Exploring cervicovaginal microbiome differences between single and multiple endometrial polyps: implications for non-invasive classification.

IF 4.6 2区 生物学 Q1 MICROBIOLOGY
mSystems Pub Date : 2025-09-15 DOI:10.1128/msystems.00023-25
Tianshu Sun, Qingyue Zheng, Roujie Huang, Leyan Yang, Zimo Liu, Zhibo Zhang, Xudong Liu, Hua Yang, Xiaochuan Li, Jiali Tong, Lan Zhu
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引用次数: 0

Abstract

Single and multiple endometrial polyps (EP) are common gynecological conditions with differing recurrence rates, influencing clinical treatment decisions. This study aimed to characterize the reproductive tract microbiome in both subtypes to support the development of methods for the non-invasive categorization of EPs. Using metagenomic sequencing, we analyzed vaginal and cervical samples from 27 reproductive-aged patients with single EP and 22 with multiple EP. Compared with controls and multiple EP cases, single EP vaginal and cervical samples exhibited a lower percentage of community state types (CST) I and II. Sneathia amnii was identified as a characteristic species in both the vagina (P = 0.0051) and cervix (P = 0.0398) of single EP patients compared with controls. Mesorhizobium sp. (vaginal P = 0.0110, cervical P = 0.0210), Acinetobacter baumannii (vaginal P = 8.0 × 10-5, cervical P = 0.0314), and Pasteurella multocida (vaginal P = 0.0173, cervical P = 0.0210) were enriched in single EP compared with multiple EP. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of vaginal microbiome revealed unique pathways in single EP, including aminoacyl-tRNA biosynthesis, pantothenate and coenzyme A (CoA) synthesis, pyrimidine metabolism, glycolysis/gluconeogenesis, and biosynthesis of phenylalanine, tyrosine, and tryptophan. Using a random forest model, we further selected microbiota and clinical parameters to differentiate single and multiple EPs, thus achieving an area under curve (AUC) of 0.861. Our findings characterized the composition of the cervicovaginal microbiota of single and multiple EPs and proposed biomarkers for their non-invasive classification based on a random forest model.IMPORTANCEThe prevalence rate of endometrial polyps (EPs), a common gynecological condition, varies between 7.8% and 34.9%. Multiple EPs are associated with higher recurrence rates and chronic endometritis than single EPs and thus require more aggressive clinical interventions. However, only laparoscopic surgery can accurately identify single and multiple polyps. Non-invasive adjunctive diagnostic methods can aid in altering surgical indications preoperatively. Using metagenomic sequencing, we thoroughly analyzed the vaginal and cervical samples of 27 single EP and 22 multiple EP patients of reproductive age. We then identified distinct microbial patterns in the single and multiple samples, which were crucial for understanding EP pathogenesis and its association with gynecological health. Using a random forest model, key bacterial taxa that differentiate single and multiple EPs were identified with high accuracy. These could potentially serve as non-invasive diagnostic biomarkers. This research delineates the cervicovaginal microbiome of the reproductive tract in EP patients, offering a basis for developing non-invasive diagnostic tools and personalized treatment strategies.

探讨单个和多个子宫内膜息肉的宫颈阴道微生物组差异:非侵入性分类的意义。
单发和多发子宫内膜息肉(EP)是常见的妇科疾病,复发率不同,影响临床治疗决策。本研究旨在表征两种亚型的生殖道微生物组,以支持EPs非侵入性分类方法的发展。使用宏基因组测序,我们分析了27例单发EP和22例多发EP的育龄患者的阴道和宫颈样本。与对照组和多发EP病例相比,单EP阴道和宫颈样本显示出较低的社区状态类型(CST) I和II的百分比。与对照组相比,单例EP患者阴道(P = 0.0051)和宫颈(P = 0.0398)的羊膜Sneathia amnii均为特征性物种。单EP与多EP相比,中根瘤菌(阴道P = 0.0110,宫颈P = 0.0210)、鲍曼不动杆菌(阴道P = 8.0 × 10-5,宫颈P = 0.0314)和多杀性巴氏杆菌(阴道P = 0.0173,宫颈P = 0.0210)在单EP中含量较高。京都基因和基因组百科(KEGG)对阴道微生物组的富集分析揭示了单个EP的独特途径,包括氨酰基trna生物合成、泛酸和辅酶A (CoA)合成、嘧啶代谢、糖酵解/糖异生,以及苯丙氨酸、酪氨酸和色氨酸的生物合成。利用随机森林模型,我们进一步选择微生物群和临床参数来区分单个和多个EPs,从而实现曲线下面积(AUC)为0.861。我们的研究结果表征了单个和多个EPs的宫颈阴道微生物群的组成,并提出了基于随机森林模型的非侵入性分类的生物标志物。子宫内膜息肉(EPs)是一种常见的妇科疾病,其患病率在7.8%至34.9%之间。多发性EPs与慢性子宫内膜炎的复发率和慢性子宫内膜炎相关,因此需要更积极的临床干预。然而,只有腹腔镜手术才能准确地识别单个和多个息肉。非侵入性辅助诊断方法可以帮助术前改变手术指征。应用宏基因组测序技术,我们对27例单发EP和22例多发EP育龄患者的阴道和宫颈样本进行了全面分析。然后,我们在单个和多个样本中确定了不同的微生物模式,这对于了解EP发病机制及其与妇科健康的关系至关重要。利用随机森林模型,对区分单EPs和多EPs的关键细菌分类群进行了高精度的鉴定。这些有可能作为非侵入性诊断生物标志物。本研究描述了EP患者生殖道的宫颈阴道微生物组,为开发无创诊断工具和个性化治疗策略提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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