SPF male SD rats (weight 180–200 g) were purchased from Zhuhai baishitong biology science and technology co., ltd. All rats were housed under standard laboratory conditions (12-h light/dark cycle, 22 ± 2 °C, 50 ± 10% humidity) with free access to food and water. After 1 week of acclimatization, rats were randomly divided into three groups (n = 10): Control group (C): Fed a standard chow diet and handled normally without Chronic Unpredictable Mild Stress (CUMS) procedures. Model group (HC): Fed a High-Fat Diet (HFD) and subjected to CUMS to induce the COMBD phenotype. EA treatment group (HCE): Subjected to the same HFD + CUMS protocol as the HC group but received EA treatment during the intervention period.

HFD Model: Rats in the HC and HCE groups were fed a HFD (containing 60% kcal from fat, Guangdong Medical Experimental Animal Center) for 12 weeks to induce obesity and metabolic dysfunction. CUMS Model: Concurrently with the HFD feeding (from the 9th week onwards), rats in the HC and HCE groups were exposed to a CUMS protocol for 4 weeks. The CUMS procedures, administered randomly, included food/water deprivation, cage tilting, soiled cage, tail clipping, cold swimming, and reversed light/dark cycle, to induce depressive-like behaviors (Chen Y. et al., 2023). In the whole the experiment, the rats in HC group and HCE group continued for a high-fat diet.

EA treatment was performed over the final 4 weeks of the experimental period. Rats in the HCE group were gently immobilized in a specially designed holder and received acupuncture at bilateral Zusanli (ST36), Fenglong (ST40), Tianshu (ST25), and Zhongwan (CV12). Sterile stainless-steel needles were inserted to a depth of 5–7 mm and subsequently connected to an electroacupuncture apparatus. Electrical stimulation was delivered in disperse-dense wave patterns (2/15 Hz) at an intensity of 0.5 mA, which induced mild vibratory movements of the hind limbs without signs of distress. Each treatment session lasted for 30 min and was conducted once daily. Rats in the control and model groups were subjected to the same immobilization procedure but did not undergo needle insertion or electrical stimulation.

All behavioral tests were conducted during the final week of the experiment, in a dedicated quiet room, and video-recorded for blinded analysis. OFT: Each rat was placed in the center of a square open-field arena and allowed to explore freely for 5 min. The total distance traveled and average speed were analyzed using supermaze software. SPT: Rats were first trained to consume 1% sucrose solution. After 24 h of water and food deprivation, they were presented with two pre-weighed bottles, one containing 1% sucrose solution and the other tap water, for 24 h. Sucrose Preference (%) = Sucrose intake/(Sucrose intake + Water intake) × 100%. TST: Rats were suspended by their tails from a bracket using adhesive tape. The total 5-min test was recorded, and the cumulative immobility time was scored. An animal was considered immobile when it hung passively and motionless.

After the behavioral tests, rats were fasted overnight and anesthetized. Blood samples were collected from the abdominal aorta. Serum was separated by centrifugation and stored at −80 °C for subsequent biochemical and metabolomic analyses. Fresh fecal samples were collected from the colon, immediately snap-frozen in liquid nitrogen, and stored at −80 °C for subsequent 16S rDNA sequencing. The liver, visceral fat (VAT), subcutaneous fat (SAT), and brown adipose tissue (BAT) were rapidly dissected, weighed, and either fixed for histology or snap-frozen. The brains were rapidly removed, and the part of hippocampus were dissected on ice for molecular biology, while the others were fixed for histology. Serum levels of triglycerides (TG) and total cholesterol (TC) were measured using Triglyceride assay kit and Total cholesterol assay kit (Nanjing Jiancheng Bioengineering Institute) following the instructions.

H&E Staining: Fixed liver and adipose tissues were embedded in paraffin, sectioned at 5 μm thickness, and stained with Hematoxylin and Eosin (H&E). Histopathological changes were observed under a tissue slice digital scanner, and adipocyte area was quantified using ImageJ software. Nissl Staining: Fixed hippocampal tissues were sectioned and stained with Nissl stain solution (Wuhan servicebio technology CO., LTD.). Golgi Staining: Fresh brain tissues were impregnated using the Servicebio GolgiStain Kit. Well-impregnated neurons in the hippocampal CA1 region were selected, and dendritic spine density was analyzed.

For PSD95/Syn and CD74/NeuN double staining, paraffin sections were deparaffinized, antigens retrieved, blocked and incubated with primary antibodies: PSD95 (servicebio, 1:200), Synaptophysin (servicebio, 1:500), CD74 (servicebio, 1:800), NeuN (servicebio, 1:500) overnight at 4 °C, followed by incubation with secondary antibodies and appropriate TSA dyestuff. Nuclei were counterstained with DAPI. Images were acquired using a fluorescence microscope.

Gut microbial DNA was extracted from the rats’ fecal samples. The V3-V4 region of the 16S rDNA gene was amplified and sequenced on an Illumina platform by Shanghai Biotree Biomedical Technology Co., Ltd. The resulting data were processed using QIIME2 to generate Amplicon Sequence Variants (ASVs). Alpha and beta diversity analyses were performed, and LEfSe was used to identify differentially abundant taxa.

Serum metabolites were analyzed using an LC–MS/MS system. Chromatographic separation was conducted on an Agilent 1,290 UPLC system with an ACQUITY UPLC BEH C18 column (2.1 × 150 mm, 1.7 μm). The mobile phase consisted of (A) water with 0.1% formic acid and (B) methanol/water (95:5). Mass spectrometry was performed on a SCIEX 6500 QTRAP+ mass spectrometer with an ESI source operating in MRM mode. The ion source parameters were as follows: curtain gas, 35 psi; ion spray voltage, ±4,500 V; temperature, 450 °C; ion source gas 1 and 2, 50 psi. Data were acquired and processed using SCIEX Analyst (v1.7.32) and BIOTREE Bio Bud (v2.0.3) software. The raw data were processed for peak alignment, retention time correction, and peak extraction. Multivariate statistical analyses, including OPLS-DA, were performed. Metabolites with VIP > 1.0 and ANOVA P-VALUE < 0.05 were considered differential metabolites. Pathway enrichment analysis was performed based on the GO and KEGG database.

The total RNA was extracted from hippocampal tissues using TRIzol reagent. RNA integrity was checked, and sequencing libraries were constructed according to the ABclonal mRNA-seq Lib Prep Kit and sequenced on an Illumina/BGI platform. After quality control, clean reads were mapped to the reference genome using HISAT2 platform. Differential expression analysis was performed using the DESeq2 R package. Genes with |log2(FoldChange)| > 1 and adjusted p-value< 0.05 were considered DEGs. GO and KEGG pathway enrichment analyses of DEGs were performed, and a PPI network was constructed using the STRING database.

Total RNA from the hippocampus was reverse-transcribed into cDNA. RT-qPCR was performed using SYBR® Green Pro Taq HS qPCR Master Mix (Accurate Biology) on a Roche LightCycler® 480 real-time fluorescence quantitative PCR system. The mRNA expression levels of target genes (Nrf2, PSD95, Syn, Cd74) were normalized to β-actin and calculated using the 2^(−ΔΔCt) method.

Hippocampal tissues were lysed in RIPA buffer to extract total protein. Proteins were separated by SDS-PAGE and transferred to PVDF membranes. After blocking for 2 h, the membranes were incubated overnight at 4 °C with primary antibodies against PSD95(1:1500), Synaptophysin(1:1500), Hif1α(1:1000), Nrf2(1:1000), and β-actin(1:5000). After incubation with HRP-conjugated secondary antibodies, protein bands were visualized using an ECL detection system and quantified using ImageJ software.

All data are presented as the mean ± standard deviation (SD). Statistical analyses were performed using GraphPad Prism software. Differences between two groups were analyzed by two-tailed Student’s t-test. For comparisons among multiple groups, one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test was applied. For body weight data measured repeatedly over time, two-way repeated measures ANOVA (factors: time, group, and their interaction) was used. A p-value of less than 0.05 was considered statistically significant.

To investigate the therapeutic effect of EA on COMBD, we established a rat model and implemented an EA intervention regimen (Figure 1A). Compared to the control group, the high-fat diet/CUMS (HC) group exhibited a significant and sustained increase in body weight throughout the experimental period (Figure 1B). Notably, the body weight gain during the EA intervention period was significantly lower in the EA-treated (HCE) group compared to the HC group (Figure 1C). In behavioral assessments, COMBD rats showed markedly reduced locomotor activity in the OFT, as indicated by decreased total distance traveled and average speed (Figure 1D). While no significant difference in sucrose preference was observed in the SPT (Figure 1E), the HC group exhibited pronounced behavioral despair in the TST, characterized by a decreased number of head lifts and increased immobility time (Figure 1F). The movement tracks and heatmaps from the OFT visually confirmed the reduced exploration and central aversion in HC rats (Figure 1G). Critically, EA intervention significantly counteracted these behavioral deficits, restoring locomotor activity and active coping behavior. These results collectively demonstrate that EA effectively alleviates both metabolic and behavioral abnormalities in COMBD rats.

We next examined the impact of EA on peripheral metabolic organs and systemic lipid metabolism. Histological analysis of adipose tissue revealed that HC rats developed severe adipocyte hypertrophy in both visceral (VAT) and subcutaneous (SAT) fat depots, while EA treatment significantly reduced adipocyte size (Figures 2A,B). The morphology of brown adipose tissue (BAT) was also improved by EA (Figure 2A). Consistent with the histological improvements, EA significantly lowered elevated serum levels of TG (p < 0.05), although the reduction in TC did not reach statistical significance (Figure 2C). Macroscopic and microscopic examination of the liver showed that HC rats developed pronounced hepatic steatosis and an increased liver index. EA intervention significantly mitigated hepatic steatosis and exhibited a trend toward reduction in the liver index, though this reduction did not reach statistical significance (Figures 2D–F). These findings indicate that EA confers comprehensive benefits against obesity-related tissue pathology and systemic metabolic dysregulation.

The involvement of the gut microbiota in obesity and depression via the peripheral-central axis is increasingly recognized. To examine whether EA modulates the gut-brain axis, we conducted 16S rDNA sequencing on fecal samples. Principal coordinates analysis (PCoA) revealed a clear separation between the CON and HC groups, suggesting that gut dysbiosis was induced by HFD feeding and CUMS (Figure 3A). Both the Simpson and Chao1 indices were significantly decreased in HC rats, and these reductions in α-diversity were reversed after EA treatment (Figures 3B,C). Taxonomic analysis further illustrated compositional differences among the groups (Figures 3D,E). LEfSe analysis identified specific microbial biomarkers that distinguished each group (Figure 3F) and revealed EA-mediated remodeling of key bacterial genera, including the restoration of beneficial short-chain fatty acid (SCFA)-producing taxa such as those belonging to f__Ruminococcaceae (Figure 3G). The bubble plot indicated that several key differential genera mainly belonged to the phylum Firmicutes (Figure 3H). Collectively, these results demonstrate that EA effectively alleviates HFD and CUMS-induced gut dysbiosis.

To investigate the microbiota-related metabolic alterations underlying the effects of EA, we performed serum metabolomic profiling. OPLS-DA revealed clear separations among the C, HC, and HCE groups, indicating distinct serum metabolic profiles (Figure 4A). Volcano plots identified differentially abundant metabolites in the C vs. HC and HC vs. HCE comparisons (Figures 4B,C). Unsupervised hierarchical clustering of these differential metabolites effectively distinguished the three groups, underscoring the substantial impact of EA on the serum metabolome (Figure 4D). Correlation and matchstick analyses further delineated specific metabolic shifts following EA treatment (Figures 4E,F). Among the most significantly altered metabolites, Isovaleric acid, D-Sedoheptulose 7-phosphate, and Propionylcarnitine were upregulated, whereas Norcholic Acid and 7-Ketodeoxycholic acid were downregulated in response to EA (Figure 4G). Subsequently, Pearson correlation analysis was conducted to explore relationships between differential gut microbes and metabolites. Indole-3-butyric acid, myristoleic acid, norepinephrine, and eicosapentaenoic acid (EPA) exhibited similar correlation patterns with differential bacterial taxa, while glucaric acid, 3-indolepropionic acid, and 3-indoleacrylic acid displayed another set of coordinated relationships (Figure 4H). KEGG enrichment analysis of the differential metabolites revealed a significant association with the ‘Synaptic vesicle cycle’ pathway, suggesting a potential link between peripheral metabolic changes and central synaptic function (Figure 4I). Together, these results suggest that EA induces a beneficial reprogramming of host metabolism, potentially initiating a gut microbiota-metabolite-brain signaling cascade.

Recent evidence indicates that gut proinflammatory bacteria are associated with abnormal functional connectivity of the hippocampus in unmedicated patients with major depressive disorder (Xiao et al., 2024). Based on this, we sought to investigate whether EA influences hippocampal synaptic plasticity. Nissl staining revealed that EA treatment attenuated neuronal damage in the hippocampal CA1, CA3, and DG regions of COMBD rats (Figure 5A). At the transcriptional level, EA up-regulated the expression of synaptic proteins PSD95 and Syn (Figure 5B). Western blot analysis further showed that EA elevated protein levels of the antioxidative stress markers Hif1α and Nrf2, while also robustly increasing the expression of PSD95 and Syn (Figures 5C,D). Immunofluorescence double staining confirmed enhanced expression and co-localization of PSD95 and Syn in the hippocampus following EA administration (Figure 5E). Moreover, Golgi staining indicated that EA significantly increased the density of dendritic spines, the primary sites of excitatory synapses, compared to the HC group (Figure 5F). It suggests that EA promotes a synaptic environment conducive to plasticity by mitigating oxidative stress and enhancing the expression of key synaptic proteins. Overall, our results demonstrate that EA not only preserves neuronal integrity in the hippocampus but also drives structural remodeling that supports improved synaptic plasticity.

To elucidate the upstream molecular regulators, we conducted hippocampal transcriptomic analysis. Volcano plots and a clustering heatmap displayed differentially expressed genes (DEGs) between the comparison groups (Figures 6A–C). GO and KEGG enrichment analyses of these DEGs pointed to a highly significant involvement of the ‘MHC class II protein complex’ pathway and the ‘Neuroactive ligand-receptor interaction’ pathway (Figures 6D,E). Protein–protein interaction (PPI) network analysis identified key hub genes (Figure 6F), and Gene Set Enrichment Analysis (GSEA) confirmed the significant enrichment of the MHC class II pathway in the HCE group compared to HC (Figure 6G). Within this pathway, Cd74 emerged as a top candidate. IF staining for CD 74 and NeuN was used to observe the expression of CD74 in hippocampal neurons (Figure 6H). RT-qPCR confirmed that EA also significantly down-regulated the mRNA expression of Cd74 in the hippocampus (Figure 6I). These results suggest that CD74, a key molecule in the MHC class II pathway, serves as a potentially critical target through which EA modulates hippocampal synaptic plasticity in the COMBD state.