The microbiota-gut-brain axis in depression: unraveling the relationships and therapeutic opportunities

Major depressive disorder (MDD) affects ~280 million individuals annually and is characterized by low mood, anhedonia, cognitive impairments, and suicidality. First-line antidepressants often have delayed onset (4–6 weeks) and limited efficacy, motivating exploration of new mechanisms and treatments. The microbiota-gut-brain axis (MGBA)—a bidirectional communication network linking gut microbiota with the CNS—has emerged as a key contributor to depression pathogenesis. Clinical and preclinical studies show gut dysbiosis in depression, FMT from depressed donors induces depressive-like phenotypes in animals, and certain probiotics alleviate symptoms. The review interrogates how gut microbiota modulate depression via three principal pathways: immune regulation (e.g., cytokines), endocrine modulation (e.g., HPA axis), and neural signaling (e.g., vagus nerve and neurotransmitters), and assesses therapeutic opportunities that target MGBA.

Preclinical evidence across multiple rodent and primate models (e.g., CUMS, CSDS, maternal separation, learned helplessness, corticosterone-induced depression, nonhuman primates) demonstrates that stress and depression paradigms consistently alter gut microbiota composition (e.g., increased Proteobacteria, Verrucomicrobia, Helicobacter, Bacteroides, Desulfovibrio; decreased Lactobacillaceae, Bifidobacteriaceae, Akkermansia). FMT from depressed models or patients induces depressive-like behaviors and neuroinflammatory changes; SCFA supplementation and probiotics reverse phenotypes. Clinical studies report increased Enterobacteriaceae and Alistipes, decreased Faecalibacterium, Coprococcus, and Roseburia in MDD, with sex- and age-specific patterns, postpartum depression-specific shifts, and dynamic microbiota changes during escitalopram treatment (notably spore-formers after 12 weeks). Trials indicate probiotics can reduce depressive and anxiety symptoms, improve cognitive function, and modulate biomarkers. The review synthesizes MGBA mechanisms: neural (ENS, vagus nerve, neurotransmitters 5-HT, GABA, dopamine), endocrine (HPA axis, SCFAs, bile acids, indoles), and immune (barrier integrity, LPS, cytokines, microglia, Th17/Treg balance).

- Gut dysbiosis is consistently associated with depression across models and clinical cohorts. In CUMS mice: Proteobacteria and Verrucomicrobia ↑; Bifidobacteriaceae and Lactobacillaceae ↓; FMT from CUMS donors transfers depressive phenotypes. In CSDS mice: Bacilli, Bacteroidia, Mollicutes, Verrucomicrobiae ↑; Erysipelotrichi ↓; Lactobacillus abundance declines; targeted strains modulate behavior and IL-1β. - Clinical MDD: Enterobacteriaceae and Alistipes ↑; Firmicutes ↓; Faecalibacterium and Coprococcus ↓, correlating with symptom severity. Female MDD: Bacteroidetes, Proteobacteria, Fusobacteria ↑; controls higher Firmicutes, Actinobacteria. Sex-specific differences include Bacteroides ↓ in males; Actinobacteria ↑ in females. Postpartum depression: Faecalibacterium, Phascolarctobacterium, Butyricicoccus, Lachnospiraceae ↓; Enterobacteriaceae ↑; microbiota linked to sex hormones. - Antidepressant interaction: Escitalopram (n=110) produced significant microbiota changes by week 12, notably in spore-forming bacteria; common antidepressants alter microbiota composition; gut bacteria can bioaccumulate drugs (e.g., venlafaxine), potentially reducing efficacy. - Neural signaling: Vagus nerve mediates microbiota effects on brain; probiotic-induced behavioral benefits abolished by vagotomy; LPS-induced depressive behaviors eliminated by subdiaphragmatic vagotomy. Gut microbiota regulate neurotransmitters: ~95% of 5-HT synthesized in gut; GF mice show ~2.8-fold lower 5-HT; probiotics modulate 5-HT/GABA/dopamine pathways and improve mood. - Endocrine modulation: HPA axis dysregulation in depression is influenced by gut microbiota; SCFAs (acetate, propionate, butyrate) reduced under chronic stress and in post-stroke depression, linked to neuroinflammation and BBB integrity; bile acid profiles altered in MDD (e.g., 2,3-deoxycholic acid ↑; TLCA, GLCA ↓); tryptophan-derived indoles (e.g., indoxyl sulfate) associate with depressive severity; indole-3-lactic acid and I3C exhibit anti-inflammatory, AhR-mediated benefits. - Immune regulation: Leaky gut and LPS translocation activate systemic and CNS inflammation (IL-6, TNF-α, IL-1β), microglial activation, and Th17/Treg imbalance; microbiota-targeted agents (rifaximin, minocycline, lactococci, lactobacilli) improve behavior and cytokine profiles. - Therapeutics: Probiotics, prebiotics, synbiotics, postbiotics, dietary interventions, and FMT show promise. Probiotic efficacy depends on dose (>10×10^9 CFU) and duration (>8 weeks). FMT can both induce and alleviate depressive phenotypes depending on donor; AI-driven donor-recipient matching proposed to optimize outcomes.

Findings consolidate the MGBA as a central framework for understanding depression pathogenesis. Dysbiotic shifts in specific taxa and metabolites (e.g., Enterobacteriaceae ↑, Faecalibacterium ↓; SCFAs ↓; LPS ↑; bile acids and indoles altered) mechanistically converge on neural, endocrine, and immune axes: vagus-mediated signaling and neurotransmitter modulation (5-HT, GABA, dopamine), HPA axis activation and metabolic signaling (SCFAs, bile acids, indoles), and systemic-to-CNS inflammatory cascades (cytokines, microglia, Th17/Treg balance). These interconnected pathways explain symptomatology (anhedonia, stress sensitivity, cognitive deficits) and identify intervention nodes. Therapeutically, microbiota-targeted strategies—probiotics, diet, syn/postbiotics, FMT—can complement pharmacotherapy and potentially address treatment resistance by reshaping microbial communities and neuroactive metabolites. Interactions between antidepressants and the microbiome underscore the need to consider bidirectional effects in clinical management. Overall, MGBA-directed diagnostics and personalized interventions may enhance outcomes beyond conventional monoamine-based approaches.

The review highlights the gut microbiota as a pivotal contributor to depression via neuroimmune, neuroendocrine, and neural signaling within the MGBA. Specific microbial signatures and metabolites emerge as diagnostic biomarkers and therapeutic targets. Microbiome-based interventions (probiotics, prebiotics, synbiotics, postbiotics, FMT) show translational promise, alongside innovative approaches (engineered psychobiotics, phage-based modulation, AI-optimized FMT). Future work should (1) establish causal mechanisms using humanized gnotobiotic models and advanced multi-omics/spatial metabolomics; (2) develop standardized, multi-omics-defined microbial consortia to reduce heterogeneity; (3) integrate precision medicine by combining microbiome-host genetics, epigenetics, and lifestyle factors; and (4) advance synthetic biology and nanotechnology platforms for targeted delivery. Interdisciplinary collaboration will be key to moving MGBA insights into clinically actionable, personalized therapies for depression.

- As a narrative review, no systematic search or quantitative synthesis methodology is detailed, limiting reproducibility and risk-of-bias assessment. - Heterogeneity across cohorts (age, sex, comorbidities, diet, medications), analytic platforms (16S vs shotgun metagenomics), and geographic factors complicates generalizability. - Causality remains incompletely established in humans; many mechanistic insights derive from animal models. - Probiotic effects are strain-, dose-, and duration-dependent, with inconsistent clinical results; optimal synbiotic/postbiotic formulations are not standardized. - FMT efficacy varies with donor selection, dose, route, and frequency; safety concerns (transient GI symptoms, infection risk) and regulatory standardization are ongoing challenges; long-term outcomes are underexplored. - Drug–microbiome interactions and polypharmacy create complex, understudied dynamics that may influence antidepressant response and adverse effects. - Biomarker development (microbial taxa, metabolite panels) requires validation in large, diverse, longitudinal cohorts.