice: Clostridium sp. MD294, Acetatifactor MGBC165152, Desulfovibrio MGBC129232, Oscillibacter MGBC161747, and Schaedlerella MGBC000001. This microbial depression score correlated strongly with immobility times in the FST (r = 0.705, p < 0.0006) and TST (r = 0.401, p < 0.09). A random forest classifier based on these taxa accurately distinguished SERT -/- from SERT +/+ mice (accuracy = 0.82). These findings suggest that gut microbial species composition is highly associated with depressive-like behaviors in SERT -/- mice, likely via alterations in serotonin signaling pathways, and may offer potential targets for microbiome-based interventions in depression.