Microbiome analysis of the cystic fluid in ovarian endometrioma: new avenues for the prevention, diagnosis, and treatment of the disease

Objective This study aimed to investigate the microbiome profile in the cystic fluid of ovarian endometrioma and explore its association with the microbial communities present in the lower and upper reproductive tracts. Design A microbial analysis was conducted across multiple compartments of the reproductive tract in patients diagnosed with ovarian endometrioma. Subjects Sixteen female patients aged 25–43 years (mean age: 31.56 years) who underwent laparoscopic surgery for ovarian endometrioma at the First Hospital of Putian City between April 2023 and February 2024 were enrolled in this study. Main outcome measures 16S rDNA sequencing was employed to characterize the microbiome of ovarian endometrioma and assess its correlations with clinical symptoms, inflammatory markers, and serum CA125 levels

Microbial communities were detected in the posterior vaginal fornix, endometrial fluid, peritoneal fluid, and cystic fluid, exhibiting distinct compositional profiles. Community diversity significantly increased along the anatomical gradient from the posterior vaginal fornix to endometrial fluid, peritoneal fluid, and cystic fluid, with the highest microbial diversity observed in the cystic fluid. Lactobacillus was the predominant genus in the posterior vaginal fornix, whereas Escherichia-Shigella was most abundant in endometrial fluid samples. Hydrogenophaga and Brevundimonas were the dominant taxa in both peritoneal and cystic fluids. Notably, the microbial composition of peritoneal fluid showed the greatest similarity to that of cystic fluid, and functional prediction analyses indicated largely overlapping biological functions between these two sites. Furthermore, Spearman correlation analysis revealed significant associations between specific microbial taxa and certain clinical manifestations or inflammatory factors.

This study demonstrates the presence of a unique and highly diverse microbiome within the cystic fluid of ovarian endometrioma. The site-specific microbial profiles and their correlations with clinical parameters suggest a potential role of microbiota in disease pathogenesis through inflammatory and metabolic mechanisms. These findings contribute novel insights that may inform future strategies for the prevention, diagnosis, and treatment of ovarian endometrioma. Similar content being viewed by others

Ovarian endometrioma (OMA) is one of the most prevalent benign gynecologic conditions, affecting an estimated 10–20% of women of reproductive age. It arises from recurrent hemorrhage of ectopic endometrial tissue within the ovarian cavity, leading to the accumulation of degraded blood products that are subsequently encapsulated by surrounding ovarian parenchyma [1]. OMA is most prevalent among women aged 40 to 44 years, with disease incidence declining after menopause [2]. It is associated with a range of clinical consequences, including subfertility, chronic pelvic pain, complications such as cyst rupture, an increased risk of malignant transformation, and substantial impairment of quality of life [3]. Laparoscopic cystectomy has become the gold standard for both diagnosis and surgical management of ovarian endometriosis, aiming to excise lesions, restore normal pelvic anatomy, and enable histopathological confirmation. However, this procedure may compromise ovarian reserve [4]. The recurrence rate following conservative laparoscopic surgery remains high, with reported rates of 21.5% at two years and 40–50% at five years postoperatively across all age groups [5, 6]. Two proposed pathogenic mechanisms for endometrioma formation include the invasion or metaplastic transformation of preexisting functional ovarian cysts by endometriotic tissue, and direct hemorrhage of ovarian endometriotic implants into the ovarian cortex [3]. Despite extensive research into the initiation and progression of ovarian endometrioma, many aspects of its underlying mechanisms remain unclear, and its precise etiology has yet to be fully elucidated. As the most common subtype of endometriosis, ovarian endometrioma affects up to 44% of women diagnosed with endometriosis worldwide [7]. Endometriosis (EMS) is recognized as a chronic inflammatory condition whose etiology and pathogenesis are not fully understood. Accumulating evidence suggests that it is closely linked to immune dysregulation, inflammatory responses, and endocrine disturbances. Emerging studies indicate that the microbiome may play a pivotal role in the development and progression of endometriosis [8]. Specifically, microbial communities may contribute to disease pathogenesis through multiple interconnected pathways, including promotion of inflammation and estrogen-mediated hormonal imbalances, modulation of cell proliferation and apoptosis, metabolic alterations, induction of oxidative stress, and stimulation of angiogenesis and vascularization. Dysbiosis—characterized by imbalances in the composition of gut and reproductive tract microbiota—can disrupt immune homeostasis, leading to elevated levels of pro-inflammatory cytokines, impaired immune surveillance, and altered profiles of immune cells, all of which may facilitate the onset and persistence of endometriosis [9, 10]. The female reproductive tract is a continuous anatomical system, allowing cervicovaginal bacteria to ascend into the uterus. However, this microbial transit is constrained by physical, chemical, and microbial barriers within the cervix [11, 12]. Uncontrolled ascent of cervicovaginal microbiota into the upper reproductive tract may trigger inflammatory responses that contribute to pathological conditions such as endometriosis. In 2017, Chen et al. utilized next-generation 16S rRNA gene sequencing to demonstrate the persistent presence of distinct microbial communities throughout the female reproductive tract—including the cervical canal, uterus, fallopian tubes, and peritoneal fluid [13]. Subsequent metagenomic analyses elucidated the structural and functional profiles of these microbial populations in the upper genital tract. Evidence suggests that the genital microbiome may influence the pathogenesis and symptomatology of endometriosis by promoting elevated levels of pro-inflammatory mediators. Based on these findings, it is plausible that microorganisms also play a significant role in the development of ovarian endometrioma. Nevertheless, the microbiome composition within the cystic fluid of ovarian endometriomas and its potential relationship with microbial communities in the lower and upper reproductive tracts remain poorly characterized. This study aimed to characterize the microbiome profile in the cystic fluid of ovarian endometrioma using 16S rDNA sequencing and to investigate its association with microbiomes from the lower and upper reproductive tracts.Systematically examine the microbial distribution in the cystic fluid of patients with ovarian endometrioma, offering novel insights that may inform future strategies for prevention, diagnosis, and treatment.

Study participants Ethical approval was obtained from the Medical Ethics Committee of the First Hospital of Putian City, and written informed consent was provided by all participants. Sixteen women aged 25–43 years (mean age: 31.56 years) undergoing laparoscopic surgery for ovarian endometrioma between April 2023 and February 2024 at the First Hospital of Putian City were enrolled. All participants had regular menstrual cycles and were aged between 18 and 44 years. Eight cases were classified as stage III and eight as stage IV according to the revised American Society for Reproductive Medicine (rASRM) classification established in 1997. Histopathological confirmation of ovarian endometrioma was obtained in all cases, and none had coexisting acute infections, malignant tumors, or autoimmune diseases. Additionally, participants had not received hormonal therapy, antibiotics, or vaginal medications within six months and three months prior to enrollment, respectively. Clinical symptoms and serum biomarkers are summarized in Supplementary Table 1. Sample collection and treatment Samples were collected 3–7 days after menstruation, during the early follicular phase, from four anatomical sites within the reproductive tract. The lower reproductive tract sample was obtained from the posterior fornix of the vagina (CU), collected before any intervention using a sterile swab rotated gently for 3–5 cycles. Secretions were stored in 2 ml tubes. For upper reproductive tract sampling, endometrial fluid (EF), peritoneal fluid (PF), and cystic fluid (CF) were collected intraoperatively. After thorough cleaning of the cervical os and ectocervix, EF was aspirated using an intrauterine insemination (IUI) catheter (Kitazato Corporation, Shizuoka, Japan), ensuring no contact with the vaginal walls, and transferred into 2 ml tubes. Approximately 10 ml of PF was collected from the Douglas pouch during surgery. Following irrigation of the ovarian cyst surface with sterile saline, 10 ml of CF was extracted via peritoneal puncture needle and placed in 15 ml centrifuge tubes. All samples were immediately flash-frozen in dry ice post-collection and transported to the research center for storage at − 80 °C until further processing. Sample microbial genome DNA extraction and detection DNA from different samples was extracted using the CTAB according to manufacturer ’s instructions. The reagent which was designed to uncover DNA from trace amounts of sample has been shown to be effective for the preparation of DNA of most bacteria. Nuclear-free water was used for blank. The total DNA was eluted in 50 µL of Elution buffer and storedat − 80 °C until measurement in the PCR. PCR amplification and 16S rDNA sequencing The V3-V4 region of the 16S rDNA genes was amplified by PCR with the universal primers V3-341F (5’-CCTACGGGNGGCWGCAG-3’) and V4-805R (5’-GACTACHVGGGTATCTAATCC-3’).The 5’ ends of the primers were tagged with specific barcods per sample and sequencing universal primers.PCR amplification was performed in a total volume of 25µL reaction mixture containing 25 ng of template DNA,12.5µL PCR Premix,2.5µL of each primer, and PCR-grade water to adjust the volume.The PCR conditions to amplify the prokaryotic 16S fragments consisted of an initial denaturation at 98℃ for 30 s;32cycles of denaturation at 98℃ for 10 s, annealing at 54℃ for 30 s, and extension at 72℃ for 45 s; and then final extension at 72℃ for 10 min.The PCR products were confirmed with 2% agarose gel electrophoresis. Throughout the DNA extraction process, ultrapure water, instead of a sample solution, was used to exclude the possibility of false-positive PCR results as a negative control. The PCR products were purifyied by AMPure XT beads (Beckman Coulter Genomics, Danvers, MA, USA) and quantified by Qubit ( Invitrogen, USA).The amplicon pools were prepared for sequencing and the size and quantity of the amplicon library were assessed on Agilent 2100 Bioanalyzer (Agilent, USA) and with the Library Quantification Kit for Illumina(Kapa Biosciences, Woburn, MA, USA), respectively.The libraries were sequenced on NovaSeq PE250 platform. Data analysis Samples were sequenced on an Illumina NovaSeq platform according to the manufacturer’s recommendations.Paired-end reads was assigned to samples based on their unique barcode and truncated by cutting off the barcode and primer sequence.Paired-end reads were merged using FLASH.Quality filtering on the raw reads were performed under specific filtering conditions to obtain the high-quality clean tags according to the fqtrim (v0.94).Chimeric sequences were filtered using Vsearch software (v2.3.4).After dereplication using DADA2,we obtained feature table and feature sequence (also refer to Amplicon Sequence Variants, ASVs).Alpha diversity and beta diversity were calculated by normalized to the same sequences randomly.Then according to SILVA (https://www.arb-silva.de/documentation/release-138) classifier, feature abundance was normalized using relative abundance of each sample.Alpha diversity is applied in analyzing complexity of species diversity for a sample through 2 indices, including Observed species and Shannon, and all this indices in our samples were calculated with QIIME2.Beta diversity were calculated by QIIME2, the graphs were drew by R package.Blast was used for sequence alignment, and the feature sequences were annotated with SILVA database for each representative sequence.Other diagrams were implemented using the R package (v3.5.2).Spearman’s correlation coefficients were used to assess the correlation between microbiota and disease. P < 0.05 represents statistical significance.

Microbial landscape of the female reproductive tract In this study, we analyzed microbial communities from four anatomical sites—cystic fluid (CF), peritoneal fluid (PF), endometrial fluid (EF), and cervical-vaginal site (CU). A total of 7,726 amplicon sequence variants (ASVs) were identified. Taxonomic classification was performed by comparing ASVs to the SILVA and NT-16S databases using the Naive Bayes consensus classifier, enabling resolution at multiple taxonomic levels: phylum, class, order, family, genus, and species. The average relative abundance of classified bacterial sequences was 99.99%, with unclassified taxa accounting for 0.01%. The dominant bacterial phyla were Proteobacteria, followed by Firmicutes, Actinobacteriota, Bacteroidota, Verrucomicrobiota, and others (Fig. 1A). At the genus level, the most abundant taxa included Lactobacillus, Escherichia-Shigella, Hydrogenophaga, Brevundimonas, and Pseudoalteromonas (Fig. 1B). The top five most prevalent species were Lactobacillus_iners, Brevundimonas_mediterranea, Lactobacillus_crispatus, uncultured_Phenylobacterium_sp., and Caulobacter_sp._NW-2013-Rh15 (Fig. 1C). Microbiome analysis: alpha diversity and beta diversity To assess microbial diversity, we evaluated both richness and evenness across sample sites. Alpha diversity was assessed using observed ASVs (analogous to OTUs) and Shannon indices. Rarefaction curves indicated that species diversity approached saturation with increasing sequencing depth, suggesting that further sequencing would yield minimal additional taxa (Fig. 2A). The average number of observed ASVs was highest in CF samples (219.68), followed by EF (190.65), PF (175.11), and CU (85.70), indicating the greatest microbial richness in cystic fluid. Although CF and EF did not differ significantly in richness, all three upper reproductive tract sites (CF, PF, EF) exhibited significantly higher richness compared to CU (Fig. 2B; Supplementary Table 2). Shannon index values further reflected these patterns, with CF showing the highest diversity (5.51), followed by PF (5.05), EF (3.41), and CU (1.65). These results indicate that the CF microbial community is not only rich but also highly diverse, whereas the CU microbiome is dominated by a limited number of genera. The microbial diversity at PF was comparable to that at CF and significantly higher than at EF and CU. Additionally, a statistically significant difference in diversity was observed between EF and CU (Fig. 2B). Despite differences in alpha diversity among tracts, samples within each site clustered closely, supporting the concept of distinct microbial niches specific to anatomical location. Beta diversity analysis was conducted to evaluate compositional dissimilarity among sample types using the Bray-Curtis index based on ASV abundance. Non-Metric Multidimensional Scaling (NMDS) plots visualized the separation of the four sample groups, with color-coding by site. Both Bray-Curtis and Weighted UniFrac analyses revealed significant differences in microbial community structure across the four sample types (Fig. 2C; Stress = 0.1744 / 0.086). Furthermore, ANOSIM confirmed statistically significant intergroup dissimilarities (Fig. 2D; p = 0.001; R = 0.4776 / 0.4708), indicating that microbial assemblages are site-specific. Differential microbial abundance analysis in the cyst fluid and other sites in women with ovarian endometrioma To To investigate shared and unique microbial components across niches, we analyzed taxon distribution patterns using nestedness analysis. Specifically, we examined the presence and variability of amplicon sequence variants (ASVs) across sample types, focusing on genus-level taxa. As shown in Fig. 3A, a total of 1,003 bacterial species were detected across all samples: 716 in CF, 698 in EF, 612 in PF, and 409 in CU. Of these, 230 species were common to all four sites. Genus-level abundance analysis revealed that Lactobacillus was most enriched in CU samples, while Escherichia-Shigella predominated in EF. In PF, Hydrogenophaga, Brevundimonas, and Phenylobacterium were the primary taxa detected. In CF, the most abundant genera included Hydrogenophaga, Pseudoalteromonas, Vibrio, and Brevundimonas (Fig. 3B and C). These findings suggest that each anatomical site harbors a distinct microbial profile (see Supplementary Table 3). We next compared microbial distributions in cystic fluid with those in the other three sites using the Wilcoxon rank-sum test. We employed the Wilcoxon rank-sum test to compare microbial abundances across sites. When comparing the microbiomes of the CF and CU sites, we identified 188 species with statistically significant differences in abundance (see Supplementary Table 4). Among these, 46 taxa were uniquely present in the CF samples and absent in CU. Lactobacillus was predominant in CU, whereas Hydrogenophaga, Phenylobacterium, Brevundimonas, Vibrio, and Pseudoalteromonas were significantly enriched in CF (Fig. 4A). A comparison between EF and CF revealed 101 taxa with significant differential abundance (see Supplementary Table 5). Seventeen taxa were detected exclusively in EF, while nine were unique to CF. Escherichia-Shigella was significantly more abundant in EF than in CF, whereas the relative abundances of 24 taxa were significantly higher in CF compared to EF (Fig. 4B). In contrast, only 45 taxa showed statistically significant differences between PF and CF, suggesting a high degree of similarity in microbial composition between these two upper reproductive tract sites (see Supplementary Table 6). Of these differentially abundant taxa, 12 were exclusive to CF. Brevundimonas, Acinetobacter, Sphingomonas, Porphyromonas, and Acetitomaculum were the most prominent in PF, while Pseudoalteromonas, Vibrio, Streptococcus, Aeromonas, Marinomonas, Aliidiomarina, Thermicanus, Shewanella, unclassified Gammaproteobacteria, Testudinibacter, and Klebsiella were the dominant taxa in CF (Fig. 4C). Prediction and analysis of functional genes We annotated the genes in the gene catalog in accordance with the Kyoto Encyclopedia of Genes and Genomes (KEGG) [14]. Comparative analysis of KEGG pathway distributions revealed that PF and CF samples were enriched in pathways related to cofactor and vitamin metabolism, secondary metabolite biosynthesis, cell motility, terpenoid and polyketide metabolism, cancer-related pathways, lipid metabolism, neurodegenerative disease pathways, and amino acid metabolism. In contrast, EF and CU samples exhibited higher representation of genes involved in membrane transport, genetic information processing, and enzyme families (Fig. 5). At the level of KEGG orthology (KO) modules, PF and CF samples showed significant enrichment of genes encoding threonine dehydratase, chromate transporter, glutamate N-acetyltransferase, citrate synthase, L-aspartate oxidase, thiamine-phosphate pyrophosphorylase, homocysteine methyltransferase, acid dehydratase, electron transfer flavoprotein beta subunit, 3-isopropylmalate/(R)-2-methylmalate dehydratase large subunit, electron transfer flavoprotein alpha subunit, diphosphate reductase, dehydratase small subunit, and ATP-dependent Lon protease systems, compared to EF and CU. Conversely, the glycerol uptake facilitator protein regulatory system was enriched in CU samples (Fig. 5). Correlation analysis of clinical manifestations/markers and microbiota Dysmenorrhea is a primary clinical symptom of ovarian endometrioma and may reflect disease severity. Pain intensity was assessed using the visual analog scale (VAS). Spearman correlation analysis revealed that the average relative abundance of Hydrogenophaga, Phenylobacterium, Caulobacter, Acinetobacter, Testudinibacter, and Sphingomonas in PF samples, as well as Bifidobacterium in EF samples, was positively correlated with dysmenorrhea severity (|correlation| >0.5, Fig. 6). In contrast, Streptococcus and Aeromonas in PF samples showed a negative correlation with pain levels. CA125, a biomarker associated with epithelial-mesenchymal transition (EMT), is elevated in both early and advanced stages of endometriosis [15]. Linear regression analysis indicated that the average relative abundance of Pseudoalteromonas, Vibrio, Shewanella, and Aeromonas in EF samples, and Brevundimonas in PF samples, was positively correlated with serum CA125 levels (|correlation coefficient| >0.5, Fig. 6). Additionally, IL-6 levels were positively associated with Streptococcus and Klebsiella abundance, and negatively associated with Christensenellaceae R-7 group and Veillonella in CU samples (Fig. 6). However, after adjusting for age and disease stage using the false discovery rate (FDR) correction for multiple testing, none of the observed associations between clinical markers and microbial taxa remained statistically significant (Supplementary Tables 7–10).

Principal findings This study presents the microbial profile of the cystic fluid (CF) in ovarian endometrioma (OMA) using 16S rDNA sequencing. Our key findings are threefold: First, we confirmed the existence of distinct microbial communities at different sites of the reproductive tract (posterior vaginal fornix CU, endometrial fluid EF, peritoneal fluid PF, and cyst fluid CF) in patients with OMA, with a significant increase in microbial alpha diversity from the lower (CU) to the upper (CF) tract. Second, the microbial composition and predicted functional profiles of the PF were most similar to those of the CF. Third, Spearman correlation analysis revealed potential associations between the abundance of specific bacterial genera and clinical parameters, including dysmenorrhea, serum CA125 levels, and the inflammatory marker IL-6. Interpretation in the context of the “microbial continuity” hypothesis The observed gradient in microbial diversity and the compositional changes from the CU to the CF lend support to the emerging hypothesis of a microbial continuum within the female reproductive tract [16, 17]. The striking similarity between the PF and CF microbiomes suggests that the microorganisms within the endometriotic cyst may primarily originate from the peritoneal environment, rather than arising de novo. This aligns with the theory that the peritoneal cavity is not sterile and that its microbial inhabitants may play a role in gynecological pathologies. However, the interpretation of this “continuity” must be approached with caution. The absence of a control group—comprising, for instance, women with benign non-endometriotic conditions undergoing laparoscopy—is a significant limitation. It remains unclear whether the microbial patterns we observed are specific to the pathogenesis of OMA or simply represent a common state associated with the presence of any pelvic pathology or even a normal variation. Therefore, our data should be interpreted as revealing an association rather than establishing a definitive pathogenic succession. Implications of key taxa and functional predictions The identification of niche-specific dominant taxa provides crucial clues for potential mechanisms. The predominance of Lactobacillus in the CU samples is consistent with a healthy cervicovaginal environment, and its marked decrease in the EF, PF, and CF may indicate a dysbiotic state in the upper reproductive tract of OMA patients. The enrichment of Escherichia-Shigella in the EF is particularly noteworthy. Previous studies have reported higher concentrations of E. coli (a member of this genus) and bacterial endotoxins in the menstrual blood and peritoneal fluid of women with endometriosis [18, 19]. These bacterial components are known to activate Toll-like receptor 4 (TLR4) signaling, potentially driving a chronic inflammatory response that facilitates the survival and growth of ectopic endometrial tissue. Our finding strengthens the “bacterial contamination” hypothesis as a contributor to OMA development. The dominance of genera such as Hydrogenophaga and Brevundimonas in the PF and CF is a novel finding. These bacteria are often found in aquatic and soil environments, and their ecological role in the human body is poorly understood. Whether they act as drivers of disease by promoting inflammation or are merely passengers thriving in the unique, iron-rich, and potentially hypoxic microenvironment of the cyst is a critical question for future research. The functional prediction analysis indicated that the PF and CF microbiomes were enriched in metabolic pathways. Clinical correlations: generating hypotheses for future research The correlations between specific microbial taxa and clinical symptoms (dysmenorrhea) and biomarkers (CA125, IL-6) are among the most translatable findings of our study. For instance, the positive correlation between Brevundimonas in the PF and CA125 levels suggests a potential link between the peritoneal microbiome and a recognized marker of endometriosis. These correlations support the concept of a “microbiota-host immune interaction” influencing disease manifestations. However, given the exploratory nature of this analysis and the small sample size, these correlations must be considered hypothesis-generating. Their validity and potential utility as diagnostic or prognostic biomarkers need to be confirmed in larger, independent cohorts.

and future directions A rigorous discussion must acknowledge the study’s limitations, which directly inform future research directions: - Lack of Control Group: The most critical limitation is the absence of appropriate controls. Future studies must include women without endometriosis to determine the specificity of our findings. - Small Sample Size: The limited sample size (n = 16) reduces statistical power and increases the risk of overinterpreting the data. Larger-scale studies are essential for validation and subgroup analyses. - Technical Constraints: 16S rDNA sequencing provides limited taxonomic resolution at the species level. Furthermore, analysis of low-biomass samples like CF and PF is highly susceptible to contamination from reagents or the environment. While negative controls were used, the potential impact of contamination cannot be fully ruled out. Future studies should employ shotgun metagenomics for more accurate taxonomic and functional profiling. - Cross-Sectional Design: This design can identify associations but cannot establish causality. Longitudinal studies tracking microbial changes before and after treatment, or experimental studies in animal models, are needed to determine if these microbes are a cause or a consequence of OMA.

In conclusion, this study provides initial evidence for the existence of a unique and diverse microbiome within ovarian endometrioma cysts, which is closely related to the peritoneal microbiome and correlated with clinical indicators. Despite its limitations, this work opens new avenues for understanding OMA pathophysiology through the lens of the microbiome. Future research focusing on controlled, large-scale, and multi-omics validation is warranted to elucidate whether the pelvic microbiome is a primary driver or a secondary passenger in OMA, and to explore its potential as a novel target for prevention and therapy. Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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We thank the volunteers for participating in this study. Funding This study was funded by grants from Research Fund Project of Putian University (Grant No.2023107) . Author information Authors and Affiliations Contributions Conceptualization, Yi Chen and SaiHua Zheng; methodology, SaiHua Zheng and ZhenHong Wang; software, SaiHua Zheng and LiNa Chen; validation, XianQian Chen; formal analysis, SaiHua Zheng and Su-Qiong Xu; resources, SaiHua Zheng and XiuXia Chen; data curation, ZhiCong Wu, ZhiJing Wang and JingJing Wang; writing—original draft preparation, SaiHua Zheng; writing—review and editing, Yi Chen and XueLian Li, Data curation/Formal analysis/Methodology, SaiHua Zheng and ZhenHong Wang. All authors have read and agreed to the published version of the manuscript. Corresponding authors Ethics declarations Ethics approval and consent to participate The study was approved by the Institutional Review Board (Clinical Research Committee) of the First Hospital of Putian City (Approval No. 2023-043) on April 13, 2023, in accordance with the principles of the Declaration of Helsinki. All participants received written and oral information and signed informed consent before any examination. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary Information Rights and permissions Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. About this article Cite this article Zheng, SH., Chen, XQ., Wang, ZH. et al. Microbiome analysis of the cystic fluid in ovarian endometrioma: new avenues for the prevention, diagnosis, and treatment of the disease. Reprod Biol Endocrinol 24, 13 (2026). https://doi.org/10.1186/s12958-025-01511-y Received: Accepted: Published: Version of record: DOI: https://doi.org/10.1186/s12958-025-01511-y