{"paper_id":"f47740b6-870f-4d52-a9c2-bebe67f2eb7a","body_text":"ARTICLE IN PRESS\nARTICLE IN PRESS\nhttps://doi.org/10.1038/s41522-026-01017-4\nReceived: 2 July 2025\nAccepted: 17 May 2026\nCite this article as: Chen, Y ., Qiu, Y .,\nPan, F. et al. Parabacteroides\ngoldsteinii and its metabolite 7-KLCA\nattenuate endometriosis via TGR5 to\nreprogram macrophages by\nmodulating the PPARγ/GPR132 axis.\nnpj Biofilms  Microbiomes (2026).\nhttps://doi.org/10.1038/\ns41522-026-01017-4\nYun Chen, Yuqing Qiu, Feifei Pan, Yanqin Zheng, Jingyao Wang, Kunxiang Gong, Lirong\nGuo, Yiming Song, Zixin Tao & Kun Shi\nWe are providing an unedited version of this manuscript to give early access to its\nfindings.  Before final  publication, the manuscript will undergo further editing. 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To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.\nnpj Biofilms  and Microbiomes\nArticle in Press\nParabacteroides goldsteinii and its metabolite 7-\nKLCA attenuate endometriosis via TGR5 to\nreprogram macrophages by modulating the PPARγ/\nGPR132 axis\n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nParabacteroides goldsteinii and Its Metabolite 7-KLCA Attenuate Endometriosis via TGR5 \nto Reprogram Macrophages by Modulating the PPARγ/GPR132 Axis \nAuthors: Yun Chen 1 2, Yuqing Qiu 1, Feifei Pan 1 2, Yanqin Zheng 1, Jingyao Wang 1 2, Kunxiang Gong 1 2, Lirong Guo \n1 2, Yiming Song 1, Zixin Tao 3*, Kun Shi 1* \n \nAffiliations:  \n1Department of Gynecology and Obstetrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical \nUniversity, Guangzhou, 510623, Guangdong, China. \n2Institute of Reproductive Health and Perinatology, Guangzhou Women and Children's Medical Center, Guangzhou \nMedical University, Guangzhou, 510623, Guangdong, China. \n3Department of Gynecology and Obstetrics, Guangzhou First People's Hospital, South China University of Technology, \nGuangzhou, 510180, Guangdong, China. \n \n*Correspondences: 329011915@qq.com (Zixin Tao) and shikun28@hotmail.com (Kun Shi) \n \nWord count: 12316 \n  \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nAbstract \nEndometriosis (EMS) remains understudied in effective management strategies. The interplay between macrophage \ndysfunction and microbiota -derived immune signals emerges as a potential mechanism in EMS pathogenesis, \nsuggesting its relevance for future therapeutic exploration. In this study, we established mouse models to demonstrate \nthat gut microbiota modulated EMS development. Integrated microbial and metabolomic profiling identified \nParabacteroides goldsteinii (Pg) as a promising probiotic candidate, whose downstream metabolite 7 -ketolithocholic \nacid (7-KLCA) exhibiting therapeutic efficacy in ameliorating EMS phenotypes upon supplementation. Mechanistically, \nPg reshapes its bile acid (BA) metabolism to elevate 7-KLCA. This bioactive metabolite acts via the receptor TGR5 to \nsuppress PPARγ expression and activate GPR132, thereby enhancing efferocytosis and promoting M1 macrophage \npolarization. These findings uncover a gut -metabolite-immune regulatory axis through which Pg  reprograms \nmacrophage function to restrain EMS progression, offering a potential microbial perspective for this chronic condition. \n \nKeywords Parabacteroides goldsteinii, bile acid, endometriosis, macrophage polarization, PPARγ/GPR132 axis, efferocytosis \n \nIntroduction  \nEMS is a chronic, estrogen -dependent inflammatory condition characterized by the ectopic growth of endometrial -\nlike tissue, affecting approximately 10% of women of reproductive age [1-3]. Patients commonly experience \ndysmenorrhea, infertility, and chronic pelvic pain, which contribute to significant physical and psychological burdens[4]. \nDespite its high prevalence, the pathogenesis of EMS remains incompletely understood, and current therapeutic \noptions are limited by high recurrence rates and systemic side effects[5]. \nGrowing evidence implicates macrophage -driven mechanisms in the pathogenesis of endometriosis [6-9]. Initially, \nproinflammatory M1 macrophages are often predominant and  appear to attempt  elimination of ectopic lesions. \nSubsequent shifts toward M2 -polarized phenotypes may contribute to  an immunosuppressive microenvironment, \npromoting angiogenesis and adhesion formation while impairing immune surveil lance through effector cell \ndysfunction[10-12]. This dysfunctional polarization points to macrophages as potential drivers of EMS pathology. \nThe role of the gut microbiota (GM) in endometriosis (EMS) is actively investigated, yet compositional studies report \nconflicting findings [13-16]. This inconsistency underscores the necessity for functi onal evidence . Although antibiotic -\nmediated GM perturbation can influence EMS phenotypes, the definitive causal links and mechanisms remain elusive[17, \n18]. In particular, it is unclear how gut -derived signals modulate macrophage polarization within the EMS \nmicroenvironment. \nIn this study, we establish mouse models of EMS and subsequently apply human fecal microbiota transplantation \n(FMT) and antibiotic treatment to modulate gut microbiota composition. Pg is identified as a key microbial species that \nattenuates EMS progression. We show that Pg reshapes bile acid metabolism, leading to elevated 7 -KLCA levels. \nCellular studies demonstrate that 7-KLCA acts via Takeda G protein-coupled receptor 5 (TGR5, also known as GPBAR1) \nto suppress PPARγ and activate GPR132, thereby promoting M1 macrophage polarization and enhancing efferocytosis. \nThese findings uncover a gut-metabolite-immune regulatory circuit that links microbial activity to macrophage-mediated \nimmunomodulation in EMS and suggest a potential microbiota-based therapeutic approach. \n \nResults \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nGut microbiota modulates EMS pathogenesis in dual murine models \nTo investigate the role of the gut microbiota in EMS, we established a FMT model. Mice were randomly assigned to \nreceive microbiota from either EMS patients (FMT_EMS) or normal controls (FMT_NC) (Figure 1A). This procedure did \nnot result in significant changes in body we ight (Figure 1B). Pain responses, assessed by oxytocin -induced writhing \nassays, revealed a significantly higher number of abdominal contractions in the FMT_EMS group compared to FMT_NC \ncontrols (Figure 1C). While adhesion scores appeared numerically elevat ed in the FMT_EMS group (Figure 1D), no \nsignificant difference was observed. In contrast, consistent with visual evidence of increased lesion number and size in \nthe FMT_EMS group (Figure 1E–1G), lesion scores were significantly higher than those in the FMT_NC group (Figure \n1H). No overt structural alterations were observed in intestinal tissues between the two groups (Figure 1I). \nGiven the proved role of macrophages in EMS pathogenesis —whereby early M1 polarization gives way to an \nimmunosuppressive M2 phenotype promoting angiogenesis, adhesion, and suppressing immune cell-mediated lesion \nclearance[11, 12]—we evaluated macrophage subsets by flow cytometry. Analysis of surface marker expression revealed \na significant reduction in CD86 mean fluorescence intensity (MFI) in the FMT_EMS group, while CD206 expression \nshowed no significant difference (Figure 1J). Collectively, these findings suggest that EMS -associated gut microbiota \nmay suppress M1 macrophage polarization, thereby contributing to disease progression. \nBuilding upon an autograft -derived endometriosis mod el (designed to avoid immune microenvironmental \nperturbations by allogeneic transplantation [19]), we developed a murine system with antibiotic -induced microbial \nperturbation to investigate the impact of gut microbial compositional changes on EMS pathogenesis (Figure 2A). Three \nexperimental groups were established: (i) the VNA group received vancomycin, neomycin, and ampicillin, targeting \nanaerobic depletion while sparin g metronidazole-sensitive species; (ii) the M group was treated with metronidazole; \nand (iii) the Blank group received sterile water. Throughout the experimental period, no significant differences in body \nweight were observed among the groups (Figure 2B). Notably, oxytocin -induced writhing was significantly reduced in \nthe M group compared to both VNA and Blank groups (Figure 2C). Pheno typic analysis demonstrated that \nmetronidazole treatment markedly alleviated disease severity, as indicated by reduced adhesion scores (Figure 2D), \nsmaller lesion size (Figure 2E), and decreased lesion weight and volume (Figure 2F and 2G). Histological examination \nrevealed thinner stromal and epithelial layers in lesions from the M group (Figure 2H), consistent with lower lesion \nscores (Figure 2I). Flow cytometry further showed a reduction in CD206⁺ M2 macrophages and a marginal increase in \nCD86⁺ M1 macrophages in the M group (Figure 2J), suggesting that metronidazole -mediated microbial shifts may \nsuppress M2 polarization. These findings align with the previous report [18] and further support a model in which gut \nmicrobiota modulate EMS pathogenesis through macrophage phenotypic reprogramming. \nPg mediates the therapeutic effects of metronidazole in an EMS model \nTo elucidate microbiota -dependent mechanisms underlying metroni dazole-mediated attenuation of EMS, we \nperformed strain -resolved metagenomic sequencing on fecal samples from VNA - and M-treated mice. Principal \ncoordinates analysis (PCoA) revealed that antibiotic perturbation led to substantial shifts in gut microbiota composition, \nwith axis 1 and axis 2 explaining 84.89% and 11.41% of the total variance, respectively (Figure 3A). Species -level \ntaxonomic profiling demonstrated clear distinctions between the two treatment groups (Figure 3B). LEfSe analysis (log₂ \nfold chang e > 3.5) further identified 14 differentially abundant taxa (Figure 3C). Notably, the M group exhibited \nenrichment of putative probiotic species such as Pg and Akkermansia muciniphila , while opportunistic pathogens \nincluding Klebsiella pneumoniae  and Enterobacter hormaechei were significantly depleted (Figure 3D). Correlation \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nanalyses using Spearman’s rank correlation revealed that Pg and Akkermansia muciniphila were inversely associated \nwith multiple clinical indices of EMS severity, including adhesion scores, frequency of abdominal writhing, lesion \nweight/volume, and histopathological scores. In contrast, Klebsiella pneumoniae and Enterobacter hormaechei showed \npositive correlations with these disease parameters (Figure 3E). Among these taxa, only Pg showed a consistent \nincrease in relative abundance in both metronidazole -treated mice and those colonized with microbiota from healthy \ncontrols, as confirmed by RT -qPCR (Figure 3F  and 3G, Supplementary Figure 1A and 1B). Importantly, in line with \nthese findings, we observed a significant reduction in the relative abundance of Pg in fecal samples from EMS patients \ncompared to healthy controls (Figure 3H). Collectively, these results suggest a potential role for Pg in modulating EMS \nprogression. \nTo directly assess whether Pg contributes to the protective effects of metronidazole, mice were orally administered \nPg prior to surgical induction of EMS (Figure 4A). Consistent  with previous findings, no significant differences in body \nweight gain were observed between groups (Figure 4B). However, Pg-pretreated mice exhibited a significant reduction \nin oxytocin -induced writhing responses and abdominal adhesion scores (Figure 4C  and 4D). Gross pathological \nevaluation revealed visibly smaller lesions with significantly decreased lesion weight and volume (Figure 4E –4G), \nindicating a mitigated disease phenotype following Pg exposure. Histological examination confirmed that Pg -treated \nmice displayed thinning of both stromal and epithelial layers in endometriotic lesions, along with significantly lower \nlesion scores (Figure 4H and 4I). Flow cytometry analysis further demonstrated a significant increase in CD86 MFI and \na concurrent reduction in CD206 MFI in Pg-treated mice compared to saline controls (Figure 4J), suggesting inhibition \nof M2 macrophage polarization. Consist ently, serum cytokine analysis showed a reduction in IL -10 levels—an anti-\ninflammatory cytokine associated with M2 macrophages —accompanied by elevated levels of M1 -associated \nproinflammatory cytokines, including TNF-α, IL-1β, and IL-6 (Figure 4K). These findings provide compelling evidence \nthat Pg contributes to the therapeutic efficacy of metronidazole in EMS by suppressing M2 macrophage polarization, \nthereby highlighting its potential as a microbial-based therapeutic candidate for endometriosis. \nBile acid metabolism mediates Pg-driven amelioration of EMS \nThe gut microbiota produces a broad spectrum of bioactive metabolites that influence disease initiation and \nprogression[20, 21]. However, whether Pg, a prevalent gut commensal, modulates EMS phenotypes through its secreted \nmetabolites remains unclear. To address this, we orally administered Pg culture medium (PgCM ) to EMS mice and \nevaluated its therapeutic efficacy (Supplementary Figure 2A). Unexpectedly, PgCM treatment alone failed to improve \ndisease features, as indicated by unaltered body weight, abdominal adhesion scores, writhing frequency, and lesion \nburden compared to positive control (Supplementary Figure 2B–2G). In addition, no significant differences in peritoneal \nmacrophage polarization profiles were observed between the PgCM and control groups. These findings suggest that \ndirect metabolite exposure may be insufficient to replicate the therapeutic effects of live Pg and highlight the need for \nfurther investigation into the specific mediators involved. \nTo explore potential metabolite-based mechanisms, we performed untargeted metabolomic profiling of cecal contents \nfrom VNA- and M-treated mice. Principal component analysis revealed a clear separation between metabolic profiles \nof the two groups (Figure 5A). In total, 191 metabolites were upregulated and 137 were downregulated in the M group \n(Figure 5B). KEGG pathway enrichment analysis identified primary bile acid biosynthesis as significantly enriched in \nthe M group (Figure 5C). We next assessed fecal bile acid composition and observed that cholic acid (CA), β-muricholic \nacid (β-MCA), deoxycholic acid (DCA), 7-KLCA, and lithocholic acid (LCA) were significantly enriched in the M group, \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nwhile taurocholic acid (TCA), taurochenodeoxycholic acid (TCDCA), and 23 -nordeoxycholic acid were elevated in the \nVNA group (Figure 5D). Furthermore, Spearman correlation analys is revealed strong associations between specific \nbile acids and key clinical metrics of EMS (Figure 5E). Given that BA composition is dynamically shaped by gut \nmicrobiota[22], we next analyzed the relationships between BA levels and bacterial species. Pearson ’s correlation \nanalysis indicated that the relative abundance of 11 bacterial taxa, including Pg, was closely associated with BA \nconcentrations (Figure 5F). \nTo identify the key bile acids driving these effects, we conducted targeted quantitative metabolomics. The results \nconfirmed distinct bile acid clustering patterns, with glycocholic acid (GCA), 7-KLCA, and chenodeoxycholic acid (CDCA) \nelevated in the M group, whereas TCDCA, TCA, and tauroursodeoxycholic acid (TUDCA) were predominantly enriched \nin the VNA group (Figure 5G). Collectively, these findings support a model in which Pg modulates bile acid metabolism, \nthereby contributing to the attenuation of EMS pathophysiology. \nPg-mediated 7-KLCA alleviates EMS via the gut microbiota-immune Axis \nAs illustrated in Supplementary Figure 3A, members of the Parabacteroides genus have previously been shown to \nexpress bile salt hydrolase (BSH) and 7α-hydroxysteroid dehydrogenase (7α-HSDH), key enzymes involved in the \nbioconversion of TCDCA to 7-KLCA [23, 24]. To determine whether Pg possesses this metabolic capacity, we conducted \ntargeted in vitro fermentation assays. As expected, supplementation of TCDCA to Pg cultures led to the accumulation \nof both 7 -KLCA and its metabolic intermediate,  CDCA (Supplementary Figure 3B and 3C). Quantitative analyses \nrevealed elevated CDCA/TCDCA and 7 -KLCA/CDCA ratios in the anaerobic culture supernatants (Supplementary \nFigure 3D), consistent with BSH-mediated deconjugation followed by 7α-HSDH-driven oxidation. \nTo further investigate microbial feedback interactions, we examined the effects of TCDCA and 7-KLCA on Pg growth \nin vitro . TCDCA at concentrations ≤200 μM did not significantly alter bacterial growth, whereas 500 μM TCDCA \nmarkedly suppressed Pg proliferation (Supplementary Figure 3E). In contrast, 7-KLCA exerted no significant effects on \nPg growth at any tested concentration (Supplementary Figure 3F). To explore the in vivo relevance of this pathway, we \nadministered Pg cultures supplemented with TCDCA (PgTCM) to EMS-induced mice via oral gavage over a five-week \nperiod. Notably, PgTCM-treated mice exhibited significant attenuation of EMS-related phenotypes—including reduced \npelvic pain, fibrotic adhesions, and lesion progression—when compared with both Vehicle- and PgCM-treated groups \n(Supplementary Figure 2B–2G). Consistent with these phenotypic improvements, an increase in CD86 MFI was \nobserved in peritoneal macrophages, whereas CD206 MFI remained unchanged (Supplementary Figure 2H). These \nfindings suggest that Pg may contribute to EMS amelioration through modulation of bile acid metabolism, particularly \nvia 7-KLCA. \nTo directly evaluate the therapeutic potential of Pg -derived 7 -KLCA, mice were administered purified 7 -KLCA \nfollowing EMS induction via uterine auto -transplantation (Figure 6 A). Consistent with prior safety data, 7 -KLCA \ntreatment did not affect body weight (Figure 6B). Behavioral analysis revealed a significant reduction in oxytocin -\ninduced writhing, as well as decreased abdominal adhesion severity in the 7-KLCA group compared with normal control \n(Figure 6C and 6D). Morphometric assessments confirmed a marked reduction in lesion volume and weight (Figure \n6E–6G), and histopathological analysis revealed diminished epithelial and stromal thickening, along with reduced lesion \nseverity scores (Figure 6H and 6I). \nAs previously reported, restoration of the disrupted M1/M2 macrophage balance may facilitate immune clearance of \nectopic endometrial tissue within the peritoneal cavity[6]. In support of this, flow cytometry showed a significant increase \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nin CD86 MFI and a corresponding decrease in CD206 MFI in 7-KLCA-treated mice compared to NS control (Figure 6J), \nindicating M1 polarization with concurrent suppression of the M2 phenotype. Serum cytokine profiling further \ncorroborated this immun e shift: M1 -associated proinflammatory cytokines IL -1β, TNF-α, and IL -6 were elevated, \nwhereas the M2 -associated anti -inflammatory cytokine IL -10 was markedly reduced (Figure 6K). These results \ndemonstrate that 7-KLCA mitigates EMS pathogenesis by modulati ng the gut microbiota -immune axis. Together with \nthe established role of Pg in producing 7-KLCA[24], our findings suggest that Pg may confer benefits via this metabolite. \n7-KLCA promotes M2-to-M1 phenotypic switch by targeting TGR5 \nTo investigate the regulatory effects of 7-KLCA on macrophage polarization, BMDMs were polarized in vitro into M0, \nM1, and M2 phenotypes. Cells were then treated with 7-KLCA at concentrations ranging from 0 to 20 μM for 24 hours, \nfollowed by cytokine quant ification in cell supernatants using ELISA. In M2 macrophages, 7 -KLCA induced a \nconcentration-dependent increase in proinflammatory cytokines, including MCP -1, IL-1β, TNF-α, and IL-6, with the \nmaximal effect observed at 10 μM, while IL-10 levels remained unchanged (Figure 7A). These cytokine changes were \nnot observed in M0 or M1 macrophages (Supplementary Figure 4A and 4B). Consistently, flow cytometry analysis \nrevealed a significant upregulation of CD86 MFI specifically in M2 macrophages following 7 -KLCA treatment, with no \ncomparable effect in M0 or M1 subsets (Figure 7B). Together, these data suggest that 7-KLCA selectively promotes the \nphenotypic conversion of M2 macrophages toward a proinflammatory M1-like state. \nGiven that bile acids typically exert the ir biological functions through BA receptors [25, 26], we next assessed the \nexpression of several canonical BA receptors in macrophage subtypes. Analysis revealed that TGR5 (encoded by \nGpbar1) expression was markedly enriched in M2 macrophages relative to M0 and M1 cells, while the expression of \nFxr, Car1, Vdr, Smpd3, and Mrp4 showed no significant variation across subtypes (Figure 7C). To further support these \nfindings, we analyzed a publicly available transcriptomic dataset (GSE213216), which demonstrated elevated GPBAR1 \ntranscript levels in M2 macrophages within endometriosis lesions (Figure 7D, Supplementary Figure 5A and 5B). \nTo validate TGR5 as a functional receptor mediating 7 -KLCA signaling in macrophages, we performed a CETSA. \nResults showed that 7-KLCA increased the thermal stability of TGR5 in heat-denatured M2 macrophages, indicating a \ndirect ligand-receptor interaction (Figure 7E). This was further confirmed by SPR analysis, which demonstrated dose -\ndependent binding of 7-KLCA to recombinant TGR5, with an equilibrium dissociation constant (KD) of 5.82 μM (Figure \n7F). To identify specific interaction sites between 7-KLCA and TGR5, we conducted molecular docking using the human \nTGR5 ligand -binding domain structure (PDB: 7BW0). The docking simulation suggested that 7 -KLCA fits into the \nreceptor's ligand-binding pocket and forms predicted interactions with residues TRP-75 and SER-270 (Figure 7G). \nTo further characterize the functional interaction between 7 -KLCA and TGR5, we employed the selective TGR5 \nantagonist SBI-115. Treatment of M2 macrophages with SBI-115 alone significantly increased CD86 MFI, mirroring the \neffect of 7-KLCA. Co-treatment with 7-KLCA and SBI-115 resulted in a combined effect, leading to a greater elevation \nof CD86 and a more pronounced reduction in CD206 MFI than treatment with SBI-115 alone (Figure 7H). This additive \npharmacological profile indicates that 7-KLCA enhances the functional outcome of TGR5 antagonism, suggesting that \n7-KLCA may function as an inhibitor of TGR5 signaling in macrophages. \n7-KLCA augments macrophage efferocytosis by modulating the PPARγ-GPR132 axis \nTo elucidate the molecular mechanisms underlying 7 -KLCA-mediated modulation of macrophage function, we \nperformed transcriptomic analysis on M2 macrophages treated with or without  10 μM 7 -KLCA. RNA sequencing \nidentified 417 upregulated and 356 downregulated DEGs (Figure 8A) . KEGG enrichment analysis revealed that these \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nDEGs were predominantly associated with osteoclast differentiation, viral protein interaction and efferocytosis, \nalongside other pathways such as TNF signaling, and B cell receptor signaling pathways  (Figure 8B). Within the \nefferocytosis pathway, 19 genes were altered, with a heatmap highlighting the upregulation of  Sphk1 and Stab1 and \nthe downregulation of Pparg (Figure 8C). To validate these changes, we selected 10 efferocytosis -related genes for \nquantitative PCR based on prior literature[27-34]. Expression of Sphk1, C1qa, Pecam1, Stab1, Gpr132, and Dusp4 was \nsignificantly increased, whereas Pparg, Cd36, Mfge8, and Dnmt3a were notably downregulated (Figure 8D).  At the \nprotein level, western blot confirmed that 7‑KLCA treatment suppressed PPARγ and concurrently upregulated GPR132 \n(Figure 8E). Functionally, this molecular reprogramming was associated with enhanced efferocytic capacity, as the \nmedian efferocytic efficiency increased from 4.08% (IQR: 2.33–7.60%) in controls to 8.70% (IQR: 6.62–12.77%) in 7-\nKLCA-treated macrophages (p < 0.05, Mann–Whitney U test) (Figure 8F). \nNotably, PPARγ has been reported to regulate both macrophage differentiation [35] and efferocytosis[36] , and it \ntranscriptionally represses Gpr132—a validated promoter of efferocytosis in immune cells[37]. Our findings that 7-KLCA \ndownregulates PPARγ and upregulates GPR132, alongside other pro-efferocytic genes (e.g., Stab1, C1qa), provide a \nmechanistic basis for the observed enhancement in efferocytic function [30, 38]. Together, our findings suggest that 7 -\nKLCA enhances macrophage efferocytosis through a mechanism that may involve a PPARγ-independent component, \npotentially mediated via the upregulation of GPR132 and other pro -efferocytic genes, thereby reshaping macrophage \nfunctional differentiation in the context of EMS. \n \nDiscussion  \nEndometriosis (EMS) is a complex and heterogeneous disease influenced by hormonal, immune, and microbial \nfactors[39, 40]. Recent advances in EMS research have enabled comprehensive microbiome profiling across multiple \nanatomical sites, revealing spatially distinct microbial dysbiosis patterns in the gut, cervical mucus, and peritoneal fluid \nthat are different from healthy controls[13, 41, 42]. Notably, the GM has emerged as a particularly promising diagnostic and \ntherapeutic target[13]. Despite associations between gut dysbiosis and EMS, the causal pathways through which specific \nspecies or its derivative modulate the disease progression remain undefined.  In this study, we identified Pg as a \nprobiotic and its downstream metabolite 7 -KLCA as a therapeutic metabolite, through microbiota man ipulation and \nreshaping in murine EMS models as well as multi-omics integration.  \nOur findings provide direct evidence linking the gut microbiota  to EMS pathology. Consistent with previous \nobservations[18], metronidazole treatment significantly attenuated EMS phenotypes. Based on metagenomic \nsequencing, we observed increased abundance of  Pg and Akkermansia muciniphila in metronidazole-treated mice, \nboth of which were negatively correlated with disease severity. Indeed, Pg is known for its probiotic potential; it produces \nkey metabolites like acetate and butyrate , contributing to enhanced gut barrier function and improved glucolipid \nmetabolism [24, 43, 44]. Immunomodulatory effects have also been reported, including the inhibition of the NF-κB pathway \nand the promotion of Treg differentiatio n [45, 46]. Although studies report that butyrate (a key short chain fatty acid ) \nimproves EMS pathogenesis—and Akkermansia muciniphila as a major microbial source may contribute to this effect—\nno significant alterations  in butyrate levels  were detected in our unt argeted metabolomics data [47-50]. Our integrated \nmulti-omics analysis revealed that  the therapeutic condition (metronidazole treatment), which enriched for Pg, was \nassociated with a distinct reshaping of BA metabolism. Notably, Pg encodes BSH and 7α-HSDH, which convert TCDCA \nto 7-KLCA—a metabolite found to be functionally involved in disease modulation [24]. The stark contrast between the \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \ntherapeutic effect of metronidazole and the lack of efficacy with broad -spectrum VNA treatment underscores th at not \nall microbiota alterations are beneficial. Together, these findings suggest that metronidazole’s therapeutic effects may \nbe mediated, at least in part, by  specific, Pg-driven changes in  bile acid metabolic outputs.  Beyond Pg, other gut \ncommensals with bile salt hydrolase (BSH) activity—such as various Bacteroides species which deconjugate primary \nbile acids—may likewise participate in shaping the host bile acid pool and its immunomodulatory potential[51]. Whether \nthese BSH-active bacteria contribute to EMS pathogenesis through similar or distinct mechanisms remains an open \nquestion for future study. Furthermore, the immunomodulatory potential of Akkermansia muciniphila warrants further \ninvestigation to elucidate its complementary or synergistic role in EMS improvement.  \nThe gut microbiota's dynamic immunoregulatory network not only governs host immune homeostasis but also \nharbors untapped therapeutic potential [52, 53] . Among the immune cell types influenced by microbial signals, \nmacrophages are central players[54, 55]. These highly plastic cells exist along a continuum from classically activated (M1) \nto alternatively activated (M2) states.  In EMS, M2-polarized macrophages dominate the peritoneal cavity and ectopic \nlesions, facilitating immune suppression, neovascularization, and fibrotic remodeling [6, 9]. Our results demonstrate that \nboth Pg and its metabolite 7-KLCA can reprogram macrophage polarization in favor of an M1 phenotype, as evidenced \nby increased CD86 and decreased CD206 expression. This shift was corroborated by serum cytokine profiles showing \nupregulation of IL-1β, TNF-α, and IL-6, alongside reduced IL-10. Mechanistically, reduced M2 polarization may disrupt \nIL-10- and TGF-β-mediated angiogenesis and suppress neurogenesis, thereby alleviating pelvic pain and limiting lesion \nexpansion[6, 56]. These findings place macrophage plasticity at the core of gut -immune communication in EMS and \nidentify it as a key therapeutic target. \nRecent studies have further demonstrated that gut-derived microbial metabolites can activate intestinal immune cells \nand promote their migration to peripheral tissues, influencing disease outcomes at extraintestinal sites[57, 58]. We show \nthat 7-KLCA treatment of M2 macrophages significantly upregulated GPR132, a receptor that promotes M1 polarization \nand, as a scavenger receptor for apoptotic cells, facilitates chemotaxis to inflammatory lesions [31]. Our data support \nthis paradigm and suggest that macrophages may serve as immunological intermediaries linking microbial metabolism \nto EMS pathology. However, whether intestinal macrophages directly migrate to the peritoneal cavity or whether \ncirculating monocytes adopt a reprogrammed phenotype in response to systemic metabolites remains an open question \nrequiring further investigation. \nIn addition to modulating polarization, 7 -KLCA was found to enhance efferocytosis —a process by which \nmacrophages clear apop totic cells and debris to resolve inflammation [59]. Dysfunctional efferocytosis has been \nimplicated in EMS, where the failure to remove cellular debris contributes to lesion implanta tion and persistence [60]. \nTranscriptomic profiling revealed that 7 -KLCA treatment significantly enriched efferocytosis -related pathways and \naltered the expression of key regulators. Notably, it suppressed Pparg while upregulating pro -efferocytic genes \nincluding Gpr132, Sphk1, Stab1, and C1qa[33, 36, 37, 61] . These coordinated transcriptional changes were directl y \nassociated with a significant gain in efferocytic capacity. Our findings thus suggest that 7 -KLCA promotes immune \nresolution not only by repolarizing macrophages but also by reprogramming a network of efferocytosis -related genes, \nwith PPARγ suppression being a central but not necessarily exclusive event in this process. \nAn intriguing aspect of our findings is that 7 -KLCA promotes a proinflammatory M1 macrophage shift via TGR5, a \nreceptor often linked to anti-inflammatory and metabolic homeostasis. This apparent paradox may be explained by the \ncontext-dependent nature of b ile acid signaling. Our pharmacological data using the TGR5 antagonist SBI -115 are \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nconsistent with a model in which 7-KLCA may act as an inhibitor or biased ligand of TGR5 in macrophages. While this \ninverse correlation invites speculation that TGR5 signali ng may influence PPARγ activity—a key transcriptional driver \nof the M2 phenotype and efferocytosis —the exact nature of this interaction and its contribution to the observed pro -\nefferocytic effect require further genetic validation. \nDespite these insights, our study has limitations. A comprehensive understanding of 7-KLCA's in vivo behavior will \nbe crucial for its translational development. Future studies utilizing labeled tracers are warranted to fully characterize \nits pharmacokinetics, biodistribution, and cellular uptake, which will provide a foundation for optimizing its therapeutic \napplication. Furthermore, while the therapeutic effects of purified 7 -KLCA demonstrate its sufficiency, an important \nfuture direction will be to establish its necessity within  the Pg-mediated response. This could be achieved through \nstudies employing Pg mutants genetically engineered to be deficient in 7-KLCA synthesis, which would further solidify \nthe causal link and open avenues for engineering next-generation probiotics. Moreover, while our analysis focused on \nmacrophage responses, the EMS immune microenvironment includes a broader array of immune cell types whose \ninteractions and functions remain unexplored. Lastly, although we identified TGR5 as a molecular target of 7 -KLCA, \nthe downstream signaling events remain to be fully elucidated. While our data show an association between 7 -KLCA \ntreatment and reduced PPARγ expression, the precise role of TGR5 activation in this process and the extent to which \nthe pro-efferocytic effects are PPARγ-independent require further dissection through genetic and rescue approaches.  \nMoreover, definitive characterization of the mode by which 7 -KLCA engages TGR5 —whether through direct \nantagonism, biased signaling, or allosteric modulation —will require direct assessment of canonical downstream \neffectors in future studies. \nIn summary, our study uncovers a previously unappreciated gut-immune axis wherein Pg mitigates EMS progression \nvia bile acid metabolic remodeling. The microbially derived metabolite 7-KLCA targets TGR5 signaling in macrophages, \ntriggering a transcriptional reprogramming that includes the suppression of PPAR γ. This in turn may alleviate the \nrepression of downstream effectors like GPR132, contributing to their upregulation . This shift promotes a \nproinflammatory M1 -like phenotype and enhances efferocytic capacity, collectively restraining endometriosis \nprogression (Figure 9). Our data further suggest that the enhancement of efferocytosis may involve both PPAR γ-\ndependent and par allel pathways, revealing a new layer of complexity in microbial metabolite -mediated \nimmunomodulation. These findings establish a mechanistic framework through which specific gut microbes and their \nmetabolites can regulate peripheral immune function and modulate chronic gynecologic disease. Collectively, this work \nprovides a strong rationale for microbiota -based therapeutic strategies targeting host -microbiota interactions in \nendometriosis. \n \nMethods  \nEthics statement and study participants \nThis study involving human participants was conducted in accordance with the International Ethical Guidelines for \nResearch Involving Human Subjects and the Declaration of Helsinki. The protocol was reviewed and approved by the \nMedical Ethics Committee of Guangzhou Women and Children ’s Medical Center, Guangzhou Medical University \n(approval number: 023A01). All participants provided written informed consent prior to enrollment, which detailed the \nstudy aims, procedures, and their right to withdraw at any time without penalty. \nWomen with a confirmed pathological diagnosis of EMS were recruited from the Department of Gynecology at \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nGuangzhou Women and Children’s Medical Center, affiliated with Guangzhou Medical University. Age-matched women \nwithout EMS, confirmed by clinical and imaging evaluation, were enrolled as controls. Detailed demographic and clinical \ncharacteristics of all participants are provided in Supplementary Table 1 and Supplementary Table 3. Participants who \nhad received antibiotics or probiotics within one month prior to sample collection were excluded. Additionally, individuals \nwith any known conditions that could potentially affect gut microbiota composition—such as inflammatory bowel disease, \nirritable bowel syndrome, autoimmune disorders, or a history of majo r gastrointestinal surgery, among others —were \nalso excluded. Fecal samples were aliquoted and stored at −80°C until further use.  \nBacteria culture \nThe Pg strain ATCC BAA-1180 was cultured in modified GAM medium under strictly anaerobic conditions (90% N ₂, \n5% H₂, 5% CO₂) at 37 °C. Colony-forming units (CFUs) were determined by performing serial dilutions and plating on \nanaerobic blood agar plates, followed by incubation under the same anaerobic conditions. To collect bacterial \nsupernatants, cultures were cen trifuged sequentially at 3,000 × g and 10,000 × g for 10 min each. The supernatants \nwere filtered through a 0.22-μm pore-size filter to remove residual bacteria and then stored at −80 °C for further analysis. \nThe growth curve of Pg was assessed by measuring the OD600 values at 0, 3, 6, 9, 12, 18, 24, 30, and 36 h using a \nmicroplate reader after treatment with TCDCA and 7 -KLCA at different concentrations (0  μM, 100 μM, 200 μM, and \n500 μM). \nTo assess Pg-dependent metabolism of TCDCA, cultures were set up in medium alone or in medium supplemented \nwith 200 µM TCDCA. A vehicle control containing 200 µM TCDCA in medium without Pg was included to account for \nany non-bacterial changes. After 24 h, supernatants were collected by sequential centrifugation and 0.22-μm filtration, \naliquoted, and stored at −80°C for subsequent analysis. \nAnimal experiments \nAll animal experiments were conducted in accordance with the National Institutes of Health Guide for the Care and \nUse of Laboratory Animals, and protocols were approved by the Animal Care and Use Committee of Ruiye bio -tech \nguangzhou Co., Ltd (RYEth-20250506699). Female BALB/c mice (8 weeks old) were purchased from GemPharmatech \nCo., Ltd. Mice were housed in a specific pathogen -free facility under a 12 h light/dark cycle,  with ad libitum access to \nfood and water. \nFor the syngeneic EMS model, estrous -stage donor mice received subcutaneous injections of estradiol benzoate \n(3 μg/mouse; HY-B1192, MCE, USA) daily for seven consecutive days. Uteri were excised, minced into unifo rm \nfragments in sterile phosphate-buffered saline (PBS), and intraperitoneally inoculated into recipient mice (two recipients \nper donor) using 16G needles. To promote lesions development, recipient mice were administered weekly \nsubcutaneous injections of estradiol benzoate throughout the experimental period. Mice were sacrificed at five weeks \nafter modeling, and ectopic lesions located on the peritoneal wall, pancreas, intestinal mesentery, and peri -ovarian \nadipose tissue were counted, measured with a vernier caliper, and weighed using a microbalance. For the autologous \nmodel, female mice received estradiol benzoate for seven days to synchronize estrous cycles. Mice were then \nanesthetized with tribromoethanol (2.5% [w/v], 250 mg/kg body weight), and the left  uterine horn was excised after \nligation at the utero-tubal and utero-cervical junctions. Four uniform fragments (~2 mm ³ each) were prepared using a \nbiopsy punch and grafted onto the peritoneal wall of the same mouse. Mice were injected with estradiol benz oate \nweekly for five weeks. At endpoint, ectopic tissues on the peritoneal surface were dissected, measured, and weighed. \nFMT was performed following a previously described protocol [62]. Briefly, mice were pretreated with an antibiotic \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \ncocktail consisting of vancomycin (100 mg/kg), neomycin sulfate (200 mg/kg), metronidazole (200 mg/kg), and \nampicillin (200 mg/kg) via oral gavage once daily for six consecutive days. Endometriosis was the n induced by \nsyngeneic transplantation. One day post -modeling, mice were randomly assigned to two groups to receive fecal \nmicrobiota pellets from 5 EMS patients or 5 healthy women, respectively. Fecal samples from donors within each group \nwere pooled to create a single inoculum per group. Fecal suspensions were administered twice per week until the end \nof the experiment. \nFor antibiotic intervention, mice received drinking water supplemented with either  mixtures of vancomycin (0.5 g/L), \nneomycin (1 g/L), ampicillin (1 g/L), or metronidazole (1 g/L), starting six days prior to autologous transplantation and \ncontinuing throughout the study period. Control mice received sterile water. \nAfter EMS induction, mice were administered 200 μL of Pg (5 × 10⁸ CFUs/mL) or saline every other day for five weeks. \nIn parallel experiments, Pg was cultured in modified GAM medium with or without taurochenodeoxycholic acid (TCDCA, \n200 μM). After 24 h, culture supernatants (Pg -conditioned medium [PgCM] or Pg -conditioned medium with TCDCA \n[PgTCM]) were collected and  orally administered to mice daily for five weeks, starting one day post -surgery. Control \nmice received equal volumes of the culture vehicle (GAM medium). \nFor bile acid intervention, 7-KLCA (HY-W018512, MCE, USA) was first dissolved in dimethyl sulfoxide (DMSO) and \nthen diluted in saline. Mice were orally gavaged with 200  μL of 7-KLCA (50 mg/kg/day) or saline alone daily for five \nweeks, followed by EMS induction. \nWrithing behavior was induced by intraperitoneal injection of oxytocin (20 IU/kg; IO1340, Solarbio, China) on day 28 \nafter EMS induction. Mice were observed for 30 min, and the number of writhes was recorded.  \nAt endpoint, mice were deeply anesthetized with tribromoethanol (250 mg/kg, i.p.)  and euthanized by cervical  \ndislocation. Blood samples were collected and centrifuged at 3,000 × g for 15 min at 4°C to isolate serum. Peritoneal \ncells were harvested by injecting 5 mL of ice -cold saline into the cavity, followed by gentle shaking and collection. \nOrgans were either snap-frozen and stored at −80°C or fixed in 4% (v/v) paraformaldehyde and embedded in paraffin \nusing standard histological protocols. \nEvaluation of Adhesions \nImmediately following the laparotomy and prior to any organ dissection for sample collection, macr oscopic intra-\nabdominal adhesions were systematically evaluated by blinded observers. The scoring was performed using a \npreviously reported system[63], which quantifies adhesions based on three parameters: the extent of the adhesion area \n(scored 0-4), the type of adhesion tissue (scored 0-4), and its tenacity (scored 0-3). The scores from these categories \nwere summed to yield a total adhesion score ranging from 0 (no adhesions) to 11 (most severe adhesions). \nShotgun metagenomic analysis \nFresh fecal pellets were collected by placing individual mice in sterile, empty cages without bedding for 30 min. \nGenomic DNA was extracted and purified using the Stool DNA Extraction Mini Kit (DNS362-03, Mabio, China), following \nthe manufacturer’s instructions. DNA quality and concentration were assessed, and qualified samples were used for \nmetagenomic library construction.  Sequencing was performed on the Illumina NovaSeq 6000 platform with 150 bp \npaired-end reads (PE150). Raw reads were quality-controlled using Fastp (v0.23.4) to remove adapter sequences, low-\nquality reads, and ambiguous bases, yielding clean data for downs tream analysis. High -quality reads were de novo \nassembled into contigs (≥500 bp) using MEGAHIT (v1.2.9). Taxonomic profiling of the microbial community was \nperformed using MetaPhlAn 4. \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nMetabolomics analysis \nFor untargeted metabolomics, 50 mg of freeze-dried cecal contents were homogenized in 500 μL of 80% methanol, \nfollowed by thorough vortexing. The mixture was centrifuged, and the resulting supernatants were collected for LC -\nMS/MS analysis. The injection volume was 10  μL. Chromatographic separation was pe rformed in both positive and \nnegative electrospray ionization modes. For the positive mode, mobile phase A consisted of 0.1% formic acid in water, \nand mobile phase B was methanol. For the negative mode, mobile phase A was 5 mM ammonium acetate in water, \nand mobile phase B was methanol. The elution gradient was programmed as follows:   \n- 0.0–1.5 min: 2% B   \n- 1.5–3.0 min: linear increase from 2% to 85% B   \n- 3.0–10.0 min: 85% to 100% B   \n- 10.0–10.1 min: 100% to 2% B   \n- 10.1–11.0 min: 2% B   \n- 11.0–12.0 min: equilibration at 2% B   \nQuality control samples were prepared by pooling equal volumes of all individual samples to monitor analytical \nstability. Data processing and statistical analyses were conducted using MetaboAnalyst 6.0[64]. \nBA targeted metabolomics analysis  \nFor metabolite extraction, 20 mg of fecal sample was mixed with 50 0 μL of cold methanol and 10  μL of internal \nstandard solution. The mixture was homogenized, sonicated, and centrifuged to precipitate proteins. The resulting \nsupernatants were collected and used for targeted metabolomics analysis by high-performance liquid chromatography-\ntandem mass spectrometry (HPLC -MS/MS). HPLC-MS/MS analysis was performed using an UHPLC (Waters Ltd.) \ncoupled to a 5500 QTRAP mass spectrometer (AB SCIEX, USA). Chromatographic separation of BAs was carried out \non an ACQUITY UPLC BEH C18 co lumn (1.7 μm, 2.1 mm × 100 mm, Waters Ltd.). Quantitative data acquisition was \nconducted in MRM mode. Quality control samples, prepared by pooling aliquots of all test samples, were inserted \nthroughout the analytical sequence to assess instrument stability and reproducibility. Data acquisition and quantification \nwere performed using MultiQuant software. \nFlow Cytometry \nFor analysis of macrophage populations , two cell sources were used: peritoneal lavage cells and bone marrow -\nderived macrophages (BMDMs). Cells were first incubated with Zombie NIR™ Fixable Viability Kit (423105, Biolegend, \nUSA) for 20 min in the dark to exclude dead cells. After washing, Fc receptors were blocked by incubation with anti -\nCD16/32 antibody (E -AB-F0997A, Elabscience, China) for 15 min at room temperature. Cell staining was then \nperformed using the following fluorescence -conjugated antibodies: FITC-conjugated anti-CD11b (101206, Biolegend, \nUSA), PE-conjugated anti-F4/80 (111704, Biolegend, USA), APC -conjugated anti-CD86 (105012, Biol egend, USA), \nand BV421 -conjugated anti -CD206 (141717, Biolegend, USA). Following staining, cells were resuspended in Cell \nStaining Buffer (420201, Biolegend, USA) and analyzed on a BD LSRFortessa ™ flow cytometer (BD Biosciences, \nUSA). Data were processed and analyzed using FlowJo software (v.10.10.0, Tree Star Inc., USA). A detailed, step-by-\nstep visualization of the gating strategy has been shown in Supplementary Figure 6. \nEnzyme-linked immunosorbent assays (ELISA) \nCytokine levels in cell culture supernatants and mouse serum were measured using commercial ELISA kits for TNF-\nα (EMC102a.96, Neobioscience Technology Co, Ltd., China), IL -1β (EMC001b.96), IL -6 (EMC004.96), IL -10 \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \n(EMC005.96), and MCP-1 (EMC113.96), following the manufacturer’s instructions. All assays were performed at room \ntemperature using a sandwich-based ELISA format. Absorbance was measured at 450 nm using a microplate reader. \nCytokine concentrations were calculated based on standard curves generated from serial dilutions of known standards. \nHematoxylin and eosin (H&E)  \nEctopic endometrial lesions and mouse colon tissues collected from mice were fixed in 4% paraformaldehyde at 4°C \nfor 48 hours, dehydrated through a graded ethanol series, embedded in paraffin, and sectioned at a thickness of 4 μm. \nTissue sections were stained with hematoxylin and eosin (H&E) following a previously described protocol[65]. The lesion \narea was determined as previously reported [66]. Briefly, for each endometriotic lesion, the longest axis (X) and the \nperpendicular width (Y) were measured using digital pathology software, and the area was calculated as X × Y. For the \npurpose of this study, the resulting area value was then divided by 1,000,000 to facilitate graphical presentation and \nrecorded as the lesion score. \nWestern blot analysis \nProteins were extracted from bone marrow-derived macrophages (BMDMs) using RIPA lysis buffer (FD009, Fudebio, \nHangzhou, China) supplemented with a protease and phosphatase inhibitor cocktail (K1015A, APExBIO, USA). Protein \nconcentrations were determined, and equal amounts of total protein were subjected to SDS -PAGE and transferred to \nPVDF membranes. Western blot was performed as previously described [65]. The membranes were incubated with the \nfollowing primary antibodies: TGR5 (1:3000, ab72608, Abcam, UK), PPAR γ (1:1000, T58124S, Abmart, China), \nGPR132 (1:500, TP72375, Abmart, China) and β-actin ( 1:5000, 66009 -1-Ig, Proteintech). After incubation with \nappropriate HRP -conjugated secondary antibodies, bands were developed using enhanced chemiluminescence \nsubstrate for 1 minute. Signals were visualized using the Alliance Q9 Advanced imaging system (UVITEC, Cambridge, \nUK) and quantified using ImageJ software. Protein expression levels were normalized to β-actin. \nRT-qPCR analysis  \nQuantitative real-time PCR (qPCR) was performed using PowerUp SYBR Green Master Mix (A25742, Thermo Fisher \nScientific, USA) o n a QuantStudio 6 Flex Real -Time PCR System (Thermo Fisher Scientific, USA). Full primer \nsequences for target genes are provided in Supplementary Table 2. Bacterial 16S rDNA and eukaryotic 18S rRNA were \nused as internal reference genes. Relative gene expression was calculated using the 2-ΔΔCt method after normalization \nto the corresponding reference gene. \nCell Culture and Treatment \nHuman immortalized endometriosis cell line (12Z) was obtained from Wuhan Pricella Biotechnology and cultured in \nthe supplier-recommended medium. Cells were maintained at 37°C in 5% CO₂. \nBMDMs were generated from 6–8-week-old female BALB/c mice. Bone marrow was flushed from femurs and tibias \nusing PBS, and single-cell suspensions were prepared by passing the cells through a 70  μm cell strainer. Cells were \nseeded into 6-well plates at a density of 1 × 10 ⁶ cells/mL in RPMI 1640 medium supplemented with 10% fetal bovine \nserum (FBS), 1% penicillin -streptomycin, and 20 ng/mL macrophage colony -stimulating factor (M -CSF; HY-P7085, \nMCE, USA). Medium was replaced every 48 hours, and cells were maintained at 37°C in 5% CO₂. \nOn day 6, cells were polarized under the following conditions for 24 hours:   \n(a) 20 ng/mL M-CSF (control),   \n(b) 20 ng/mL IFN-γ (315-05, Peprotech, USA) plus 100 ng/mL l ipopolysaccharide (LPS; 297-473-0, SIGMA, USA) for \nM1 polarization,   \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \n(c) 20 ng/mL IL-4 (214-14, Peprotech, USA) for M2 polarization.   \nOn day 7, BMDMs were treated with 7 -KLCA at concentrations of 0 μM, 5 μM, 10 μM, or 20 μM for 24 hours. After \ntreatment, culture supernatants were collected and stored at −80 °C for subsequent assays. Cells were washed with \nsterile PBS and processed for downstream experiments. \nBased on our findings, 10 μM was identified as the most effective concentration and was therefore selected for all \nfurther investigations. To evaluate the interaction between 7 -KLCA and TGR5 signaling, a separate experiment was \nperformed. M2 macrophages were pretreated with 5 μM of the TGR5 antagonist SBI-115 (HY-111534, MCE, USA) for \n2 hours[67]. The medium was then replaced, and cells were treated with 10 μM 7-KLCA for an additional 22 hours. Cells \nwere collected for downstream analysis. \nRNA extraction and transcriptome analysis \nTotal RNA was extracted from cultured cells using TRIzol  reagent according to the manufacturer ’s instructions. \nFollowing phase separation with chloroform, the aqueous phase containing RNA was collected after centrifugation \n(12,000 rpm, 15 min, 4°C). RNA was then precipitated with isopropanol, washed with 75% et hanol, and resuspended \nin RNase -free water. Complementary DNA (cDNA) was synthesized using a commercial reverse transcription kit \n(CW2020M, CWBIO, China). PCR amplification products were purified, and library quality was assessed using an \nAgilent 2100 Bioanalyzer. Libraries were sequenced on the Illumina NovaSeq platform. Gene expression levels were \nquantified as fragments per kilobase of transcript per million mapped reads (FPKM). Sequence alignment was \nperformed using Hisat2 (v2.0.5), and read counts were obtained with featureCounts (v1.5.0-p3). Downstream analyses \nwere conducted in R (v4.4.3). Differentially expressed genes (DEGs) were identified using the DESeq2 package \n(v1.46.0)[68], with significance thresholds set at an adjusted p-value < 0.05 and absolute log2 fold change ≥ 1. Kyoto \nEncyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed in R, and visualization of \nenriched pathways was generated using ggplot2 (v3.3.3) and OmicStudioKits (v3.49.0). \nAnalysis of Publicly Available Single-Cell RNA-seq Data (GSE213216) \nPublicly available single -cell RNA-seq data from endometrial samples (accession GSE213216) were downloaded \nfrom the Gene Expression Omnibus (GEO). The dataset includes samples from endometrioma, eutopic endometrium, \nendometriosis, unaffected ovary, and non-endometriosis control tissues.  \nRaw count matrices were processed using the Seurat package (v4.3.0) in R (v4.2.0). Cells were filtered based on \nthe number of detected genes, total counts, and mitochondrial gene percentage. Specifically, cells with fewer than 200 \ndetected genes or with mitochondrial content exceeding 20% were excluded.  \nData were normalized using the LogNormalize method with a scale factor of 10,000. Highly variable features were \nidentified using the FindVariableFeatures function with the \"vst\" selection method. Principal component analysis (PCA) \nwas performed, and the first 30 principal components were used for downstream analysis. UMAP (Uniform Manifold \nApproximation and Projection) dimensionality reduction was performed using the RunUMAP function with default \nparameters (n.neighbors = 30, min.dist = 0.3) to visualize cell populations across different tissue types.  \nImmune cell subsets were annotated based on the expression of canonical marker genes: cDC1 (CLEC9A, CADM1), \ncDC2 (CD1C, CLEC10A), DC3 (LAMP3, CCR7), monocytes (CD14, FCGR3A), macrophages (CD68, CD163), M1 \nmacrophages (IL1B, CCL3), M2 macrophages (CD163, MRC1), and neutrophils (CSF3R, S100A8). Normalized marker \ngene expression was visualized using heatmaps with Z-score transformation, where red indicates high expression and \nblue indicates low expression.  \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nThe expression of bile acid -related genes, including GPBAR1 (TGR5), was examined across different \nhistopathological tissue types and immune cell subsets. Average gene expression levels were calculated for each cell \ntype and tissue condition, and visualized as heatmaps. GPBAR1 expression was specifically examined across all tissue \ntypes (endometrioma, endometrium, endometriosis, unaffected ovary, and non -endometriosis controls) using feature \nplots overlaid on UMAP projections. \nMolecular docking analysis \nThe binding conformations of 7-KLCA with the TGR5 receptor were analyzed using AutoDock4. The crystal structure \nof TGR5 (PDB ID 7BW0) was prepared by removing water molecules and non-essential ligands, and adding counter-\nions as needed. A grid box was defined and adjusted to fully encompass the ligand-binding pocket. The structure of 7-\nKLCA (CID 444262) was retrieved from the PubChem database and prepared for docking using AutoDock4 tools. \nMolecular docking was then performed, and docking scores were used to evaluate the binding affinity between 7-KLCA \nand TGR5. \nCellular thermal shift assay (CETSA) \nHEK 293T cells were transfected with the TGR5 -Flag plasmids using Lipof ectamine 3000 (L3000001, Thermo \nFishe, USA). Following transfection, the cells were lysed with NP -40 buffer (HY-Y1884, MCE, USA) and subjected to \nthree freeze-thaw cycles in liquid nitrogen. The lysates were then centrifuged at 15,000 × g for 15 min at 4°C . The \nresulting supernatants were aliquoted into eight PCR tubes and incubated with 10 μM 7-KLCA or vehicle (DMSO) for 2 \nhours at room temperature. Each aliquot was subsequently heated for 3 min at a specific temperature in a gradient \n(35°C, 40°C, 45°C, 50°C, 55°C, 60°C, 70°C, and 80°C), followed by centrifugation to collect the supernatant. Protein \nstability was assessed by western blot according to standard procedures. \nSurface plasmon resonance (SPR) analysis \nBinding kinetics of  7-KLCA to immobilized TGR5  protein were measured at 25°C on a B IAcore 1K (Cytiva) using \nCM5 chips. TGR5 in 10 mM sodium acetate (pH 5.0) was covalently immobilized on EDC/NHS-activated surfaces (200 \nmM EDC/50 mM NHS; 10 μL/min, 7 min). Reference flow cells were identically prepared but immobilized with PBS (pH \n5.0). All surfaces were blocked with 1 M ethanolamine (10 μL/min, 7 min). \nSerially diluted 7 -KLCA in PBS was injected (10 μL/min, 150 s association) followed by regeneration with 10 mM \nglycine-HCl (pH 2.0; 10 μL/min, 5 min). Data collected via Biacore Insight (v2.0) were reference-subtracted and globally \nfitted to a 1:1 Langmuir model using B IAcore 1K Evaluation Software to determine K D, Ka, and Kd. Figures were \nprepared in Origin 7 (v7.0552). \nEfferocytosis assay \nAdherent macrophages were labeled with DiI cell -labeling solution (C1991S, Beyotime, China) for 15 min at 37 °C, \nfollowed by nuclear counterstaining with Hoechst 33342 (C1028, Beyotime, China). In parallel, 12Z cells were induced \nto undergo apoptosis by ul traviolet irradiation for 15 min, followed by a 6 -hour incubation at 37 °C in a humidified \natmosphere containing 5% CO₂ to allow apoptotic progression. Early apoptotic cells (ACs) were identified as annexin \nV-positive populations by flow cytometry. Prior t o co-culture, ACs were resuspended in complete culture medium and \nadded to macrophages at a 5:1 AC-to-macrophage ratio. After 3 hours of co-culture, non-engulfed ACs were removed \nby two gentle washes with PBS. Internalized apoptotic cells were then detected by TUNEL staining (C1086, Beyotime, \nChina) for 1 hour at 37 °C. The experiment was independently repeated three times. For each replicate, three random \nmicroscopic fields per condition were captured. Fluorescence images were acquired using a Leica TCS SP 8 \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nfluorescence microscope.  Efferocytic efficiency was calculated as the fraction of macrophages with at least one \nefferosome. \nStatistical analysis \nStatistical analyses were performed using GraphPad Prism software (v10.3.1). Data normality was assessed using the \nShapiro-Wilk test. For normally distributed data, two -group comparisons were performed using unpaired Student ’s t-\ntest. One -way and two -way analyses of variance (ANOVA) followed by Bonferroni ’s post hoc test were used for \ncomparisons among multiple g roups. For non-normally distributed data, the Mann -Whitney U test was used for two -\ngroup comparisons, while the Kruskal -Wallis test followed by Dunn ’s post hoc test was used for multiple group \ncomparisons. A p-value of < 0.05 was considered statistically significant. \n \nData Availability: The data that support the findings of this study are openly available in National Microbiology Data \nCenter (NMDC) at https://nmdc.cn/resource/genomics/project/detail/NMDC10019913, reference number \nNMDC20394524. \n \nCode Availability: Not applicable. \n \nAcknowledgements: This work was supported by the National Natural Science Foundation of China  under Grant \n82072859; Guangdong Basic and Applied Basic Research Foundation  under Grant  2022A1515220127; China \nPostdoctoral Science Foundation under Grant 2024M750643. and Guangzhou Health Science and Technology Youth \nTalent Cultivation Project under Grant 20261A031007. \n \nAuthor Contributions: \nYC, and ZT designed this study. YC, ZT, and YQ wrote the manuscript. YC, ZT, YQ, FP, YZ, LG and YS performed \nexperiments. YC, ZT, KG and JW analyzed the data. All authors helped revise the manuscript. YC, ZT and KS acquired \nfunding for the project. All authors contributed to the study and approved the final version of the manuscript. \n \nCompeting Interests: The authors declare no competing financial or non-financial interests. \n \n  \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nReferences: \n[1] Taylor HS, Kotlyar AM, Flores VA. Endometriosis is a chronic systemic disease: clinical challenges and novel \ninnovations. Lancet, 2021, 397(10276): 839-852. \n[2] Wu N, Han Z, Lv W, Huang Y, Zhu J, Deng J, Xue Q. Reprogramming peritoneal macrophages with outer membrane \nvesicle-coated PLGA nanoparticles for endometriosis prevention. Biomaterials, 2025, 319: 123198. \n[3] Capobianco A, Monno A, Cottone L, Venneri MA, Biziato D, Di Puppo F, Ferrari S, De Palma M, Manfredi AA, \nRovere-Querini P. 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After one week of concurrent EE 2 injections and antibiotic cocktail treatment, \nmice received twice -weekly FMT either from EMS patients or from healthy controls with weekly EE2 injections.  (B) \nBody weight changes (n = 6/group). (C) Number of writhing events (n = 6/group). (D) Adhesion scores (n = 6/group). \n(E) Representative images of intraperitoneal endometriotic lesions (white circles). (F) Lesion number per mouse (n = \n6/group). (G) Representative images of ectopic lesions stained with H&E (magnification, 40×; scale bar = 500 μm). (H) \nLesion histopathology scores  (n = 6/group). (I) Representative images of intesti nal tissues stained with H&E. \n(magnification, 200×; scale bar = 200 μm). (J) The MFI of CD86 and CD206 on peritoneal lavage-derived macrophages \nwas measured by flow cytometry (n = 6/ group). Results were expressed as mean ± SEM. For panel B, two-way ANOVA \nfollowed by Bonferroni’s multiple-comparison test was performed for statistical analysis ; for C, F, H, and J, data was \nanalyzed using a two-tailed t-test; for panel D, the two-sided Mann-Whitney U test was performed for statistical analysis. \n*p < 0.05, **p < 0.01, ***p < 0.001. ABX, antibiotic cocktail treatment; FMT, fecal microbiota transplantation; NC, normal \ncontrol; EMS, endometriosis; ns, not significant; EE 2: estradiol benzoate; H&E, Hematoxylin & Eosin ; MFI: mean \nfluorescence intensity. \n \nFigure 2 Antibiotic therapy with metronidazole slows EMS progression in mice. (A) Schematic illustration of the \nanimal experiments. Mice were injected with EE2 for 7 days, followed by weekly injections. The mice were then randomly \nassigned to three groups. Except for the control group, which received sterile water, the other groups received VNA or \nM drinking water respectively. (B) Body weight changes (n = 6/group). (C) The number of writhing (n = 6/group). (D) \nAdhesion scores (n = 6/group). (E) Ectopic endometriotic lesion representative images (scale bar = 5 mm). (F) The \naverage weight of lesions (n = 6/group). (G) The average volume of lesions (n = 6/group). (H) H&E-stained ectopic \nlesions (magnification, 30×; scale bar = 500 μm). (I) Lesion score (n = 6/group). (J) The MFI of CD86 and CD206 was \nmeasured by flow cytometry in macrophages derived from peritoneal lavage (n = 6/group). Data was expressed as the \nmean ± SEM. In panel B, data was determined using the two-way ANOVA followed by Bonferroni’s post-hoc test; for C \nand D, data was analy zed using Kruskal -Wallis test followed by Dunn ’s test; for F, G, I, and J, the one-way ANOVA \nfollowed by Bonferroni’s post-hoc test was used for statistical analysis. *p < 0.05, **p < 0.01, ***p < 0.001. EE2, estradiol \nbenzoate; EMS: endometriosis; VNA, vancomycin, neomycin and ampicillin; M, metronidazole; ns: not significant; MFI, \nmean fluorescence intensity. \n \nFigure 3 Metronidazole induced GM structural changes in EMS mice. (A) Principal coordinate analysis  of β-\ndiversity (based on the Bray-Curtis matrix) revealed significant separation between the M and VNA groups in species-\nlevel microbial community structure (M group n = 5, VNA group n = 6). (B) Overall microbial composition at the species \nlevel. (C) Linear discriminant analysis effect size (LEfSe) plots to identify the bacterial strains that characterize M versus \nVNA group. (D) Comparison of relative abundance of microbial species between M and VNA groups ( M group n = 5, \nVNA group n = 6 ). Results were expressed as median and IQR.  All plotted relative abundance values are non -zero \nmeasurements. (E) Correlation analysis between the relative abundance of microbial species and the observed \nphenotypes of mice. (F) Comparative analysis of Pg relative abundance across Blank, VNA, and M groups (n = 6/group). \n(G) The relative abundance of Pg between FMT_NC and FMT_EMS groups (n = 6/group). (H) The relative abundance \nof Pg between Non-EMS controls (n = 12) and EMS patients (n = 16). Data in panels F and G was presented as mean \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \n± SEM. In panels D and G, data was analyzed using the two-tailed t-test. In panel E, Spearman’s correlation test was \nused for statistical analysis. The differences in panel F between groups were compared using one-way ANOVA followed \nby Bonferroni’s post-hoc test for multiple comparisons. Data in panel H was presented as median  and interquartile \nrange (IQR) and was analyzed using Mann–Whitney U test. *p < 0.05, **p < 0.01, ***p < 0.001. FMT, fecal microbiota \ntransplantation; NC, normal control; EMS, endometriosis; VNA, vancomycin, neomycin and ampicillin; M, metronidazole.  \n  \nFigure 4 Pg attenuates EMS progression. (A) The schematic diagram of the animal experimental design. The mice \nwere administered EE2 via daily injections for 7 days, followed by weekly injections thereafter. They were then divided \ninto two groups and received NS or Pg respectively. (B) Body weight changes (n = 6/group). (C) The number of writhing \n(n = 6/group). (D) Adhesion scores (n = 6/group). (E) Ectopic endometriotic lesion representative images (scale bar = \n5 mm ). (F) The average weight of lesions (n = 6/group). (G) The average volume of lesions (n = 6/group). (H) \nRepresentative images of ectopic lesions from two groups stained with H&E (magnification, 30×; scale bar = 500 μm). \n(I) Lesion score (n = 6/group). (J) Peritoneal lavage-derived macrophages were analyzed for CD86 and CD206 MFI by \nflow cytometry (n = 6/group). (K) The serum levels of IL-10, TNF-α, IL-1β, and IL-6 were measured by ELISA (n = \n6/group). Results were expressed as mean ± SEM. Two-way-ANOVA with Bonferroni post-hoc test was performed for \ndata analysis in panel B . The two-sided Mann-Whitney U test was used to analyze TNF-α concentrations and CD86 \nMFI levels. All additional data was analyzed with a two-tailed t-test. *p < 0.05, **p < 0.01, ***p < 0.001. EE2, estradiol \nbenzoate; Pg, Parabacteroides goldsteinii ; NS, normal saline; ns: not significant; EMS: endometriosis; MFI, mean \nfluorescence intensity. \n \nFigure 5 Metronidazole modulates bile acid metabolism. (A) Principal component analysis (PCA) score plot of cecal \nmetabolomic (M group n = 5, VNA group n = 6 ). (B) Volcano plot illustrates the significant differences in metabolites \nenriched between M and VNA group. Each point represents one metabolite. (C) The top 10 most significantly enriched \nfunctional terms were identified based on p-value and enrichment ratio. (D) Peak intensity of the BAs (M group n = 5, \nVNA group n = 6). (E) Correlation analysis between the BAs and the observed phenotypes of mice. (F) Correlations \nbetween the relative abundance of microbial species and bile acids. (G) Targeted BA concentration in feces of VNA \nand M groups (n = 6/group). Concentrations are in nmol/g. Data was presented as median and IQR, analyzed by the \ntwo-tailed t-tests. In panels E and F, Spearman’s correlation test was used for statistical analysis. *p < 0.05, **p < 0.01, \n***p < 0.001. VNA, vancomycin, neomycin and ampicillin; M, metronidazole; ND, not detected. \n \nFigure 6 7 -KLCA supplementation alleviates EMS progression.  A) Schematic representation of the animal \nexperiment. Mice were subjected to 7-day daily EE2 injections followed by weekly maintenance, then stratified into two \ngroups receiving either NS or 7-KLCA via oral gavage every day for five weeks. (B) Body weight changes (n = 6/group), \nas determined using a two-way ANOVA followed by Bonferroni’s post-hoc test. (C) The number of writhing (n = 6/group). \n(D) Adhesion scores (n = 6/group). (E) Ectopic endometriotic lesion representative images (scale bar = 5 mm). (F) The \naverage weight of lesions (n = 6/group). (G) The average volume of lesions (n = 6/group). (H) Representative images \nof ectopic lesions from two groups stained with H&E (magnification, 30× ; scale bar = 500 μm). (I) Lesion score (n = \n6/group). (J) The MFI of CD86 and CD206 on peritoneal lavage-derived macrophages was measured by flow cytometry \n(n = 6/group). (K) The serum levels of IL-10, TNF-α, IL-1β, and IL-6 were detected using ELISA (n = 6/group). Results \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nwere expressed as mean ± SEM and analyzed using the two-tailed t-test. *p < 0.05, ** p < 0.01, *** p < 0.001. EE 2, \nestradiol benzoate; 7-KLCA, 7-ketolithocholic acid; NS, normal saline; ns: not significant; EMS: endometriosis; MFI, \nmean fluorescence intensity. \n \nFigure 7 TGR5 promotes macrophage polarization from the M2 to M1 phenotype. (A) The MCP-1, IL-1β, TNF-α, \nIL-6, and IL-10 levels in M2 culture medium supernatant under 7 -KLCA treatment at various concentrations (0  μM, 5 \nμM, 10 μM, and 20 μM) were measured by ELISA (n = 3/group). (B) Bone marrow-derived macrophages (BMDMs) \nwere analyzed for the MFI of CD86 and CD206 in their M0, M1, and M2 phenotypes after treatment with 10 μM 7-KLCA \nfor 24 hours (n = 3/group). (C) Relative expression of bile acid -related receptors in M0, M1, and M2 macrophages  by \nRT-qPCR. The data was presented as mean ± SEM.  (D) The heat map shows the average expression of bile acid -\nrelated genes across different histopathological types and various immune cell types based on data set (GSE213216) \nanalysis. (E) Comparative western blot analysis of TGR5 degradation in M2 macrophage lysates treated with or without \n10 µM 7-KLCA. (F) SPR analysis for TGR5 protein with different doses of 7 -KLCA. (G) Molecular docking analysis of \nTGR5 and 7-KLCA, and the potential interaction binding site.  TGR5 (light blue) and the ligand 7 -KLCA (pink) bind via \nkey amino acid residues TRP-75 and SER-270 (red), with their interaction distances measured at 2.6 and 2.9 Å and a \ncalculated binding energy of -9.1 kcal/mol. (H) M2 macrophages were treated as indicated: Control (DMSO), SBI -115 \n(5 µM), or SBI -115 plus 7-KLCA (10 µM). Flow cytome tric analysis of CD86 and CD206 expression (MFI) is shown. \nData shown as median and IQR unless otherwise indicated. The differences between groups were compared using \nANOVA followed by Bonferroni’s post-hoc test for  multiple comparisons in panels A, B, C and H (except for the Rel. \nexpression of Fxr, which was analyzed by Kruskal-Wallis test followed by Dunn ’s test). *p < 0.05, ** p < 0.01, *** p < \n0.001. 7-KLCA, 7-ketolithocholic acid; TGR5, G protein-coupled bile acid receptor 1. \n \nFigure 8 7-KLCA promotes macrophage efferocytosis by reprogramming a pro -efferocytic gene network. (A) \nNumber of DEGs in M2+7-KLCA compared to M2, with padj < 0.05 (n = 3 /group). (B) Top 5 KEGG enrichment analysis \nregarding the DEGs of M2 vs. M2+7KLCA-10 (padj < 0.05). (C) DEGs of efferocytosis pathway between M2 and M2+7-\nKLCA (padj < 0.05, with padj < 0.01 highlighted in red).  (D) Relative expression of efferocytosis related DEGs in each \ngroup. Data w as expressed as mean ± SEM . (E) Representative western blot images and quantitative analysis of \nPPARγ and GPR132 levels in each group. Data shown as median and IQR. (F) Efferocytosis assay in M2 macrophages \ntreated with or without 7 -KLCA. (Left) Representative fluorescence microscopy images from three independent \nexperiments, demonstrating efferocytosis activity in BMDMs treated with or without 7-KLCA (magnification, 630×; scale \nbar = 10 μm). For each experiment, three random fields per condition were captured. Dil-labeled BMDM were incubated \nwith ACs labeled by TUNEL for 3 hours. (Right) Quantification of efferocytic efficiency, presented as the percentage of \nmacrophages that engulfed one or more ACs. The median efferocytosis rate was 4.08% (IQR: 2.33–7.60%) in the \ncontrol group and 8. 70% (IQR: 6.62–12.77%) in the 7 -KLCA-treated group (Mann –Whitney U test).  Results were \nanalyzed using the two-tailed t-test in panel D and E (except for the Rel. expression of Gpr132, which was analyzed by \nMann-Whitney U test). *p < 0.05, **p < 0.01, ***p < 0.001. ACs, apoptosis cells. \n \nFigure 9 Schematic overview of the gut -immune axis in endometriosis suppression.  Pg remodels bile acid \nmetabolism to generate the microbially derived metabolite 7 -KLCA. This metabolite targets macrophage TGR5 \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n \n \nsignaling, suppresses PPAR γ expression, and thereby upregulates GPR132, thus promoting M1 polarization while \nenhancing efferocytosis. These immunomodulatory actions collectively mitigate endometriosis progression, \nestablishing a mechanistic framework for microbiota-based therapeutic strategies. AC, apoptosis cell. \n \n\nARTICLE IN PRESS\nARTICLE IN PRESS\n\n\nARTICLE IN PRESS\nARTICLE IN PRESS\n\n\nARTICLE IN PRESS\nARTICLE IN PRESS\n\n\nARTICLE IN PRESS\nARTICLE IN PRESS\n\n\nARTICLE IN PRESS\nARTICLE IN PRESS\n\n\nARTICLE IN PRESS\nARTICLE IN PRESS\n\n\nARTICLE IN PRESS\nARTICLE IN PRESS\n\n\nARTICLE IN PRESS\nARTICLE IN PRESS\n\n\nARTICLE IN PRESS\nARTICLE IN PRESS","source_license":"CC0","license_restricted":false}