Sialic acid exacerbates polycystic ovary syndrome in mice by modulating gut microbiota-mediated bile acid metabolism and FXR activation

Domain: biology
Published: 2026-03-31
Editorial outcome: major_revision

Abstract
Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder in women. Accumulating evidence indicates that gut dysbiosis and metabolic disturbances are associated with the pathogenesis of PCOS. However, the mechanisms by which metabolic alterations influence gut homeostasis and contribute to PCOS progression remain poorly understood. Here, we show that N-acetylneuraminic acid (Neu5Ac) exacerbates dehydroepiandrosterone (DHEA)-induced PCOS phenotypes in female mice in a gut microbiota-dependent manner. Specifically, Neu5Ac promotes the expansion of the gut Ligilactobacillus salivarius (L. sa) with bile salt hydrolase (BSH) activity. Administration of L. sa to DHEA-treated mice worsens PCOS symptoms by reducing levels of the conjugated bile acid tauroursodeoxycholic acid (TUDCA) via BSH activity. Reduced TUDCA enhances intestinal farnesoid X receptor (FXR) activation, leading to suppression of IL-22 production. Mechanistically, IL-22 attenuates DHEA-induced ovarian ferroptosis by activating the STAT3 signaling pathway. These findings reveal that sialic acid-mediated bile acid–FXR–IL-22 signaling contributes to PCOS pathogenesis, highlighting a potential therapeutic strategy for PCOS intervention.

Introduction
Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder characterized by ovarian dysfunction and insulin resistance, adversely affecting ovarian health and female reproductive function 1,2. In PCOS, the ovary exhibits increased inflammation, oxidative stress, and cell death, including ferroptosis 3-5. Deficiency of glutathione peroxidase 4 (GPX4), a key regulator of redox homeostasis during ferroptosis, exacerbates ferroptosis and contributes to endometrial epithelial fibrosis in PCOS 5. Additionally, the gut microbiota has been implicated in PCOS pathogenesis 6-8. For instance, patients with PCOS exhibit significant gut dysbiosis, particularly elevated levels of fecal Bacteroides vulgatus (B. vulgatus), and administration of B. vulgatus induces PCOS-like symptoms in mice 1,7. Modulation of the gut microbiota through inulin and tempol treatment alleviates PCOS and associated metabolic disturbances 9,10. However, the roles of specific microbial species in PCOS pathogenesis remains poorly understood.

Gut microbiota-derived metabolites are key mediators that regulate the crosstalk between the intestinal microbiota and the host. For example, patients with PCOS exhibit altered bile acid profiles, particularly increased levels of non-conjugated bile acids and reduced levels of conjugated bile acids such as glycodeoxycholic acid (GDCA) and tauroursodeoxycholic acid (TUDCA) 1. Treatment of mice with GDCA and TUDCA ameliorates PCOS by increasing interleukin-22 (IL-22) levels 1, which may be attributed to enhanced IL-22 production and subsequent activation of signal transducer and activator of transcription 3 (STAT3) 1,11. Conjugated bile acids can be converted into non-conjugated forms by gut microbiota through bile salt hydrolase (BSH) activity 12, and bacterial genera enriched in PCOS patients—such as Bacteroides and Lactobacillus—exhibit high BSH expression 13,14. Notably, conjugated bile acids, including TUDCA, and GDCA, typically act as antagonists of farnesoid X receptor (FXR) 12,14-16. Enhanced intestinal FXR activation promotes the development of metabolic disorders through multiple mechanisms, such as promoting ceramide synthesis 17. Additionally, gut-specific FXR activation reduces IL-22 levels by promoting intestinal epithelial ferroptosis and lipid peroxide accumulation 18. Inhibition of BSH activity or intestinal FXR signaling exerts beneficial effects against metabolic syndrome and pathological cell death 18,19.

Although gut microbiota-derived metabolites directly influence metabolic health and the development of PCOS—such as agmatine produced by B. vulgatus, which promotes PCOS via FXR activation 7, and AT-C1, a metabolite derived from Aspergillus tubingensis, which induces PCOS by suppressing IL-22 production 8—the reciprocal impact of microbial metabolism on gut homeostasis remains poorly understood. For example, alterations in the gut microbiota and the presence of gut inflammation increase the release of free N-acetylneuraminic acid (Neu5Ac, also known as sialic acid), a 9-carbon monosaccharide located on the outer layer of the intestinal mucosa 20. This release exacerbates gut dysbiosis, promotes intestinal inflammation, and contributes to extraintestinal diseases such as mastitis 20-23. Bacteroides efficiently produces free sialic acid via its sialidase enzyme but lacks the capacity to utilize sialic acid for growth 20. In contrast, commensal Lactobacillus and opportunistic pathobionts such as Escherichia/Shigella can exploit sialic acid as a carbon source to support their proliferation in the gut, thereby influencing disease outcomes 21. However, it remains unclear whether Bacteroides-derived sialic acid facilitates the expansion of Lactobacillus and Escherichia/Shigella and thereby promotes the development of PCOS.

In this study, we found that patients with PCOS exhibited elevated fecal Neu5Ac levels, which exacerbated PCOS in a gut microbiota-dependent manner. Specifically, Neu5Ac treatment promoted the expansion of the gut Ligilactobacillus salivarius (L. sa) and increased BSH activity, thereby reducing levels of the conjugated bile acid TUDCA, enhancing intestinal FXR activation, and suppressing IL-22 release. This cascade ultimately aggravates PCOS by promoting ovarian ferroptosis through modulation of STAT3 signaling. These findings indicate that sialic acid promotes gut dysbiosis and FXR activation, thereby exacerbating PCOS outcomes.

Results
1. Neu5Ac exacerbate DHEA-induced PCOS in mice in a gut microbiota-dependent manner.
To investigate metabolic alterations associated with PCOS, fecal samples were collected from 16 PCOS patients (P) and 16 controls (C) for untargeted metabolomics analysis (clinical characteristics are provided in Supplementary Table 1). Principal component analysis (PCA) revealed a clear separation between the metabolic profiles of PCOS patients and control individuals (Fig. 1A). This distinction was further confirmed by partial least squares discriminant analysis (PLS-DA) score plots (Fig. S1A). Additionally, volcano plots illustrated the global distribution of differentially expressed metabolites (Fig. 1B). Compared with the control group, 332 upregulated and 274 downregulated metabolites were identified in PCOS patients (Fig. 1B and Supplementary Data 1). Notably, among the 20 most abundant metabolites, Neu5Ac was significantly increased in the P group and exhibited the lowest p-value (Fig. 1C). We further confirmed that PCOS patients had higher fecal Neu5Ac levels than those in the C group (Fig. 1D). This finding was replicated in an independent cohort consisting of 19 PCOS patients and 14 control individuals (Fig. 1E and Supplementary Table 2). However, no significant difference in Neu5Ac levels was observed in serum between PCOS patients and controls (Fig. S1B). Moreover, fecal Neu5Ac, but not serum levels, showed a positive correlation with PCOS severity and insulin resistance (Fig. 1F).

Similarly, mice subjected to DHEA treatment exhibited increased fecal Neu5Ac levels compared to the control group (Fig. 1G). Neu5Ac can be produced by both microbial and host cells, and elevated free Neu5Ac has been closely linked to inflammation and disease progression 21,22. We then investigated whether exogenous Neu5Ac administration influences DHEA-induced PCOS in mice (Fig. 1H). The results showed that Neu5Ac administration exacerbated insulin resistance induced by DHEA, as assessed by glucose tolerance tests (GTTs) and insulin tolerance tests (ITTs) (Fig. 1I and S1C). Moreover, Neu5Ac treatment aggravated DHEA-induced disruptions in the estrous cycle (Fig. 1J and S1D). Histological analysis demonstrated that DHEA-treated mice displayed ovarian morphological impairments, characterized by an increased number of cyst-like follicles and a reduced number of corpora lutea compared to controls; these abnormalities were further exacerbated by Neu5Ac administration (Fig. 1K, S1E and F). Consistently, Neu5Ac treatment enhanced the DHEA-induced increases in serum hormone levels, including testosterone and luteinizing hormone (LH) (Fig. S1G).

Since sialic acids, including Neu5Ac, have been reported to modulate the gut microbiota and promote inflammatory responses 21,22, we further investigated whether the effects of Neu5Ac on PCOS are mediated by the gut microbiota. First, mice were pretreated with antibiotics (ABX) to deplete commensal microbes prior to administration of Neu5Ac and DHEA (Fig. S1H). The results showed that ABX treatment abolished the exacerbating effect of Neu5Ac on DHEA-induced insulin resistance (Fig. S1I and J). ABX administration also reversed the aggravation of Neu5Ac on DHEA-induced disruptions in the estrous cycle (Fig. S1K and L). Moreover, depletion of the gut microbiota eliminated the worsening effects of Neu5Ac on ovarian histological alterations under DHEA treatment (Fig. S1M), as well as on elevated serum testosterone and LH levels (Fig. S1N). To confirm these findings, fecal microbiota transplantation (FMT) was performed using donor mice treated with Neu5Ac (N-FMT) or vehicle control (C-FMT) (Fig. 1L). We found that mice receiving N-FMT exhibited lower insulin sensitivity than those receiving C-FMT following DHEA treatment (Fig. 1M and S2A). N-FMT also exacerbated DHEA-induced estrous cycle disruptions (Fig. 1N and S2B). Additionally, mice receiving N-FMT displayed more severe ovarian histological damage compared to those receiving C-FMT (Fig. 1O and P), along with higher serum testosterone and LH levels (Fig. S2C). Altogether, these results demonstrate that Neu5Ac exacerbates DHEA-induced PCOS in a gut microbiota-dependent manner.

2. Neu5Ac exacerbates DHEA-induced PCOS by promoting Ligilactobacillus expansion.
We next investigated how Neu5Ac treatment alters the gut microbiota in the context of DHEA-induced PCOS. The results showed that Neu5Ac treatment induced only minor changes in the alpha diversity of the gut microbiota (Fig. 2A and S2D). However, Neu5Ac significantly altered gut microbial community structure (Fig. 2B). At the phylum level, increased abundances of Bacillota and Campylobacterota, and reduced abundance of Bacteroidota were observed in DHEA-treated mice compared to the control group (Fig. 2C). Notably, these alterations were further enhanced by Neu5Ac treatment (Fig. 2C). At the genus level, Neu5Ac promoted the expansion of Ligilactobacillus induced by DHEA (Fig. 2D). Similarly, in recipient mice, no significant differences were detected in alpha diversity indices between N-FMT and C-FMT groups (Fig. S2E). Consistently, N-FMT significantly altered gut microbial structures compared to C-FMT (Fig. 2E). At the phylum level, N-FMT increased Bacillota and Campylobacterota abundances and decreased Bacteroidota abundance relative to C-FMT (Fig. S2F). At the genus level, higher fecal abundances of Ligilactobacillus and Helicobacter were observed in the N-FMT group than the C-FMT group (Fig. 2F). LEfSe analysis further revealed that Ligilactobacillus was enriched in the DHEA group, with greater enrichment following Neu5Ac or N-FMT treatment (Fig. 2G–J), and Neu5Ac treatment alone also increased fecal Ligilactobacillus abundance compared to control mice (Fig. S2G).

We then sought to explore whether the enhanced expansion of Ligilactobacillus contributes to Neu5Ac-mediated exacerbation of DHEA-induced PCOS in mice. First, mice were treated with ampicillin (Amp) or vancomycin (Van) under DHEA and Neu5Ac co-treatment conditions (Fig. 3A), given that Ligilactobacillus is sensitive to ampicillin but resistant to vancomycin 11. Interestingly, Amp treatment, but not Van, alleviated insulin resistance compared to Neu5Ac- and DHEA-treated mice (Fig. 3B and S3A). Improved estrous cyclicity was also observed in Amp-treated mice, but not in Van-treated mice, compared to those receiving both Neu5Ac and DHEA (Fig. 3C and S3B). Moreover, Amp treatment attenuated Neu5Ac-aggravated ovarian damage and serum hormone dysregulation caused by DHEA (Fig. 3D, S3C and D). We next quantified different Ligilactobacillus species using qPCR and found that Ligilactobacillus salivarius (L. sa) was elevated in Neu5Ac+DHEA-exposed mice and N-FMT-treated mice (Fig. 3E and F). Moreover, L. reuteri and L. rhamnosus appeared to be increased in Neu5Ac+DHEA- and N-FMT-treated mice (Fig. S3E and F). However, only L. sa abundance was significantly increased in PCOS patients compared with the control group (Fig. 3G and S3G). Importantly, fecal Neu5Ac levels were positively correlated with L. sa abundance in PCOS patients (Fig. 3H). We then administered L. sa to mice with DHEA-induced PCOS (Fig. 3I). As expected, L. sa treatment exacerbated DHEA-induced insulin resistance and estrous cycle disruption (Fig. 3J–L and S3H). Additionally, L. sa treatment worsened DHEA-induced ovarian injury and increases in serum testosterone and LH levels (Fig. 3M, N and S3I). Since Neu5Ac can promote the growth of both commensal and opportunistic bacteria 21, we cultured L. sa with Neu5Ac and found that Neu5Ac significantly enhanced L. sa growth compared to glucose (Fig. 3O). Collectively, these findings demonstrate that Neu5Ac exacerbates DHEA-induced PCOS by promoting Ligilactobacillus expansion.

3. Ligilactobacillus promotes PCOS by altering bile acid profiles via bile salt hydrolase.
Bile acid metabolism is closely associated with the pathogenesis of PCOS 1, and Ligilactobacillus is a key modulator of host bile acid profiles through BSH activity 13,19. We therefore investigated whether bile acid metabolism contributes to Neu5Ac- and L. sa-mediated exacerbation of PCOS. The results showed that DHEA treatment increased levels of unconjugated bile acids and decreased conjugated bile acid levels compared to control mice, and both Neu5Ac and L. sa treatments amplified these effects (Fig. 4A, B, S4A and B). Specifically, Neu5Ac and L. sa appear to facilitate the DHEA-induced reduction in taurochenodeoxycholic acid (TCDCA) and TUDCA (Fig. 4A, B, S4A and B). In PCOS patients, reduced levels of conjugated bile acids and TUDCA were also detected (Fig. 4C-D). Similarly, DHEA-treated mice exhibited elevated fecal BSH activity, which was further increased by Neu5Ac and L. sa treatments (Fig. 4E and F). Patients with PCOS also exhibited increased BSH activity (Fig. 4G). Moreover, TUDCA levels were negatively correlated with fecal Neu5Ac and L. sa abundance in PCOS patients (Fig. 4H).

To examine the role of conjugated bile acids in Neu5Ac-mediated PCOS exacerbation, we supplemented mice with TUDCA (Fig. 4I). TUDCA administration alleviated insulin resistance induced by combined Neu5Ac and DHEA treatment (Fig. 4J and S4C). Mice receiving TUDCA also showed improved estrous cyclicity compared to those treated with Neu5Ac and DHEA alone (Fig. S4D and E). Moreover, TUDCA treatment attenuated ovarian damage and suppressed the rise in serum hormone levels caused by Neu5Ac and DHEA co-treatment (Fig. 4K, L and S4F). To confirm the involvement of BSH in mediating unconjugated bile acid production and PCOS exacerbation under Neu5Ac exposure, mice were treated with the BSH inhibitor caffeic acid phenethyl ester (CAPE) 24 (Fig. 4M). Notably, CAPE administration alleviated insulin resistance in Neu5Ac- and DHEA-co-treated mice (Fig. 4N and S4G). Furthermore, CAPE-treated mice exhibited improved estrous cycle regularity compared to the Neu5Ac and DHEA co-treatment group (Fig. S4H). Additionally, BSH inhibition by CAPE reduced ovarian injury and lowered serum hormone levels in mice exposed to Neu5Ac and DHEA (Fig. 4O, P and S4I). Collectively, these findings demonstrate that Neu5Ac-driven Ligilactobacillus expansion promotes PCOS by modulating bile acid metabolism through BSH-mediated deconjugation.

4. Alterations in bile acid profiles exacerbate PCOS by activating FXR.
Since unconjugated bile acids act as FXR ligands and FXR is implicated in the pathogenesis of PCOS 7,16, we investigated whether Neu5Ac- and L. sa-mediated exacerbation of PCOS is regulated by FXR signaling. As expected, DHEA-treated mice exhibited increased Fxr and downstream fibroblast growth factor 15 (Fgf15) mRNA levels in the ileum compared to control mice, and Neu5Ac treatment further enhanced these upregulations (Fig. 5A). Consistently, Neu5Ac exacerbated the DHEA-induced increase in plasma FGF15 concentrations (Fig. 5B). Similar results were observed in L. sa-treated mice (Fig. 5C and D). We confirmed that these changes in FXR and FGF15 were mediated by BSH-derived unconjugated bile acids, as treatment with TUDCA or the BSH inhibitor CAPE suppressed the increases in ileal Fxr and Fgf15 expression and plasma FGF15 levels (Fig. S5A and B). Similarly, patients with PCOS had significantly higher plasma FGF19 levels—a human ortholog of murine FGF15 and a direct FXR target 18, —compared to the control group (Fig. 5E).

To assess the functional role of FXR, mice were treated with the FXR antagonist Gly-β-MCA 18 (Fig. 5F). Gly-β-MCA administration alleviated insulin resistance induced by co-treatment with Neu5Ac and DHEA (Fig. 5G and S5C). Furthermore, Gly-β-MCA improved estrous cycle disruption caused by Neu5Ac and DHEA co-treatment (Fig. S5D). In addition, FXR inhibition by Gly-β-MCA attenuated ovarian damage and reduced the elevation in serum hormone levels induced by Neu5Ac and DHEA (Fig. 5H, I and S5E). We also inhibited FXR during L. sa and DHEA co-treatment (Fig. S5F) and demonstrated that FXR blockade ameliorated insulin resistance (Fig. S5G and H), the rise in serum hormone levels (Fig. S5I), estrous cycle disruption (Fig. S5J), and ovarian injury (Fig. S5K and L) caused by L. sa and DHEA.

To confirm the role of intestinal FXR activation in Neu5Ac-mediated exacerbation of PCOS, we treated intestine-specific Fxr knockout (Fxr△IE) and control floxed (Fxrfl/fl) mice with Neu5Ac under DHEA-induced PCOS conditions (Fig. 5J). Knockout efficiency was confirmed by qPCR (Fig. S6A). The results showed that Neu5Ac exacerbated DHEA-induced PCOS in Fxrfl/fl mice, whereas these exacerbating effects were abolished in Fxr△IE mice (Fig. 5K-M and S6B-E). Moreover, TUDCA treatment alleviated PCOS induced by co-treatment with Neu5Ac and DHEA in Fxrfl/fl mice. However, intestinal Fxr knockout significantly attenuated TUDCA-mediated protection against PCOS (Fig. 5N–Q and S5G–I). Altogether, these findings demonstrate that Neu5Ac- and L. sa-induced alterations in bile acid profiles exacerbate PCOS through FXR activation.

5. Increased FXR activation exacerbates PCOS by inhibiting IL-22 production.
We next investigated how FXR activation promotes DHEA-induced PCOS in mice. FXR activation has been recently associated with suppression of IL-22 release in the gut 18, and reduced IL-22 levels are negatively correlated with PCOS development 1. To this end, we measured IL-22 levels under various treatment conditions. Indeed, DHEA-treated mice exhibited decreased ileal mRNA expression of IL-22 and its downstream target Reg3β compared to control mice, and Neu5Ac treatment further exacerbated these reductions (Fig. 6A). Similarly, serum IL-22 levels were reduced in DHEA-treated mice and further declined following Neu5Ac administration (Fig. 6B). Consistently, L. sa treatment also intensified the DHEA-induced decrease in IL-22 (Fig. 6C and D). We confirmed that the Neu5Ac- and L. sa-mediated reduction in IL-22 is mediated by bile acid-regulated FXR activation, as inhibition of BSH or FXR inhibition alleviated the decline in IL-22 caused by Neu5Ac and DHEA co-treatment (Fig. 6E and F). Moreover, TUDCA treatment reversed the reduction in IL-22 levels induced by Neu5Ac and DHEA co-treatment in Fxrfl/fl mice, whereas this effect was abolished in Fxr△IE mice (Fig. 6G). We then administered recombinant murine IL-22 (rMuIL-22) to mice during Neu5Ac and DHEA exposure 11 (Fig. 6H). rMuIL-22 treatment alleviated insulin resistance in Neu5Ac- and DHEA-co-treated mice (Fig. 6I and S7A). Administration of rMuIL-22 also improved estrous cycle disruption under Neu5Ac and DHEA co-treatment (Fig. 6J). Additionally, rMuIL-22 ameliorated ovarian damage and normalized serum hormone levels in mice receiving Neu5Ac and DHEA (Fig. 6K, L and S7B). Since bile acid-mediated TGR5 activation regulates IL-22 production and is involved in PCOS pathogenesis 1, we investigated whether the TUDCA-mediated increase in IL-22 was regulated by TGR5 activation. To this end, TUDCA-treated mice were subjected to TGR5 inhibition using SBI-115 25,26. However, TGR5 inhibition by SBI-115 did not affect the TUDCA-mediated increase in IL-22 (Fig. S7D) or the alleviation of PCOS in mice (Fig. S7E–J). Collectively, these findings demonstrate that increased FXR activation exacerbates PCOS by suppressing IL-22 production.

6. IL-22 alleviates DHEA-induced PCOS by inhibiting ferroptosis through STAT3 activation.
Ferroptosis is closely implicated in the pathogenesis of PCOS, and IL-22 has been associated with potential anti-ferroptotic effects 5,11. To investigate whether IL-22 ameliorates PCOS by suppressing ferroptosis under Neu5Ac treatment, we first showed that DHEA-treated mice exhibited increased ovarian cell death compared to control mice, and this effect was further exacerbated by Neu5Ac or L. sa administration (Fig. 7A and S8A). However, treatment with Neu5Ac alone did not affect cell viability in vitro (Fig. S8B). Inhibition of FXR or treatment with rMuIL-22 attenuated ovarian cell death induced by co-treatment with Neu5Ac and DHEA (Fig. 7B and S8C). Moreover, DHEA treatment increased ovarian expression of PTGS2 and reduced GPX4 levels relative to controls, and these changes were amplified by Neu5Ac treatment (Fig. 7C). Importantly, rMuIL-22 treatment mitigated the DHEA- and Neu5Ac-induced upregulation of PTGS2 and downregulation of GPX4 in the ovary (Fig. 7D). Additionally, DHEA-treated mice displayed elevated oxidative stress, as evidenced by increased malondialdehyde (MDA) and decreased glutathione (GSH) levels, which were further aggravated by Neu5Ac and L. sa treatments (Fig. S8D and E). Similarly, DHEA increased ovarian Fe²⁺ levels compared to control mice, an effect further intensified by Neu5Ac and L. sa (Fig. S8F). In contrast, FXR inhibition or rMuIL-22 administration reduced ovarian oxidative stress and Fe²⁺ accumulation in Neu5Ac- and DHEA-co-treated mice (Fig. S8G and H).

To determine the extent to which the protective effect of IL-22 against PCOS is mediated by ferroptosis inhibition, we treated cells and mice with ferrostatin-1 (Fer-1), a specific ferroptosis inhibitor 5,11. In vitro, both rMuIL-22 and Fer-1 alleviated DHEA-induced cell death compared to control cells, and no additional benefit was observed with combined rMuIL-22 and Fer-1 treatment relative to either agent alone (Fig. 7E). Additionally, both rMuIL-22 and Fer-1 individually improved insulin resistance (Fig. S9A and B) and ameliorated estrous cycle disruption caused by Neu5Ac and DHEA co-treatment (Fig. S9C and D). Furthermore, both treatments attenuated ovarian damage and normalized serum hormone levels (Fig. 7F, G and S9E). However, the effects in mice receiving rMuIL-22 and Fer-1 together were comparable to those treated with either agent alone (Fig. 7F, G and S9A–E).

STAT3 is a downstream signaling target of IL-22 and has been reported to exert anti-ferroptotic effects 11. As expected, mice subjected to Neu5Ac and DHEA co-treatment exhibited reduced phosphorylated STAT3 (p-STAT3) levels compared to controls, and rMuIL-22 treatment reversed this suppression (Fig. 7H). Administration of Stattic, a selective STAT3 inhibitor 11, abolished the protective effects of rMuIL-22 against DHEA-induced cell death (Fig. 7I) and attenuated rMuIL-22-mediated downregulation of PTGS2 and upregulation of GPX4 (Fig. 7J). Likewise, Stattic treatment reversed the beneficial effects of rMuIL-22 on insulin resistance (Fig. 7K and S9F), estrous cycle disruption (Fig. S9G), ovarian injury (Fig. 7L and M), and serum hormone imbalances in the context of Neu5Ac and DHEA co-treatment (Fig. S9H). Collectively, these findings demonstrate that IL-22 alleviates DHEA-induced PCOS by inhibiting ferroptosis via STAT3 activation.

Methods
Human participants
The study was approved by the Institutional Ethics Committee of China-Japan Union Hospital, Jilin University (2025101111). The 2003 Rotterdam criteria were used to distinguish patients with PCOS from healthy controls. A diagnosis of PCOS requires the presence of at least two of the following three features, as previously defined 1,7: (a) oligo- and/or anovulation; (b) clinical and/or biochemical evidence of hyperandrogenism; and (c) polycystic ovarian morphology. In addition, other potential etiologies—such as congenital adrenal hyperplasia, androgen-secreting tumors, and Cushing’s syndrome—were excluded through appropriate clinical evaluations. Moreover, all participants had not used antibiotics, probiotics, or hormonal medications in the past month and had not been pregnant or breastfeeding within the previous year. All PCOS patients were newly diagnosed and had not received any pharmacological or non-pharmacological interventions for PCOS prior to enrollment. In Cohort 1, human serum and fecal samples were collected from 16 PCOS patients and 16 healthy controls at the China-Japan Union Hospital of Jilin University. The clinical characteristics of these participants are presented in Supplementary Table 1. In an independent validation cohort (Cohort 2), fecal samples were collected from 19 PCOS patients and 14 healthy controls at the same institution (clinical characteristics are provided in Supplementary Table 2) for measurement of fecal Neu5Ac levels. This study included only female participants, with sex determined by self-report. Written informed consent was obtained from all individuals prior to participation.

Animal and treatments
The animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of Jilin University (SY2025120304). Female C57BL/6 mice at the prepubertal stage (21 days old) were obtained from Liaoning Changsheng Biotechnology Co., Ltd. (Benxi, China) and housed under a 12-hour light/dark cycle with ad libitum access to food and water at a temperature of 22.5 ± 2.5 °C and humidity of 50 ± 5% in a strictly controlled SPF environment. Villin Cre mice and Fxr-fl/fl mice were purchased from Cyagen. Intestinal-specific Fxr knockout (Fxr△IE) mice were generated by crossing 6–8-week-old villin Cre mice and Fxr-fl/fl mice. Villin Cre mice, Fxr-fl/fl mice and Fxr△IE mice were on a C57BL/6J genetic background.

To induce PCOS, prepubertal female mice were subcutaneously injected with DHEA (HY-14650, MCE) at a dose of 60 mg/kg body weight daily for 21 consecutive days 1. Mice in the control group received 200 μL of sesame oil via the same administration route. For Neu5Ac treatment, mice were fed a standard AIN93G diet and supplemented with 1% Neu5Ac (A0812, Sigma-Aldrich, MO, USA) in drinking water, along with oral gavage of 1 mg/200 μL Neu5Ac twice daily for 21 days 21. For antibiotic-mediated depletion of commensal microbes, mice received 1 g/L ampicillin (Cat# A5354, Sigma), neomycin (Cat# N6386, Sigma), and metronidazole (Cat# 16677, Sigma), and 0.5 g/L vancomycin (Cat# V2002, Sigma) in drinking water throughout the experimental period. For fecal microbiota transplantation (FMT), recipient mice were treated with a cocktail of antibiotics (200 mg/kg body weight/day of ampicillin, neomycin, and metronidazole; 100 mg/kg body weight/day vancomycin) for 6 days, followed by a 1-day washout period with regular water, then subjected to FMT for 7 consecutive days, and maintained under standard conditions thereafter. For L. sa treatment, mice were pretreated with the same antibiotic regimen for 6 days, followed by a 1-day washout, and then orally administered L. sa (2 × 10⁸ CFUs per mouse) daily for 7 days, followed by continued treatment during the subsequent 21-day DHEA exposure period. For TUDCA treatment, mice were administered 30 mg/kg TUDCA (HY-19696, MCE) daily for 21 days 1. For TGR5 inhibition in the context of TUDCA treatment, mice were treated with TUDCA and either with or without SBI-115 (80 mg/kg/day, HY-111534, MCE) for 21 days 26. For BSH inhibition, mice were treated with caffeic acid phenethyl ester (CAPE) (75 mg/kg/day, HY-N0274, MCE) for 21 days 24. For FXR inhibition, mice received Gly-β-MCA (50 mg/kg, HY-114392, MCE) daily for 21 days in combination with Neu5Ac or L. sa treatment 32. For IL-22 treatment, mice were injected with recombinant murine IL-22 (rMuIL-22, HY-P7079, MCE) at 1 mg/kg daily for 21 days 11. For ferroptosis inhibition, mice were treated with ferrostatin-1 (Fer-1, 10 mg/kg, HY-100579, MCE) daily, administered 2 hours prior to DHEA injection, for 21 days 11. For STAT3 inhibition, mice were treated with 10 mg/kg Stattic (HY-13818, MCE) daily for 21 days concurrently with Neu5Ac and DHEA administration 11.

Cell culture and treatments
KGN cells were obtained from the Japanese Collection of Research Bioresources (JCRB 1150) and cultured in F12 medium supplemented with 10% fetal bovine serum (Gibco, CA, USA) and 1% antibiotic-antimycotic solution (penicillin/streptomycin) at 37°C in a humidified atmosphere containing 5% CO₂. Cells were seeded into six-well plates and allowed to adhere overnight, after which the medium was replaced with antibiotic-free culture medium. For Neu5Ac treatment, cells were treated with Neu5Ac (0, 6.25, 12.5 and 25 mg/mL) for 24 h 28. For Fer-1 treatment, cells were pretreated with 1 μM Fer-1 with or without 0.1 μg/mL rMuIL-22 for 2 h, followed by incubation with DHEA (20 μM) for an additional 24 h 11. For STAT3 inhibition, cells were pretreated with 20 μM Stattic for 1 h, then exposed to rMuIL-22 (0.1 μg/mL) for 2 h, and subsequently treated with DHEA (20 μM) for 24 h 11.

Vaginal smears and estrous cycle determination
Vaginal smears and estrous cycle assessment were performed as previously described 36. Briefly, vaginal smears were collected daily from the 10th to the 19th day after the initiation of DHEA treatment. The stage of the estrous cycle was determined by microscopic examination of the predominant cell types in the smears following Shorr staining. The estrous cycle consists of four stages: proestrus (P), characterized by round, nucleated epithelial cells; estrus (E), marked by cornified squamous epithelial cells; metestrus (M), identified by a mixture of epithelial cells and leukocytes; and diestrus (D), dominated by leukocytes with scattered nucleated epithelial cells.

GTT and ITT assays
For the glucose tolerance test (GTT), mice were fasted for 12 hours on day 21 after the initiation of DHEA treatment. For the insulin tolerance test (ITT), a 4-hour fasting period was implemented. Baseline fasting blood glucose levels were measured prior to intraperitoneal injection of 2 mg/kg D-glucose (for GTT) or 1 IU/kg insulin (for ITT). Blood samples were then collected from the tail vein at 15, 30, 60, 90, and 120 min post-injection, and blood glucose concentrations were determined using the Roche Diagnostics Accu-Chek Performa blood glucose monitoring system.

Serum biochemical assays
Peripheral blood samples were processed using standardized pre-analytical procedures to ensure analyte stability. Blood samples were centrifuged at 1,000 × g for 5 min at 4 °C, after which serum was collected and combined with freshly obtained fecal samples; both were then aliquoted and immediately snap-frozen at −80 °C for batch analysis at a later time. Clinically relevant parameters were measured using previously established methods 1,7. Luteinizing hormone and follicle-stimulating hormone concentrations were determined by radioimmunoassay. Circulating levels of estradiol, testosterone, and androstenedione were quantified using liquid chromatography–tandem mass spectrometry (LC–MS/MS) on a Sciex Triple Quad 6500+ system. Glucose homeostasis was evaluated by calculating the homeostatic model assessment of insulin resistance (HOMA-IR) index using the standard formula: fasting blood glucose (mmol L−1) × fasting insulin (μIU mL−1) / 22.5. Mouse and human blood samples for ELISA were collected and centrifuged at 3,000 × g for 15 min at 4 °C. Serum levels of IL-22 (88-7422-88, Thermo Scientific, USA), FGF15 (BES3006K, BIOESN, China), and FGF19 (EHFGF19, Thermo Scientific, USA) were measured according to the manufacturers’ instructions.

Histological analysis
Ovarian tissues for histological analysis were collected and fixed in 4% paraformaldehyde. After dehydration and paraffin embedding, 5-μm-thick sections were prepared and stained with hematoxylin and eosin (H&E) as previously described 1,37. Histological changes were assessed using an optical microscope (Olympus, Tokyo, Japan).

Immunofluorescence
Ovarian tissue sections were deparaffinized and rehydrated prior to apoptosis assessment using a terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) assay kit, following the manufacturer’s instructions (S7111, Sigma-Aldrich, USA). Apoptotic cells were labeled with fluorescence and visualized under a confocal microscope (Olympus, Japan). Fluorescent signals were quantified using ImageJ software 11.

Bacterial cultivation and growth analysis
Ligilactobacillus salivarius BNCC 138618 (L. salivarius) was cultivated in de Man, Rogosa, and Sharpe (MRS) broth (HB0384-1, Haibo, China) at 37 °C anaerobic conditions 13. To investigate the effect of Neu5Ac on bacterial proliferation, L. salivarius was cultured in M9 minimal medium (M9956, Sigma-Aldrich, USA) supplemented with either 10 mM Neu5Ac or an equimolar concentration of glucose as the sole carbon source. Bacterial growth was monitored by measuring optical density at 600 nm (OD₆₀₀) 21.

Cell viability analysis
Cells were treated as described above, and cell viability was determined using a commercial CCK-8 assay kit (Solarbio, Beijing, China) in accordance with the manufacturer’s instructions. Absorbance was measured after incubation of cells with the CCK-8 reagent in a 24-well plate 11.

GSH and MDA detections
GSH and MDA levels were determined using assay kits for GSH (A006-2, Nanjing Jiancheng Bioengineering Institute, China) and MDA (MAK085, Sigma-Aldrich, USA) following the manufacturers’ instructions.

Fe2+ level assay
Cellular Fe²⁺ levels were determined using a commercial kit according to the manufacturer’s instructions (E-BC-F101, Elabscience, China).

Neu5Ac level determination
Fecal and serum Neu5Ac levels were determined using the Sialic Acid Assay Kit (MAK314, Sigma-Aldrich, MO, USA) according to the manufacturer’s instructions.

DNA Extraction and 16S rRNA sequencing
Microbial genomic DNA was extracted from mouse fecal samples using the FastDNA® Spin Kit for Soil (MP Biomedicals, USA) according to the manufacturer’s instructions. DNA quality and concentration were evaluated by 1% agarose gel electrophoresis and with a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA). The V3–V4 hypervariable region of the bacterial 16S rRNA gene was amplified using primers 338F and 806R on a GeneAmp® 9700 PCR system (ABI, USA). The PCR protocol included an initial denaturation at 95 °C for 3 min, followed by 27 cycles of 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 45 s, and a final extension at 72 °C for 10 min. Each reaction was performed in triplicate. Amplified products were purified from 2% agarose gels using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, USA) and quantified using a Quantus™ Fluorometer (Promega, USA). Equimolar amounts of purified amplicons were pooled and sequenced using paired-end technology on the Illumina MiSeq PE300 or NovaSeq PE250 platforms (Illumina, USA) at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). Sequences were clustered into operational taxonomic units (OTUs) at a 97% sequence similarity threshold using UPARSE (v7.1), with chimeric sequences removed during the process. Taxonomic assignment was performed using the RDP Classifier (v2.2) against the 16S rRNA gene database with a minimum confidence threshold of 0.7. Microbial community structure was visualized by principal coordinate analysis (PCoA), and statistical differences were assessed using Adonis. Differentially abundant bacterial taxa were identified through linear discriminant analysis effect size (LEfSe).

Untargeted metabolomics
Fecal metabolomics profiling was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Briefly, serum samples were extracted with 400 µL of a methanol:water (4:1, v/v) solution containing 0.02 mg/mL L-2-chlorophenylalanine as the internal standard. The mixture was incubated at –20 °C for 30 minutes and then homogenized using a high-throughput tissue homogenizer (Wonbio-96c, Shanghai Wanbo Biotechnology Co., Ltd.) at 50 Hz for 6 minutes. This was followed by ultrasonication at 40 kHz for 30 minutes at 5 °C. Subsequently, the samples were maintained at –20 °C for an additional 30 minutes to induce protein precipitation. After centrifugation at 13,000×g at 4 °C for 15 minutes, the supernatant was carefully transferred into sample vials for LC-MS/MS analysis. Chromatographic conditions: A 2 μL sample was separated on an HSS T3 column (100 mm × 2.1 mm i.d., 1.8 µm) and then introduced into the mass spectrometer. The mobile phases consisted of 0.1% formic acid in water:acetonitrile (95:5, v/v) and 0.1% formic acid in acetonitrile:isopropanol:water (47.5:47.5:5, v/v). MS conditions: Mass spectrometric data were acquired using a Thermo UHPLC-Q Exactive mass spectrometer equipped with an electrospray ionization (ESI) source operating in both positive and negative ion modes. Following mass spectrometry, raw LC-MS data were preprocessed using Progenesis QI software (Waters Corporation, Milford, USA). Variance analysis was performed on the matrix file after data preprocessing. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted using the R package ropls (Version 1.6.2). A seven-cycle interactive validation was applied to assess model stability. Additionally, Student’s t-test and fold-change analysis were performed. Significantly different metabolites were selected based on the variable importance in the projection (VIP) values derived from the OPLS-DA model and the p-values from Student’s t-tests. Metabolites with VIP > 1 and p < 0.05 were considered statistically significant. Differential metabolites between groups were summarized and mapped to biochemical pathways through metabolic enrichment and pathway analysis via database searching (KEGG, http://www.genome.jp/kegg/). Data analysis was carried out using the free online platform MajorBio Cloud Platform (cloud.majorbio.com).

BSH Activity Assay
Ileal contents and fecal samples (50 mg each) were suspended in 250 μL of phosphate-buffered saline (PBS, pH 7.4) and homogenized by vortexing for 1 min. Bacterial lysis was achieved through sonication on ice (90 s total duration with a 30 s interval). After centrifugation (15,000 × g, 30 min, 4 °C), the supernatant was collected. Protein concentration was determined using the BCA Protein Assay Kit (Thermo Fisher Scientific, USA) with bovine serum albumin (BSA) as the standard, following the manufacturer’s protocol. The original protein solution was then diluted with PBS to a final working concentration of 2 mg/mL. BSH activity was measured by quantifying the enzymatic conversion of deuterium-labeled taurochenodeoxycholic acid (d4-TCDCA) to deuterium-labeled chenodeoxycholic acid (d4-CDCA). The reaction mixture (200 μL) consisted of 3 mM sodium acetate buffer (pH 5.2), 0.1 mM d4-TCDCA, and 0.1 mg/mL of the diluted protein solution. Following incubation at 37 °C for 20 min, reactions were terminated by immediate freezing in dry ice. Methanol (100 μL) was added, followed by vortex mixing for 5 min and centrifugation (15,000 × g, 20 min, 4 °C). The resulting supernatant was analyzed by UPLC-TQMS (Waters, Milford, MA, USA) to quantify d4-CDCA levels, based on which BSH activity was calculated 19.

Bile acid analysis
Bile acid composition was analyzed using an established protocol 13. Quantification of bile acids in murine ileal content and human fecal samples was performed using an Agilent 1290 Infinity Liquid Chromatography system coupled to an Agilent 6470 triple quadrupole mass spectrometer. The method included a comprehensive panel of deuterated internal standards covering both conjugated and unconjugated bile acid species: cholic acid (CA), chenodeoxycholic acid (CDCA), deoxycholic acid (DCA), lithocholic acid (LCA), ursodeoxycholic acid (UDCA), and their glycine- and taurine-conjugated forms (GCA, GCDCA, GDCA, GLCA, GUDCA, TCA, TCDCA, TDCA, TLCA, TUDCA). Detection was conducted in negative electrospray ionization mode with multiple reaction monitoring (MRM). Instrument control and data acquisition were carried out using Agilent MassHunter software (B.08.00).

RNA extraction and qPCR
Total RNA was extracted using an RNA extraction kit (K0732, Thermo Scientific, USA). Briefly, cells were lysed with 1 mL of TRIzol reagent and subsequently subjected to phase separation using chloroform, followed by RNA precipitation with isopropanol and washing with 75% ethanol under RNase-free conditions. Following RNA extraction, complementary DNA (cDNA) was synthesized using TransStart Tip Green qPCR SuperMix (TransGen Biotech, Beijing, China). Quantitative RT–PCR was performed using gene-specific primers and FastStart Universal SYBR Green Master Mix (ROX) (Roche, Basel, Switzerland) on a StepOnePlus Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). The primers used in this study were provided in Supplementary Table 3. The thermal cycling conditions were as follows: 52 °C for 2 min, 95 °C for 10 min, followed by 45 cycles of 95 °C for 15 s and 60 °C for 1 min 37,38. The 16S rRNA or GAPDH gene was used as the internal reference control. Relative gene expression levels were calculated using the 2−ΔΔCt method normalized to the control group.

Western blotting
Ovarian tissues or cultured cells were collected and subjected to protein extraction using a commercially available kit (Thermo Fisher Scientific, USA). Total protein concentration was determined using the BCA Protein Assay Kit (Thermo Fisher Scientific, USA). Target proteins were separated by SDS-PAGE (sodium dodecyl sulfate-polyacrylamide gel electrophoresis) according to their molecular weights. The proteins were then transferred onto 0.45 μm PVDF membranes and blocked with 5% skim milk for 3 hours at room temperature. Subsequently, the following primary antibodies were applied for overnight incubation at 4 °C: PTGS2 (1:1000, AF7003, Affinity Biosciences, USA), GPX4 (1:1000, AF7003, Affinity Biosciences, USA), STAT3 (1:1000, AF6294, Affinity Biosciences, USA), p-STAT3 (1:1000, AF3293, Affinity Biosciences, USA), and β-actin (1:1000, AF7018, Affinity Biosciences, USA). Following three 20-minute washes with PBST to remove unbound antibodies, the membranes were incubated with horseradish peroxidase-conjugated secondary antibodies (1:2000, goat anti-rabbit or rabbit anti-mouse IgG) for 2 hours at room temperature. After an additional three PBST washes, protein expression levels were visualized using an ECL Plus Western Blotting Detection System (Tanon 4500, Shanghai, China).

Statistical analysis
Statistical analysis was performed using GraphPad Prism 8.0 (San Diego, CA, USA). No statistical methods were used to predetermine sample size for animal experiments or in vitro studies; however, the sample sizes used in this study are consistent with those reported in previously published work 1,7. Data are presented as mean ± standard deviation (SD) or boxplots, where the center line represents the median, the box spans the interquartile range (25th to 75th percentiles), and the whiskers extend to the minimum and maximum values. Normality of data distribution was assessed using the Kolmogorov–Smirnov test. The Mann–Whitney U test (non-parametric) and two-tailed unpaired Student’s t-test (parametric) were used to evaluate significant differences between two groups. For comparisons involving more than two groups, one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test was applied. Two-way repeated-measures ANOVA with Sidak’s multiple-comparisons correction was used to analyze the GTT and ITT assays. For these assays, p values with a bracket line connecting two groups refer to the whole curves and p values on top of individual datapoints refer only to indicated time point. A p-value < 0.05 was considered statistically significant. All experiments were performed at least three independent experiments, with similar results across replicates.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript, the authors report the identification of N-acetylneuraminic acid (Neu5Ac) as a novel biomarker for\npolycystic ovary syndrome (PCOS) through non-targeted metabolomics of a clinical cohort. They further propose that\nNeu5Ac aggravates PCOS mainly by increasing the abundance of Lactobacillus salivarius (L.sa) and its bile-salt-hydrolase\n(BSH) activity, leading to a reduction in the conjugated bile acid TCDCA. The decrease in TCDCA, in turn, exacerbates\nPCOS via FXR–IL-22 axis. While the discovery of Neu5Ac is interesting, the clinical evidence is preliminary and the\nmechanistic elaboration remains superficial. Major revisions are required.\n1. Sample size is too small. The authors should expand the discovery cohort and, ideally, validate the findings in an\nindependent cohort. Do public metabolomic datasets show a similar association between Neu5Ac and PCOS?\n2. Which organ/tissue is the primary source of Neu5Ac? What are the concentrations of Neu5Ac in peripheral blood and the\novarian micro-environment? Does Neu5Ac exert any direct effect on ovarian cells (granulosa/theca cells or oocytes)?\n3. Is serum or follicular-fluid Neu5Ac level correlated with PCOS severity, phenotype (hyper-androgenic vs. non-hyper-\nandrogenic), BMI, insulin resistance indices, or ovulatory dysfunction?\n4. In PCOS patients, is Neu5Ac abundance correlated with L.sa relative abundance? Can Neu5Ac, in vitro, directly promote\nthe growth of L.sa or other BSH-expressing taxa?\n5. In PCOS patients, does Neu5Ac correlate with the overall bile-acid profile, especially with FXR-antagonistic conjugated\nbile acids?\n6. The bile-acid pool composition differs markedly between humans and rodents; glycine-conjugated species (GUDCA,\nGDCA) are abundant in humans and are potent FXR/TGR5 modulators. The authors should quantify these human-relevant\nbile acids in their clinical samples rather than relying solely on murine data.\n7. Bile acids usually regulate FXR at the transcriptional-activity level, not by altering FXR protein abundance. The\nobservation that DHEA, Neu5Ac and L.sa increase FXR protein levels is counter-intuitive. What is the underlying molecular\nmechanism (stabilization of FXR protein? decreased proteasomal degradation? transcriptional up-regulation)?\n8. Genetic loss-of-function studies are indispensable. Does Neu5Ac-dependent exacerbation of PCOS phenotypes\ndisappear in intestinal-specific FXR-knockout mice (FXRΔint)?\n9. GDCA–TGR5–IL-22 axis is reported to involve in PCOS pathogenesis. TCDCA is not only an FXR antagonist but also a\nTGR5 agonist. Is the suppression of IL-22 by Neu5Ac mediated via TGR5, FXR, or both?", "reviewer_2": "The role of the gut microbiota in PCOS progression remains unclear. Although the gut microbiome differs in individuals with\nPCOS, these differences alone do not establish a causal role in disease development. Drug treatments are known to alter\nthe gut microbiota, further complicating interpretation and weakening arguments for causation. A major limitation of both\npreclinical and clinical studies is the lack of in-depth mechanistic investigation into how gut microbiota might interact with\nandrogen excess. While elevated androgens may contribute to dysbiosis, evidence that gut microbiota alterations can drive\nPCOS pathophysiology is scarce, if not entirely absent. For this reason, the statement that “the gut microbiota has been\nrecognized as an important modulator of PCOS pathogenesis” overstates the current evidence base.\nThat said, I appreciate the authors’ ambitious approach in this manuscript, particularly their efforts to dissect mechanistic\nunderpinnings. The authors present evidence for an intriguing pathway in which Ligilactobacillus influences Neu5Ac\navailability, thereby altering bile acid metabolism. This shift activates intestinal FXR signaling, ultimately reducing IL-22\nproduction. Diminished circulating IL-22 may have systemic consequences, including impaired ovarian function. These\nfindings suggest a promising therapeutic opportunity targeting the bile acid–FXR–IL-22 axis for the treatment of PCOS.\nSuggestions for revision.\nThe introduction is too long.\nRefrain to use the term healthy controls, healthy group or healthy individuals. They may have other conditions although not\nPCOS. Controls is an appropriate term.\nResults\nFig. 1C. Present all differently expressed metabolites as supplemental material.\nFig 1G-M. Neu5Ac exposure alone does not have an effect in mice with a normal gut flora. How can this be explained? Why\nis the combination with DHEA necessary for an effect?\nDo not cut the axes in graphs as this is misleading.\nDouble-check the statistics in Fig 2B, is this really a significant difference? The curves are basically on top of each other.\nCheck this statement on line 184: We next quantified different Ligilactobacillus species using qPCR and found that\nLigilactobacillus salivarius (L. sa), but not L. reuteri or L. rhamnosus, was elevated in Neu5Ac- and N-FMT-treated mice, as\nwell as in PCOS patients (Fig. 4F–H and S2D–F). I belive it should be that Ligilactobacillus salivarius was elevated in\nNeu5Ac+DHEA exposed mice. Moreover, L. reuteri and L. rhamnosus, seems to be elevated in Neu5Ac+DHEA and N-FMT-\ntreated mice (S2D-E).\nCheck labelling of groups in Fig 6B.\nStatistics.\nGlucose curves following ITT and GTT should be analyzed using repeated measurement ANOVA with appropriate\ncorrection for multiple groups.\nInclude the statistics used in all graphs in the figure legend. For example, the statistics used in 1D is missing.\nMaterial and methods\nDescribe the clinical cohort in more detail. Include, age, weight, BMI, androgen levels, LH, FSH, FG-score, ovarian\nmorphology, insulin and glucose levels etc.\nTestosterone should not be measured by ELISA or RIA since they are unspecific. Tanden mass spectrometry should be\nused for accurate measurements of androgens in humans and mice."}, "author_response": "Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled\n“Sialic acid exacerbates polycystic ovary syndrome in mice by modulating the bile acid–FXR–\nIL-22–ferroptosis axis” (NCOMMS-25-82445). These comments are all valuable and very helpful\nfor revising and improving our paper, as well as the important guiding significance to our researches.\nWe have addressed all the concerns raised by reviews. Below are our responses to the editors' and\nreviewers' comments.\nIn order to facilitate the review, the blue font indicates reviewer’s comments, the black font indicates\nthe responses to reviewers, and the red font indicates the modification in the revised manuscript.\nThe responds to the reviewer’s comments are as follows:\nPoint-by-point response.\nReviewer #1 (Remarks to the Author):\nIn this manuscript, the authors report the identification of N-acetylneuraminic acid (Neu5Ac) as a\nnovel biomarker for polycystic ovary syndrome (PCOS) through non-targeted metabolomics of a\nclinical cohort. They further propose that Neu5Ac aggravates PCOS mainly by increasing the\nabundance of Lactobacillus salivarius (L.sa) and its bile-salt-hydrolase (BSH) activity, leading to a\nreduction in the conjugated bile acid TCDCA. The decrease in TCDCA, in turn, exacerbates PCOS\nvia FXR–IL-22 axis. While the discovery of Neu5Ac is interesting, the clinical evidence is\npreliminary and the mechanistic elaboration remains superficial. Major revisions are required.\nComment 1: Sample size is too small. The authors should expand the discovery cohort and, ideally,\nvalidate the findings in an independent cohort. Do public metabolomic datasets show a similar\nassociation between Neu5Ac and PCOS?\nResponse 1: We gratefully acknowledge the reviewer for the valuable time spent providing\nconstructive comments. We have measured fecal Neu5Ac levels in an independent cohort and\nobserved consistent results. Additionally, we analyzed the association between Neu5Ac and PCOS\nusing published metabolic datasets. However, most studies have primarily focused on serum\nmetabolic alterations in PCOS, with limited attention paid to fecal metabolic profiles. To date, no\nstudies have reported an association between fecal Neu5Ac levels and PCOS. We sincerely thank\nthe reviewer once again.\nLine 81-83: This finding was replicated in an independent cohort consisting of 19 PCOS patients\nand 14 control individuals (Fig. 1E and Supplementary table 3).\nFig. 1. Neu5Ac exacerbates DHEA-induced PCOS in a gut microbiota-dependent manner in\nmice. (D and E) Fecal Neu5Ac levels in healthy individuals and PCOS patients (D, Cohort 1, n =\n16; E, Cohort 2, n = 14-19).\nComment 2: Which organ/tissue is the primary source of Neu5Ac? What are the concentrations of\nNeu5Ac in peripheral blood and the ovarian micro-environment? Does Neu5Ac exert any direct\neffect on ovarian cells (granulosa/theca cells or oocytes)?\nResponse 2: We sincerely appreciate your professional suggestions. Studies have reported that\nNeu5Ac is released from the mucosa under conditions of gut dysbiosis by bacteria expressing\nsialidase (e.g., Bacteroides species, which are increased in PCOS) and by host macrophages;\nhowever, these findings require further validation within the context of PCOS pathogenesis, and we\nhave discussed this limitation. We also measured circulating Neu5Ac concentrations and evaluated\nthe effects of Neu5Ac on ovarian cells. Thank you again for your valuable comments.\nLine 308-312: Using untargeted metabolomics, we revealed that PCOS patients had elevated fecal\nNeu5Ac levels. This may be linked to the expansion of Bacteroides during PCOS, as Bacteroides\nexpresses sialidase but lacks enzymes required for sialic acid utilization 19. However, we cannot\nrule out the possibility that host cells in a diseased state may drive the release of Neu5Ac 27.\nLine 374-382:\nLimitations of the study\nAlthough we have elucidated the crucial roles of Neu5Ac-mediated bile acid metabolism and FXR\nactivation in the pathogenesis of PCOS, the specific bacterial sources or host tissues responsible for\nNeu5Ac production remain unclear. The mechanisms underlying the interaction between gut\nmicrobiota and hormonal fluctuations in PCOS, as well as how this process is regulated by Neu5Ac,\nare still unknown. Moreover, the contribution of metabolic alterations beyond bile acid\ndysregulation to Neu5Ac-mediated PCOS progression remains to be determined. Future studies\nshould investigate the precise regulatory mechanisms by which Neu5Ac modulates the gut\nmicrobiota and assess the therapeutic potential of targeting this pathway in PCOS.\nLine 83-84: However, no significant difference in Neu5Ac levels was observed in serum between\nPCOS patients and controls (Fig. S1B).\nFig. S1. Neu5Ac exacerbates DHEA-induced PCOS in a gut microbiota-dependent manner in\nmice. (B) Serum Neu5Ac levels in PCOS patients and healthy controls (n = 16).\nLine 256-257: However, treatment with Neu5Ac alone did not affect cell viability in vitro (Fig.\nS8B).\nFig. S8. Ferroptosis is involved in Neu5Ac-mediated exacerbation of PCOS in mice. (B) KNG\ncells were treated with Neu5Ac (0, 6.5, 12.5, and 25 mg/mL) for 24 h, and cell viability was assessed\n(n = 5).\nComment 3: Is serum or follicular-fluid Neu5Ac level correlated with PCOS severity, phenotype\n(hyper-androgenic vs. non-hyper-androgenic), BMI, insulin resistance indices, or ovulatory\ndysfunction?\nResponse 3: We thank you for your comprehensive consideration and constructive comments. We\ndid not detect any differences in Neu5Ac concentrations in serum between the control group and\nPCOS patients, nor was there a correlation between Neu5Ac levels in serum and the severity of\nPCOS. We appreciate your feedback once again.\nLine 84-85: Moreover, fecal Neu5Ac, but not serum levels, showed a positive correlation with\nPCOS severity and insulin resistance (Fig. 1F).\nFig. 1. Neu5Ac exacerbates DHEA-induced PCOS in a gut microbiota-dependent manner in\nmice. (F) Correlations between stool and serum Neu5Ac levels and clinical characteristics, as\ndetermined by Spearman’s rank correlation test.\nComment 4: In PCOS patients, is Neu5Ac abundance correlated with L.sa relative abundance? Can\nNeu5Ac, in vitro, directly promote the growth of L.sa or other BSH-expressing taxa?\nResponse 4: We sincerely thank you for your valuable comments. We have included the correlation\nbetween Neu5Ac abundance and L. sa levels in PCOS patients, as well as the effect of Neu5Ac on\nthe growth of L. sa. We appreciate your feedback once again.\nLine 151-152: Importantly, fecal Neu5Ac levels were positively correlated with L. sa abundance in\nPCOS patients (Fig. 3H).\nFig. 3. Neu5Ac exacerbates DHEA-induced PCOS by facilitating Ligilactobacillus expansion.\n(H) Correlation between fecal Neu5Ac levels and L. sa abundance in PCOS patients was assessed\nby Pearson correlation analysis.\nLine 156-158: Since Neu5Ac can promote the growth of both commensal and opportunistic bacteria\n20, we cultured L. sa with Neu5Ac and found that Neu5Ac significantly enhanced L. sa growth\ncompared to glucose (Fig. 3O).\nFig. 3. Neu5Ac exacerbates DHEA-induced PCOS by facilitating Ligilactobacillus expansion.\n(O) The effect of Neu5Ac on the growth of L. sa was monitored by measuring optical density at 600\nnm (OD600), and glucose was used as the control carbon source (n = 5).\nComment 5: In PCOS patients, does Neu5Ac correlate with the overall bile-acid profile, especially\nwith FXR-antagonistic conjugated bile acids?\nResponse 5: We thank you for your rigorous consideration and constructive comments. We have\nexamined the correlation between Neu5Ac levels and the bile acid profile in patients with PCOS,\nwith particular focus on FXR-antagonistic conjugated bile acids. We appreciate your feedback once\nagain.\nLine 172-173: Moreover, TUDCA levels were negatively correlated with fecal Neu5Ac and L. sa\nabundance in PCOS patients (Fig. 4H).\nFig. 4. Ligilactobacillus expansion promotes PCOS by altering bile acid profiles via bile salt\nhydrolase. (H) Correlations between fecal Neu5Ac levels, L. sa abundance, and stool bile acid\nlevels in PCOS patients, as determined by Spearman’s rank correlation test.\nComment 6: The bile-acid pool composition differs markedly between humans and rodents;\nglycine-conjugated species (GUDCA, GDCA) are abundant in humans and are potent FXR/TGR5\nmodulators. The authors should quantify these human-relevant bile acids in their clinical samples\nrather than relying solely on murine data.\nResponse 6: Thanks so much for your valuable comments. We have detected bile acid profiles in\nPCOS patients and healthy individuals. Thanks again.\nLine 169-170: In PCOS patients, reduced levels of conjugated bile acids and TUDCA were also\ndetected (Fig. 4C-D).\nFig. 4. Ligilactobacillus expansion promotes PCOS by altering bile acid profiles via bile salt\nhydrolase. (C and D) Fecal bile acid profiles in PCOS patients and controls (n = 16).\nComment 7: Bile acids usually regulate FXR at the transcriptional-activity level, not by altering\nFXR protein abundance. The observation that DHEA, Neu5Ac and L.sa increase FXR protein levels\nis counter-intuitive. What is the underlying molecular mechanism (stabilization of FXR protein?\ndecreased proteasomal degradation? transcriptional up-regulation)?\nResponse 7: We sincerely thank you for your valuable and constructive suggestions. We fully agree\nwith the reviewer's viewpoint that bile acids typically regulate FXR at the transcriptional level.\nHowever, studies have also reported that bile acids can modulate FXR protein levels (Science. 2025.\nPMID: 40179178; Nat Commun. 2019. PMID: 31672964). In this study, we observed that DHEA,\nNeu5Ac, and L. sa increase both the transcriptional and protein levels of FXR. This effect may result\nfrom transcriptional upregulation mediated by bile acid metabolism. However, we are currently\nunable to confirm the specific molecular mechanisms involved, and cannot exclude other potential\npathways—such as FXR protein stabilization, reduced proteasomal degradation (as suggested by\nthe reviewer), or bile acid-independent mechanisms. To avoid misinterpretation, we have removed\nthe data related to FXR protein levels and plan to investigate this question in greater depth in future\nstudies. We appreciate your constructive feedback once again.\nComment 8: Genetic loss-of-function studies are indispensable. Does Neu5Ac-dependent\nexacerbation of PCOS phenotypes disappear in intestinal-specific FXR-knockout mice (FXRΔint)?\nResponse 8: We gratefully appreciate for your valuable comments. We have supplemented genetic\nloss-of-function studies by using intestinal epithelial-specific FXR-knockout mice (FxrΔIE), and\nfound that Neu5Ac-mediated exacerbation on PCOS was eliminated in FxrΔIE mice. Thanks again.\nLine 215-219: To confirm the role of intestinal FXR activation in Neu5Ac-mediated exacerbation\nof PCOS, we treated intestine-specific Fxr knockout (Fxr△IE) and control floxed (Fxrfl/fl) mice with\nNeu5Ac under DHEA-induced PCOS conditions (Fig. 5J). Knockout efficiency was confirmed by\nqPCR (Fig. S6A). The results showed that Neu5Ac exacerbated DHEA-induced PCOS in Fxrfl/fl\nmice, whereas these exacerbating effects were abolished in Fxr△IE mice (Fig. 5K-M and S6B-E).\nFig. 5. Alterations in bile acid profile aggravate PCOS by activating FXR. (J) Schematic\ndiagram illustrating the experimental design of Neu5Ac treatment in Fxrfl/fl and intestine-specific\nFxr knockout (Fxr△IE) mice. (K) GTT and ITT assays in the different treatment groups (n = 5). *p\n< 0.05 and ***p < 0.001 indicate significant differences between the Neu5Ac + DHEA + Fxrfl/fl\ngroup and the DHEA + Fxrfl/fl group; #p < 0.05, ##p < 0.01, and ###p < 0.001 indicate significant\ndifferences between the Neu5Ac + DHEA + Fxr△IE group and the Neu5Ac + DHEA + Fxrfl/fl group.\n(L) Representative H&E-stained ovarian tissue sections from each group (scale bar: 200 μm). (M)\nQuantification of cystic follicles and corpora lutea (n = 5).\nComment 9: GDCA–TGR5–IL-22 axis is reported to involve in PCOS pathogenesis. TCDCA is\nnot only an FXR antagonist but also a TGR5 agonist. Is the suppression of IL-22 by Neu5Ac\nmediated via TGR5, FXR, or both?\nResponse 9: We gratefully appreciate your professional advice. We fully agree with the reviewer's\nobservation that conjugated bile acids may influence the PCOS process not only through FXR\ninhibition but also via activation of the TGR5-IL-22 signaling pathway. However, our findings\nindicate that Neu5Ac-mediated exacerbation of PCOS is primarily driven by FXR dysregulation.\nFirst, the detrimental effects of Neu5Ac were alleviated by treatment with the FXR antagonist Gly-\nβ-MCA. Second, Neu5Ac-mediated exacerbation of PCOS was abolished in FxrΔIE mice.\nFurthermore, in response to the reviewers' suggestions, we analyzed human bile acid profiles and\nfound that Neu5Ac levels were predominantly associated with reduced concentrations of TUDCA—\na bile acid with weak TGR5 activation potential. Notably, TUDCA supplementation ameliorated\nNeu5Ac-induced worsening of PCOS in mice, and this beneficial effect persisted in the presence of\na TGR5 inhibitor but was reversed in FxrΔIE mice. We thank you once again for your valuable\nfeedback.\nLine 2025-223: To assess the functional role of FXR, mice were treated with the FXR antagonist\nGly-β-MCA (Fig. 5F). Gly-β-MCA administration alleviated insulin resistance induced by co-\ntreatment with Neu5Ac and DHEA (Fig. 5G and S5C). Furthermore, Gly-β-MCA improved estrous\ncycle disruption caused by Neu5Ac and DHEA co-treatment (Fig. S5D). In addition, FXR inhibition\nby Gly-β-MCA attenuated ovarian damage and reduced the elevation in serum hormone levels\ninduced by Neu5Ac and DHEA (Fig. 5H, I and S5E). We also inhibited FXR during L. sa co-\ntreatment (Fig. S5F) and demonstrated that FXR blockade ameliorated insulin resistance (Fig. S5G\nand H), the rise in serum hormone levels (Fig. S5I), estrous cycle disruption (Fig. S5J), and ovarian\ninjury (Fig. S5K and L) caused by L. sa and DHEA.\nTo confirm the role of intestinal FXR activation in Neu5Ac-mediated exacerbation of PCOS, we\ntreated intestine-specific Fxr knockout (Fxr△IE) and control floxed (Fxrfl/fl) mice with Neu5Ac under\nDHEA-induced PCOS conditions (Fig. 5J). Knockout efficiency was confirmed by qPCR (Fig.\nS6A). The results showed that Neu5Ac exacerbated DHEA-induced PCOS in Fxrfl/fl mice, whereas\nthese exacerbating effects were abolished in Fxr△IE mice (Fig. 5K-M and S6B-E). Moreover,\nTUDCA treatment alleviated PCOS induced by co-treatment with Neu5Ac and DHEA in Fxrfl/fl\nmice. However, intestinal Fxr knockout significantly attenuated TUDCA-mediated protection\nagainst PCOS (Fig. 5N–Q and S5G–I). Altogether, these findings demonstrate that Neu5Ac- and L.\nsa-induced alterations in bile acid profiles exacerbate PCOS through FXR activation.\nFig. 5. Alterations in bile acid profile aggravate PCOS by activating FXR. (F) Schematic\ndiagram illustrating the experimental design of FXR inhibition using Gly-β-MCA during Neu5Ac\ntreatment. Mice were administered Gly-β-MCA (50 mg/kg/day) orally for 21 days, concurrently\nwith daily Neu5Ac and DHEA (60 mg/kg) treatments. (G) GTT and ITT assays in the different\ntreatment groups (n = 5). *p < 0.05, **p < 0.01, and ***p < 0.001 indicate significant differences\nbetween the Neu5Ac + DHEA group and the control group. #p < 0.05, and ##p < 0.01 indicate\nsignificant differences between the Gly-β-MCA + Neu5Ac + DHEA group and the Neu5Ac + DHEA\ngroup. (H) Representative H&E-stained ovarian tissue sections from each group (scale bar: 200 μm).\n(I) Quantification of cystic follicles and corpora lutea based on H&E-stained ovarian sections (n =\n5). (J) Schematic diagram illustrating the experimental design of Neu5Ac treatment in Fxrfl/fl and\nintestine-specific Fxr knockout (Fxr△IE) mice. (K) GTT and ITT assays in the different treatment\ngroups (n = 5). *p < 0.05 and ***p < 0.001 indicate significant differences between the Neu5Ac +\nDHEA + Fxrfl/fl group and the DHEA + Fxrfl/fl group; #p < 0.05, ##p < 0.01, and ###p < 0.001 indicate\nsignificant differences between the Neu5Ac + DHEA + Fxr△IE group and the Neu5Ac + DHEA +\nFxrfl/fl group. (L) Representative H&E-stained ovarian tissue sections from each group (scale bar: 200\nμm). (M) Quantification of cystic follicles and corpora lutea (n = 5). (N) Schematic diagram\nillustrating the experimental design of TUDCA treatment in Fxrfl/fl and Fxr△IE mice under co-\ntreatment with Neu5Ac and DHEA. (O) GTT and ITT assays in the different treatment groups (n =\n5). *p < 0.05, **p < 0.01, and ***p < 0.001 indicate significant differences between the TUDCA +\nNeu5Ac + DHEA + Fxrfl/fl group and the Neu5Ac + DHEA + Fxrfl/fl group; #p < 0.05, ##p < 0.01,\nand ###p < 0.001 indicate significant differences between the Neu5Ac + DHEA + Fxr△IE group and\nthe Neu5Ac + DHEA + Fxrfl/fl group. (P) Representative H&E-stained ovarian tissue sections from\neach group (scale bar: 200 μm). (Q) Quantification of cystic follicles and corpora lutea (n = 5). Data\nare presented as mean ± SD. *p < 0.05, **p < 0.01, and ***p < 0.001 indicate statistical significance\nby one-way ANOVA followed by Tukey’s post hoc test (A–D, G, I, K, M, O and Q) and two-tailed\nunpaired Student’s t-test (E).\nLine 234-238: We confirmed that the Neu5Ac- and L. sa-mediated reduction in IL-22 is mediated\nby bile acid-regulated FXR activation, as inhibition of BSH or FXR inhibition alleviated the decline\nin IL-22 caused by Neu5Ac and DHEA co-treatment (Fig. 6E and F). Moreover, TUDCA treatment\nreversed the reduction in IL-22 levels induced by Neu5Ac and DHEA co-treatment in Fxrfl/fl mice,\nwhereas this effect was abolished in Fxr△IE mice (Fig. 6G).\nFig. 6. Increased FXR activation exacerbates PCOS by inhibition of IL-22 production. (E–G)\nIleal mRNA levels of Il-22 and Reg3β, and serum IL-22 levels in CAPE- (E) and Gly-β-MCA-\ntreated mice (F), and TUDCA-treated Fxr△IE mice (G, n = 5).\nLine 243-248: Since bile acid-mediated TGR5 activation regulates IL-22 production and is involved\nin PCOS pathogenesis, we investigated whether the TUDCA-mediated increase in IL-22 was\nregulated by TGR5 activation. To this end, TUDCA-treated mice were subjected to TGR5 inhibition\nusing SBI-115 24,25. However, TGR5 inhibition by SBI-115 did not affect the TUDCA-mediated\nincrease in IL-22 (Fig. S7D) or the alleviation of PCOS in mice (Fig. S7E–J).\nFig. S7. Inhibition of TGR5 does not affect TUDCA-mediated IL-22 production or protection\nagainst PCOS in mice. (C) Schematic diagram illustrating the experimental design of SBI-115\ntreatment in the context of TUDCA, Neu5Ac, and DHEA administration. Mice were orally\nadministered SBI-115 (80 mg/kg/day) for 21 days, concurrently with daily TUDCA, Neu5Ac, and\nsubcutaneous DHEA (60 mg/kg) treatments. (D) Ileal mRNA levels of Il-22 and Reg3β, and serum\nIL-22 levels in the indicated mice (n = 5). (E) GTT and ITT assays in the different treatment groups\n(n = 5). *p < 0.05, **p < 0.01, and ***p < 0.001 indicate significant differences between the TUDCA\n+ Neu5Ac + DHEA group and the Neu5Ac + DHEA group; #p < 0.05 and ##p < 0.01 indicate\nsignificant differences between the TUDCA + Neu5Ac + DHEA + SBI-115 group and the Neu5Ac\n+ DHEA group. (F and G) Estrous cycle assessment based on vaginal cytology (n = 5). (H)\nRepresentative H&E-stained ovarian tissue sections from each group (scale bar: 200 μm). (I)\nQuantification of cystic follicles and corpora lutea (n = 5). (J) Serum testosterone and LH levels in\nthe indicated groups (n = 5). Data are presented as mean ± SD. Statistical significance was\ndetermined by one-way ANOVA followed by Tukey’s post hoc test (A, B, D, E, F, G, H, I, and J);\n*p < 0.05, **p < 0.01, ***p < 0.001.\nReviewer #2 (Remarks to the Author):\nComment 1: The role of the gut microbiota in PCOS progression remains unclear. Although the\ngut microbiome differs in individuals with PCOS, these differences alone do not establish a causal\nrole in disease development. Drug treatments are known to alter the gut microbiota, further\ncomplicating interpretation and weakening arguments for causation. A major limitation of both\npreclinical and clinical studies is the lack of in-depth mechanistic investigation into how gut\nmicrobiota might interact with androgen excess. While elevated androgens may contribute to\ndysbiosis, evidence that gut microbiota alterations can drive PCOS pathophysiology is scarce, if not\nentirely absent. For this reason, the statement that “the gut microbiota has been recognized as an\nimportant modulator of PCOS pathogenesis” overstates the current evidence base.\nThat said, I appreciate the authors’ ambitious approach in this manuscript, particularly their efforts\nto dissect mechanistic underpinnings. The authors present evidence for an intriguing pathway in\nwhich Ligilactobacillus influences Neu5Ac availability, thereby altering bile acid metabolism. This\nshift activates intestinal FXR signaling, ultimately reducing IL-22 production. Diminished\ncirculating IL-22 may have systemic consequences, including impaired ovarian function. These\nfindings suggest a promising therapeutic opportunity targeting the bile acid–FXR–IL-22 axis for the\ntreatment of PCOS.\nResponse 1: We gratefully acknowledge the reviewer for the valuable time spent providing\nconstructive comments. We have reworded this description to avoid overstatement. Thank you again\nfor your feedback.\nLine 25: Additionally, the gut microbiota has been implicated in PCOS pathogenesis.\nLine 374-382:\nLimitations of the study\nAlthough we have elucidated the crucial roles of Neu5Ac-mediated bile acid metabolism and FXR\nactivation in the pathogenesis of PCOS, the specific bacterial sources or host tissues responsible for\nNeu5Ac production remain unclear. The mechanisms underlying the interaction between gut\nmicrobiota and hormonal fluctuations in PCOS, as well as how this process is regulated by Neu5Ac,\nare still unknown. Moreover, the contribution of metabolic alterations beyond bile acid\ndysregulation to Neu5Ac-mediated PCOS progression remains to be determined. Future studies\nshould investigate the precise regulatory mechanisms by which Neu5Ac modulates the gut\nmicrobiota and assess the therapeutic potential of targeting this pathway in PCOS.\nSuggestions for revision.\nComment 2: The introduction is too long.\nResponse 2: We sincerely thank you for your careful consideration. In accordance with the\nreviewers' suggestions, we have shortened the Introduction section of the manuscript. We appreciate\nyour feedback once again.\nLine 19-67: Introduction\nPolycystic ovary syndrome (PCOS) is a prevalent endocrine disorder characterized by ovarian\ndysfunction and insulin resistance, adversely affecting ovarian health and female reproductive\nfunction. In PCOS, the ovary exhibits increased inflammation, oxidative stress, and cell death,\nincluding ferroptosis. Deficiency of glutathione peroxidase 4 (GPX4), a key regulator of redox\nhomeostasis during ferroptosis, exacerbates ferroptosis and contributes to endometrial epithelial\nfibrosis in PCOS. Additionally, the gut microbiota has been implicated in PCOS pathogenesis. For\ninstance, patients with PCOS exhibit significant gut dysbiosis, particularly elevated levels of fecal\nBacteroides vulgatus (B. vulgatus), and administration of B. vulgatus induces PCOS-like symptoms\nin mice. Modulation of the gut microbiota through inulin and tempol treatment alleviates PCOS and\nassociated metabolic disturbances. However, the roles of specific microbial species in PCOS\npathogenesis remains poorly understood.\nGut microbiota-derived metabolites are key mediators that regulate the crosstalk between the\nintestinal microbiota and the host. For example, patients with PCOS exhibit altered bile acid profiles,\nparticularly increased levels of non-conjugated bile acids and reduced levels of conjugated bile acids\nsuch as glycodeoxycholic acid (GDCA) and tauroursodeoxycholic acid (TUDCA). Treatment of\nmice with GDCA and TUDCA ameliorates PCOS by increasing interleukin-22 (IL-22) levels, which\nmay be attributed to enhanced IL-22 production and subsequent activation of signal transducer and\nactivator of transcription 3 (STAT3). Conjugated bile acids can be converted into non-conjugated\nforms by gut microbiota through bile salt hydrolase (BSH) activity, and bacterial genera enriched in\nPCOS patients—such as Bacteroides and Lactobacillus—exhibit high BSH expression. Notably,\nconjugated bile acids, including TUDCA, and GDCA, typically act as antagonists of farnesoid X\nreceptor (FXR). Enhanced intestinal FXR activation promotes the development of metabolic\ndisorders through multiple mechanisms, such as promoting ceramide synthesis. Additionally, gut-\nspecific FXR activation reduces IL-22 levels by promoting intestinal epithelial ferroptosis and lipid\nperoxide accumulation. Inhibition of BSH activity or intestinal FXR signaling exerts beneficial\neffects against metabolic syndrome and pathological cell death.\nAlthough gut microbiota-derived metabolites directly influence metabolic health and the\ndevelopment of PCOS, little is known about how microbial metabolism reciprocally affects gut\nhomeostasis. For example, alterations in the gut microbiota and the presence of gut inflammation\nincrease the release of free N-acetylneuraminic acid (Neu5Ac, also known as sialic acid), a 9-carbon\nmonosaccharide located on the outer layer of the intestinal mucosa. This release exacerbates gut\ndysbiosis, promotes intestinal inflammation, and contributes to extraintestinal diseases such as\nmastitis. Bacteroides efficiently produces free sialic acid via its sialidase enzyme but lacks the\ncapacity to utilize sialic acid for growth. In contrast, commensal Lactobacillus and opportunistic\npathobionts such as Escherichia/Shigella can exploit sialic acid as a carbon source to support their\nproliferation in the gut, thereby influencing disease outcomes. However, it remains unclear whether\nBacteroides-derived sialic acid facilitates the expansion of Lactobacillus and Escherichia/Shigella\nand thereby promotes the development of PCOS.\nIn this study, we found that patients with PCOS exhibited elevated fecal Neu5Ac levels, which\nexacerbated PCOS in a gut microbiota-dependent manner. Specifically, Neu5Ac treatment promoted\nthe expansion of the gut Ligilactobacillus salivarius (L. sa) and increased BSH activity, thereby\nreducing levels of the conjugated bile acid TUDCA, enhancing intestinal FXR activation, and\nsuppressing IL-22 release. This cascade ultimately aggravates PCOS by promoting ovarian\nferroptosis through modulation of STAT3 signaling. These findings indicate that sialic acid\npromotes gut dysbiosis and FXR activation, thereby exacerbating PCOS outcomes.\nComment 3: Refrain to use the term healthy controls, healthy group or healthy individuals. They\nmay have other conditions although not PCOS. Controls is an appropriate term.\nResponse 3: We thank you for your comprehensive consideration and constructive comments. In\nthe revised manuscript, we have replaced the term \"healthy controls\" with \"control\" in accordance\nwith the reviewer's suggestion. We appreciate your feedback once again.\nLine 71-73: To investigate metabolic alterations associated with PCOS, fecal samples were\ncollected from 16 PCOS patients (P) and 16 controls (C) for untargeted metabolomics analysis\n(clinical characteristics are provided in Supplementary Table 1).\nComment 4: Fig. 1C. Present all differently expressed metabolites as supplemental material.\nResponse 4: We sincerely thank you for your valuable comments. We have provided a complete\nlist of differential metabolites in Supplementary Table 2. We appreciate your feedback once again.\nComment 5: Fig 1G-M. Neu5Ac exposure alone does not have an effect in mice with a normal gut\nflora. How can this be explained? Why is the combination with DHEA necessary for an effect?\nResponse 5: We gratefully acknowledge your constructive comments. We have included a\ndiscussion addressing why Neu5Ac alone does not exert significant effects on PCOS, whereas it\nexacerbates the condition in the context of DHEA-induced PCOS. We appreciate your feedback\nonce again.\nLine 313-322: Administration of Neu5Ac alone had minimal effects on PCOS in the absence of\nDHEA treatment, but significantly exacerbated DHEA-induced PCOS in mice. Notably, we found\nthat Neu5Ac-mediated exacerbation of PCOS was dependent on the gut microbiota, as demonstrated\nby antibiotic depletion and FMT experiments—despite reports that Neu5Ac can directly induce\nsystemic immune exhaustion and accelerate memory deficits in diet-induced obese Alzheimer’s\ndisease mouse models 27. These findings suggest that although exogenous Neu5Ac can alter the\ncomposition of the intestinal microbiota, the dynamic regulation of the normal gut microbiota may\ncounteract its impact on PCOS development. Similarly, Neu5Ac exerts effects on intestinal\ninflammation and mastitis progression only under conditions of intestinal microbiota disruption\n19,20.\nComment 6: Do not cut the axes in graphs as this is misleading.\nResponse 6: We sincerely thank you for your valuable comment. In accordance with the reviewers'\nsuggestions, we have made every effort to avoid truncating the axes while ensuring the readability\nof the presented data. We appreciate your feedback once again.\nComment 7: Double-check the statistics in Fig 2B, is this really a significant difference? The curves\nare basically on top of each other.\nResponse 7: We apologize for our oversight. We have corrected this error. We sincerely appreciate\nyour suggestion.\nFig. S1. Neu5Ac exacerbates DHEA-induced PCOS in a gut microbiota-dependent manner in\nmice. (I) GTT assay and area under the curve (AUC) analysis in the different treatment groups (n =\n5).\nComment 8: Check this statement on line 184: We next quantified different Ligilactobacillus\nspecies using qPCR and found that Ligilactobacillus salivarius (L. sa), but not L. reuteri or L.\nrhamnosus, was elevated in Neu5Ac- and N-FMT-treated mice, as well as in PCOS patients (Fig.\n4F–H and S2D–F). I belive it should be that Ligilactobacillus salivarius was elevated in\nNeu5Ac+DHEA exposed mice. Moreover, L. reuteri and L. rhamnosus, seems to be elevated in\nNeu5Ac+DHEA and N-FMT-treated mice (S2D-E).\nResponse 8: We gratefully acknowledge your comments. We have reworded these descriptions\nbased on the reviewer's feedback. We appreciate your input once again.\nLine 146-151: We next quantified different Ligilactobacillus species using qPCR and found that\nLigilactobacillus salivarius (L. sa) was elevated in Neu5Ac+DHEA-exposed mice and N-FMT-\ntreated mice (Fig. 3E and F). Moreover, L. reuteri and L. rhamnosus appeared to be increased in\nNeu5Ac+DHEA- and N-FMT-treated mice (Fig. S3E and F). However, only L. sa abundance was\nsignificantly increased in PCOS patients compared with the control group (Fig. 3G and S3G).\nComment 9: Check labelling of groups in Fig 6B.\nResponse 9: We apologize for our oversight and the inconvenience caused to the reviewer. We have\nrevised this issue and carefully reviewed all figures. We appreciate your feedback once again.\nComment 10: Glucose curves following ITT and GTT should be analyzed using repeated\nmeasurement ANOVA with appropriate correction for multiple groups.\nResponse 10: We thank you for your rigorous consideration. In response to the reviewer's comment,\nwe have reanalyzed the ITT and GTT curves. We appreciate your feedback once again.\nFig. 1. Neu5Ac exacerbates DHEA-induced PCOS in a gut microbiota-dependent manner in\nmice. (I) GTT and ITT assays in the indicated mouse groups (n = 5). *p < 0.05, **p < 0.01, and\n***p < 0.001 indicate significant differences between the DHEA group and the control group. #p <\n0.05 indicates significant differences between the Neu5Ac + DHEA group and the DHEA group.\nData are presented as mean ± SD. *p < 0.05, **p < 0.01, and ***p < 0.001 indicate statistical\nsignificance by two-tailed unpaired Student’s t-test (C-E, G, M, N and P), and one-way ANOVA\nfollowed by Tukey’s post hoc test (I and J).\nComment 11: Include the statistics used in all graphs in the figure legend. For example, the statistics\nused in 1D is missing.\nResponse 11: We sincerely thank you for your constructive suggestions. We have included all\nstatistical information used in the graphs within the figure legends. We appreciate your feedback\nonce again.\nFig. 1. Neu5Ac exacerbates DHEA-induced PCOS in a gut microbiota-dependent manner in\nmice. (A) PCA score plots revealed distinct metabolic differences between the control and PCOS\ngroups (n = 16). *p < 0.05 by Adonis. (B) Volcano plots identified 332 upregulated and 274\ndownregulated metabolites in the PCOS group compared to the control group; N-acetylneuraminic\nacid (Neu5Ac) was highlighted. (C) Boxplots showing the relative abundances of the 20 most\nabundant fecal metabolites in the control and PCOS groups (n = 16). (D and E) Fecal Neu5Ac levels\nin healthy individuals and PCOS patients (D, Cohort 1, n = 16; E, Cohort 2, n = 14-19). (F)\nCorrelations between stool and serum Neu5Ac levels and clinical characteristics, as determined by\nSpearman’s rank correlation test. (G) Fecal Neu5Ac levels in DHEA-treated mice (n = 6). (H)\nSchematic diagram illustrating the experimental design of Neu5Ac treatment. Mice were fed a\nstandard AIN93G diet and supplemented with 1% Neu5Ac in drinking water, along with oral gavage\nof 1 mg/200 μL Neu5Ac twice daily for 21 days, concurrently with daily DHEA (60 mg/kg)\nadministration. (I) GTT and ITT assays in the indicated mouse groups (n = 5). *p < 0.05, **p < 0.01,\nand ***p < 0.001 indicate significant differences between the DHEA group and the control group.\n#p < 0.05 indicates significant differences between the Neu5Ac + DHEA group and the DHEA group.\n(J) Estrous cycle assessment based on vaginal cytology. P, proestrus; E, estrus; M, metestrus; D,\ndiestrus. (K) Representative H&E-stained ovarian tissue sections from each group (scale bar: 200\nμm). Arrows indicate cystic follicles, and asterisks mark corpora lutea. (L) Schematic diagram\nillustrating the fecal microbiota transplantation (FMT) experiment. Recipient mice were treated with\na cocktail of antibiotics (200 mg/kg body weight (BW)/day for ampicillin, neomycin, and\nmetronidazole; 100 mg/kg BW/day vancomycin) for 6 days, followed by a 1-day washout period\nwith regular water, and then subjected to FMT for 7 days prior to initiation of Neu5Ac and DHEA\n(60 mg/kg) treatment, with antibiotic-free water maintained throughout the subsequent experimental\nperiod. (M) GTT and ITT assays in the different treatment groups (n = 5). (N) Estrous cycle\nassessment based on vaginal cytology (n = 5). (O) Representative H&E-stained ovarian tissue\nsections from each group (scale bar: 200 μm). (P) Quantification of cystic follicles and corpora lutea\nbased on H&E-stained ovarian sections (n = 6). Data are presented as mean ± SD. *p < 0.05, **p <\n0.01, and ***p < 0.001 indicate statistical significance by two-tailed unpaired Student’s t-test (C-E,\nG, M, N and P), and one-way ANOVA followed by Tukey’s post hoc test (I and J).\nMaterial and methods\nComment 12: Describe the clinical cohort in more detail. Include, age, weight, BMI, androgen\nlevels, LH, FSH, FG-score, ovarian morphology, insulin and glucose levels etc.\nResponse 12: We thank you for your rigorous consideration. We have added the details regarding\nthe clinical cohort. We appreciate your feedback once again.\nLine 71-73: To investigate metabolic alterations associated with PCOS, fecal samples were\ncollected from 16 PCOS patients (P) and 16 controls (C) for untargeted metabolomics analysis\n(clinical characteristics are provided in Supplementary Table 1).\nSupplementary Table 1. Cohort 1 clinical characteristics in women with or without PCOS.\nControl (n=16) PCOS(n=16) P value\nAge (year) 29.0 ± 0.55 29.7 ± 0.77 0.4672\nBody Mass Index 22.6 ± 0.24 23.1 ± 0.30 0.2293\nWaist-Hip ratio 0.83 ± 0.01 0.84 ± 0.01 0.3187\nFerriman-Gallwey score 0.25 ± 0.11 3.25 ± 0.25 < 0.0001\nFSH (mIU/mL) 6.67 ± 0.16 6.06 ± 0.20 0.0265\nLH (mIU/mL) 4.82 ± 0.06 8.14 ± 0.13 < 0.0001\nLH/FSH 0.73 ± 0.02 1.36 ± 0.05 < 0.0001\nEstradiol (pg/mL) 51.7 ± 3.39 61.9 ± 3.70 0.0505\nTestosterone (ng/mL) 0.44 ± 0.02 0.61 ± 0.02 < 0.0001\nAndrostenedione (ng/mL) 2.27 ± 0.17 4.18 ± 0.21 < 0.0001\nDHEAs (ng/mL) 2264 ± 98 2902 ± 159 0.0019\nFasting glucose level 4.46 ± 0.20 5.07 ± 0.10\n(mmol/L) 0.0117\nFasting insulin level (μIU/mL) 5.96 ± 0.50 9.84 ± 0.89 0.0006\nHOMA-IR 1.23 ± 0.15 2.26 ± 0.23 0.0008\nFSH, follicle-stimulating hormone; LH, luteinizing hormone; DHEAs, dehydroepiandrosterone\nsulfate; HOMA-IR, insulin resistance index. All data are expressed as the mean ± sem. Data were\nanalyzed by two-tailed Student’s t test (for two groups).\nComment 13: Testosterone should not be measured by ELISA or RIA since they are unspecific.\nTanden mass spectrometry should be used for accurate measurements of androgens in humans and\nmice.\nResponse 13: We thank you for your rigorous consideration. In accordance with the reviewer's\nsuggestion and relevant literature, we have remeasured testosterone levels. We appreciate your\nfeedback once again.\nLine 472-481:\nSerum biochemical assays\nPeripheral blood samples were processed using standardized pre-analytical procedures to ensure\nanalyte stability. Blood samples were centrifuged at 1,000 × g for 5 min at 4 °C, after which serum\nwas collected and combined with freshly obtained fecal samples; both were then aliquoted and\nimmediately snap-frozen at −80 °C for batch analysis at a later time. Clinically relevant parameters\nwere measured using previously established methods. Luteinizing hormone and follicle-stimulating\nhormone concentrations were determined by radioimmunoassay. Circulating levels of estradiol,\ntestosterone, and androstenedione were quantified using liquid chromatography–tandem mass\nspectrometry (LC–MS/MS) on a Sciex Triple Quad 6500+ system. Glucose homeostasis was\nevaluated by calculating the homeostatic model assessment of insulin resistance (HOMA-IR) index\nusing the standard formula: fasting blood glucose (mmol L−1) × fasting insulin (μIU mL−1) / 22.5."}, {"round": 2, "reviewer_comments": {"reviewer_1": "It’s OK for me.", "reviewer_2": "Thank you for the revised manuscript. Although large improvements there are still a few points that\nthe authors have not addressed or changed properly.\nComment 1:\nWhile elevated androgens may contribute to dysbiosis, evidence that gut microbiota alterations can drive\nPCOS pathophysiology is scarce, if not entirely absent. For this reason, the statement that “the gut microbiota has been\nrecognized as an important modulator of PCOS pathogenesis” overstates the current evidence base.\nResponse 1: We gratefully acknowledge the reviewer for the valuable time spent providing constructive comments. We have\nreworded this description to avoid overstatement. Thank you again for your feedback.\nLine 25: Additionally, the gut microbiota has been implicated in PCOS pathogenesis.\nTrue phrasing line 24: Accumulating evidence indicates that gut dysbiosis and metabolic disturbances are closely\nassociated with the pathogenesis of PCOS.\nand\nLine 69: Although gut microbiota-derived metabolites directly influence metabolic health and the\ndevelopment of PCOS, little is known about how microbial metabolism reciprocally affects gut\nhomeostasis. There are no references after this statement. Which are the studies showing that gut microbiota-derived\nmetabolites directly influence the development of PCOS? I still think these statements are too strong.\nComment 6: Do not cut the axes in graphs as this is misleading.\nResponse 6: We sincerely thank you for your valuable comment. In accordance with the reviewers' suggestions, we have\nmade every effort to avoid truncating the axes while ensuring the readability of the presented data. We appreciate your\nfeedback once again."}, "author_response": "Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled\n“Sialic acid exacerbates polycystic ovary syndrome in female mice by modulating gut\nmicrobiota-mediated bile acid metabolism and FXR activation” (NCOMMS-25-82445A).\nThese comments are all valuable and very helpful for revising and improving our paper, as well as\nthe important guiding significance to our researches. We have addressed all the concerns raised by\nreviews. Below are our responses to the editors' and reviewers' comments.\nIn order to facilitate the review, the blue font indicates reviewer’s comments, the black font indicates\nthe responses to reviewers, and the red font indicates the modification in the revised manuscript.\nThe responds to the reviewer’s comments are as follows:\nPoint-by-point response.\nReviewer #2 (Remarks to the Author):\nThank you for the revised manuscript. Although large improvements there are still a few points that\nthe authors have not addressed or changed properly.\nComment 1: True phrasing line 2-4: Accumulating evidence indicates that gut dysbiosis and\nmetabolic disturbances are closely associated with the pathogenesis of PCOS.\nLine 69: Although gut microbiota-derived metabolites directly influence metabolic health and the\ndevelopment of PCOS, little is known about how microbial metabolism reciprocally affects gut\nhomeostasis. There are no references after this statement. Which are the studies showing that gut\nmicrobiota-derived metabolites directly influence the development of PCOS? I still think these\nstatements are too strong.\nResponse 1: We gratefully acknowledge the reviewer for the valuable time spent providing\nconstructive comments. Studies have reported that gut dysbiosis and associated metabolic\ndisturbances can contribute to PCOS pathogenesis independently of DHEA administration. For\nexample, patients with PCOS had elevated levels of fecal Bacteroides vulgatus (B. vulgatus), and\nadministration of B. vulgatus induces PCOS-like symptoms in mice by reducing GDCA levels and\nlimiting IL-22 release (Nat Med. 2019. PMID: 31332392). Moreover, B. vulgatus-derived agmatine\ncauses PCOS through reducing GLP-1 level via activating FXR (Nat Metabolism. 2024. PMID:\n38769396). Additionally, Aspergillus tubingensis-derived AT-C1 induces PCOS in mice by\nsuppressing AhR-mediated IL-22 production (Cell Host Microbe. 2025. PMID: 39788092). We\nhave added references for gut microbiota-derived metabolites in the pathogenesis of PCOS, and\nreworded these descriptions mentioned by the reviewer. Thank you again for your valuable\ncomments.\nLine 2-4: Accumulating evidence indicates that gut dysbiosis and metabolic disturbances are\nassociated with the pathogenesis of PCOS.\nLine 48-52: Although gut microbiota-derived metabolites directly influence metabolic health and\nthe development of PCOS—such as agmatine produced by B. vulgatus, which promotes PCOS via\nFXR activation 7, and AT-C1, a metabolite derived from Aspergillus tubingensis, which induces\nPCOS by suppressing IL-22 production 8—the reciprocal impact of microbial metabolism on gut\nhomeostasis remains poorly understood.\nComment 2: The truncated axis for AUC is still misleading. There is no difference in ITT or GTT\nbut the truncated axis implicates that there could be a trend. Please change this. Use the same scale\nfor AUC for GTT and ITT respectively. In supplemental Figure 1 for example the axes are different\nin S1C and S1I and J. Be consistent so the reader easily can judge the data between different cohorts\nof animals, in all figures.\nResponse 2: We thank you for your comprehensive consideration and constructive comments. We\nhave corrected all axis for AUC to avoid misleading by using same scale. We appreciate your\nfeedback once again.\nFig. S1. Neu5Ac exacerbates DHEA-induced PCOS in a gut microbiota-dependent manner in\nmice. (C) GTT and ITT area under the curve (AUC) analysis (n = 5). (I) GTT assay and area under\nthe curve (AUC) analysis in the different treatment groups (n = 5). (J) ITT assay and AUC analysis\nin the different treatment groups (n = 5).\nComment 3: Glucose curves following ITT and GTT should be analyzed using repeated measures-\nANOVA with appropriate correction for multiple groups when comparing more than two groups.\nThis will give you one p-value for the whole curve, not one at each time point. Alternatively, use\nlinear mixed-effects model (LMM).\nThe legend and graphs show that a single p-value is generated for each time point which is the case\nwith a one-way ANOVA.\nResponse 3: We thank you for your rigorous consideration and constructive comments. We have\nreanalyzed GTT and ITT assays by using two-way repeated-measures ANOVA with Sidak’s\nmultiple-comparisons correction. We appreciate your feedback once again.\nFig. 1. Neu5Ac exacerbates DHEA-induced PCOS in a gut microbiota-dependent manner in\nmice. (I) GTT and ITT assays in the indicated mouse groups (n = 5). #p < 0.05 indicates significant\ndifferences between the Neu5Ac + DHEA group and the DHEA group. *p < 0.05, **p < 0.01, and\n***p < 0.001 indicate statistical significance by two-tailed unpaired Student’s t-test (C-E, G, N and\nP), and two-way repeated-measures ANOVA with Sidak’s multiple-comparisons correction (I and\nM).\nLine 644-647:\nStatistical analysis\nTwo-way repeated-measures ANOVA with Sidak’s multiple-comparisons correction was used to\nanalyze the GTT and ITT assays. For these assays, p values with a bracket line connecting two\ngroups refer to the whole curves and p values on top of individual datapoints refer only to indicated\ntime point."}, {"round": 3, "reviewer_comments": {"reviewer_2": "I think that the authors have adequately addressed the comments made by the reviewers in the\nrevised version of the manuscript. Therefore, I have no further comments."}, "author_response": "Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled\n“Sialic acid exacerbates polycystic ovary syndrome in female mice by modulating gut\nmicrobiota-mediated bile acid metabolism and FXR activation” (NCOMMS-25-82445B).\nThese comments are all valuable and very helpful for revising and improving our paper, as well as\nthe important guiding significance to our researches. We have addressed all the concerns raised by\nreviews. Below are our responses to the editors' and reviewers' comments.\nIn order to facilitate the review, the blue font indicates reviewer’s comments, the black font indicates\nthe responses to reviewers, and the red font indicates the modification in the revised manuscript.\nThe responds to the reviewer’s comments are as follows:\nPoint-by-point response.\nReviewer #2 (Remarks to the Author):\nComment: I think that the authors have adequately addressed the comments made by the reviewers\nin the revised version of the manuscript. Therefore, I have no further comments.\nResponse: We gratefully acknowledge the reviewer for the valuable time spent providing\nconstructive comments and for their positive evaluation of our article."}]

Decision letter