GDNF signaling modulation by Akkermansia muciniphila ameliorates constipation–depression comorbidity in Parkinson’s disease

Chunyan Mu; Zairen Zhou; Jingyu Li; Mingyu Su; Ke Xue; Jingyuan Zhang; Shijie Shi; Ye Li; Xiaoyu Yao; Mengxue Wang; Wanxiang Zhang; Zhe Wang; Jianguo Zhu; Shuguang Fang; Wei Wang; Chuanxi Tang; Xiaoling Qin

doi:10.1038/s41531-025-01190-x

. 2025 Nov 28;11:342. doi: 10.1038/s41531-025-01190-x

GDNF signaling modulation by Akkermansia muciniphila ameliorates constipation–depression comorbidity in Parkinson’s disease

Chunyan Mu ^1,^2,^3,^#, Zairen Zhou ^4,^#, Jingyu Li ^3,⁵, Mingyu Su ^3,⁶, Ke Xue ³, Jingyuan Zhang ³, Shijie Shi ³, Ye Li ³, Xiaoyu Yao ³, Mengxue Wang ⁵, Wanxiang Zhang ⁶, Zhe Wang ⁷, Jianguo Zhu ⁷, Shuguang Fang ⁷, Wei Wang ^3,^5,^✉, Chuanxi Tang ^3,^✉, Xiaoling Qin ^1,^✉

PMCID: PMC12663421 PMID: 41315295

Abstract

Constipation and depression are prevalent non-motor symptoms (NMS) of Parkinson’s disease (PD) that often co-occur, yet their shared pathophysiology remains unclear. Here, we identify enteric glial cells (EGCs) as central regulators of the gut–brain axis, wherein aberrant activation of the TLR4/NEDD4/CX43 signaling axis drives sustained ATP release, impairing serotonin (5-HT) synthesis in enterochromaffin (EC) cells. This ATP-mediated purinergic toxicity provides a unifying molecular mechanism for PD-associated constipation and depression (PD-CD). Mechanistically, TLR4 activation promotes TRAF6-dependent ubiquitination and degradation of NEDD4, reducing CX43 clearance. CX43 accumulation at the plasma membrane enhances ATP release, suppressing EC-derived 5-HT and contributing to gut dysmotility and mood disturbances. Critically, glial cell–derived neurotrophic factor (GDNF) stabilizes NEDD4 via the Ret–Src pathway, restores CX43 ubiquitination, limits ATP leakage, and rescues 5-HT synthesis, alleviating constipation and depressive phenotypes in PD mice. The probiotic Akkermansia muciniphila Akk11 (Akk11) similarly induces endogenous GDNF, producing comparable protective effects. Together, these findings establish an “EGC–EC axis” model for PD-CD and highlight GDNF-centered interventions as a promising multi-target strategy for PD NMS.

Subject terms: Diseases, Gastroenterology, Neuroscience

Introduction

Parkinson’s disease (PD), the second most common neurodegenerative disorder, is increasing with population aging. While motor symptoms remain central to diagnosis, non-motor symptoms (NMS)—including gastrointestinal dysfunction and mood disorders—are increasingly recognized as key contributors to early PD pathogenesis. Among the wide spectrum of NMS in PD, constipation is one of the most prevalent, affecting more than 60% of patients. Growing evidence further indicates that constipation is not merely an isolated symptom but can aggravate other non-motor manifestations, such as rapid eye movement sleep behavior disorder (RBD), thereby amplifying the overall disease burden¹. Crucially, PD-associated constipation (PDC) often precedes core motor symptoms by decades, suggesting involvement in PD’s early stages^2–4. PDC severely impairs quality of life and disrupts the absorption of key therapeutics like levodopa, diminishing treatment efficacy^5,6. Our cross-sectional survey of PD patients in the Huaihai region found ~49.7% exhibited significant constipation, highlighting an urgent need for therapies improving gut function. Importantly, PDC shows a significant positive correlation with PD-associated depressive disorders, a finding substantiated by multiple clinical and animal studies^7,8. Depression in PD exacerbates disease burden, impairs medication adherence and social functioning, with its underlying mechanisms potentially rooted in gut–brain axis dysfunction⁹. Gut dysbiosis, aberrant neuro-immune activation, and ascending propagation of gut-derived inflammatory signals may induce central neuroinflammation and neurotransmitter dysmetabolism, leading to mood disturbances^10–12. Clinically, PD patients with PDC exhibit significantly higher rates of anxiety and depression compared to non-constipated PD patients. Furthermore, improvement in gastrointestinal function often coincides with mood symptom alleviation, suggesting shared pathological pathways^7,13. Thus, dissecting the pathological basis of PDC from an intestinal perspective may reveal common drivers of mood disorders in PD.

Within this comorbidity, gut-derived 5-hydroxytryptamine (serotonin, 5-HT), a key neurotransmitter regulating gut motility, mood, and central neural activity, has garnered significant attention^14–16. Research indicates reduced 5-HT synthesis is a hallmark of PDC^17,18. Primarily produced by enterochromaffin cells (ECs) in the gut, its release is modulated by purinergic signaling. Normally, low ATP concentrations activate P2Y purinoceptor 1 (P2Y1), promoting 5-HT release¹⁹. However, in the PD gut, elevated ATP activates P2Y purinoceptor 12 (P2Y12), suppressing tryptophan hydroxylase (TPH) expression and reducing 5-HT synthesis^20,21. This ATP excess likely originates from aberrant surface expression and opening of the hemichannel protein connexin 43 (CX43) on enteric glial cells (EGCs), causing sustained ATP leakage and creating a pro-purinergic toxic microenvironment that impairs EC function. In essence, EGC-EC metabolic coupling via CX43 is pivotal, and its dysregulation may represent a critical initiating point for both gut dysfunction and mood dysregulation in PD. Therefore, investigating potential abnormalities in the EGC-CX43 pathway is key to deciphering PDC and its comorbid mechanisms.

Significantly, recent studies highlight glial cell line-derived neurotrophic factor (GDNF) as playing multifaceted roles in maintaining enteric nervous system (ENS) homeostasis and modulating central-peripheral neural function, emerging as a crucial target for PD NMS intervention^22,23. Initially studied extensively for its protective and restorative effects on midbrain dopaminergic neurons in the context of motor symptoms, new evidence indicates GDNF is also widely expressed within the ENS, influencing EGC function and neurotransmitter balance. Our preliminary studies demonstrate that adeno-associated virus (AAV)-mediated GDNF overexpression significantly increased colonic 5-HT synthesis, improved fecal output in mice, and alleviated depressive-like behaviors^24,25. This suggests GDNF may simultaneously ameliorate PD-related gastrointestinal and mood symptoms via dual gut-brain pathways. Moreover, accumulating evidence indicates that the intestinal inflammatory milieu serves as a primary driver of EGC activation, with Toll-Like receptor 4 (TLR4) signaling playing a central role in EGC proliferation and dysfunction^26,27. Based on the evidence above, the present study seeks to elucidate the aberrant activation mechanisms of the TLR4/NEDD4/CX43 signaling axis in EGCs underlying constipation–depression comorbidity in PD.

In parallel, Akkermansia muciniphila Akk11 (Akk11), a next-generation probiotic strain with potent immunomodulatory and metabolic regulatory properties, has emerged as a promising microbiota-based therapeutic strategy. Consistent with recent findings, our preliminary studies also demonstrated that Akk11 administration markedly attenuates intestinal inflammation and neural injury in PD mouse models²⁸. An intriguing question, therefore, is whether Akk11 exerts these beneficial effects, at least in part, by upregulating colonic GDNF expression, thereby synergistically contributing to restoring ENS–CNS communication and alleviating the intertwined constipation–depression comorbidity in PD.

In this study, using 6-OHDA-induced neurotoxicity PD-like mouse models and TLR4 agonist-induced EGC cell models, we systematically investigated the pathological mechanism whereby TLR4 activation induces persistent CX43 surface expression and ATP leakage. We further validated that GDNF mitigates EGC-EC dysfunction and restores purinergic homeostasis by modulating the TLR4-neuronal precursor cell expressed developmentally downregulated protein 4 (NEDD4)–CX43 ubiquitination signaling axis. This mechanism not only provides a theoretical basis for PDC pathogenesis but also offers a novel perspective for exploring the “constipation–depression” comorbidity. Additionally, we discovered that the specific probiotic strain Akk11 upregulates GDNF expression in EGCs, enhancing gut-derived 5-HT synthesis and improving both PD-like constipation and depressive behaviors. GDNF supplementation combined with probiotic intervention holds promise as a novel integrated strategy targeting gut–brain axis imbalance, offering fresh theoretical support for the comprehensive management of PD NMS.

Results

GDNF alleviates constipation, restores colonic 5-HT secretion, and improves depression-like behavior in 6-OHDA mouse model

A PD-like model was established by stereotaxic injection of 6-OHDA (2 μL, 4 μg/μL) into the brains of 6–8-week-old mice (Fig. 1A). Two weeks later, intraperitoneal injection of APO (0.1 mg/100 g) was used to induce mouse rotation, with PD model mice showing stable rotation toward the contralateral side at speeds greater than 5 r/min (Fig. 1B). Western blot analysis revealed a significant decrease in TH expression in the SNc brain region of the 6-OHDA model group compared to the Sham group. Immunofluorescence showed reduced distribution and expression of TH in the 6-OHDA group (Fig. 1C–F), confirming successful PD-like modeling.

On the basis of 6-OHDA stereotaxic injection, AAV-GDNF or AAV-NC was injected intraperitoneally (Fig. 1A). Western blot analysis showed a significant increase in GDNF expression in the colon tissue of the 6-OHDA + AAV-GDNF group compared to the 6-OHDA + AAV-NC group (Fig. 1G and H), indicating successful GDNF overexpression.

At weeks 1–5 following 6-OHDA brain stereotaxic injection, 24-h fecal weight and 2-h fecal water content were measured. The results showed that as the modeling time increased, the 24-h fecal weight and 2-h fecal water content in the 6-OHDA + AAV-NC group were reduced compared to the Sham group, while the 6-OHDA + AAV-GDNF group showed improvements (Fig. 1I and J), confirming that GDNF overexpression improved constipation-related indicators in 6-OHDA mice.

A 5% activated carbon gavage (0.6 mL/mouse) was used to assess intestinal motility. Propulsion ratio (%) was calculated as (the length from the pylorus to the red arrow (activated carbon)/the length from the pylorus to the anus)×100. The higher propulsion ratio indicates better gut motility and less severe constipation symptoms. The results showed a reduced intestinal propulsion rate in the 6-OHDA + AAV-NC group compared to the Sham group, while the 6-OHDA + AAV-GDNF group showed improvements (Fig. 1K and L), indicating that GDNF could improve the weakened intestinal motility in 6-OHDA mice.

The 5-HT content in the colon supernatant of each group was measured, showing that the 6-OHDA + AAV-NC group had reduced 5-HT secretion compared to the Sham group, while the 6-OHDA + AAV-GDNF group showed improvements (Fig. 1M), suggesting that GDNF could improve the 5-HT secretion deficit in the colons of 6-OHDA mice.

The tail suspension test was used to measure immobility time in mice. The 6-OHDA + AAV-NC group showed reduced immobility time compared to the Sham group, indicating depressive-like despair behavior, while the 6-OHDA + AAV-GDNF group had a significantly shorter immobility time compared to the 6-OHDA + AAV-NC group (Fig. 1N), suggesting that GDNF intervention could improve the motor depression-like behavior.

Additionally, the sugar water preference rate was significantly reduced in the 6-OHDA + AAV-NC group compared to the Sham group, indicating anhedonia. The 6-OHDA + AAV-GDNF group had a significantly higher sugar water preference rate than the 6-OHDA + AAV-NC group (Fig. 1O), suggesting that GDNF has a significant role in improving anhedonia

GDNF alleviates TLR4-TRAF6-mediated inflammatory activation in EGCs and improves colonic function in a 6-OHDA mouse model

This study performed RNA sequencing (RNA-Seq) on colonic tissues from Sham and 6-OHDA-induced PD-like model mice to detect gene transcriptional differences. After log-transformation of the transcriptomic data, both groups followed a normal distribution, and quantile normalization was performed to make the data comparable between groups (Fig. S1A and B). Principal component analysis (PCA) showed significant differences between the groups under different interventions (Fig. S1C). Differential analysis revealed that in the 6-OHDA group, 473 genes were upregulated and 249 genes were downregulated in the colonic tissue (Fig. S1D). Among the 473 upregulated genes, protein expression of inflammation-related pathway genes was significantly elevated in 6-OHDA model mice (Fig. 2A). Enrichment analysis of the top 50 upregulated differential genes was performed using the Enrichr database to analyze their pathways and biological processes (Biological Process, BP). KEGG analysis showed that these upregulated genes were mainly enriched in inflammation and cell response regulation, Toll-like receptor signaling, Jak-STAT signaling, and interleukin signaling pathways (Fig. S1E and F). GO-BP analysis indicated that these genes were involved in the regulation of lipopolysaccharide and inflammatory responses, intracellular signal transduction, and cytokine-mediated responses (Fig. S1G and H). Further network analysis was performed on the 50 significantly upregulated differential expression genes (DEGs). Protein–protein interaction (PPI) networks were constructed using the STRING database (v11.5) and imported into Cytoscape (v3.9.1). Four topological algorithms (maximal clique centrality (MCC), maximum neighborhood component (MNC), degree, closeness) were applied to evaluate node importance, and hub genes were identified. The results indicated that TLR4 occupies a central position in the differential regulation network of 6-OHDA model mice and may participate in disease progression through downstream inflammatory pathways (Fig. S1I–L).

Fig. 2 — A Heatmap of relative expression levels of differential genes in Sham and PD groups, where red indicates higher expression and blue indicates lower expression (n = 3). B and C Expression levels of TLR4 protein in mouse colonic tissue (n = 3, Sham vs. 6-OHDA + AAV-NC, P = 0.0025, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P = 0.0099, F(2, 6) = 19.19). D–F Immunofluorescence intensity and colocalization of EGCs (GFAP, green) and TLR4 (red) (n = 6, Sham vs. 6-OHDA + AAV-NC, P = 0.0001, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P = 0.0370, F(2, 15) = 16.10). G Timeline of drug injection and model induction in mice. H and I Intestinal propulsion rate after activated carbon gavage in mice, propulsion ratio (%) was calculated as (the length from the pylorus to the red arrow (activated carbon)/the length from the pylorus to the anus)×100 (n = 6, Sham vs. 6-OHDA + AAV-NC, P < 0.0001, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P = 0.0212, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + RS09, P = 0.0001, F(3, 20) = 30.33). J 5-HT content in mouse colonic supernatant (n = 3, Sham vs. 6-OHDA + AAV-NC, P = 0.0005, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P = 0.0441, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + RS09, P = 0.0025, F(3, 8) = 32.59). K and L Expression levels of inflammatory factors TNF-α, IL-6, IL-1β in mouse colonic tissue (n = 3, Sham vs. 6-OHDA + AAV-NC, *P < 0.05, **P < 0.005, ***P < 0.0005, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, *P < 0.05, **P < 0.005, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + RS09, **P < 0.005, ***P < 0.0005, F(3, 8) = 7.967). M and N Immunofluorescence of EGCs (GFAP, green) and TRAF6 (red) in mouse colonic tissue (n = 6, Sham vs. 6-OHDA + AAV-NC, P < 0.0001, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P < 0.0001, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + RS09, P < 0.0001, F(3, 20) = 45.52). O and P Western blot analysis of TRAF6 expression in EGCs (n = 3, Sham vs. RS09, P = 0.0042, RS09 vs. RS09 + GDNF, P = 0.0031, F(2, 6) = 20.27). Q and R Immunofluorescence of TRAF6 (red) in EGCs (n = 6, Sham vs. RS09, P < 0.0001, RS09 vs. RS09 + GDNF, P < 0.0001, F(2, 15) = 67.47).

Western blot analysis showed that TLR4 protein expression in the colonic tissue of the 6-OHDA + AAV-NC group was upregulated compared to the Sham group, while the 6-OHDA + AAV-GDNF group showed improvement (Fig. 2B, C). Additionally, immunofluorescence staining of EGCs labeled with GFAP (green) and TLR4 (red) demonstrated upregulated TLR4 expression in the 6-OHDA + AAV-NC group compared to Sham, and improvements were observed in the 6-OHDA + AAV-GDNF group, with co-localization of GFAP and TLR4 also changing accordingly (Fig. 2D–F). This confirmed that GDNF improves the abnormal upregulation of TLR4 expression in the colonic EGCs of 6-OHDA mice.

To verify whether GDNF improves various indicators in the 6-OHDA model mice through the TLR4 signaling pathway, 6–8-week-old mice were stereotaxically injected with 6-OHDA and given an intraperitoneal injection of AAV-GDNF. Four weeks later, the TLR4 agonist RS09 (6 mg/kg) was administered intraperitoneally for 3 days, forming the 6-OHDA + AAV-GDNF + RS09 experimental group (Fig. 2G). Activated carbon gavage (5%, 0.6 mL/mouse) was used to assess intestinal motility, and the results showed that the 6-OHDA + AAV-GDNF group had improved motility compared to the 6-OHDA + AAV-NC group, but this improvement disappeared after treatment with the TLR4 agonist RS09 (Fig. 2H and I). Furthermore, 5-HT levels in the colonic supernatant were measured, and the results indicated that the 6-OHDA + AAV-GDNF group had improved colonic 5-HT secretion compared to the 6-OHDA + AAV-NC group, but this effect was abolished upon treatment with RS09 (Fig. 2J). This suggests that GDNF likely exerts its effects through the blockade of TLR4 signaling.

Western blot analysis of colonic inflammatory markers showed elevated inflammation indicators in the 6-OHDA + AAV-NC group compared to the Sham group, which were reduced in the 6-OHDA + AAV-GDNF group. These reductions were reversed after RS09 administration (Fig. 2K and L), confirming that GDNF improves colonic inflammation and constipation in 6-OHDA mice by inhibiting TLR4 pathway activation.

TLR4 is an essential component of the immune system, and tumor necrosis factor receptor-associated factor 6 (TRAF6), as a key downstream signaling molecule of TLR4, plays a central role in immune responses and inflammation. Therefore, we further examined the expression changes of TRAF6 in the EGCs of the mouse colon and in the EGC cell line (EGC CRL-2690). Immunofluorescence staining of EGCs labeled with GFAP (green) and TRAF6 (red) showed that TLR4 expression was upregulated in the 6-OHDA + AAV-NC group compared to Sham, with corresponding increases in co-localization between GFAP and TRAF6. These changes were reversed in the 6-OHDA + AAV-GDNF group, and the improvement disappeared after the addition of the TLR4 agonist RS09 (Fig. 2M and N). This confirmed that GDNF inhibits the abnormal activation of TLR4, further reducing the elevated expression of TRAF6 in the colonic EGCs of 6-OHDA mice.

EGCs were treated with RS09 (64 μmol/L) for 24 h to mimic PD colonic glial cells, and GDNF (0.1 ng/mL) was added for intervention for 24 h to simulate the GDNF administration group. Western blot analysis showed that TRAF6 expression was elevated in the RS09 group compared to Sham, but this elevation was abolished after GDNF treatment (Fig. 2O and P). Correspondingly, immunofluorescence staining also confirmed that TRAF6 expression was elevated in the RS09 group compared to Sham, but the increase disappeared after GDNF treatment (Fig. 2Q and R). This further supports that GDNF inhibits the abnormal activation of TLR4, leading to a reduction in the elevated expression of TRAF6 in EGCs.

GDNF competitively binds TRAF6 through GDNF-Ret-Src signaling to block TRAF6-mediated NEDD4 ubiquitination degradation in the colon of 6-OHDA mice

This experiment further investigates the relationship between TRAF6 expression and the regulation of NEDD4 ubiquitination. The study found that TRAF6 can form a complex with NEDD4, participating in and catalyzing the ubiquitination degradation of NEDD4. GDNF’s mechanism of action in vivo can be progressively achieved through the activation of GDNF-Ret-Src signaling. Therefore, we explored whether activated Src plays a role in TRAF6-mediated NEDD4 ubiquitination regulation.

In the Zdock docking simulation of Src binding with TRAF6, Src binds to an α-helix between positions 195–200 and an unstructured loop and β-sheet between positions 215–255 of TRAF6, primarily interacting non-covalently with tyrosine at position 198, cysteine at position 218, threonine at position 237, and glutamine at position 254 (Fig. 3A). In the docking model of NEDD4 and TRAF6, NEDD4 binds between the α-helices at positions 205–235 of TRAF6, interacting non-covalently with serine at position 207 and aspartic acid at position 232 (Fig. 3B). Based on these results, we hypothesized a competitive binding relationship between Src-TRAF6-NEDD4 and conducted corresponding validation experiments.

We constructed a TRAF6 overexpression plasmid (Fig. 3C). CO-IP was used to detect the binding between TRAF6 and Src in EGCs from different experimental groups. The results showed that in the RS09 group, TRAF6 binding to Src was reduced compared to the Sham group, and after GDNF intervention, this reduction disappeared. TRAF6 overexpression further increased the binding between TRAF6 and Src (Fig. 3D and E). Additionally, CO-IP was used to detect the interaction between TRAF6 and NEDD4. The results showed that in the RS09 group, TRAF6 binding to NEDD4 increased compared to the Sham group, and after GDNF intervention, this increase was reversed. TRAF6 overexpression also showed trends consistent with the RS09 group (Fig. 3F and G).

In vivo experiments confirmed these binding differences between TRAF6 and Src, and TRAF6 and NEDD4, with results consistent with the cell experiments (Fig. 3H–J). These findings suggest that GDNF likely competes with TRAF6 to bind to NEDD4 through activated Src.

Next, we used protein immunoblotting and in vivo immunofluorescence experiments to further validate the expression and ubiquitination modification differences of NEDD4. Immunofluorescence staining of EGCs, with GFAP (green) marking and NEDD4 (red) dual labeling, showed that in the 6-OHDA + AAV-NC group, NEDD4 expression was downregulated compared to Sham. This downregulation was improved in the 6-OHDA + AAV-GDNF group, but the improvement disappeared in the 6-OHDA + AAV-GDNF + RS09 group (Fig. 3K and L).

Subsequently, Western blot experiments at the cellular level showed that NEDD4 expression was downregulated in the RS09 group compared to Sham. GDNF intervention improved this downregulation, and further TRAF6 overexpression showed trends consistent with the RS09 group (Fig. 3M and N). These results suggest that GDNF can improve the downregulation of NEDD4 expression by inhibiting the abnormal elevation of TLR4-TRAF6 signaling.

Finally, CO-IP was used to detect the differences in NEDD4 ubiquitination modifications. The results showed that in the RS09 group, NEDD4 ubiquitination was increased compared to Sham. However, after GDNF intervention, the increased ubiquitination modification of NEDD4 disappeared, and TRAF6 overexpression showed a trend consistent with the RS09 group (Fig. 3O and P). These findings suggest that GDNF may block the TRAF6-mediated NEDD4 ubiquitination degradation by activating Src, thereby increasing NEDD4 expression in 6-OHDA mice.

GDNF promotes NEDD4 expression in EGCs to target CX43 for ubiquitination and degradation

Previous studies from our lab have shown that 6-OHDA mice exhibit gut inflammation accompanied by abnormal expression of cell junction proteins, particularly the abnormally high expression of CX43. To investigate whether NEDD4 is directly associated with the abnormal changes in CX43, we developed a 6-OHDA + AAV-GDNF model in GFAP-cre mice and intraperitoneally injected RNAi-NEDD4 virus. Western blotting confirmed the effectiveness of the viral infection, showing significant suppression of NEDD4 expression (Fig. 4A–C). Subsequently, we performed immunofluorescence staining, marking EGCs with GFAP, and co-labeled GFAP (green) with CX43 (red). The results indicated that CX43 expression was upregulated in the 6-OHDA + AAV-NC group compared to the Sham group. In the 6-OHDA + AAV-GDNF group, this upregulation was improved, and in the 6-OHDA + AAV-GDNF + NEDD4 KD group, the improvement was lost (Fig. 4D and E).

Fig. 4 — A NEDD4 knockdown plasmid map. B and C Western blot analysis detecting NEDD4 expression in the colonic tissue of GFAP-cre mice to assess viral transfection efficiency (n = 3, Sham vs. 6-OHDA + AAV-NC, P = 0.0163, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P = 0.0735, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + NEDD4 KD, P < 0.0001, F(3, 8) = 55.65). D and E Immunofluorescence of EGCs (GFAP, green) and CX43 (red) in mouse colonic tissue, showing the intensity and spatial distribution (n = 6, Sham vs. 6-OHDA + AAV-NC, P < 0.0001, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P < 0.0001, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + NEDD4 KD, P < 0.0001, F(3, 20) = 75.42). F and G Western blot analysis detecting CX43 expression in EGCs (n = 3, Sham vs. RS09, P = 0.0027, RS09 vs. RS09 + GDNF, P = 0.6526, RS09 + GDNF vs. RS09 + GDNF + NEDD4 KD, P = 0.0002, F(3, 8) = 50.75). H and I Immunofluorescence of CX43 (red) in EGCs in mouse colonic tissue, showing the intensity and spatial distribution (n = 6, Sham vs. RS09, P = 0.0021, RS09 vs. RS09 + GDNF, P = 0.0378, RS09 + GDNF vs. RS09 + GDNF + NEDD4 KD, P = 0.0030, F(3, 20) = 12.51). J Three-dimensional model of the binding between NEDD4 and CX43, with the yellow part representing NEDD4 and the purple-blue part representing CX43. K and L CO-IP assay detecting the binding between NEDD4 and CX43 in EGCs and quantitative analysis (n = 3, Sham vs. RS09, P = 0.0285, RS09 vs. RS09 + GDNF, P = 0.0008, RS09 + GDNF vs. RS09 + GDNF + NEDD4 KD, P = 0.0002, F(3, 8) = 26.32). M and N PLA-Duolink assay detecting the binding between NEDD4 and CX43 in EGCs and quantitative analysis (n = 6, Sham vs. RS09, P < 0.0001, RS09 vs. RS09 + GDNF, P < 0.0001, RS09 + GDNF vs. RS09 + GDNF + NEDD4 KD, P < 0.0001, F(3, 20) = 73.20). O and P CO-IP assay detecting the ubiquitination of CX43 in EGCs and quantitative analysis (n = 3, Sham vs. RS09, P = 0.0015, RS09 vs. RS09 + GDNF, P = 0.0298, RS09 + GDNF vs. RS09 + GDNF + NEDD4 KD, P = 0.0014, F(3, 8) = 28.01). Q Predicted interaction diagram for the ubiquitination of CX43.

We then examined CX43 expression at the cellular level using Western blot, and found that CX43 expression was upregulated in the RS09 group compared to the Sham group. After GDNF intervention, the upregulation of CX43 expression was improved. However, after NEDD4 knockdown, CX43 upregulation became more pronounced (Fig. 4F and G). Immunofluorescence results corroborated the Western blot data (Fig. 4H and I). These findings suggest that CX43 expression is abnormally elevated in the colons of 6-OHDA mice, GDNF has some improvement effects, and NEDD4 expression directly influences CX43 expression. As NEDD4 is an E3 ubiquitin ligase, we hypothesized that NEDD4 might regulate CX43 expression changes by participating in its ubiquitination modification. In the Zdock docking simulation, we found that NEDD4 binds to CX43 between positions 100-105 in the α-helix, primarily interacting non-covalently with arginine at position 101 and glutamic acid at position 104 (Fig. 4J). CO-IP was then used to detect the binding between NEDD4 and CX43 in EGCs from different experimental groups. The results showed that in the RS09 group, NEDD4 binding to CX43 was reduced compared to the Sham group. After GDNF intervention, NEDD4 binding to CX43 increased again, and after NEDD4 knockdown, the binding almost disappeared (Fig. 4K and L). We further validated the interaction between NEDD4 and CX43 using proximity ligation assay (PLA-Duolink). The appearance of distinct red fluorescence dots indicates protein-protein interaction, with the intensity of red fluorescence corresponding to the strength or quantity of the interaction. PLA-Duolink results were consistent with the previous CO-IP findings (Fig. 4M and N).

Finally, we used CO-IP to detect the differences in CX43 ubiquitination modifications across the experimental groups. The results showed that in the RS09 group, CX43 ubiquitination was reduced compared to the Sham group. After GDNF intervention, CX43 ubiquitination increased again. However, after NEDD4 knockdown, the ubiquitination of CX43 nearly disappeared (Fig. 4O and P). Additionally, ubiquitination prediction indicated that CX43 (GJA1) ubiquitination is largely regulated by NEDD4 (Fig. 4Q).

Together, the experimental results from CX43 expression, NEDD4-CX43 binding, and CX43 ubiquitination modifications confirm that NEDD4 targets CX43 for ubiquitination and participates in its degradation. As shown in Fig. 3, GDNF can increase NEDD4 expression, suggesting that GDNF may promote NEDD4 expression to facilitate its targeting of CX43 for ubiquitination and degradation.

Overexpression of CX43 on EGCs membrane creates an extracellular hyperuricemic environment, increasing P2Y12 expression on ECs, negatively regulating 5-HT synthesis and secretion, exacerbating constipation and depressive-like behavior in 6-OHDA mice

To investigate the effects of overexpression of CX43 on the EGCs membrane, we used the EGC CRL-2690 cell line to overexpress CX43 through plasmid transfection (Fig. 5A). Western blotting was used to verify the transfection efficiency and expression of CX43 in other groups, showing that CX43 expression in the CX43 OE group was significantly higher than in the other groups. In the RS09 group, CX43 expression was abnormally upregulated compared to the Sham group, and this upregulation was improved after GDNF intervention (Fig. 5B and C). Next, we collected the extracellular medium and measured various indicators. We found significant differences in the relative ATP content in the extracellular fluid. The RS09 group showed an increase in ATP relative content compared to the Sham group, which was restored to Sham levels after GDNF intervention. Notably, the CX43 OE group exhibited significantly higher ATP relative content than other groups (Fig. 5D), suggesting that abnormally activated CX43 releases excessive ATP, creating an extracellular hyperuricemic environment that may contribute to neuroinflammation and other pathological processes. We further explored the effects of extracellular hyperuricemia on physiological states using in vivo experiments in mice. We found that purinergic receptors, such as P2Y12 and P2Y1, were regulated: through immunofluorescence staining with CgA to mark enteroendocrine cells (ECs), we co-labeled CgA (green) with P2Y12 (red). The results showed that P2Y12 expression in ECs was upregulated in the 6-OHDA + AAV-NC group compared to the Sham group, and the upregulation was inhibited in the 6-OHDA + AAV-GDNF group (Fig. 5E and F). This indicates that overactivation of CX43 on EGCs in the colon of 6-OHDA mice leads to excessive ATP release, creating an extracellular hyperuricemic environment that regulates purinergic receptors like P2Y12 and P2Y1 on ECs.

Fig. 5 — A Schematic of the CX43 overexpression plasmid. B and C Western blot analysis detecting the expression of CX43 in EGCs (n = 3, Sham vs. RS09, P = 0.0055, RS09 vs RS09 + GDNF, P = 0.0068, RS09 + GDNF vs. RS09 + GDNF + CX43 OE, P = 0.0004, F(3, 8) = 27.20). D ELISA analysis detecting the ATP content in the extracellular supernatant of EGCs (n = 3, Sham vs. RS09, P = 0.0044, RS09 vs. RS09 + GDNF, P = 0.0387, RS09 + GDNF vs. RS09 + GDNF + CX43 OE, P = 0.0015, F(3, 8) = 23.50). E and F Immunofluorescence intensity and spatial distribution of ECs (CgA marker, green) and P2Y12 (red) in mouse colonic tissue (n = 6, Sham vs. 6-OHDA + AAV-NC, P < 0.0001, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P < 0.0001, F(2, 15) = 66.27). G–J Western blot analysis detecting the expression of P2Y12, P2Y1 and TPH in human pancreatic cancer cells (QGP-1) under different concentrations of ATP (the expression of P2Y12, n = 3, Sham vs. ATP 10 μM, P = 0.0186, Sham vs. ATP 100 μM, P = 0.0008, Sham vs. ATP 250 μM, P < 0.0001, F(3, 8) = 50.27; the expression of P2Y1, n = 3, Sham vs. ATP 10 μM, P = 0.0842, Sham vs. ATP 100 μM, P = 0.0007, Sham vs. ATP 250 μM, P < 0.0001, F(3, 8) = 52.47; the expression of TPH: n = 3, Sham vs. ATP 10 μM, P = 0.3232, Sham vs. ATP 100 μM, P = 0.0100, Sham vs. ATP 250 μM, P = 0.0001, F(3, 8) = 27.38). K and L Immunofluorescence intensity and spatial distribution of P2Y12 (red) in human pancreatic cancer cells (QGP-1) under ATP treatment (n = 6, Sham vs ATP 250 μM, P < 0.0001, t = 11.08, df = 10). M 24-h fecal mass over weeks 1–5 after 6-OHDA injection in mice (n = 3, Sham vs. 6-OHDA + AAV-NC, *P < 0.05, **P < 0.005, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-NC + PSB0739, #P < 0.05, F(16, 40) = 8.239). N 2-h fecal water content over weeks 1–5 after 6-OHDA injection in mice (n = 3, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-NC + PSB0739, #P < 0.05, F(16, 40) = 3.343). O and P Gut propulsion rate after activated carbon gavage in mice, propulsion ratio (%) was calculated as (the length from the pylorus to the red arrow (activated carbon)/the length from the pylorus to the anus)×100 (n = 6, Sham vs. 6-OHDA + AAV-NC, P < 0.0001, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P = 0.0212, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + MRS2179, P = 0.2227, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-NC + PSB0739, P = 0.0022, F(4, 25) = 10.27). Q 5-HT content in mouse colonic supernatant (n = 3, Sham vs. 6-OHDA + AAV-NC, P = 0.0073, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P = 0.3252, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + MRS2179, P = 0.0002, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-NC + PSB0739, P = 0.0002, F(4, 10) = 44.73). R Immobility time in the tail suspension test in mice (n = 6, Sham vs. 6-OHDA + AAV-NC, P < 0.0001, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P < 0.0001, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + MRS2179, P < 0.0001, 6-OHDA + AAV-NC vs. 6-OHDA + A.AV-NC + PSB0739, P < 0.0001, F(4, 25) = 105.7). S Sugar water preference ratio in the mouse sucrose preference test (n = 6, Sham vs. 6-OHDA + AAV-NC, P < 0.0001, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-GDNF, P = 0.0002, 6-OHDA + AAV-GDNF vs. 6-OHDA + AAV-GDNF + MRS2179, P = 0.0318, 6-OHDA + AAV-NC vs. 6-OHDA + AAV-NC + PSB0739, P < 0.0001, F(4, 25) = 31.23).

To further investigate the effects of different ATP concentrations on P2Y12 and P2Y1 receptor expression, we treated QGP-1 cells with various concentrations of exogenous ATP (10, 100, 250 μM). Western blotting revealed that as extracellular ATP concentration increased, P2Y12 expression was upregulated, while P2Y1 and TPH expression was downregulated (Fig. 5G–J). This confirms that P2Y12 is positively regulated by ATP, while P2Y1 is negatively regulated by ATP. In parallel in vivo experiments, we observed that P2Y12 expression was significantly upregulated in the ATP 250 μM group compared to the Sham group (Fig. 5K, L), consistent with the cell Western blot data. Thus, we hypothesize that overexpression of CX43 on the membrane of EGCs in 6-OHDA mice creates a hyperuricemic environment, leading to increased P2Y12 expression on ECs. To explore the effects of P2Y12 and P2Y1 receptor expression changes on 6-OHDA mice, we administered P2Y1 receptor antagonist (MRS2179) to the 6-OHDA + AAV-GDNF group and P2Y12 receptor antagonist (PSB0739) to the 6-OHDA + AAV-NC group. We then measured the 24-h fecal weight and 2-hour fecal moisture content at weeks 1–5 after 6-OHDA brain stereotactic injection. The results showed that, over time, the 6-OHDA + PSB0739 group exhibited significant improvements in fecal weight and moisture content compared to the 6-OHDA group. These improvements were suppressed in the 6-OHDA + AAV-GDNF + MRS2179 group compared to the 6-OHDA + AAV-GDNF group (Fig. 5M, N). This confirms that inhibition of the P2Y1 receptor can reverse the improvements in the GDNF group, while inhibition of the P2Y12 receptor can reverse the abnormal changes in the 6-OHDA group. These findings suggest that the improvement in the GDNF group may be mediated by P2Y1 activation, whereas the abnormal changes in the 6-OHDA group may be driven by P2Y12 activation. We then verified this hypothesis by testing gut motility with 5% activated charcoal gavage (0.6 mL per mouse). The results showed that the 6-OHDA + PSB0739 group had significantly improved gut propulsion compared to the 6-OHDA group, while the 6-OHDA + AAV-GDNF + MRS2179 group showed suppressed improvement compared to the 6-OHDA + AAV-GDNF group (Fig. 5O, P). Moreover, measuring the 5-HT content in the colon supernatant of each group showed that the 6-OHDA + PSB0739 group had increased 5-HT secretion compared to the 6-OHDA group, while the improvement in the 6-OHDA + AAV-GDNF + MRS2179 group was suppressed (Fig. 5Q).

In summary, we hypothesize that overactivation of P2Y1 and P2Y12 receptors, respectively, positively and negatively regulate 5-HT synthesis and secretion, contributing to constipation in PD-like mice. In the tail suspension test, the 6-OHDA + PSB0739 group showed significantly reduced immobility time compared to the 6-OHDA group. In contrast, the 6-OHDA + AAV-GDNF + MRS2179 group had significantly increased immobility time compared to the 6-OHDA + AAV-GDNF group (Fig. 5R). These results suggest that activation of the P2Y1 receptor can reverse the improvement in motor depression-like behavior in the GDNF group, while inhibition of the P2Y12 receptor can alleviate depressive-like behavior in mice. Furthermore, the 6-OHDA + PSB0739 group showed significantly increased sugar water preference compared to the 6-OHDA group, while the 6-OHDA + AAV-GDNF + MRS2179 group showed decreased sugar water preference compared to the 6-OHDA + AAV-GDNF group (Fig. 5S), indicating that P2Y1 receptor inhibition can reverse the improvement in depressive-like behavior in the GDNF group.

Akk11 alleviates constipation and improves depressive-like behavior in 6-OHDA mouse model, associated with upregulation of GDNF

Several studies have reported that probiotics can improve certain motor and NMS in PD patients. To further explore the effect of the gut microbiota Akk11 on the improvement of 6-OHDA-induced PD-like models in mice, we administered Akk11 by gavage. 6-OHDA models were established in 6–8-week-old mice by stereotactic injection of 6-OHDA (2 μL, 4 μg/μL) into the brain, followed by Akk11 gavage treatment once a week for 4 weeks, starting 4 days after the injection (Fig. 6A). Compared to the Sham group, GDNF protein expression in the colon tissue of 6-OHDA group mice was significantly reduced. However, after adding Akk11 gavage treatment to the 6-OHDA intervention, GDNF protein expression was significantly increased compared to the 6-OHDA group (Fig. 6B and C). In vitro, GDNF expression in EGC cells was also higher in the Sham and RS09+Akk11 groups compared to the RS09 group (Fig. 6D and E). These results suggest that Akk11 can partially reverse the decline of GDNF in PD-like models. Next, we assessed gut motility using 5% activated charcoal gavage (0.6 mL per mouse). The results showed that the 6-OHDA+Akk11 group had significantly improved gut propulsion compared to the 6-OHDA group (Fig. 6F). Akk11 not only altered GDNF protein expression in the colon tissue of 6-OHDA mice but also significantly improved impaired gut motility. Additionally, the tail suspension test revealed that the 6-OHDA+Akk11 group had significantly reduced immobility time compared to the 6-OHDA group (Fig. 6G), suggesting that Akk11 alleviates the despair-like state in mice. Furthermore, the 6-OHDA+Akk11 group showed a significant increase in sugar water preference compared to the 6-OHDA group (Fig. 6H), indicating that Akk11 also has an improving effect on depressive-like behavior in mice.

Fig. 6 — A Timeline of drug injection modeling and Akk11 intervention in mice. B and C GDNF expression in mouse colonic tissue (n = 3, Sham vs. 6-OHDA, P = 0.0045, 6-OHDA vs. 6-OHDA+Akk11, P = 0.0260, F(2, 6) = 14.58). D and E GDNF expression in EGC cells (n = 3, Sham vs. RS09, P = 0.0022, RS09 vs. RS09+Akk11, P = 0.0320, F(2, 6) = 18.39). F Intestinal propulsion rate after activated carbon gavage in mice (n = 6, Sham vs. 6-OHDA, P < 0.0001, 6-OHDA vs. 6-OHDA+Akk11, P = 0.0003, F(2, 15) = 29.937). G Immobility time in the tail suspension test in mice (n = 6, Sham vs 6-OHDA, P < 0.0001, 6-OHDA vs. 6-OHDA+Akk11, P < 0.0001, F(2, 15) = 74.73). H Sugar water preference ratio in the mouse sucrose preference test (n = 6, Sham vs. 6-OHDA, P < 0.0001, 6-OHDA vs. 6-OHDA+Akk11, P < 0.0001, F(2, 15) = 48.85).

Discussion

This study elucidates mechanisms underlying constipation–depression comorbidity in PD, highlighting EGCs as central regulators of the gut–brain axis (Fig. 7). We show that aberrant TLR4/NEDD4/CX43 signaling drives ATP leakage and impairs 5-HT synthesis, linking gut dysfunction to depressive-like behaviors. GDNF, via the Ret-Src pathway, restores EGC homeostasis by modulating NEDD4 and CX43 ubiquitination, alleviating both constipation and depressive symptoms, while the probiotic Akk11 synergistically enhances endogenous GDNF. These findings establish a unified pathological framework for PD NMS and suggest novel therapeutic strategies.

Traditionally, constipation and depression have been considered independent NMS in PD. Yet, accumulating clinical and preclinical evidence indicates a high degree of comorbidity, often preceding motor deficits^2–4. Although the gut-brain axis has long been proposed as a key physiological basis regulating gastrointestinal function and emotional state, its specific role in the pathogenesis of PD NMS remains incompletely elucidated^7,8. This study is the first to demonstrate that aberrant activation of EGCs is closely associated with sustained extracellular ATP leakage, constituting a critical upstream event impairing intestinal 5-HT synthesis. Specifically, TLR4-mediated EGC overactivation induces high membrane expression of CX43 hemichannels, leading to massive intracellular ATP efflux and the creation of a pro-purinergic toxic microenvironment. This state significantly reduces 5-HT levels, resulting in gut dysmotility and simultaneously triggering central mood disturbances via the gut–brain axis. As a key signaling molecule bridging the central and peripheral nervous systems, 5-HT deficiency not only compromises gastrointestinal motility but also affects brain mood regulation, providing a potential unified pathological basis for the constipation–depression comorbidity^29,30. Recent studies highlight the role of gut-derived 5-HT in regulating central mood. Morinda officinalis oligosaccharides, for instance, can enhance 5-HT levels in the brain and alleviate depressive behaviors by promoting 5-hydroxytryptophan (5-HTP) production in the gut. Similarly, providing slow-release 5-HTP chow to TPH2-R439H mice restores central 5-HT levels and mitigates depressive-like behaviors³¹. Supporting this gut-brain connection, McVey Neufeld et al. demonstrated that selective 5-HT reuptake inhibitors (SSRIs) increase vagal activity in control mice, whereas vagotomized mice exhibited impaired performance in the tail suspension test, reflecting a diminished antidepressant response^32,33. Collectively, these findings indicate that gut-derived 5-HT can significantly influence central mood regulation, emphasizing the importance of gut–brain interactions in the pathophysiology of depression. In intervention experiments, we found that GDNF treatment significantly improved 24-h fecal pellet output, colonic transit rate, and colonic tissue 5-HT content in PD model mice, indicating a clear reparative effect on gastrointestinal dysmotility. This result aligns with previous studies confirming that GDNF, as a crucial member of the neurotrophic factor family, participates in ENS homeostasis by modulating EGC function²³. However, this study further reveals that GDNF’s role in PD pathology extends beyond neurotrophic support; it also exerts anti-inflammatory effects by suppressing aberrant TLR4 signaling activation. RNA-Seq analysis showed significant enrichment of TLR4 pathway-related genes in the colon of PD-like model mice, while GDNF intervention downregulated the expression of TLR4 and its downstream inflammatory cytokines (e.g., IL-1β, TNF-α). This finding resonates with recent research highlighting the central role of TLR4 in neuroinflammation^34,35. We found that TLR4 activation drives inflammation and, by suppressing the E3 ligase NEDD4, prevents ubiquitin-mediated degradation of CX43, thereby stabilizing its membrane expression and sustaining ATP leakage. This establishes a novel causal link between TLR4 signaling, the ubiquitin pathway, and EGC dysfunction, highlighting TLR4 as a therapeutic target in PD intestinal pathology. Importantly, we further showed that GDNF, via Ret-Src signaling, restores NEDD4, promotes CX43 degradation, reduces ATP release, and rescues 5-HT synthesis. By repairing the gut neuro-endocrine-immune microenvironment, GDNF alleviated depressive-like behaviors in PD mice through the gut-brain axis, underscoring its potential for “dual gut-brain protection” in non-motor symptom management.

At the molecular level, we show that TLR4 activation in EGCs engages the TRAF6 pathway. Co-immunoprecipitation and molecular docking reveal that the GDNF-activated Ret–Src axis competitively binds key residues (Tyr198, Cys218) in TRAF6, blocking its interaction with NEDD4. This prevents TRAF6-mediated K48-linked ubiquitination and degradation of NEDD4, stabilizing the protein. Restored NEDD4 then ubiquitinates CX43, reversing its abnormal accumulation and membrane localization in PD models. Previous studies indicate that GDNF, by activating the Ret receptor, induces its tyrosine kinase activity, prompting Ret dimerization and autophosphorylation, and further recruits and activates Src family kinases, forming a functional Ret–Src signaling complex^36–38. Within the TLR4-mediated innate immune pathway, TRAF6 is a core signaling node. Upon TLR4 activation, it is recruited via the myeloid differentiation primary response gene 88 (MyD88)-dependent pathway involving interleukin-1 receptor-associated kinases (IRAKs). Relying on its E3 ubiquitin ligase activity, TRAF6 catalyzes the formation of K63-linked ubiquitin chains, activating the TGF-β-activated kinase 1 (TAK1) complex and triggering nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and mitogen-activated protein kinase (MAPK) cascades, ultimately promoting the expression of inflammatory cytokines like TNF-α and IL-6^39–41. Further research suggests that the GDNF-activated Ret–Src signal may directly phosphorylate TRAF6 via Src kinase, altering its conformation or ubiquitin ligase activity and weakening its interaction with downstream signaling molecules⁴². Additionally, the Ret–Src complex or its associated adapter proteins might competitively bind the TRAF domain of TRAF6, occupying its critical binding site within the TLR4 signaling complex and thereby blocking its participation in ubiquitin-dependent TAK1 activation⁴³. This dual inhibitory effect leads to decreased kinase activity of the TAK1 complex, subsequently suppressing IKK and MAPK phosphorylation, reducing NF-κB nuclear translocation, and diminishing pro-inflammatory cytokine transcription⁴⁴.

CX43 overexpression forms hemichannels that trigger aberrant ATP release⁴⁵. In EGC-CRL2690 cells, elevated CX43 increases extracellular ATP, which suppresses 5-HT secretion by activating P2Y12 receptors on EC cells, as confirmed via PLA-Duolink and receptor antagonist experiments. ATP effects are concentration-dependent: low ATP (10 μM) activates P2Y1 to promote 5-HT release, whereas high ATP (250 μM) inhibits it via P2Y12, suggesting a “purinergic imbalance” in PDC⁴⁶. Normally, ATP and its metabolites finely regulate 5-HT through P2X and P2Y receptors: P2X purinoceptor 3 (P2X3) mediates Ca²⁺ influx, activating calcium-dependent protein kinase II (CaMKII) and TPH1 phosphorylation; P2Y1 enhances ER Ca²⁺ release via phospholipase C inositol trisphosphate (PLC-IP3), promoting vesicle fusion; adenosine activates adenosine receptor B (A2B) receptors, upregulating cyclic adenosine monophosphate-protein kinase A (cAMP-PKA) and prolonging EC excitability^47,48. Under chronic inflammation, excessive ATP activates P2X purinoceptor 7 (P2X7)/NLRP3 inflammasomes and indoleamine 2,3-dioxygenase 1 (IDO1)⁴⁹, diverting tryptophan from 5-HT synthesis, while adenosine accumulation via A1 inhibits cAMP-PKA, further impairing 5-HT release^32,50. Dysregulated purinergic signaling is evident in irritable bowel syndrome (IBS) and constipation: downregulated P2Y1 reduces 5-HT, and P2X3 antagonists (e.g., AF-353) restore 5-HT homeostasis and motility^51–53.

Research on Akkermansia muciniphila (Akk) remains subject to considerable debate. While substantial evidence supports its therapeutic potential in improving metabolic homeostasis, mitigating inflammatory responses, and enhancing gut barrier integrity, divergent observations indicate that its efficacy may vary depending on contextual factors. These include host-specific characteristics, baseline microbiota composition, and dietary patterns. Studies have associated reduced abundance of Akk with conditions such as obesity and type 2 diabetes, and intervention trials suggest that supplementation may ameliorate metabolic abnormalities^54,55. In patients with inflammatory bowel disease (IBD), Akk has been shown to reduce colonic infiltration of macrophages and CD8+ cytotoxic T lymphocytes (CTLs), thereby contributing to the alleviation of intestinal inflammation⁵⁶. However, under conditions of dietary fiber deficiency, Akk may proliferate and actively degrade the host’s colonic mucus barrier, leading to thinning of the mucus layer and increased susceptibility to pathogenic infections⁵⁷. In such settings, its presence has been correlated with worsened clinical outcomes. Furthermore, critical aspects such as safety profiles, effective dosage, and long-term implications of its use as a next-generation probiotic remain to be fully elucidated. Notably, the efficacy of Akk11 exhibits significant synergism with specific dietary strategies. A prebiotic diet rich in dietary fibers—such as pectin and inulin—can thus supply Akk11 with sufficient nutritional substrates, curb its potential damage to the intestinal mucus layer, and enhance its survival in the gut. Meanwhile, an anti-inflammatory diet (e.g., foods rich in omega-3 fatty acids and polyphenols) may suppress excessive activation of the TLR4 pathway, synergizing with Akk11 to mitigate neuroinflammation, further stabilize NEDD4 expression, reduce CX43 membrane accumulation, and ATP leakage. Additionally, supplementation with tryptophan precursor-rich foods (such as nuts, seeds, and poultry) provides essential substrates for 5-HT synthesis, complementing the 5-HT-restoring effect of Akk11.

Remarkably, the probiotic Akk11 markedly induced GDNF expression in EGCs. Oral administration elevated GDNF levels without exogenous gene delivery, increased colonic 5-HT, and alleviated both constipation and depressive-like symptoms. Compared with exogenous GDNF, probiotic intervention is more practical and clinically translatable. Moreover, its combination with GDNF showed synergistic effects, offering a promising microecological strategy targeting the “EGC-GDNF-CX43” axis. Despite these advances in clarifying how GDNF mitigates PD constipation–depression comorbidity, several limitations remain. 1. Currently, several PD models are available. The 6-OHDA model represents the “top-down” or brain-first mechanism, whereas the colon-injected α-synuclein (α-syn) fibril model aligns with the “bottom-up” or body-first hypothesis⁵⁸. The 6-OHDA model reliably induces damage to the nigrostriatal dopaminergic pathway within a controllable experimental timeframe (several weeks), faithfully recapitulating core early PD pathology and motor deficits, while also producing gastrointestinal dysfunction, with high reproducibility^59,60. In contrast, the α-syn fibril model requires months to develop motor deficits and exhibits substantial variability. Importantly, these two pathogenic pathways are not mutually exclusive⁶¹. In this study, our results primarily reflect brain-first PD pathology induced by 6-OHDA. Future studies will investigate whether α-syn-related inflammatory deposits can influence 5-HT release through the EGC–EC axis in the colon-injected α-syn fibril model. 2. Simplified Interaction Modeling: The interaction mechanism between EGCs and ECs was primarily simulated using in vitro cultures. However, in the in vivo environment, their functions are modulated by multiple factors, including cytokines and microbial metabolites, and culture conditions differ substantially from the real physiological milieu. Future studies should utilize intestinal organoids or intravital imaging to enhance reliability. 3. Ubiquitination Site Specificity: While we confirmed NEDD4-mediated ubiquitination of CX43, the specific ubiquitination sites remain unidentified, precluding precise mechanistic understanding of how this modification affects CX43 function. Mass spectrometry is required to map key modification sites to guide targeted drug development. 4. Future research directions: Future efforts should focus on elucidating how intestinal Akk11 modulates EGCs' function to promote GDNF, developing microbiota-targeted GDNF sustained-release formulations, clarifying the role of TLR4/TRAF6 signaling in α-syn gut-to-brain propagation, and designing subtype-specific drugs targeting purinergic receptors to advance the pathological research and therapeutic optimization for PD constipation-depression comorbidity. 5. This study was conducted solely on male mice and did not include female mice. As an important biological factor, gender may influence the presentation and treatment response of PD. Previous studies have shown significant gender differences in the impact on motor symptoms, NMS, and psychological outcomes^62–65. Therefore, the results of this study may have gender-related limitations, and future research should explore the differences between male and female mice in PD models.

In summary, this study reveals a shared pathological mechanism underlying constipation-depression comorbidity in PD, focusing on the gut–brain axis. We identify the EGC-CX43 pathway’s aberrant activation, leading to ATP leakage and disrupted 5-HT synthesis in ECs, as a key factor in PD-related constipation and mood disorders. TLR4 signaling activation promotes TRAF6-mediated NEDD4 degradation, causing CX43 accumulation. GDNF, through Src signaling, reduces CX43 levels, mitigates ATP leakage, and enhances 5-HT synthesis, improving symptoms. Probiotic Akk11 also induces GDNF expression, providing a synergistic intervention. This study offers a novel, multi-target approach for treating PD NMS.

Methods

Animals

All experimental procedures in this study were strictly conducted in accordance with the National Institutes of Health (NIH) Guide for the Care and Use of Laboratory Animals, ensuring scientific rigor and procedural compliance. Furthermore, the study protocol was reviewed and approved by the Experimental Animal Ethics Committee of Xuzhou Medical University (Ethical Approval No. L202211S018). To minimize potential confounding effects due to hormonal variations between males and females, we chose to use only male mice in this study, ensuring more consistent experimental outcomes⁶⁶. Male C57BL/6J mice and GFAP-cre transgenic mice were housed under controlled specific pathogen-free (SPF) conditions (temperature: 23 ± 1.5 °C; relative humidity: 45 ± 15%) with a standardized 12-h light/dark cycle (lights on: 19:00–07:00). Mice aged six to eight weeks were used for experiments and were acclimatized to the facility for a minimum of seven days prior to any procedures. Each group consisted of 3–6 mice, with the sample size determined based on statistical power analysis to ensure the ability to detect differences between the experimental and control groups. Both experimental and control groups were housed individually to minimize potential interference from social interactions on behavioral outcomes. This study primarily focuses on comorbid depression and constipation, and it was necessary to avoid the impact of group effects on behavioral and physiological parameters⁶⁷. All animals were obtained from the Experimental Animal Center of Xuzhou Medical University, which operates under the national animal use license SYXK(Su)2020-0048.

Virus intervention

Virus (titer: 7.72 × 10¹³ vg/mL) (Table 1) was diluted in PBS to 7.72 × 10¹² vg/mL under biosafety cabinet conditions following brief centrifugation. Mice received intraperitoneal injections of 200 μL (containing 1.54 × 10¹² vg), within the effective dose range (1 × 10¹⁰–5 × 10¹¹ vg).

Table 1.

The relevant viruses used in this study

Name	Source
AAV5-Nedd4-RNAi	GENE
AAV-NC	BrainVTA
AAV-GDNF	BrainVTA

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Cell culture

The cell included the EGC CRL-2690 cell line and the QGP-1 human pancreatic cancer cell line. Both are adherent cell lines exhibiting epithelial-like morphology. The culture conditions were as follows: EGC CRL-2690 cells were maintained in DMEM (BasalMedia Co., Ltd, Cat# L130KJ) supplemented with 10% fetal bovine serum (FBS) (NEST Biotechnology, Cat# 209111) and 1% penicillin–streptomycin; QGP-1 cells were cultured in RPMI-1640 medium (BasalMedia Co., Ltd, Cat#L210KJ) supplemented with 10% FBS and 1% penicillin–streptomycin. All cells were incubated at 37 °C in a humidified atmosphere containing 5% CO₂ and 95% air. All cell culture procedures were performed under strict aseptic conditions to prevent contamination.

Plasmid transfection

Transfection was performed using Lipofectamine 3000 reagent (Thermo Fisher) according to the manufacturer’s recommended protocol. Briefly, 2 × 10⁵ cells were seeded in a six-well plate and cultured for 16–20 h until they reached ~70% confluence. Plasmid DNA was mixed with Lipofectamine 3000 reagent in Opti-MEM medium to form the transfection complex. After transfection, cells were collected at 48–72 h post-transfection for further analysis or experiments.

Viral infection

The 2 × 10⁵ cells were seeded in a six-well plate (BaiDi Biotechnology Co., Ltd. Cat#H803000) and cultured for 16–20 h until they reached ~70% confluence. The virus solution was then mixed with 10 μg/mL Polybrene (Sigma-Aldrich) and added to the target cells. The virus was diluted in ice-cold PBS to achieve a multiplicity of infection (MOI) of 10⁴–10⁵ viral genomes (vg) per cell. After 24 h of infection, the medium was replaced with fresh growth medium. Cells were subsequently collected at the appropriate time for further analysis or fluorescence-based assays, depending on the experimental needs.

6-Hydroxydopamine hydrobromide (6-OHDA) induced PD-like model

Mice (6–8 weeks, 20–24 g) were chosen based on the experimental design to undergo intraperitoneal injection. Following body weight measurement, mice were anesthetized by intraperitoneal injection of sodium pentobarbital (45 mg/kg). PD-like model was established by unilateral stereotaxic injection of 6-OHDA (HY-B1081A, MedChemExpress, USA) into the target brain region. Stereotaxic coordinates relative to bregma were: Anteroposterior (AP) + 0.6 mm, Mediolateral (ML) −2.0 mm, Dorsoventral (DV) −3.2 mm. Each mouse in the 6-OHDA group received a 2 μL injection of 6-OHDA (4 μg/μL). Control group mice received an equivalent volume of sterile phosphate-buffered saline (PBS) as the vehicle control.

Intraperitoneal injection

RS09 (HY-P1439, MedChemExpress, US) was dissolved in PBS (6 mg/kg) for daily intraperitoneal injections at 8:00 AM. Mice were restrained in a head-down position, and injections (25 G insulin syringe) were administered at 45° with midline vessel avoidance. Solutions (0.1 mL over 10 s) were slowly delivered to prevent peritoneal irritation; controls received PBS equivalently. Needles remained inserted for 5–10 s post-injection before vertical withdrawal with hemostatic pressure, followed by recovery on 37 °C-preheated bedding with activity monitoring.

Akk11 intervention treatment

The AKK11, utilized in this study, was originally isolated from the fecal samples of healthy infants in Hongyuan County, Sichuan, China. It is currently stored at the German Collection of Microorganisms and Cell Cultures GmbH (DSM 35205). Akk11 was propagated in brain heart infusion (BHI) broth (HB8297-4, Hopebio, China) under strictly anaerobic conditions at 37 °C. Following incubation, the bacterial culture was harvested via centrifugation, washed, and then diluted in anaerobic phosphate-buffered saline (PBS) supplemented with 2.5% glycerol. The final bacterial suspension was prepared to a concentration of 1 × 10⁹ CFU/mL and administered orally to mice at a volume of 0.2 mL. 6-OHDA model mice received daily oral gavage (200 μL Akk11 suspension, 22 G blunt needle) at 9:00 AM for 4 weeks (5 days/week), while controls received glycerol–PBS equivalently; post-administration monitoring ensured absence of aspiration.

Co-culture of Akk11 with EGC Cells

EGC cells were seeded at a density of 1 × 10⁵ cells/mL in culture dishes. The cells were washed three times with sterile PBS for 1 min each time to ensure no residual medium. EGC cells were cultured in DMEM containing 10% FBS, without antibiotics, in a 37 °C, 5% CO₂ incubator for 24 h until they reached 80% confluence. The culture medium was then removed, and the cells were gently washed twice with pre-chilled PBS. Next, 6 mL of antibiotic-free medium containing Akk11 at a final concentration of 5 × 10⁶ CFU/mL was added. The co-culture was maintained at 37 °C, 5% CO₂, and microaerophilic conditions (5% O₂), with gentle shaking of the plate every 2 h to prevent bacterial sedimentation. After 6 h of co-culture, the medium containing 100 μg/mL gentamicin was added to stop bacterial proliferation. The culture was further incubated for 30 minutes to remove any residual live bacteria. The medium was then discarded, and the cells were washed three times with ice-cold PBS.

Apomorphine-Induced Rotational Behavior in Mice

Mice were acclimated to the behavioral observation chamber for 1-2 h. Apomorphine (APO) (HY-12723, MedChemExpress, USA) was administered via intraperitoneal injection at a dose of 0.1 mg per 100 g body weight. During injection, mice were restrained by the scruff, placed in a supine position, and the lower abdomen near the midline was disinfected with an alcohol swab. The needle was inserted at an ~30° angle; correct intraperitoneal placement was confirmed by a slight reduction in resistance and aspiration to confirm absence of blood or fluid before slow injection. Immediately post-injection, mice were returned to the observation chamber, and rotation direction, number of rotations, and pattern were recorded for 30 min. 6-OHDA model mice were identified by stable, continuous contralateral rotation (relative to the lesioned brain hemisphere) exceeding 5 rotations per minute.

Tail suspension test (TST)

Mice were individually suspended by the tail for a 6-min test period. Mice were secured using medical adhesive tape placed ~1.5 cm from the tip of the tail and attached to a horizontal bar affixed to the top of an enclosed apparatus, positioning the head downward approximately 30–40 cm above the base. Immobility, defined as the absence of any limb or body movement, cessation of struggling, and passive hanging, was manually scored throughout the entire 6-min session. Scoring was performed by two independent investigators blinded to the experimental conditions of the mice. The total time spent immobile by each mouse was recorded and used as the primary behavioral measure, with increased immobility interpreted as depression-like behavior.

Sucrose preference test (SPT)

Sucrose preference was assessed after 48-h acclimation with dual-bottle choice (1% sucrose vs. water) and 24-h apparatus habituation. Following 12-h water deprivation, mice underwent a 24-h test with pre-weighed bottles (filtered 1% sucrose vs. ultrapure water) randomly positioned and manually alternated every 6 h to counter spatial bias. Liquid consumption was calculated from mass changes corrected for evaporation (<0.5 g/cage), with sucrose preference index (SPI) defined as [sucrose intake/(sucrose + water intake)] × 100% and total intake as their sum.

2-hour Fecal water content

Fecal water content was measured in mice transferred to clean cages to avoid contamination. At weekly intervals for 5 weeks post-6-OHDA stereotaxic injection, fecal pellets were collected from subgroups. Mice were housed individually in clean cages with free access to food and water for 2 h; feces were then collected using forceps onto pre-weighed culture dishes. The mass of the empty dish (m₀) and the dish with fresh feces (m₁) were recorded. Samples were dried in an oven at 105 °C for 48 h, cooled, and reweighed (m₂). Water content (%) was calculated as [(m₁−m₂)/(m₁−m₀)] × 100.

2-hour Carbon dust propulsion rate

Charcoal propulsion ratio was assessed in mice fasted for 12–24 h (water ad libitum) to minimize gastrointestinal interference. A 5% activated charcoal suspension in saline (0.6 mL/mouse) was administered by oral gavage using a ball-tipped needle; correct gastric intubation was confirmed by smooth insertion to a depth of 3–4 cm without resistance. Mice were euthanized via cervical dislocation 2 h post-gavage, and the entire intestine from pylorus to anus was excised. Total intestinal length and charcoal migration distance were measured. Propulsion ratio (%) was calculated as (charcoal migration distance/total intestinal length) × 100.

24-hour fecal mass measure

24-hour fecal mass was quantified weekly for 5 consecutive weeks post 6-OHDA stereotaxic surgery. Per intervention group, three subgroups were housed individually in metabolic cages with pre-weighed collection containers. After 24 h, feces were transferred to pre-weighed culture dishes; fecal mass was calculated as dish-plus-feces mass (m₁) minus dish mass (m₀).

Perfusion fixation

Cardiac perfusion fixation was performed in mice anesthetized with sodium pentobarbital (45 mg/kg, i.p.), confirmed by loss of corneal and pedal reflexes. Following thoracotomy, a needle was inserted into the left ventricle (depth 2–3 mm) and secured after blood aspiration; the right atrial appendage was excised for outflow. Perfusion initiated with saline (20–30 mL, 5 mL/min) until liver blanching and clear effluent, followed by 4% paraformaldehyde (30–40 mL, 5 mL/min), with efficacy confirmed by tail rigidity and limb stiffening. Post-fixation, brain (olfactory bulb to medulla) and colon (fecal-cleared) were dissected with minimal mechanical damage, immersed in 4% paraformaldehyde for 24 h, then cryoprotected in sequential sucrose gradients (10% → 30%) until tissue sedimentation.

Freezing tissue slices

Frozen sections (brain: 10 μm; colon: 20 μm) of cryoprotected brain or colon tissues were prepared using a cryostat equilibrated at −20 °C(CM1950, Leica, Germany). Brain tissue was trimmed to create a flat mounting surface, while 1 cm colon segments were oriented vertically; both were embedded in OCT compound without bubbles and flash-frozen for 10 min. Sections were cut with anti-roll plates, with brain sections mapped to target regions using stereotaxic atlases prior to slide mounting. All sections were air-dried at room temperature for 24 h and stored at −20 °C.

Transcriptome sequencing

Total RNA was extracted and subjected to rRNA depletion using the GenSeq® rRNA Removal Kit (GenSeq, Inc.) to enhance mRNA detection. rRNA-depleted RNA was then processed with the GenSeq® Low Input RNA Library Prep Kit (GenSeq, Inc.) for library construction, including RNA fragmentation, cDNA synthesis, end repair, adapter ligation, and PCR amplification according to the manufacturer’s protocol. Library quality and concentration were assessed with a BioAnalyzer 2100 system (Agilent Technologies, USA). Qualified libraries were sequenced on an Illumina NovaSeq 6000 platform to generate 150-bp paired-end reads (PE150). Raw data quality was evaluated by Q30 scores, and adapter sequences and low-quality reads were removed using Cutadapt (v1.9.3) to obtain clean reads. Clean reads were aligned to the human reference genome (hg19) using HISAT2 (v2.0.5). Gene-level read counts were generated with HTSeq (v0.9.1), normalized, and analyzed for differential expression with edgeR. Significantly differentially expressed genes were defined by |log2FC | > 1 and FDR < 0.05. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to annotate functional categories and enriched pathways.

Western blot

Western blotting was performed for brain and colon protein extracts following SDS-PAGE and electrophoretic transfer. The protein concentrations were determined utilizing the BCA protein assay (Yeasen Biotechnology (Shanghai) Co., Ltd, Cat# 20200) and protease inhibitors (KeyGen BioTECH, Cat#KGP610) were added to the samples. SDS–polyacrylamide gels were cast with optimized separation/stacking gel concentrations based on target molecular weights, loaded with 30–60 μg protein/lane, and electrophoresed at 80 V (30 min) then 120 V until dye front migration (Bio-Red Laboratories, US). Proteins were transferred to NC membranes (VH-WBLZ10, Vicmed, China) via wet transfer (300 mA, [target kDa + 20] min) in ice-cooled chambers. Membranes were blocked in 5% skim milk (2 h, RT), incubated with primary antibodies (4 °C, 14–16 h) and fluorescence secondary antibodies (RT, 2 h, light-protected) (Table 2), with three 10-min TBST washes between steps. Signal detection used an Odyssey CLx Imaging System (LI-COR Odyssey CLX, Odyssey, USA). The gray value of the bands was analyzed using the ImageJ software. The relative value of the target protein gray value to the actin gray value was recorded. Statistical analysis was conducted in GraphPad, and the images were generated.

Table 2.

Primary and secondary antibodies and reagents employed in the study

	Source	Item no.	WB	IF
Primary antibodies
Anti-GFAP	Huabio	EM140707	1:5000	1:500
Anti-IL-6	Huabio	EM1701-58	1:500	1:100
Anti-Src	Huabio	ET1702-03	1:2500	1:100
Anti-Ubiquitin	Huabio	ST46-03	1:2500	1:100
IL-1β Rabbit mAb	ABclonal	A22257	1:2500	\
TLR4 Rabbit pAb	ABclonal	A0007	1:1000	1:200
Connexin 43 Rabbit pAb	ABclonal	A11752	1:2000	1:200
TRAF6 Rabbit pAb	ABclonal	A16991	1:1000	1:200
P2RY1 Rabbit pAb	ABclonal	A7706	1:1000	\
NEDD4 Polyclonal	proteintech	21698-1-AP	1:1000	1:200
Anti-P2Y12	Abcam	ab184411	1:2000	1:80
Anti-Tyrosine Hydroxylase	Abcam	ab112	1:200	\
Anti-GDNF	Abcam	ab176564	1:2000	\
Anti-TNF-α	Abcam	ab9739	1:50,000	\
Anti-GAPDH	proteintech	60004-1-IG	1:50,000	\
Anti-beta Actin	Abcam	ab8226	1:10,000	\
Secondary antibodies
IRDye®680RD Goat anti-Mouse IgG	LI-COR	NC0252290	1:20,000	1:20,000
IgG H&L (Alexa Fluor 488)	Abcam	ab150077	\	1:200
IgG H&L (Alexa Fluor 594)	Abcam	ab150080	\	1:200
IRDye®800CW Goat anti-Rabbit IgG	LI-COR	C50331-03	1:20,000	1:20,000

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Immunofluorescence

For cell staining, cells on coverslips (60–70% confluency) were fixed (4% paraformaldehyde, 25 min), permeabilized (0.3% Triton X-100, 20 min, RT), and blocked (30 min, RT). For tissue staining, cryosections were thawed, washed with PBS to remove OCT, and dried (37 °C, 15 min), followed by the same permeabilization and blocking steps. In both cases, primary antibodies were applied overnight (4 °C), followed by Alexa Fluor-conjugated secondary antibodies (2 h, RT, light-protected) (Table 2), DAPI counterstaining (5 min), and PBS washes. Coverslips or sections were mounted with antifade medium for confocal or fluorescence imaging.

ATP assay

ATP levels were quantified using an Enhanced ATP Assay Kit (S0027, Beyotime, China) with tissue homogenates prepared in ice-cold lysis buffer (100–200 μL per 20 mg tissue). Samples were centrifuged at 12,000×g (4 °C, 5 min), and supernatants were assayed alongside ATP standards (0.01–10 μM). Working reagent (detection reagent diluted 1:4) was added to samples/standards (100 μL), incubated for 3–5 min (room temperature) to deplete background ATP, followed by immediate RLU/CPM measurement after adding 20 μL sample using a chemiluminometer.

5-HT assay

5-HT levels were quantified by ELISA (CSB-E08365m, CUSABIO, China) using intestinal homogenates prepared in ice-cold PBS (9 mL/g tissue) and centrifuged at 2500 rpm (4 °C, 20 min). Supernatants were diluted 5-fold in sample diluent and assayed alongside serially diluted standards (15–240 pg/mL) on antibody-coated plates. After 30-min incubation (37 °C), plates were washed 5 times, incubated with HRP-conjugated detection antibody (37 °C, 30 min), rewashed, and developed with TMB substrate (10 min, 37 °C, light-protected). Reactions were stopped with sulfuric acid, and absorbance was measured at 450 nm within 15 min, with concentrations calculated against the standard curve.

Plasmid construction

The TRAF6 overexpression plasmid was constructed by PCR amplification of the CDS region of the rat TRAF6 gene with primers in Table 3. The amplified product was cloned into the linearized pCDH vector using the One Step Gibson Cloning Kit. The CX43 overexpression plasmid was constructed by PCR amplification of the CDS region of the rat CX43 gene with primers in Table 3. The amplified fragment was cloned into the linearized pCDH vector using the One Step Gibson Cloning Kit to generate the CX43 overexpression plasmid. To knock down the rat NEDD4 gene, shRNA targeting NEDD4 was designed. The target sequence is GTATGGGAGTTCTGTCTGGAT. The annealed oligo fragments (Table 4) were ligated into the linearized pLKO.1 vector using T4 DNA ligase to construct the NEDD4 knockdown plasmid.

Table 3.

Primers used for the construction of overexpression plasmids

Plasmids	Primer	5’–3’
TRAF6 OE	Forward	ACGCTGTTTTGACCTCCATAGAAGATTGCCACCATGAGTCTCTTAAACTGTGAAAACAGCTG
TRAF6 OE	Reverse	GGATCCGATTTAAATTCGAATTCGCTAGCTCTACACGCCTGCATCAGTACTCC
CX43 OE	Forward	ACGCTGTTTTGACCTCCATAGAAGATTGCCACCATGGGTGACTGGAGTGCC
CX43 OE	Reverse	GGATCCGATTTAAATTCGAATTCGCTAGCTTTAAATCTCCAGGTCATCAGGCCG

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Table 4.

Oligos used for the construction of knockdown plasmids

Plasmids

Oligo

5’–3’

NEDD4

Forward

CCGGGTATGGGAGTTCTGTCTGGATTTCTCGAGAATCCAGACAGAACTCCCATACTTTTTG

Reverse

AATTCAAAAAGTATGGGAGTTCTGTCTGGATTCTCGAGAATCCAGACAGAACTCCCATAC

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Molecular docking

The study employed computer-aided molecular docking techniques for interaction analysis. Initially, the two-dimensional (2D) structures of ligand molecules were retrieved from the NCBI PubChem compound database (https://pubchem.ncbi.nlm.nih.gov/). These structures were converted into three-dimensional (3D) format using Open Babel 3.0.1 and subsequently subjected to energy minimization optimization using Chem3D 20.0 molecular modeling software, resulting in the generation of ligand files in PDBQT format. The crystal structure of the receptor protein was sourced from the RCSB PDB database (https://www.rcsb.org/). Following preprocessing with AutoDockTools (involving the removal of crystallographic water molecules and redundant groups, and the addition of polar hydrogen atoms), the receptor structure was also converted to PDBQT format. Subsequently, within AutoDockTools, a docking grid box encompassing potential binding sites was constructed based on the characteristics of the receptor binding domain by defining coordinate parameters. Molecular docking calculations were performed using the command-line mode of AutoDock Vina. Upon completion of the calculations, conformation analysis was conducted using the PyMOL 2.5 molecular visualization system, with a specific focus on intermolecular interaction patterns within the ligand-receptor complex, such as hydrogen bonding and hydrophobic interactions. Two-dimensional interaction diagrams were generated using the automated analysis module of the ProteinsPlus web platform (https://proteins.plus/).

Statistical analysis

Experimental data in this study were comprehensively processed and analyzed using GraphPad Prism 9.0 (GraphPad, La Jolla, CA, USA), combined with Adobe Creative Suite software Photoshop 2022 (Adobe, San Jose, CA, USA). The layout and schematic diagrams are original and were collaboratively created in this study using Illustrator 2021 (Adobe, San Jose, CA, USA). For quantitative statistics, independent samples t-tests were employed for comparisons between two groups. For multi-group comparisons, one-way analysis of variance (ANOVA) was performed, followed by Tukey’s post-hoc test to identify specific group differences. The significance level was uniformly set at P < 0.05. All quantitative data are presented as mean ± standard deviation. For image analysis, quantification of immunofluorescence and grayscale detection of SDS–PAGE bands were performed using the NIH-developed ImageJ platform (v1.53k, National Institutes of Health, USA), with colocalization analysis conducted using the EzColocalization plugin. The quantity “n” in the statistical analysis represents the number of biological replicates. Specific details regarding statistical methods applied in the experimental procedures are elaborated in the corresponding figure and table legends. Visual refinement, optimization, and layout design of figures were completed using the Adobe Creative Cloud professional suite.

Supplementary information

Supplementary Information^{(2.3MB, docx)}

Acknowledgements

We would like to thank all members, past and present, who participated in this project. This work was supported by the grant from the Fourth Affiliated Hospital of Tongji University (No. SY-KYQD-02701), the Science and Technology Committee of Hongkou District, Shanghai (No. 220232), Natural Science Research General Project of Higher Education Institutions in Jiangsu Province (No. 25KBJ310017), and Jiangsu Training Programs of Innovation and Entrepreneurship for Undergraduates (No. S202510313030), National Natural Science Foundation of China (No. 82500710), Jiangsu Province Science Foundation for Youths (BK20251042), the Research Foundation for Talented Scholars of Xuzhou Medical University (RC20552421).

Author contributions

X.L.Q. and C.X.T. conceived and designed the study; C.Y.M. and X.L.Q. provided supervision and mentorship; J.Y.L., M.Y.S., K.X., J.Y.Z., S.J.S., Y.L., X.Y.Y., M.X.W., and W.X.Z. performed the in vivo and in vitro experiments; J.Y.L, M.Y.S, K.X, S.G.F and W.X.Z. conducted the behavioral tests; J.Y.Z., S.J.S., Y.L., J.G.Z., and M.X.W. collected and analyzed the biochemical and molecular data; W.W., X.Y.Y., and Z.W. assisted with data analysis and visualization; J.G.Z., Z.W., and S.G.F. provided experimental guidance such as bacterial powder and intervention strategies. C.Y.M., Z.R.Z., W.W., and C.X.T. wrote the manuscript with input from all authors; all authors reviewed, discussed, and approved the final version of the manuscript.

Data availability

All data generated or analyzed during this study are included in this published article (and its Supplementary information files).

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Chunyan Mu, Zairen Zhou.

Contributor Information

Wei Wang, Email: weiwang@xzhmu.edu.cn.

Chuanxi Tang, Email: chxtang@xzhmu.edu.cn.

Xiaoling Qin, Email: doctorqx0@126.com.

Supplementary information

The online version contains supplementary material available at 10.1038/s41531-025-01190-x.

References

1.Liu, H., Shen, L., Zhao, H. A., Yang, J. & Huang, D. Y. Parkinson’s disease patients combined with constipation tend to have higher serum expression of microRNA 29c, prominent neuropsychiatric disorders, possible RBD conversion, and a substandard quality of life. Neurol. Sci.44, 3141–3150 (2023). [DOI] [PubMed] [Google Scholar]
2.Cheesman, M., Ho, H., Bishop, K. & Sin, M.-K. Constipation management in Parkinson disease. J. Neurosci. Nurs53, 262–266 (2021). [DOI] [PubMed] [Google Scholar]
3.Lajoie, A. C., Lafontaine, A.-L. & Kaminska, M. The spectrum of sleep disorders in Parkinson disease. Chest159, 818–827 (2021). [DOI] [PubMed] [Google Scholar]
4.Li, L.-C. et al. Trends of complications in patients with Parkinson’s disease in seven major cities of China from 2016 to 2019. Int. Clin. Psychopharmacol36, 274–278 (2021). [DOI] [PubMed] [Google Scholar]
5.Ogawa, E., Sakakibara, R., Kishi, M. & Tateno, F. Constipation triggered the malignant syndrome in Parkinson’s disease. Neurol. Sci.33, 347–350 (2011). [DOI] [PubMed] [Google Scholar]
6.Ramu, S. K. et al. Defecatory disorders are a common cause of chronic constipation in Parkinson disease. Neurogastroenterol. Motil.36, e14767 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Xiao-ling, Q. et al. Depression is associated with constipation in patients with Parkinson’s disease. Front. Neurol.11, 567574 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Chang, T.-Y., Chen, Y.-H., Chang, M.-H. & Lin, C.-H. Is there a close association of depression with either constipation or dysosmia in Parkinson’s disease. Sci. Rep.10, 15476 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Huang, Z. P. et al. The significance of psychological support in managing depression in Parkinson’s disease: combining venlafaxine with pramipexole and psychological care. Actas Esp. Psiquiatr.53, 19–25 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Tse, J. K. Y. Gut Microbiota, nitric oxide, and microglia as prerequisites for neurodegenerative disorders. Acs Chem. Neurosci.8, 1438–1447 (2017). [DOI] [PubMed] [Google Scholar]
11.Trisal, A., Singh, I., Garg, G., Jorwal, K. & & Singh, A. K. Gut–brain axis and brain health: modulating neuroinflammation, cognitive decline, and neurodegeneration. 3 Biotech15, 25 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
12.de la Fuente-Nunez, C., Meneguetti, B. T., Franco, O. L. & Lu, T. K. Neuromicrobiology: how microbes influence the brain. ACS Chem. Neurosci.9, 141–150 (2018). [DOI] [PubMed] [Google Scholar]
13.Gan, J. et al. A survey of subjective constipation in Parkinson’s disease patients in Shanghai and literature review. BMC Neurol.18, 29 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Gershon, M. D. 5-Hydroxytryptamine (serotonin) in the gastrointestinal tract. Curr. Opin. Endocrinol., Diabetes Obes20, 14–21 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Kyodo, R. et al. Modulation of intestinal motility in an adolescent rat model of irritable bowel syndrome. Digestion105, 99–106 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Koopman, N. et al. The multifaceted role of serotonin in intestinal homeostasis. Int. J. Mol. Sci.22, 9487 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Sawamura, T. et al. Alterations in descending brain-spinal pathways regulating colorectal motility in a rat model of Parkinson’s disease. Am. J. Physiol.-Gastrointest. Liver Physiol.326, G195–G204 (2024). [DOI] [PubMed] [Google Scholar]
18.Murtomäki, K. et al. Dopamine transporter binding in the brain is linked to irritable bowel syndrome in Parkinson’s disease. Brain Behav.13, e3098 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Linan-Rico, A. et al. Mechanosensory signaling in enterochromaffin cells and 5-HT release: potential implications for gut inflammation. Front. Neurosci.10, 564 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Andersen, M. S. et al. Heritability enrichment implicates microglia in Parkinson’s disease pathogenesis. Ann. Neurol.89, 942–951 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Liñán-Rico, A. et al. Purinergic autocrine regulation of mechanosensitivity and serotonin release in a human EC model. Inflamm. Bowel Dis.19, 2366–2379 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Chmielarz, P. et al. GDNF/RET signaling pathway activation eliminates lewy body pathology in midbrain dopamine neurons. Mov. Disord.35, 2279–2289 (2020). [DOI] [PubMed] [Google Scholar]
23.Chen, G. et al. Lower GDNF serum level is a possible risk factor for constipation in patients with Parkinson disease: a case-control study. Front. Neurol.12, 777591 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Tang, C. et al. Distinct serum GDNF coupling with brain structural and functional changes underlies cognitive status in Parkinson’s disease. CNS Neurosci. Ther.30, e14461 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Xiaoling, Q. et al. GDNF’s role in mitigating intestinal reactive gliosis and inflammation to improve constipation and depressive behavior in rats with Parkinson’s disease. J. Mol. Neurosci.74, 78 (2024). [DOI] [PubMed] [Google Scholar]
26.Cerantola, S. et al. Involvement of enteric glia in small intestine neuromuscular dysfunction of toll-like receptor 4-deficient mice. Cells9, 838 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Esposito, G. et al. Palmitoylethanolamide improves colon inflammation through an enteric glia/toll like receptor 4-dependent PPAR-α activation. Gut63, 1300–1312 (2014). [DOI] [PubMed] [Google Scholar]
28.Wang, W. et al. Akk11 supplementation attenuates MPTP-induced neurodegeneration by inhibiting microglial NLRP3 inflammasome. Probiot. Antimicrob. Proteins17, 2348–2361 (2025). [DOI] [PubMed] [Google Scholar]
29.Soto, N. N., Gaspar, P. & Bacci, A. Not just a mood disorder─is depression a neurodevelopmental, cognitive disorder? Focus on prefronto-thalamic circuits. ACS Chem. Neurosci.15, 1611–1618 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Tack, J. et al. A review of the cardiovascular safety of prucalopride in patients with chronic idiopathic constipation. Am. J. Gastroenterol.118, 955–960 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Zhang, Z. W. et al. Oligosaccharides increase serotonin in the brain and ameliorate depression promoting 5-hydroxytryptophan production in the gut microbiota. Acta Pharm. Sin. B12, 3298–3312 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Fredholm, B. B., Jonzon, B. & Lindström, K. Effect of adenosine receptor agonists and other compounds on cyclic AMP accumulation in forskolin-treated hippocampal slices. Naunyn-Schmiedeberg’s Arch. Pharmacol332, 173–178 (1986). [DOI] [PubMed] [Google Scholar]
33.Israelyan, N. et al. Effects of serotonin and slow-release 5-hydroxytryptophan on gastrointestinal motility in a mouse model of depression. Gastroenterology157, 507–521 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Huang, L. et al. N-acetyldopamine dimer inhibits neuroinflammation through the TLR4/NF-κB and NLRP3/Caspase-1 pathways. Acta Biochim. Biophys. Sin.55, 23–33 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Zhao, Z. et al. Novel compound FLZ alleviates rotenone-induced PD mouse model by suppressing TLR4/MyD88/NF-κB pathway through microbiota–gut–brain axis. Acta Pharm. Sin. B11, 2859–2879 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Zeng, X. Z. et al. Artesunate attenuates LPS-induced osteoclastogenesis by suppressing TLR4/TRAF6 and PLCγ1-Ca2+-NFATc1 signaling pathway. Acta Pharmacol. Sin41, 229–236 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Yang, J. et al. Protopine ameliorates OVA-induced asthma through modulating TLR4/MyD88/NF-κB pathway and NLRP3 inflammasome-mediated pyroptosis. Phytomedicine126, 155410 (2024). [DOI] [PubMed] [Google Scholar]
38.Drilon, A., Hu, Z. I., Lai, G. G. Y. & Tan, D. S. W. Targeting RET-driven cancers: lessons from evolving preclinical and clinical landscapes. Nat. Rev. Clin. Oncol.15, 151–167 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Crowder, R. J., Enomoto, H., Yang, M., Johnson, E. M. & Milbrandt, J. Dok-6, a novel p62 Dok family member, promotes Ret-mediated neurite outgrowth. J. Biol. Chem.279, 42072–42081 (2004). [DOI] [PubMed] [Google Scholar]
40.Wi, S. M. et al. TAK1-ECSIT-TRAF6 complex plays a key role in the TLR4 signal to activate NF-κB. J. Biol. Chem.289, 35205–35214 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Xu, Y.-R. & Lei, C.-Q. TAK1–TABs complex: a central signalosome in inflammatory responses. Front. Immunol.11, 608976 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Lin, C. et al. Apatinib inhibits cellular invasion and migration by fusion kinase KIF5B-RET via suppressing RET/Src signaling pathway. Oncotarget7, 59236–59244 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Zhang, Z. et al. Spata2L suppresses TLR4 signaling by promoting CYLD-mediated deubiquitination of TRAF6 and TAK1. Biochemistry (Moscow)87, 957–964 (2022). [DOI] [PubMed] [Google Scholar]
44.Sessler, T., Healy, S., Samali, A. & Szegezdi, E. Structural determinants of DISC function: new insights into death receptor-mediated apoptosis signalling. Pharmacol. Ther.140, 186–199 (2013). [DOI] [PubMed] [Google Scholar]
45.Sengiku, A. et al. Circadian coordination of ATP release in the urothelium via connexin43 hemichannels. Sci. Rep.8, 1996 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Neary, J. T. et al. Mitogenic signaling by ATP/P2Y purinergic receptors in astrocytes: involvement of a calcium-independent protein kinase C, extracellular signal-regulated protein kinase pathway distinct from the phosphatidylinositol-specific phospholipase C/calcium pathway. J. Neurosci.19, 4211–4220 (1999). [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Wang, W. et al. Study on the regulatory effect of electro-acupuncture on Hegu point (LI4) in cerebral response with functional magnetic resonance imaging. Chin. J. Integr. Med.13, 10–16 (2007). [DOI] [PubMed] [Google Scholar]
48.Mader, F. et al. P2Y receptor-mediated transient relaxation of rat longitudinal ileum preparations involves phospholipase C activation, intracellular Ca²⁺ release and SK channel activation. Acta Pharmacol. Sin.37, 617–628 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Jacobson, K. A. E. B. Hershberg Award: taming inflammation by tuning purinergic signaling. Acc. Chem. Res.58, 958–970 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Cooper, J. A., Hill, S. J., Alexander, S. P., Rubin, P. C. & Horn, E. H. Adenosine receptor-induced cyclic AMP generation and inhibition of 5- hydroxytryptamine release in human platelets. Br. J. Clin. Pharmacol.40, 43–50 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Martin, C. R., Osadchiy, V., Kalani, A. & Mayer, E. A. The brain–gut–microbiome axis. Cell. Mol. Gastroenterol. Hepatol.6, 133–148 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Wang, W. et al. Gastrodin regulates the TLR4/TRAF6/NF-κB pathway to reduce neuroinflammation and microglial activation in an AD model. Phytomedicine128, 155518 (2024). [DOI] [PubMed] [Google Scholar]
53.So, S. Y. & Savidge, T. C. Sex-bias in irritable bowel syndrome: linking steroids to the gut–brain axis. Front. Endocrinol.12, 684096 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Dao, M. C. et al. and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology. Gut65, 426–436 (2016). [DOI] [PubMed] [Google Scholar]
55.Plovier, H. et al. A purified membrane protein from Akkermansia muciniphila or the pasteurized bacterium improves metabolism in obese and diabetic mice. Nat. Med.23, 107–113 (2016). [DOI] [PubMed] [Google Scholar]
56.Wang, L. et al. A purified membrane protein from Akkermansia muciniphila or the pasteurised bacterium blunts colitis associated tumourigenesis by modulation of CD8+ T cells in mice. Gut69, 1988–1997 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Desai, M. S. et al. A dietary fiber-deprived gut microbiota degrades the colonic mucus barrier and enhances pathogen susceptibility. Cell167, 1339–1353 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Passaretti, M. et al. Clinical progression and genetic pathways in body-first and brain-first Parkinson’s disease. Mol. Neurodegener.20, 74 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Blandini, F., Armentero, M.-T. & Martignoni, E. The 6-hydroxydopamine model: news from the past. Parkinsonism Relat. Disord.14, S124–S129 (2008). [DOI] [PubMed] [Google Scholar]
60.Karasawa, H. et al. New ghrelin agonist, HM01 alleviates constipation and L-dopa-delayed gastric emptying in 6-hydroxydopamine rat model of Parkinson’s disease. Neurogastroenterol. Motil.26, 1771–1782 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
61.Travagli, R. A., Browning, K. N. & Camilleri, M. Parkinson disease and the gut: new insights into pathogenesis and clinical relevance. Nat. Rev. Gastroenterol. Hepatol.17, 673–685 (2020). [DOI] [PubMed] [Google Scholar]
62.Miquel-Rio, L. et al. Early synaptic changes and reduced brain connectivity in PD-like mice with depressive phenotype. npj Parkinson’s Disease11, 242 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
63.Hendriks, M., Vinke, R. S. & Georgiev, D. Gender discrepancies and differences in motor and non-motor symptoms, cognition, and psychological outcomes in the treatment of Parkinson’s disease with subthalamic deep brain stimulation. Front. Neurol. 14, 1257781 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Martinez-Martin, P. et al. Gender-related differences in the burden of non-motor symptoms in Parkinson’s disease. J. Neurol.259, 1639–1647 (2012). [DOI] [PubMed] [Google Scholar]
65.Cerri, S., Mus, L. & Blandini, F. Parkinson’s disease in women and men: what’s the difference? J. Parkinson’s Dis9, 501–515 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Somensi, N. et al. Role of toll-like receptor 4 and sex in 6-hydroxydopamine-induced behavioral impairments and neurodegeneration in mice. Neurochem. Int.151, 105215 (2021). [DOI] [PubMed] [Google Scholar]
67.Archer, T., Palomo, T. & Fredriksson, A. Functional deficits following neonatal dopamine depletion and Isolation housing: circular water maze acquisition under pre-exposure conditions and motor activity. Neurotox. Res.4, 503–522 (2002). [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Information^{(2.3MB, docx)}

Data Availability Statement

All data generated or analyzed during this study are included in this published article (and its Supplementary information files).

[CR1] 1.Liu, H., Shen, L., Zhao, H. A., Yang, J. & Huang, D. Y. Parkinson’s disease patients combined with constipation tend to have higher serum expression of microRNA 29c, prominent neuropsychiatric disorders, possible RBD conversion, and a substandard quality of life. Neurol. Sci.44, 3141–3150 (2023). [DOI] [PubMed] [Google Scholar]

[CR2] 2.Cheesman, M., Ho, H., Bishop, K. & Sin, M.-K. Constipation management in Parkinson disease. J. Neurosci. Nurs53, 262–266 (2021). [DOI] [PubMed] [Google Scholar]

[CR3] 3.Lajoie, A. C., Lafontaine, A.-L. & Kaminska, M. The spectrum of sleep disorders in Parkinson disease. Chest159, 818–827 (2021). [DOI] [PubMed] [Google Scholar]

[CR4] 4.Li, L.-C. et al. Trends of complications in patients with Parkinson’s disease in seven major cities of China from 2016 to 2019. Int. Clin. Psychopharmacol36, 274–278 (2021). [DOI] [PubMed] [Google Scholar]

[CR5] 5.Ogawa, E., Sakakibara, R., Kishi, M. & Tateno, F. Constipation triggered the malignant syndrome in Parkinson’s disease. Neurol. Sci.33, 347–350 (2011). [DOI] [PubMed] [Google Scholar]

[CR6] 6.Ramu, S. K. et al. Defecatory disorders are a common cause of chronic constipation in Parkinson disease. Neurogastroenterol. Motil.36, e14767 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR7] 7.Xiao-ling, Q. et al. Depression is associated with constipation in patients with Parkinson’s disease. Front. Neurol.11, 567574 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Chang, T.-Y., Chen, Y.-H., Chang, M.-H. & Lin, C.-H. Is there a close association of depression with either constipation or dysosmia in Parkinson’s disease. Sci. Rep.10, 15476 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR9] 9.Huang, Z. P. et al. The significance of psychological support in managing depression in Parkinson’s disease: combining venlafaxine with pramipexole and psychological care. Actas Esp. Psiquiatr.53, 19–25 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Tse, J. K. Y. Gut Microbiota, nitric oxide, and microglia as prerequisites for neurodegenerative disorders. Acs Chem. Neurosci.8, 1438–1447 (2017). [DOI] [PubMed] [Google Scholar]

[CR11] 11.Trisal, A., Singh, I., Garg, G., Jorwal, K. & & Singh, A. K. Gut–brain axis and brain health: modulating neuroinflammation, cognitive decline, and neurodegeneration. 3 Biotech15, 25 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR12] 12.de la Fuente-Nunez, C., Meneguetti, B. T., Franco, O. L. & Lu, T. K. Neuromicrobiology: how microbes influence the brain. ACS Chem. Neurosci.9, 141–150 (2018). [DOI] [PubMed] [Google Scholar]

[CR13] 13.Gan, J. et al. A survey of subjective constipation in Parkinson’s disease patients in Shanghai and literature review. BMC Neurol.18, 29 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR14] 14.Gershon, M. D. 5-Hydroxytryptamine (serotonin) in the gastrointestinal tract. Curr. Opin. Endocrinol., Diabetes Obes20, 14–21 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Kyodo, R. et al. Modulation of intestinal motility in an adolescent rat model of irritable bowel syndrome. Digestion105, 99–106 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR16] 16.Koopman, N. et al. The multifaceted role of serotonin in intestinal homeostasis. Int. J. Mol. Sci.22, 9487 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Sawamura, T. et al. Alterations in descending brain-spinal pathways regulating colorectal motility in a rat model of Parkinson’s disease. Am. J. Physiol.-Gastrointest. Liver Physiol.326, G195–G204 (2024). [DOI] [PubMed] [Google Scholar]

[CR18] 18.Murtomäki, K. et al. Dopamine transporter binding in the brain is linked to irritable bowel syndrome in Parkinson’s disease. Brain Behav.13, e3098 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR19] 19.Linan-Rico, A. et al. Mechanosensory signaling in enterochromaffin cells and 5-HT release: potential implications for gut inflammation. Front. Neurosci.10, 564 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR20] 20.Andersen, M. S. et al. Heritability enrichment implicates microglia in Parkinson’s disease pathogenesis. Ann. Neurol.89, 942–951 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.Liñán-Rico, A. et al. Purinergic autocrine regulation of mechanosensitivity and serotonin release in a human EC model. Inflamm. Bowel Dis.19, 2366–2379 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR22] 22.Chmielarz, P. et al. GDNF/RET signaling pathway activation eliminates lewy body pathology in midbrain dopamine neurons. Mov. Disord.35, 2279–2289 (2020). [DOI] [PubMed] [Google Scholar]

[CR23] 23.Chen, G. et al. Lower GDNF serum level is a possible risk factor for constipation in patients with Parkinson disease: a case-control study. Front. Neurol.12, 777591 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR24] 24.Tang, C. et al. Distinct serum GDNF coupling with brain structural and functional changes underlies cognitive status in Parkinson’s disease. CNS Neurosci. Ther.30, e14461 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR25] 25.Xiaoling, Q. et al. GDNF’s role in mitigating intestinal reactive gliosis and inflammation to improve constipation and depressive behavior in rats with Parkinson’s disease. J. Mol. Neurosci.74, 78 (2024). [DOI] [PubMed] [Google Scholar]

[CR26] 26.Cerantola, S. et al. Involvement of enteric glia in small intestine neuromuscular dysfunction of toll-like receptor 4-deficient mice. Cells9, 838 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR27] 27.Esposito, G. et al. Palmitoylethanolamide improves colon inflammation through an enteric glia/toll like receptor 4-dependent PPAR-α activation. Gut63, 1300–1312 (2014). [DOI] [PubMed] [Google Scholar]

[CR28] 28.Wang, W. et al. Akk11 supplementation attenuates MPTP-induced neurodegeneration by inhibiting microglial NLRP3 inflammasome. Probiot. Antimicrob. Proteins17, 2348–2361 (2025). [DOI] [PubMed] [Google Scholar]

[CR29] 29.Soto, N. N., Gaspar, P. & Bacci, A. Not just a mood disorder─is depression a neurodevelopmental, cognitive disorder? Focus on prefronto-thalamic circuits. ACS Chem. Neurosci.15, 1611–1618 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR30] 30.Tack, J. et al. A review of the cardiovascular safety of prucalopride in patients with chronic idiopathic constipation. Am. J. Gastroenterol.118, 955–960 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR31] 31.Zhang, Z. W. et al. Oligosaccharides increase serotonin in the brain and ameliorate depression promoting 5-hydroxytryptophan production in the gut microbiota. Acta Pharm. Sin. B12, 3298–3312 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR32] 32.Fredholm, B. B., Jonzon, B. & Lindström, K. Effect of adenosine receptor agonists and other compounds on cyclic AMP accumulation in forskolin-treated hippocampal slices. Naunyn-Schmiedeberg’s Arch. Pharmacol332, 173–178 (1986). [DOI] [PubMed] [Google Scholar]

[CR33] 33.Israelyan, N. et al. Effects of serotonin and slow-release 5-hydroxytryptophan on gastrointestinal motility in a mouse model of depression. Gastroenterology157, 507–521 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR34] 34.Huang, L. et al. N-acetyldopamine dimer inhibits neuroinflammation through the TLR4/NF-κB and NLRP3/Caspase-1 pathways. Acta Biochim. Biophys. Sin.55, 23–33 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR35] 35.Zhao, Z. et al. Novel compound FLZ alleviates rotenone-induced PD mouse model by suppressing TLR4/MyD88/NF-κB pathway through microbiota–gut–brain axis. Acta Pharm. Sin. B11, 2859–2879 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR36] 36.Zeng, X. Z. et al. Artesunate attenuates LPS-induced osteoclastogenesis by suppressing TLR4/TRAF6 and PLCγ1-Ca2+-NFATc1 signaling pathway. Acta Pharmacol. Sin41, 229–236 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR37] 37.Yang, J. et al. Protopine ameliorates OVA-induced asthma through modulating TLR4/MyD88/NF-κB pathway and NLRP3 inflammasome-mediated pyroptosis. Phytomedicine126, 155410 (2024). [DOI] [PubMed] [Google Scholar]

[CR38] 38.Drilon, A., Hu, Z. I., Lai, G. G. Y. & Tan, D. S. W. Targeting RET-driven cancers: lessons from evolving preclinical and clinical landscapes. Nat. Rev. Clin. Oncol.15, 151–167 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR39] 39.Crowder, R. J., Enomoto, H., Yang, M., Johnson, E. M. & Milbrandt, J. Dok-6, a novel p62 Dok family member, promotes Ret-mediated neurite outgrowth. J. Biol. Chem.279, 42072–42081 (2004). [DOI] [PubMed] [Google Scholar]

[CR40] 40.Wi, S. M. et al. TAK1-ECSIT-TRAF6 complex plays a key role in the TLR4 signal to activate NF-κB. J. Biol. Chem.289, 35205–35214 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR41] 41.Xu, Y.-R. & Lei, C.-Q. TAK1–TABs complex: a central signalosome in inflammatory responses. Front. Immunol.11, 608976 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR42] 42.Lin, C. et al. Apatinib inhibits cellular invasion and migration by fusion kinase KIF5B-RET via suppressing RET/Src signaling pathway. Oncotarget7, 59236–59244 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR43] 43.Zhang, Z. et al. Spata2L suppresses TLR4 signaling by promoting CYLD-mediated deubiquitination of TRAF6 and TAK1. Biochemistry (Moscow)87, 957–964 (2022). [DOI] [PubMed] [Google Scholar]

[CR44] 44.Sessler, T., Healy, S., Samali, A. & Szegezdi, E. Structural determinants of DISC function: new insights into death receptor-mediated apoptosis signalling. Pharmacol. Ther.140, 186–199 (2013). [DOI] [PubMed] [Google Scholar]

[CR45] 45.Sengiku, A. et al. Circadian coordination of ATP release in the urothelium via connexin43 hemichannels. Sci. Rep.8, 1996 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR46] 46.Neary, J. T. et al. Mitogenic signaling by ATP/P2Y purinergic receptors in astrocytes: involvement of a calcium-independent protein kinase C, extracellular signal-regulated protein kinase pathway distinct from the phosphatidylinositol-specific phospholipase C/calcium pathway. J. Neurosci.19, 4211–4220 (1999). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR47] 47.Wang, W. et al. Study on the regulatory effect of electro-acupuncture on Hegu point (LI4) in cerebral response with functional magnetic resonance imaging. Chin. J. Integr. Med.13, 10–16 (2007). [DOI] [PubMed] [Google Scholar]

[CR48] 48.Mader, F. et al. P2Y receptor-mediated transient relaxation of rat longitudinal ileum preparations involves phospholipase C activation, intracellular Ca²⁺ release and SK channel activation. Acta Pharmacol. Sin.37, 617–628 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR49] 49.Jacobson, K. A. E. B. Hershberg Award: taming inflammation by tuning purinergic signaling. Acc. Chem. Res.58, 958–970 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR50] 50.Cooper, J. A., Hill, S. J., Alexander, S. P., Rubin, P. C. & Horn, E. H. Adenosine receptor-induced cyclic AMP generation and inhibition of 5- hydroxytryptamine release in human platelets. Br. J. Clin. Pharmacol.40, 43–50 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR51] 51.Martin, C. R., Osadchiy, V., Kalani, A. & Mayer, E. A. The brain–gut–microbiome axis. Cell. Mol. Gastroenterol. Hepatol.6, 133–148 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR52] 52.Wang, W. et al. Gastrodin regulates the TLR4/TRAF6/NF-κB pathway to reduce neuroinflammation and microglial activation in an AD model. Phytomedicine128, 155518 (2024). [DOI] [PubMed] [Google Scholar]

[CR53] 53.So, S. Y. & Savidge, T. C. Sex-bias in irritable bowel syndrome: linking steroids to the gut–brain axis. Front. Endocrinol.12, 684096 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR54] 54.Dao, M. C. et al. and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology. Gut65, 426–436 (2016). [DOI] [PubMed] [Google Scholar]

[CR55] 55.Plovier, H. et al. A purified membrane protein from Akkermansia muciniphila or the pasteurized bacterium improves metabolism in obese and diabetic mice. Nat. Med.23, 107–113 (2016). [DOI] [PubMed] [Google Scholar]

[CR56] 56.Wang, L. et al. A purified membrane protein from Akkermansia muciniphila or the pasteurised bacterium blunts colitis associated tumourigenesis by modulation of CD8+ T cells in mice. Gut69, 1988–1997 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR57] 57.Desai, M. S. et al. A dietary fiber-deprived gut microbiota degrades the colonic mucus barrier and enhances pathogen susceptibility. Cell167, 1339–1353 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR58] 58.Passaretti, M. et al. Clinical progression and genetic pathways in body-first and brain-first Parkinson’s disease. Mol. Neurodegener.20, 74 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR59] 59.Blandini, F., Armentero, M.-T. & Martignoni, E. The 6-hydroxydopamine model: news from the past. Parkinsonism Relat. Disord.14, S124–S129 (2008). [DOI] [PubMed] [Google Scholar]

[CR60] 60.Karasawa, H. et al. New ghrelin agonist, HM01 alleviates constipation and L-dopa-delayed gastric emptying in 6-hydroxydopamine rat model of Parkinson’s disease. Neurogastroenterol. Motil.26, 1771–1782 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR61] 61.Travagli, R. A., Browning, K. N. & Camilleri, M. Parkinson disease and the gut: new insights into pathogenesis and clinical relevance. Nat. Rev. Gastroenterol. Hepatol.17, 673–685 (2020). [DOI] [PubMed] [Google Scholar]

[CR62] 62.Miquel-Rio, L. et al. Early synaptic changes and reduced brain connectivity in PD-like mice with depressive phenotype. npj Parkinson’s Disease11, 242 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR63] 63.Hendriks, M., Vinke, R. S. & Georgiev, D. Gender discrepancies and differences in motor and non-motor symptoms, cognition, and psychological outcomes in the treatment of Parkinson’s disease with subthalamic deep brain stimulation. Front. Neurol. 14, 1257781 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR64] 64.Martinez-Martin, P. et al. Gender-related differences in the burden of non-motor symptoms in Parkinson’s disease. J. Neurol.259, 1639–1647 (2012). [DOI] [PubMed] [Google Scholar]

[CR65] 65.Cerri, S., Mus, L. & Blandini, F. Parkinson’s disease in women and men: what’s the difference? J. Parkinson’s Dis9, 501–515 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR66] 66.Somensi, N. et al. Role of toll-like receptor 4 and sex in 6-hydroxydopamine-induced behavioral impairments and neurodegeneration in mice. Neurochem. Int.151, 105215 (2021). [DOI] [PubMed] [Google Scholar]

[CR67] 67.Archer, T., Palomo, T. & Fredriksson, A. Functional deficits following neonatal dopamine depletion and Isolation housing: circular water maze acquisition under pre-exposure conditions and motor activity. Neurotox. Res.4, 503–522 (2002). [DOI] [PubMed] [Google Scholar]

PERMALINK

GDNF signaling modulation by Akkermansia muciniphila ameliorates constipation–depression comorbidity in Parkinson’s disease

Chunyan Mu

Zairen Zhou

Jingyu Li

Mingyu Su

Ke Xue

Jingyuan Zhang

Shijie Shi

Ye Li

Xiaoyu Yao

Mengxue Wang

Wanxiang Zhang

Zhe Wang

Jianguo Zhu

Shuguang Fang

Wei Wang

Chuanxi Tang

Xiaoling Qin

Abstract

Introduction

Results

GDNF alleviates constipation, restores colonic 5-HT secretion, and improves depression-like behavior in 6-OHDA mouse model

Fig. 1. GDNF alleviates constipation in the 6-OHDA mouse model, restores colonic 5-HT secretion, and improves depressive-like behavior.

GDNF alleviates TLR4-TRAF6-mediated inflammatory activation in EGCs and improves colonic function in a 6-OHDA mouse model

Fig. 2. GDNF reduces TLR4-TRAF6-mediated inflammatory activation in EGCs and improves colonic function in a 6-OHDA mouse model.

GDNF competitively binds TRAF6 through GDNF-Ret-Src signaling to block TRAF6-mediated NEDD4 ubiquitination degradation in the colon of 6-OHDA mice

Fig. 3. GDNF-Ret-Src competitively binds to TRAF6, blocking TRAF6-mediated NEDD4 ubiquitination and degradation in the colon of 6-OHDA mice.

GDNF promotes NEDD4 expression in EGCs to target CX43 for ubiquitination and degradation

Fig. 4. GDNF promotes NEDD4 expression in EGCs, leading to the targeted ubiquitination and degradation of CX43.

Overexpression of CX43 on EGCs membrane creates an extracellular hyperuricemic environment, increasing P2Y12 expression on ECs, negatively regulating 5-HT synthesis and secretion, exacerbating constipation and depressive-like behavior in 6-OHDA mice

Fig. 5. Overexpression of CX43 on the membrane of EGCs creates an extracellular hyperuricemic environment, which increases P2Y12 expression on ECs and negatively regulates the synthesis and secretion of 5-HT, exacerbating constipation and depression-like behavior in 6-OHDA mice.

Akk11 alleviates constipation and improves depressive-like behavior in 6-OHDA mouse model, associated with upregulation of GDNF

Fig. 6. Akk11 alleviates constipation and improves depression-like behavior in 6-OHDA mouse model.

Discussion

Fig. 7.

Methods

Animals

Virus intervention

Table 1.

Cell culture

Plasmid transfection

Viral infection

6-Hydroxydopamine hydrobromide (6-OHDA) induced PD-like model

Intraperitoneal injection

Akk11 intervention treatment

Co-culture of Akk11 with EGC Cells

Apomorphine-Induced Rotational Behavior in Mice

Tail suspension test (TST)

Sucrose preference test (SPT)

2-hour Fecal water content

2-hour Carbon dust propulsion rate

24-hour fecal mass measure

Perfusion fixation

Freezing tissue slices

Transcriptome sequencing

Western blot

Table 2.

Immunofluorescence

ATP assay

5-HT assay

Plasmid construction

Table 3.

Table 4.

Molecular docking

Statistical analysis

Supplementary information

Acknowledgements

Author contributions

Data availability

Competing interests

Footnotes

Contributor Information

Supplementary information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK