Analysis of metagenomic sequencing characteristics of vaginal microbiota in vaginal inflammatory diseases

Analysis of metagenomic sequencing characteristics of vaginal microbiota in vaginal inflammatory diseases | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of metagenomic sequencing characteristics of vaginal microbiota in vaginal inflammatory diseases Ruichen Wang, Siqi Li, Xiao Yang, Honglan Zhu, Jianliu Wang, Xudong Liang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9061730/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract OBJECTIVE To investigate whether different types of vaginitis have distinct microbiota in the female reproductive tract, and whether bacteria may have specific functions. METHODS This is a cross-sectional study involving 53 patients who visited the gynecology clinic of Peking University People's Hospital for examination. Vaginal secretions were collected from each participant Samples were used for metagenomic sequencing. RESULTS Our results identified that patients with various types of vaginitis exhibited increased vaginal microbiota diversity. The vaginal microbiota of patients with AV is mainly composed of Streptococcus , Enterococcus , and Prevotella . Mobiluncus.mulieris is an important biomarker for patients in the AV_BV group. CARD analysis showed that the relative abundance of resistance gene efrB in the healthy group was significantly higher than in the other vaginitis groups. The relative abundance of the immune modulation-related virulence factor LOS (VF0044) in the healthy group was significantly lower than in the AV group, AV_BV group, and the BV group. CONCLUSION The vaginal flora of patients in the AV_BV and VVC_BV groups exhibited structural similarities to that of the BV group. The antibiotic resistance genes in the microbiota urgently require clinical attention. Vaginal microbiota metagenomic sequencing vaginal inflammatory diseases aerobic vaginitis mixed vaginitis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Among all gynecological diseases, vaginitis is recognized as one of the most widespread afflictions. More than 70% of women have had vaginitis at some point in their lives. A large-scale survey revealed that 88.8% of individuals with vaginitis were seeking treatment from professional medical institutions. 1 – 2 Vaginal microbiota in the lower reproductive tract, which constitutes a dynamic and complex ecosystem, is vital in preventing infections. 3 Lactobacillus, the dominant bacterial genus in the vagina of healthy women, maintains the balance of the vaginal microecosystem by sustaining a low pH environment in the vagina and secreting substances such as hydrogen peroxide, thereby inhibiting the proliferation of other harmful microorganisms. 4 When the vaginal microbiota becomes dysregulated and the abundance of pathogenic microorganisms (such as Candida albicans and Gardnerella vaginalis ) changes, it may induce the onset of vaginal inflammatory diseases such as bacterial vaginosis (BV) and vulvovaginal candidiasis (VVC). 5 Patients with aerobic vaginitis (AV) exhibit increased diversity and dysbiosis of the vaginal microbiota, with the main pathogens identified in cultivation studies as group B Streptococcus , Escherichia coli , and Staphylococcus aureus . 6 AV has been associated with an elevated risk of adverse pregnancy outcomes such as premature delivery, abortion, premature rupture of membranes (PROM), and stillbirth. 7 Clinically, approximately 4.44% to 35.06% of women experience at least two types of vaginitis simultaneously, also known as mixed vaginitis. 8 Some women exhibit symptoms of microbial communities, as evidenced by clue cells and the presence of multiple aerobic bacteria. However, mixed vaginitis poses a therapeutic challenge. The main objectives are to recognize polymicrobial interactions in mixed vaginitis, to utilize them therapeutically, and restore a healthy vaginal microbiota. Previously, the diagnosis of vaginitis relied on morphological examination to determine the diversity and density of the vaginal microbiota and pathogenic microorganisms. 9 16S rRNA sequencing technology enables a more comprehensive study of the vaginal microbiome. 10 Here, we use metagenomic sequencing to directly obtain genetic information of the entire microbiome, including rare, novel, and hard-to-detect pathogens, from clinical samples to identify specific microbial species associated with different types of vaginitis. It can also be used to study microbial gene functions and predict antibiotic resistance. 11 Methods Human subjects and sample collection Human subjects All selected subjects were patients and healthy women at the Gynecological Outpatient Department of Peking University People’s Hospital in China between August 2025 and October 2025, and each participant provided informed consent. The study was approved by the Ethics Committee of the Peking University People’s Hospital (2025PHB009-001) and was strictly conducted in accordance with the Declaration of Helsinki. The inclusion criteria were as follows: (1) being over 18 years old, (2) a history of sexual activity, and (3) having a regular menstrual cycle. The exclusion criteria were as follows: (1) lactation period, (2) antibiotic use within 30 days, (3) sexual activity,vaginal medication, or lavage within 7 days, and (4) individuals with tumors or cervical lesions. Microbiological diagnosis of all kinds of vaginitis Each female underwent vaginal microecological examination. The diagnostic criterion for BV was a Nugent score ≥ 7. 12 Women were diagnosed with VVC when fungal spores or hyphae were observed under a microscope after Gram staining of vaginal secretion. 13 The diagnosis of AV is made by an AV score analysis (a score of ≥ 3 is diagnostic). 14 Healthy women should undergo a normal vaginal microecological examination, including no clue cells, spores, or hyphae. The 53 samples were divided into five groups: VVC (N = 12), VVC_BV (N = 8), AV (N = 10), AV_BV (N = 3), BV (N = 7), and healthy (N = 13). Sample collection Vaginal secretions were collected from each participant from the upper 1/3 of the vaginal lateral wall using their sterile cotton swabs. One sample was used for vaginal microbiological morphology analysis. Two samples were stored in 2 mL Eppendorf tubes at − 80°C for subsequent metagenomic sequencing. DNA extraction and metagenomic sequencing Total DNA was extracted using the E.Z.N.A.® Soil Omega Kit (Omega Bio-Tek, Norcross, GA, US) according to the manufacturer’s instructions and stored at − 20°C. After detecting the concentration and purity of DNA, DNA integrity was detected by 1% agarose gel electrophoresis. After passing the quality inspection, DNA was randomly fragmented to 350 bp using a Covaris S220 (Gene Company Limited, China) for paired-end library construction. Paired-end sequencing was performed on Illumina NovaSeq™ X Plus (Illumina Inc., San Diego, CA, USA) at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) using NovaSeq X Series 25B Reagent Kit according to the manufacturer’s instructions ( www.illumina.com ). Processing of metagenome sequencing data The raw sequencing reads were trimmed of adapters, and low-quality reads (length < 50 bp or average quality value < 20) were removed using fastp (version 0.20.0). Reads were aligned to the human genome by BWA (version 0.7.17), and any hits associated with the reads and their mated reads were removed. Contigs ≥ 300 bp in length were selected as the final assembly result. Open reading frames (ORFs) from each assembled contig were predicted using Prodigal(version 2.6.3), and ORFs with a length of ≥ 100 bp were retrieved. A non-redundant gene catalog was constructed using CD-HIT(version 4.7) with 90% sequence identity and 90% coverage. Gene abundance for a certain sample was estimated by SOAPaligner with 95% identity. Taxonomic and functional annotation The best-hit taxonomy of non-redundant genes was obtained by aligning them against the NCBI NR database by DIAMOND (version 2.0.13) with an e-value cutoff of 1e-5. The NR library was used for species taxonomic annotation to obtain the relative abundance of microbial communities at various levels, from phylum to species. Statistics on species abundance were conducted at the classification levels of kingdom, phylum, class, order, family, genus, and species. Alpha diversity analysis is used to evaluate the richness and diversity of microbial communities in samples.PCoA (principal coordinates analysis) was used to evaluate similarities and differences in the composition of sample communities using Bray-Curtis distances in ANOSIM. Linear discriminant analysis effect size (LEfSe) was used to identify statistically significant biological markers between groups. The best-hit taxonomy of non-redundant genes was obtained by aligning them against the NCBI NR database with DIAMOND, using an e-value cutoff of 1e-5. Similarly, the functional annotation (CARD, PHI) of non-redundant genes was obtained. Based on taxonomic and functional annotations and the abundance profiles of non-redundant genes, the differential analysis was carried out at each taxonomic, functional, or gene-wise level using the Kruskal-Wallis test. Results Diversity analysis of vaginal microbiota between healthy women and patients with vaginitis Significant differences were observed between the healthy and BV groups, and between the BV and VVC groups, based on the Ace index (P < 0.01 and P < 0.01, respectively, Fig. 1 -a). There were significant differences between the healthy and BV, AV_BV groups, or the VVC and AV_BV groups, based on the Shannon index (P < 0.05, P < 0.05, P < 0.05, and P < 0.05, respectively, Fig. 1 -b). The alpha diversity of the vaginal microbiota in women with AV and AV_BV groups was marginally higher than that in healthy women, and this difference was statistically significant based on the Chao index (p < 0.05, p < 0.05, Fig. 1 -c). According to the β-diversity analysis, significant differences in vaginal microbiota diversity were observed between the healthy group and the AV, BV, VVC, AV_BV, and VVC_BV groups (R = 0.568, P = 0.001, Fig. 1 -d). Results showed that the AV group differed significantly from the BV and AV_BV groups, whereas no significant differences were detected between the BV and AV_BV groups (R = 0.317, P = 0.103, Fig. 1 -e). Results of principal coordinate analysis (PCoA) showed significant differences between the BV and VVC groups, the VVC and VVC_BV groups, but no significant difference between the BV and VVC_BV groups (R = 0.563, P = 0.001, Fig. 1 -f). Analysis of vaginal microbiota composition The overall composition of the vaginal microbiome in the six groups is as follows. In the healthy group, at the genus level, Lactobacillus (91.5%) exhibited the highest abundance, which was significantly greater compared to its levels in the other groups, followed by Gardnerella (4.8%). In comparison, the BV group was dominated by Gardnerella (57.8%), followed by Prevotella (9.05%) and Fannyhesse a (4.76%). For the AV_BV group, Gardnerella (34.58%) was the most abundant, with Fannyhessea (15.72%) and Mobiluncus (12.86%) following. In the AV group, Streptococcus (39.82%) showed the highest abundance, next to Enterococcus (17.29%) and Prevotella (8.75%). The VVC group exhibited dominance of Lactobacillus (83.87%), Candida (5.07%), and Pseudomonas (3.16%). Finally, in the VVC_BV group, Gardnerella (58.71%), Lactobacillus (21.49%), and Fannyhessea (9.27%) were dominant (Fig. 2 -a). At the species level, L.crispatus (46.05%) and Lactobacillus iners (26.81%) were the most abundant in the healthy group. At the species level of Gardnerella , G.vaginalis was the most abundant in the BV group, AV_BV group, AV group, VVC_BV group, and VVC group (45.92%, 17.73%, 0.91%, 33.32% and 0.44%, respectively). At the species level of Lactobacillus , L. crispatus was the dominant Lactobacillus in the healthy group (46.05%) and AV group (3.78%). Lactobacillus iners was the dominant Lactobacillus in the BV group (2.14%), AV_BV group (2.16%), VVC_BV group (12.92%), and VVC group (47.23%). In the AV group, Streptococcus_sp (29.11%) was the most abundant, followed by Streptococcus_anginosus (4.92%). In the VVC and VVC_BV groups, C.albicans (4.34% and 1.34%, respectively) was the dominant Candida species (Fig. 2 -b). At the genus level, the relative abundance of Streptococcus was significantly higher in the AV group compared to the AV_BV, BV, Healthy, VVC, and VVC_BV groups (P < 0.01, P < 0.001, P < 0.001, P < 0.001, and P < 0.001, respectively, Fig. 2 -c). At the species level of Streptococcus , the relative abundance of Streptococcus agalactiae was significantly higher in the AV group compared to the AV_BV, BV, Healthy, VVC, and VVC_BV groups (P < 0.05, P < 0.05, P < 0.05, P < 0.05, and P < 0.05, respectively, Fig. 2 -d). The relative abundance of Enterococcus was significantly higher in the AV group than in the other groups (Fig. 2 -e). Compared to the other group, the relative abundance of C. albicans was higher in the VVC_BV group as well as in the VVC group. However, no significant difference in C. albicans was observed between any two groups (Fig. 2 -f). The relative abundance of Mobiluncus was significantly higher in the AV_BV group compared to the AV, BV, Healthy, VVC, and VVC_BV groups (P < 0.001, P < 0.001, P < 0.001, P < 0.001, and P < 0.001, respectively, Fig. 2 -g). At the species level of Mobiluncus , the relative abundance of Mobiluncus.mulieris was significantly higher in the AV_BV group compared to the AV, BV, Healthy, VVC, and VVC_BV groups (P < 0.001, P < 0.001, P < 0.001, P < 0.001, and P < 0.001, respectively, Fig. 2 -h). Linear discriminant analysis effect size variance analysis We next conducted linear discriminant analysis (LDA) and effect size (LEfSe) between each patient group and the healthy groups. Significant changes were observed at the species level in 11 microbes between the healthy and AV groups (LDA > 4) (Fig. 3 -a). Streptococcus.sp , Enterococcus.sp , Prevotella.Bivia , Streptococcus.anginosus , Enterococcus. faecalis , Lactobacillus.delbrueckii , and Streptococcus.agalactiae were significantly enriched in the AV group, while L.crispatus , Lactobacillus. iners , Lactobacillus.sp , and Lactobacillus.jensenii were significantly enriched in the healthy group. Significant changes were observed at the species level in 10 microbes between the healthy and AV_BV groups (LDA > 4) (Fig. 3 -b). Mobiluncus.mulieris , Fannyhessea.vaginae , G.vaginalis , Gardnerella.sp , Hoylesella.timonensis , Gardnerella.sp.KA00735 , and Porphyromonas.sp were significantly enriched in the AV_BV group, while L. crispatus , Lactobacillus sp. , and Lactobacillus.jensenii were significantly enriched in the healthy group. Significant changes were observed at the species level in 11 microbes between the healthy and BV groups (LDA > 4). G.vaginalis , Gardnerella.sp , Fannyhessea.vaginae , Prevotella.amnii , Sneathia.sanguinegens , Prevotella.bivia , Megasphaera.lornae , and Amygdalobacter.indicium were significantly enriched in the BV group, while L.crispatus , Lactobacillus.sp , and Lactobacillus.jensenii were significantly enriched in the healthy group. Significant species-level differences were observed in 12 microbes when comparing the AV_BV and AV groups (LDA > 4) (Fig. 3 -c). Streptococcus.sp , Streptococcus.anginosus , Enterococcus.faecalis , Pseudomonas.sp , Streptococcus.agalactiae , and Lactobacillus.delbrueckii were significantly enriched in the AV group, while G.vaginalis , Fannyhessea.vaginae , Mobiluncus.mulieris , Gardnerella.sp , Gardnerella.sp.KA00735 , and Schwartzia.sp.in.firmicutes were significantly enriched in the AV_BV group. Between the AV_BV and BV groups (LDA > 2.5) (Fig. 3 -d), three microbes at the species level showed significant differences. Atopobium.deltae , and Anaerococcus.sp were significantly enriched in the BV group, while Bifidobacterium.sp was significantly enriched in the AV_BV group. Significant differences in vaginal flora functional potentials of virulence factor and antibiotic resistance between healthy women and patients with vaginitis To characterize the gene features of the healthy vaginal microbiome, we constructed a non-redundant gene catalog from metagenomic data and annotated it using the Virulence Factor Database (VFDB) and the Comprehensive Antibiotic Resistance Database (CARD) with Diamond software. We then used the Spearman correlation to assess the association between gene relative abundance and disease states, and the Wilcoxon rank-sum test to identify differential genes across groups. Wilcoxon rank-sum test analysis revealed that the relative abundance of fluoroquinolone antibiotic, macrolide antibiotic, rifamycin antibiotic resistance gene efrB in the healthy group was significantly higher than in the AV group (p < 0.01), AV_BV group (p < 0.01), and the BV group (p < 0.01) (Fig. 4 -a). The relative abundance of aminocoumarin antibiotic resistance gene novA (Fig. 4 -b), tetracycline antibiotic resistance gene tetB (60) (Fig. 4 -c), and tetA (46) (Fig. 4 -d) in the healthy group was significantly higher than in the BV group (p < 0.01). In the comparison between the healthy and the BV group, the relative abundance of the macrolide antibiotic resistance gene macB, the glycopeptide antibiotic resistance gene mlaF, the nitroimidazole antibiotic resistance gene msbA, and the fluoroquinolone antibiotic resistance gene patB in the BV group was significantly higher than in the healthy group (Fig. 4 -e). The relative abundance of macrolide antibiotic resistance gene macB, nitroimidazole antibiotic resistance gene msbA, and pleuromutilin antibiotic resistance gene TaeA in the AV_BV group was significantly higher than in the healthy group (Fig. 4 -f). The relative abundance of macrolide antibiotic resistance gene macB and aminoglycoside antibiotic resistance gene RanA in the AV group was significantly higher than in the healthy group. Besides the aminocoumarin antibiotic resistance gene novA, the fluoroquinolone antibiotic resistance gene PatA, and the lincosamide antibiotic resistance gene lmrD, which were also higher in the healthy group than in the AV group (Fig. 4 -g). The relative abundance of immune modulation related virulence factor LOS (VF0044) in the healthy group was significantly lower than in the AV group (p < 0.001), AV_BV group (p < 0.001) and the BV group (p < 0.001) (Fig. 4 -h). The relative abundance of nutritional/metabolic factor related virulence factor MgtBC (VF0106) in the healthy group was significantly higher than in the AV group (p < 0.001), AV_BV group (p < 0.001) and the BV group (p < 0.001) (Fig. 4 -i). Discussion Lactobacillus is the main bacterium of the normal vaginal microbiota. 15 Not only the predominance of a specific Lactobacillus but also its relative abundance were pivotal in maintaining vaginal physiologic status. 16 Imbalance in the vaginal microbiota might lead to numerous vaginal diseases, including AV and BV. 17 Previous studies showed that a reduction of Firmicutes (mainly L. crispatus and L. iners ) was accompanied by an increase in Streptococcus agalactiae , Staphylococcus aureu s, and Escherichia coli , leading to inflammation symptoms in AV. 18 However, the description of microbial populations in AV often relies on 16S rRNA gene sequencing technology and cultivation. 6 In our study, we adopted metagenomic sequencing to characterize the microbial population associated with vaginitis. We discovered the vaginal microbiota and functional relationships among patients with AV, BV, and both AV and BV. These discoveries enhanced our cognition of the unique characteristics and treatment improvements of vaginal microbiota in vaginitis. The abundance of Streptococcus was the highest in the AV group, followed by Enterococcus and Prevotella . In the AV group, Streptococcus was the most abundant, and the relative abundance of Streptococcus was significantly higher in the AV group compared to the AV_BV, BV, Healthy, VVC, and VVC_BV groups. Streptococcus was the biomarker associated with AV. At the species level of Lactobacillus , L. crispatus was the dominant Lactobacillus in the AV group, whereas L.crispatus and Lactobacillus iners were the most abundant in the healthy group, suggesting that L.crispatus and Lactobacillus iners play an important role in maintaining the homeostasis of the vaginal microenvironment. 19 Mixed vaginitis refers to the presence of at least two types of vaginitis simultaneously, leading to an abnormal vaginal environment. In the current study, there were significant differences between the healthy and AV_BV groups based on the Simpson index (P < 0.05). The alpha diversity of the vaginal microbiota in women with AV_BV groups was higher than that in healthy women, as measured by the Chao index(p < 0.05).In the AV_BV group, Gardnerella was the most abundant, followed by Fannyhessea and Mobiluncus . Gardnerella , Lactobacillus , and Fannyhessea were the top three dominant genera in the VVC_BV group. Lactobacillus iners was the dominant Lactobacillus in both the AV_BV and VVC_BV groups. These results suggest that the diversity of vaginal microbiota in patients with mixed vaginitis increases, and their microbiota structure undergoes significant changes, while the abundance of healthy lactobacilli decreases. Gardnerella and Fannyheshsea , which were clinically considered the pathogens of BV, have a dominant position in the vaginal microbiome of patients with AV and BV, consistent with previous research findings. 20 The AV_BV group showed a composition of vaginal microbiota close to the BV group. An increase in Lactobacillus abundance in the vagina during treatment for AV and mixed vaginitis may help reduce disease recurrence. The vaginal microbiota of healthy women is dominated by lactobacilli, which is more conducive to preventing the invasion of pathogenic microorganisms and maintaining the stability of the vaginal microbiota. In patients with different types of vaginitis, the vaginal microbiota is more diverse and enriched, leading to a significant increase in the number of bacterial species involved in the pathogenesis of vaginitis and a more complex bacterial composition. Antimicrobial drug resistance is one of the biggest threats to the failure of vaginal inflammation treatment. Understanding the mechanisms of microbial resistance in microbes is crucial to the study of drug therapy for vaginitis. Resistance to antibiotics may result from multiple mechanisms. The first line of bacterial defense is to actively efflux antimicrobial compounds. 21 Bacteria carrying antibiotic-resistant genes (ARGs) may become the predominant pathogens. 22 Studying ARGs and leveraging the synergistic effects of antibiotic combinations may enable low-dose treatment of infections with multiple antibiotics. 23 Matthew Igo et al. found that, in a study examining the effects of antibiotic treatment on the gut microbiota of BALB/c mice, low-dose monotherapy increased ARG abundance compared to control and high-dose monotherapy. 24 Integral membrane proteins known as drug efflux pumps actively export antibiotics from the cell. This process is recognized as a vital cellular protection mechanism against the toxicity of these and other therapeutic agents. 25 The ABC-type drug efflux pump macB is highly conserved and widespread among bacterial species. 26 As found in our research, the abundance of the macrolide antibiotic resistance gene macB is higher in various cases than in healthy women. In this study, the relative abundance of the glycopeptide antibiotic resistance gene mlaF, the nitroimidazole antibiotic resistance gene msbA, and the fluoroquinolone antibiotic resistance gene patB was significantly higher in the BV group than in the healthy group. This indicates that the resistance mechanism of BV to nitroimidazole drugs was analyzed from the perspective of antibiotic resistance genes. The AV_BV group not only tends to be similar to the BV group in vaginal microbiota composition but also shows an increase in the abundance of nitroimidazole antibiotic resistance gene msbA. The PatAB multidrug efflux pump is involved in resistance to ciprofloxacin (CPX) and norfloxacin in clinical isolates of Streptococcus. 27 LmrD is a chromosomally encoded efflux pump that confers resistance to lincosamides in Streptomyces lincolnensis and Lactococcus lactis. It can dimerize with lmrC, which can confer resistance to antibiotics, such as macrolides, lincomamides, and streptococcins. 28 In this study, the abundance of the fluoroquinolone antibiotic resistance gene PatA and the lincosamide antibiotic resistance gene lmrD was lower in the AV group than in the healthy group. This indicates that the possibility of resistance in the vaginal microbiota of AV women through this mechanism is lower than in healthy women. The lipooligosaccharide (LOS) is a molecule that provides critical protection to the bacterium against host defenses, may act as an adhesin, and is an endotoxin that signals through toll-like receptor 4 and NF-κB to cause inflammation. 29 The relative abundance of the virulence factor LOS in the healthy group was significantly lower than in the AV, AV_BV and the BV groups. Therefore, the LOS is a critical component that enables pathogenic microorganisms in vaginitis to resist host defenses and cause disease. Conclusions In conclusion, our study provided valuable insights into the characteristics of the vaginal flora in AV and BV combined with AV (AV_BV). We found that the vaginal flora of patients in the AV_BV and VVC_BV groups exhibited structural similarities to that of the BV group. This finding emphasizes the complexity of mixed vaginal infections and may have clinical implications for treatment strategies. Metagenomic technology offers a valuable tool for investigating the composition and function of vaginal microbiota in cases of vaginitis. In this study, we preliminarily explored ARGs and virulence factors, elucidated the functional status of vaginal microbiota in vaginitis, and provided insights into the treatment of vaginitis. Declarations Acknowledgments: Thanks for support by the gynecology clinic of Peking University People's Hospital. Data availability: All the data generated or analyzed during this study are included in this published article (and its supplementary information files). Author contributions: Ruichen Wang arranged the samples, did the experiment, analyzed the data, and wrote the article; Ruichen Wang and Siqi Li collected the data; Xiao Yang contributed to the sample collection and data analysis; Honglan Zhu collected the references; Jianliu Wang and Xudong Liang conceived and designed the study; and all the authors read and approved the final manuscript. 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Gut Microbes 15(2):2271150. https://doi.org/10.1080/19490976.2023.2271150 Nishino K, Nikaido E, Yamaguchi A (2009) Regulation and physiological function of multidrug efflux pumps in Escherichia coli and Salmonella. Biochim Biophys Acta 1794(5):834–843. https://doi.org/10.1016/j.bbapap.2009.02.002 Rouquette-Loughlin CE, Balthazar JT, Shafer WM (2005) Characterization of the MacA-MacB efflux system in Neisseria gonorrhoeae. J Antimicrob Chemother 56(5):856–860. https://doi.org/10.1093/jac/dki333 Alvarado M, Martín-Galiano AJ, Ferrándiz MJ et al (2017) Upregulation of the PatAB Transporter Confers Fluoroquinolone Resistance to Streptococcus pseudopneumoniae. Frontiers in microbiology, 8, 2074. https://doi.org/10.3389/fmicb.2017.02074 Koberska M, Vesela L, Vimberg V et al (2021) Beyond Self-Resistance: ABCF ATPase LmrC Is a Signal-Transducing Component of an Antibiotic-Driven Signaling Cascade Accelerating the Onset of Lincomycin Biosynthesis. mBio 12(5):e0173121. https://doi.org/10.1128/mBio.01731-21 Inzana TJ (2016) The Many Facets of Lipooligosaccharide as a Virulence Factor for Histophilus somni. Curr Top Microbiol Immunol 396:131–148. https://doi.org/10.1007/82_2015_5020 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 16 Apr, 2026 Editor assigned by journal 14 Mar, 2026 Submission checks completed at journal 10 Mar, 2026 First submitted to journal 07 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9061730","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627792792,"identity":"e36290a8-c1c2-4790-b3df-2cd57d491175","order_by":0,"name":"Ruichen Wang","email":"","orcid":"","institution":"Peking University People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ruichen","middleName":"","lastName":"Wang","suffix":""},{"id":627792793,"identity":"b6d7108b-b4ed-4b5b-b135-7ebc6c1dcf7d","order_by":1,"name":"Siqi Li","email":"","orcid":"","institution":"Peking University People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Siqi","middleName":"","lastName":"Li","suffix":""},{"id":627792794,"identity":"f521936b-405d-43c8-a1e4-fa9ba797d548","order_by":2,"name":"Xiao Yang","email":"","orcid":"","institution":"Peking University People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Yang","suffix":""},{"id":627792795,"identity":"24aca429-2529-428a-b05c-ecc300167607","order_by":3,"name":"Honglan Zhu","email":"","orcid":"","institution":"Peking University People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Honglan","middleName":"","lastName":"Zhu","suffix":""},{"id":627792796,"identity":"d36602c5-1ec4-4b99-9ce9-be5e6b36fdac","order_by":4,"name":"Jianliu Wang","email":"","orcid":"","institution":"Peking University People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jianliu","middleName":"","lastName":"Wang","suffix":""},{"id":627792797,"identity":"ac47b590-ecb9-48df-b6c8-bd1f5a723d9b","order_by":5,"name":"Xudong Liang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYBACPmYIzdgAJA4kGNjARXACNiQtjAc+VKTBRXBrYUBoYT4448xhuAhuLezMzx5+bTss2y/dfuEwb9t5eTZ2HjPpAgY7Od0GXA5jMzeWOXPYeOacMwVALbcN25iBWmYwJBubHcDpFzNpiYrDiRtu5CSAtDCCtfAwHEjchlML+zdpCQO4lnP2RGjhMZP8ALYl/QDQ+wcSidFSJs1wJt145owcBmAgJye3MbMVW/MY4PYLP//xbZI/26xl+yXSH39IMLCz7ec/vPE2T4WdHC4tIMDMA6Z4DKB8DiDDALdyEGD8AabYH0D5cMYoGAWjYBSMAjAAAOUQWACMSEFeAAAAAElFTkSuQmCC","orcid":"","institution":"Peking University People's Hospital","correspondingAuthor":true,"prefix":"","firstName":"Xudong","middleName":"","lastName":"Liang","suffix":""}],"badges":[],"createdAt":"2026-03-08 03:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9061730/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9061730/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107652046,"identity":"3b7593ae-fb43-46df-a28c-9deb2228889c","added_by":"auto","created_at":"2026-04-23 15:11:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":141797,"visible":true,"origin":"","legend":"\u003cp\u003eThe comparisons of diversity analysis of vaginal microbiota between healthy females and patients with different types of vaginitis. ACE’s, shannon’s, and chao’s indices of vaginal microbiota diversity in the six groups of women. (a) ACE’s, (b) shannon’s, and (c) chao’s indices. (d) The difference of β-diversity among the six groups (Bray-Curtis Anosim, R = 0.568, P = 0.001). (e) The difference of β-diversity between the BV, and AV_BV groups (Bray-Curtis Anosim, R = 0.317, P = 0.103). (f) The difference of β-diversity among the BV, VVC, and VVC_BV groups (Bray-Curtis Anosim, R = 0.563, P = 0.001).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9061730/v1/c1561152d8332d762a850805.png"},{"id":107652000,"identity":"7ee174f9-518e-4950-bb6f-e0e1637f19f4","added_by":"auto","created_at":"2026-04-23 15:11:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":541791,"visible":true,"origin":"","legend":"\u003cp\u003eThe vaginal microbiome composition between healthy women and females with different types of vaginitis. (a and b) Top 20 most abundant bacteria in six groups at the genus (a) and species (b) levels. (c, d, e, f, g, and h)The comparison of the relative abundance of \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eStreptococcus agalactiae\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eCandida albicans\u003c/em\u003e, \u003cem\u003eMobiluncus\u003c/em\u003eand \u003cem\u003eMobiluncus mulieris\u003c/em\u003e among the five groups.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9061730/v1/5679bf8cfeb39e267e915fdc.png"},{"id":107652010,"identity":"9320e076-f7ce-47d1-b71b-6677d7899fcf","added_by":"auto","created_at":"2026-04-23 15:11:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":440224,"visible":true,"origin":"","legend":"\u003cp\u003eLinear discriminant analysis (LDA) and effect size (LEfSe) between groups. (a) The different microbes between the AV and Healthy groups by LEfSe (P \u0026lt; 0.05 and LDA \u0026gt;4). (b) The different microbes between the AV_BV and Healthy groups by LEfSe (P \u0026lt; 0.05 and LDA \u0026gt;4). (c) The different microbes between the AV and AV_BV groups by LEfSe (P \u0026lt; 0.05 and LDA \u0026gt;4). (d) The different microbes between the AV_BV and BV groups by LEfSe (P \u0026lt; 0.05 and LDA \u0026gt;2.5).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9061730/v1/ee0b7d51e090b378b44123b9.png"},{"id":107651999,"identity":"e41e71be-dd4c-4792-8fe8-e571215f8ace","added_by":"auto","created_at":"2026-04-23 15:11:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":493805,"visible":true,"origin":"","legend":"\u003cp\u003eAbundance of comprehensive antibiotic resistance database (CARD) genes and Virulence Factor Database (VFDB) genes in different groups. (a) Comparison of efrB gene abundance. (b) Comparison of novA gene abundance. (c) Comparison of tetB(60) gene abundance. (d) Comparison of tetA(46) gene abundance. (e) The different CARD genes between the healthy and AV_BV groups (P \u0026lt; 0.05). (f) The different CARD genes between the healthy and BV groups (P \u0026lt; 0.01). (g) The different CARD genes between the healthy and AV groups (P \u0026lt; 0.01). (h and i) Comparison of VF0044 gene (h) and VF0106 gene (i) abundance among the healthy, BV, AV_BV, and AV groups.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9061730/v1/c6e0dffe8fada1239d497e91.png"},{"id":107652158,"identity":"b80dfe0b-888f-4efb-ae1c-17e13c28f4d0","added_by":"auto","created_at":"2026-04-23 15:11:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1727186,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9061730/v1/9a7a901a-da29-4377-8fdc-314686b790d1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of metagenomic sequencing characteristics of vaginal microbiota in vaginal inflammatory diseases","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAmong all gynecological diseases, vaginitis is recognized as one of the most widespread afflictions. More than 70% of women have had vaginitis at some point in their lives. A large-scale survey revealed that 88.8% of individuals with vaginitis were seeking treatment from professional medical institutions.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Vaginal microbiota in the lower reproductive tract, which constitutes a dynamic and complex ecosystem, is vital in preventing infections.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Lactobacillus, the dominant bacterial genus in the vagina of healthy women, maintains the balance of the vaginal microecosystem by sustaining a low pH environment in the vagina and secreting substances such as hydrogen peroxide, thereby inhibiting the proliferation of other harmful microorganisms.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e When the vaginal microbiota becomes dysregulated and the abundance of pathogenic microorganisms (such as \u003cem\u003eCandida albicans\u003c/em\u003e and \u003cem\u003eGardnerella vaginalis\u003c/em\u003e) changes, it may induce the onset of vaginal inflammatory diseases such as bacterial vaginosis (BV) and vulvovaginal candidiasis (VVC).\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Patients with aerobic vaginitis (AV) exhibit increased diversity and dysbiosis of the vaginal microbiota, with the main pathogens identified in cultivation studies as group B \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e, and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e AV has been associated with an elevated risk of adverse pregnancy outcomes such as premature delivery, abortion, premature rupture of membranes (PROM), and stillbirth.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Clinically, approximately 4.44% to 35.06% of women experience at least two types of vaginitis simultaneously, also known as mixed vaginitis.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Some women exhibit symptoms of microbial communities, as evidenced by clue cells and the presence of multiple aerobic bacteria. However, mixed vaginitis poses a therapeutic challenge. The main objectives are to recognize polymicrobial interactions in mixed vaginitis, to utilize them therapeutically, and restore a healthy vaginal microbiota. Previously, the diagnosis of vaginitis relied on morphological examination to determine the diversity and density of the vaginal microbiota and pathogenic microorganisms.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e 16S rRNA sequencing technology enables a more comprehensive study of the vaginal microbiome.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Here, we use metagenomic sequencing to directly obtain genetic information of the entire microbiome, including rare, novel, and hard-to-detect pathogens, from clinical samples to identify specific microbial species associated with different types of vaginitis. It can also be used to study microbial gene functions and predict antibiotic resistance.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHuman subjects and sample collection\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eHuman subjects\u003c/h2\u003e \u003cp\u003e All selected subjects were patients and healthy women at the Gynecological Outpatient Department of Peking University People\u0026rsquo;s Hospital in China between August 2025 and October 2025, and each participant provided informed consent. The study was approved by the Ethics Committee of the Peking University People\u0026rsquo;s Hospital (2025PHB009-001) and was strictly conducted in accordance with the Declaration of Helsinki. The inclusion criteria were as follows: (1) being over 18 years old, (2) a history of sexual activity, and (3) having a regular menstrual cycle. The exclusion criteria were as follows: (1) lactation period, (2) antibiotic use within 30 days, (3) sexual activity,vaginal medication, or lavage within 7 days, and (4) individuals with tumors or cervical lesions.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eMicrobiological diagnosis of all kinds of vaginitis\u003c/h3\u003e\n\u003cp\u003eEach female underwent vaginal microecological examination. The diagnostic criterion for BV was a Nugent score\u0026thinsp;\u0026ge;\u0026thinsp;7.\u003csup\u003e12\u003c/sup\u003e Women were diagnosed with VVC when fungal spores or hyphae were observed under a microscope after Gram staining of vaginal secretion.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e The diagnosis of AV is made by an AV score analysis (a score of \u0026ge;\u0026thinsp;3 is diagnostic).\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Healthy women should undergo a normal vaginal microecological examination, including no clue cells, spores, or hyphae. The 53 samples were divided into five groups: VVC (N\u0026thinsp;=\u0026thinsp;12), VVC_BV (N\u0026thinsp;=\u0026thinsp;8), AV (N\u0026thinsp;=\u0026thinsp;10), AV_BV (N\u0026thinsp;=\u0026thinsp;3), BV (N\u0026thinsp;=\u0026thinsp;7), and healthy (N\u0026thinsp;=\u0026thinsp;13).\u003c/p\u003e\n\u003ch3\u003eSample collection\u003c/h3\u003e\n\u003cp\u003e Vaginal secretions were collected from each participant from the upper 1/3 of the vaginal lateral wall using their sterile cotton swabs. One sample was used for vaginal microbiological morphology analysis. Two samples were stored in 2 mL Eppendorf tubes at \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent metagenomic sequencing.\u003c/p\u003e\n\u003ch3\u003eDNA extraction and metagenomic sequencing\u003c/h3\u003e\n\u003cp\u003eTotal DNA was extracted using the E.Z.N.A.\u0026reg; Soil Omega Kit (Omega Bio-Tek, Norcross, GA, US) according to the manufacturer\u0026rsquo;s instructions and stored at \u0026minus;\u0026thinsp;20\u0026deg;C. After detecting the concentration and purity of DNA, DNA integrity was detected by 1% agarose gel electrophoresis. After passing the quality inspection, DNA was randomly fragmented to 350 bp using a Covaris S220 (Gene Company Limited, China) for paired-end library construction. Paired-end sequencing was performed on Illumina NovaSeq\u0026trade; X Plus (Illumina Inc., San Diego, CA, USA) at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) using NovaSeq X Series 25B Reagent Kit according to the manufacturer\u0026rsquo;s instructions (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.illumina.com\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.illumina.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eProcessing of metagenome sequencing data\u003c/h2\u003e \u003cp\u003eThe raw sequencing reads were trimmed of adapters, and low-quality reads (length\u0026thinsp;\u0026lt;\u0026thinsp;50 bp or average quality value\u0026thinsp;\u0026lt;\u0026thinsp;20) were removed using fastp (version 0.20.0). Reads were aligned to the human genome by BWA (version 0.7.17), and any hits associated with the reads and their mated reads were removed. Contigs\u0026thinsp;\u0026ge;\u0026thinsp;300 bp in length were selected as the final assembly result. Open reading frames (ORFs) from each assembled contig were predicted using Prodigal(version 2.6.3), and ORFs with a length of \u0026ge;\u0026thinsp;100 bp were retrieved. A non-redundant gene catalog was constructed using CD-HIT(version 4.7) with 90% sequence identity and 90% coverage. Gene abundance for a certain sample was estimated by SOAPaligner with 95% identity.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTaxonomic and functional annotation\u003c/h3\u003e\n\u003cp\u003eThe best-hit taxonomy of non-redundant genes was obtained by aligning them against the NCBI NR database by DIAMOND (version 2.0.13) with an e-value cutoff of 1e-5. The NR library was used for species taxonomic annotation to obtain the relative abundance of microbial communities at various levels, from phylum to species. Statistics on species abundance were conducted at the classification levels of kingdom, phylum, class, order, family, genus, and species.\u003c/p\u003e \u003cp\u003eAlpha diversity analysis is used to evaluate the richness and diversity of microbial communities in samples.PCoA (principal coordinates analysis) was used to evaluate similarities and differences in the composition of sample communities using Bray-Curtis distances in ANOSIM. Linear discriminant analysis effect size (LEfSe) was used to identify statistically significant biological markers between groups.\u003c/p\u003e \u003cp\u003eThe best-hit taxonomy of non-redundant genes was obtained by aligning them against the NCBI NR database with DIAMOND, using an e-value cutoff of 1e-5. Similarly, the functional annotation (CARD, PHI) of non-redundant genes was obtained. Based on taxonomic and functional annotations and the abundance profiles of non-redundant genes, the differential analysis was carried out at each taxonomic, functional, or gene-wise level using the Kruskal-Wallis test.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDiversity analysis of vaginal microbiota between healthy women and patients with vaginitis\u003c/h2\u003e \u003cp\u003eSignificant differences were observed between the healthy and BV groups, and between the BV and VVC groups, based on the Ace index (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-a). There were significant differences between the healthy and BV, AV_BV groups, or the VVC and AV_BV groups, based on the Shannon index (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-b). The alpha diversity of the vaginal microbiota in women with AV and AV_BV groups was marginally higher than that in healthy women, and this difference was statistically significant based on the Chao index (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-c). According to the β-diversity analysis, significant differences in vaginal microbiota diversity were observed between the healthy group and the AV, BV, VVC, AV_BV, and VVC_BV groups (R\u0026thinsp;=\u0026thinsp;0.568, P\u0026thinsp;=\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-d). Results showed that the AV group differed significantly from the BV and AV_BV groups, whereas no significant differences were detected between the BV and AV_BV groups (R\u0026thinsp;=\u0026thinsp;0.317, P\u0026thinsp;=\u0026thinsp;0.103, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-e). Results of principal coordinate analysis (PCoA) showed significant differences between the BV and VVC groups, the VVC and VVC_BV groups, but no significant difference between the BV and VVC_BV groups (R\u0026thinsp;=\u0026thinsp;0.563, P\u0026thinsp;=\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-f).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of vaginal microbiota composition\u003c/h2\u003e \u003cp\u003eThe overall composition of the vaginal microbiome in the six groups is as follows. In the healthy group, at the genus level, \u003cem\u003eLactobacillus\u003c/em\u003e (91.5%) exhibited the highest abundance, which was significantly greater compared to its levels in the other groups, followed by \u003cem\u003eGardnerella\u003c/em\u003e (4.8%). In comparison, the BV group was dominated by \u003cem\u003eGardnerella\u003c/em\u003e (57.8%), followed by \u003cem\u003ePrevotella\u003c/em\u003e (9.05%) and \u003cem\u003eFannyhesse\u003c/em\u003ea (4.76%). For the AV_BV group, \u003cem\u003eGardnerella\u003c/em\u003e (34.58%) was the most abundant, with \u003cem\u003eFannyhessea\u003c/em\u003e (15.72%) and \u003cem\u003eMobiluncus\u003c/em\u003e (12.86%) following. In the AV group, \u003cem\u003eStreptococcus\u003c/em\u003e (39.82%) showed the highest abundance, next to \u003cem\u003eEnterococcus\u003c/em\u003e (17.29%) and \u003cem\u003ePrevotella\u003c/em\u003e (8.75%). The VVC group exhibited dominance of \u003cem\u003eLactobacillus\u003c/em\u003e (83.87%), \u003cem\u003eCandida\u003c/em\u003e (5.07%), and \u003cem\u003ePseudomonas\u003c/em\u003e (3.16%). Finally, in the VVC_BV group, \u003cem\u003eGardnerella\u003c/em\u003e (58.71%), \u003cem\u003eLactobacillus\u003c/em\u003e (21.49%), and \u003cem\u003eFannyhessea\u003c/em\u003e (9.27%) were dominant (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-a).\u003c/p\u003e \u003cp\u003eAt the species level, \u003cem\u003eL.crispatus\u003c/em\u003e (46.05%) and \u003cem\u003eLactobacillus iners\u003c/em\u003e (26.81%) were the most abundant in the healthy group. At the species level of \u003cem\u003eGardnerella\u003c/em\u003e, \u003cem\u003eG.vaginalis\u003c/em\u003e was the most abundant in the BV group, AV_BV group, AV group, VVC_BV group, and VVC group (45.92%, 17.73%, 0.91%, 33.32% and 0.44%, respectively). At the species level of \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eL. crispatus\u003c/em\u003e was the dominant \u003cem\u003eLactobacillus\u003c/em\u003e in the healthy group (46.05%) and AV group (3.78%). \u003cem\u003eLactobacillus iners\u003c/em\u003e was the dominant \u003cem\u003eLactobacillus\u003c/em\u003e in the BV group (2.14%), AV_BV group (2.16%), VVC_BV group (12.92%), and VVC group (47.23%). In the AV group, \u003cem\u003eStreptococcus_sp\u003c/em\u003e (29.11%) was the most abundant, followed by \u003cem\u003eStreptococcus_anginosus\u003c/em\u003e (4.92%). In the VVC and VVC_BV groups, \u003cem\u003eC.albicans\u003c/em\u003e (4.34% and 1.34%, respectively) was the dominant \u003cem\u003eCandida\u003c/em\u003e species (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-b).\u003c/p\u003e \u003cp\u003eAt the genus level, the relative abundance of \u003cem\u003eStreptococcus\u003c/em\u003e was significantly higher in the AV group compared to the AV_BV, BV, Healthy, VVC, and VVC_BV groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-c). At the species level of \u003cem\u003eStreptococcus\u003c/em\u003e, the relative abundance of \u003cem\u003eStreptococcus agalactiae\u003c/em\u003e was significantly higher in the AV group compared to the AV_BV, BV, Healthy, VVC, and VVC_BV groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-d). The relative abundance of \u003cem\u003eEnterococcus\u003c/em\u003e was significantly higher in the AV group than in the other groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-e). Compared to the other group, the relative abundance of \u003cem\u003eC. albicans\u003c/em\u003e was higher in the VVC_BV group as well as in the VVC group. However, no significant difference in \u003cem\u003eC. albicans\u003c/em\u003e was observed between any two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-f). The relative abundance of \u003cem\u003eMobiluncus\u003c/em\u003e was significantly higher in the AV_BV group compared to the AV, BV, Healthy, VVC, and VVC_BV groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-g). At the species level of \u003cem\u003eMobiluncus\u003c/em\u003e, the relative abundance of \u003cem\u003eMobiluncus.mulieris\u003c/em\u003e was significantly higher in the AV_BV group compared to the AV, BV, Healthy, VVC, and VVC_BV groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-h).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLinear discriminant analysis effect size variance analysis\u003c/h2\u003e \u003cp\u003eWe next conducted linear discriminant analysis (LDA) and effect size (LEfSe) between each patient group and the healthy groups. Significant changes were observed at the species level in 11 microbes between the healthy and AV groups (LDA\u0026thinsp;\u0026gt;\u0026thinsp;4) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-a). \u003cem\u003eStreptococcus.sp\u003c/em\u003e, \u003cem\u003eEnterococcus.sp\u003c/em\u003e, \u003cem\u003ePrevotella.Bivia\u003c/em\u003e, \u003cem\u003eStreptococcus.anginosus\u003c/em\u003e, \u003cem\u003eEnterococcus. faecalis\u003c/em\u003e, \u003cem\u003eLactobacillus.delbrueckii\u003c/em\u003e, and \u003cem\u003eStreptococcus.agalactiae\u003c/em\u003e were significantly enriched in the AV group, while \u003cem\u003eL.crispatus\u003c/em\u003e, \u003cem\u003eLactobacillus. iners\u003c/em\u003e, \u003cem\u003eLactobacillus.sp\u003c/em\u003e, and \u003cem\u003eLactobacillus.jensenii\u003c/em\u003e were significantly enriched in the healthy group. Significant changes were observed at the species level in 10 microbes between the healthy and AV_BV groups (LDA\u0026thinsp;\u0026gt;\u0026thinsp;4) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-b). \u003cem\u003eMobiluncus.mulieris\u003c/em\u003e, \u003cem\u003eFannyhessea.vaginae\u003c/em\u003e, \u003cem\u003eG.vaginalis\u003c/em\u003e, \u003cem\u003eGardnerella.sp\u003c/em\u003e, \u003cem\u003eHoylesella.timonensis\u003c/em\u003e, \u003cem\u003eGardnerella.sp.KA00735\u003c/em\u003e, and \u003cem\u003ePorphyromonas.sp\u003c/em\u003e were significantly enriched in the AV_BV group, while \u003cem\u003eL. crispatus\u003c/em\u003e, \u003cem\u003eLactobacillus sp.\u003c/em\u003e, and \u003cem\u003eLactobacillus.jensenii\u003c/em\u003e were significantly enriched in the healthy group. Significant changes were observed at the species level in 11 microbes between the healthy and BV groups (LDA\u0026thinsp;\u0026gt;\u0026thinsp;4). \u003cem\u003eG.vaginalis\u003c/em\u003e, \u003cem\u003eGardnerella.sp\u003c/em\u003e, \u003cem\u003eFannyhessea.vaginae\u003c/em\u003e, \u003cem\u003ePrevotella.amnii\u003c/em\u003e, \u003cem\u003eSneathia.sanguinegens\u003c/em\u003e, \u003cem\u003ePrevotella.bivia\u003c/em\u003e, \u003cem\u003eMegasphaera.lornae\u003c/em\u003e, and \u003cem\u003eAmygdalobacter.indicium\u003c/em\u003e were significantly enriched in the BV group, while \u003cem\u003eL.crispatus\u003c/em\u003e, \u003cem\u003eLactobacillus.sp\u003c/em\u003e, and \u003cem\u003eLactobacillus.jensenii\u003c/em\u003e were significantly enriched in the healthy group.\u003c/p\u003e \u003cp\u003eSignificant species-level differences were observed in 12 microbes when comparing the AV_BV and AV groups (LDA\u0026thinsp;\u0026gt;\u0026thinsp;4) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-c). \u003cem\u003eStreptococcus.sp\u003c/em\u003e, \u003cem\u003eStreptococcus.anginosus\u003c/em\u003e, \u003cem\u003eEnterococcus.faecalis\u003c/em\u003e, \u003cem\u003ePseudomonas.sp\u003c/em\u003e, \u003cem\u003eStreptococcus.agalactiae\u003c/em\u003e, and \u003cem\u003eLactobacillus.delbrueckii\u003c/em\u003e were significantly enriched in the AV group, while \u003cem\u003eG.vaginalis\u003c/em\u003e, \u003cem\u003eFannyhessea.vaginae\u003c/em\u003e, \u003cem\u003eMobiluncus.mulieris\u003c/em\u003e, \u003cem\u003eGardnerella.sp\u003c/em\u003e, \u003cem\u003eGardnerella.sp.KA00735\u003c/em\u003e, and \u003cem\u003eSchwartzia.sp.in.firmicutes\u003c/em\u003e were significantly enriched in the AV_BV group. Between the AV_BV and BV groups (LDA\u0026thinsp;\u0026gt;\u0026thinsp;2.5) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-d), three microbes at the species level showed significant differences. \u003cem\u003eAtopobium.deltae\u003c/em\u003e, and \u003cem\u003eAnaerococcus.sp\u003c/em\u003e were significantly enriched in the BV group, while \u003cem\u003eBifidobacterium.sp\u003c/em\u003e was significantly enriched in the AV_BV group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eSignificant differences in vaginal flora functional potentials of virulence factor and antibiotic resistance between healthy women and patients with vaginitis\u003c/em\u003e \u003c/p\u003e \u003cp\u003eTo characterize the gene features of the healthy vaginal microbiome, we constructed a non-redundant gene catalog from metagenomic data and annotated it using the Virulence Factor Database (VFDB) and the Comprehensive Antibiotic Resistance Database (CARD) with Diamond software. We then used the Spearman correlation to assess the association between gene relative abundance and disease states, and the Wilcoxon rank-sum test to identify differential genes across groups.\u003c/p\u003e \u003cp\u003eWilcoxon rank-sum test analysis revealed that the relative abundance of fluoroquinolone antibiotic, macrolide antibiotic, rifamycin antibiotic resistance gene efrB in the healthy group was significantly higher than in the AV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), AV_BV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and the BV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-a). The relative abundance of aminocoumarin antibiotic resistance gene novA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-b), tetracycline antibiotic resistance gene tetB (60) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-c), and tetA (46) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-d) in the healthy group was significantly higher than in the BV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eIn the comparison between the healthy and the BV group, the relative abundance of the macrolide antibiotic resistance gene macB, the glycopeptide antibiotic resistance gene mlaF, the nitroimidazole antibiotic resistance gene msbA, and the fluoroquinolone antibiotic resistance gene patB in the BV group was significantly higher than in the healthy group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-e). The relative abundance of macrolide antibiotic resistance gene macB, nitroimidazole antibiotic resistance gene msbA, and pleuromutilin antibiotic resistance gene TaeA in the AV_BV group was significantly higher than in the healthy group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-f). The relative abundance of macrolide antibiotic resistance gene macB and aminoglycoside antibiotic resistance gene RanA in the AV group was significantly higher than in the healthy group. Besides the aminocoumarin antibiotic resistance gene novA, the fluoroquinolone antibiotic resistance gene PatA, and the lincosamide antibiotic resistance gene lmrD, which were also higher in the healthy group than in the AV group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-g).\u003c/p\u003e \u003cp\u003eThe relative abundance of immune modulation related virulence factor LOS (VF0044) in the healthy group was significantly lower than in the AV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), AV_BV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and the BV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-h). The relative abundance of nutritional/metabolic factor related virulence factor MgtBC (VF0106) in the healthy group was significantly higher than in the AV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), AV_BV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and the BV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-i).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cem\u003eLactobacillus\u003c/em\u003e is the main bacterium of the normal vaginal microbiota.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Not only the predominance of a specific \u003cem\u003eLactobacillus\u003c/em\u003e but also its relative abundance were pivotal in maintaining vaginal physiologic status.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Imbalance in the vaginal microbiota might lead to numerous vaginal diseases, including AV and BV.\u003csup\u003e17\u003c/sup\u003e Previous studies showed that a reduction of \u003cem\u003eFirmicutes\u003c/em\u003e (mainly \u003cem\u003eL. crispatus\u003c/em\u003e and \u003cem\u003eL. iners\u003c/em\u003e) was accompanied by an increase in \u003cem\u003eStreptococcus agalactiae\u003c/em\u003e, \u003cem\u003eStaphylococcus aureu\u003c/em\u003es, and \u003cem\u003eEscherichia coli\u003c/em\u003e, leading to inflammation symptoms in AV.\u003csup\u003e18\u003c/sup\u003e However, the description of microbial populations in AV often relies on 16S rRNA gene sequencing technology and cultivation.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e In our study, we adopted metagenomic sequencing to characterize the microbial population associated with vaginitis. We discovered the vaginal microbiota and functional relationships among patients with AV, BV, and both AV and BV. These discoveries enhanced our cognition of the unique characteristics and treatment improvements of vaginal microbiota in vaginitis.\u003c/p\u003e \u003cp\u003eThe abundance of \u003cem\u003eStreptococcus\u003c/em\u003e was the highest in the AV group, followed by \u003cem\u003eEnterococcus\u003c/em\u003e and \u003cem\u003ePrevotella\u003c/em\u003e. In the AV group, \u003cem\u003eStreptococcus\u003c/em\u003e was the most abundant, and the relative abundance of \u003cem\u003eStreptococcus\u003c/em\u003e was significantly higher in the AV group compared to the AV_BV, BV, Healthy, VVC, and VVC_BV groups. \u003cem\u003eStreptococcus\u003c/em\u003e was the biomarker associated with AV. At the species level of \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eL. crispatus\u003c/em\u003e was the dominant \u003cem\u003eLactobacillus\u003c/em\u003e in the AV group, whereas \u003cem\u003eL.crispatus\u003c/em\u003e and \u003cem\u003eLactobacillus iners\u003c/em\u003e were the most abundant in the healthy group, suggesting that \u003cem\u003eL.crispatus\u003c/em\u003e and \u003cem\u003eLactobacillus iners\u003c/em\u003e play an important role in maintaining the homeostasis of the vaginal microenvironment.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMixed vaginitis refers to the presence of at least two types of vaginitis simultaneously, leading to an abnormal vaginal environment. In the current study, there were significant differences between the healthy and AV_BV groups based on the Simpson index (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The alpha diversity of the vaginal microbiota in women with AV_BV groups was higher than that in healthy women, as measured by the Chao index(p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).In the AV_BV group, \u003cem\u003eGardnerella\u003c/em\u003e was the most abundant, followed by \u003cem\u003eFannyhessea\u003c/em\u003e and \u003cem\u003eMobiluncus\u003c/em\u003e. \u003cem\u003eGardnerella\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, and \u003cem\u003eFannyhessea\u003c/em\u003e were the top three dominant genera in the VVC_BV group. \u003cem\u003eLactobacillus iners\u003c/em\u003e was the dominant \u003cem\u003eLactobacillus\u003c/em\u003e in both the AV_BV and VVC_BV groups. These results suggest that the diversity of vaginal microbiota in patients with mixed vaginitis increases, and their microbiota structure undergoes significant changes, while the abundance of healthy lactobacilli decreases. \u003cem\u003eGardnerella\u003c/em\u003e and \u003cem\u003eFannyheshsea\u003c/em\u003e, which were clinically considered the pathogens of BV, have a dominant position in the vaginal microbiome of patients with AV and BV, consistent with previous research findings.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e The AV_BV group showed a composition of vaginal microbiota close to the BV group. An increase in \u003cem\u003eLactobacillus\u003c/em\u003e abundance in the vagina during treatment for AV and mixed vaginitis may help reduce disease recurrence.\u003c/p\u003e \u003cp\u003eThe vaginal microbiota of healthy women is dominated by lactobacilli, which is more conducive to preventing the invasion of pathogenic microorganisms and maintaining the stability of the vaginal microbiota. In patients with different types of vaginitis, the vaginal microbiota is more diverse and enriched, leading to a significant increase in the number of bacterial species involved in the pathogenesis of vaginitis and a more complex bacterial composition.\u003c/p\u003e \u003cp\u003eAntimicrobial drug resistance is one of the biggest threats to the failure of vaginal inflammation treatment. Understanding the mechanisms of microbial resistance in microbes is crucial to the study of drug therapy for vaginitis. Resistance to antibiotics may result from multiple mechanisms. The first line of bacterial defense is to actively efflux antimicrobial compounds.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Bacteria carrying antibiotic-resistant genes (ARGs) may become the predominant pathogens.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Studying ARGs and leveraging the synergistic effects of antibiotic combinations may enable low-dose treatment of infections with multiple antibiotics.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Matthew Igo et al. found that, in a study examining the effects of antibiotic treatment on the gut microbiota of BALB/c mice, low-dose monotherapy increased ARG abundance compared to control and high-dose monotherapy.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIntegral membrane proteins known as drug efflux pumps actively export antibiotics from the cell. This process is recognized as a vital cellular protection mechanism against the toxicity of these and other therapeutic agents.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e The ABC-type drug efflux pump macB is highly conserved and widespread among bacterial species.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e As found in our research, the abundance of the macrolide antibiotic resistance gene macB is higher in various cases than in healthy women. In this study, the relative abundance of the glycopeptide antibiotic resistance gene mlaF, the nitroimidazole antibiotic resistance gene msbA, and the fluoroquinolone antibiotic resistance gene patB was significantly higher in the BV group than in the healthy group. This indicates that the resistance mechanism of BV to nitroimidazole drugs was analyzed from the perspective of antibiotic resistance genes. The AV_BV group not only tends to be similar to the BV group in vaginal microbiota composition but also shows an increase in the abundance of nitroimidazole antibiotic resistance gene msbA.\u003c/p\u003e \u003cp\u003eThe PatAB multidrug efflux pump is involved in resistance to ciprofloxacin (CPX) and norfloxacin in clinical isolates of Streptococcus.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e LmrD is a chromosomally encoded efflux pump that confers resistance to lincosamides in Streptomyces lincolnensis and Lactococcus lactis. It can dimerize with lmrC, which can confer resistance to antibiotics, such as macrolides, lincomamides, and streptococcins.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e In this study, the abundance of the fluoroquinolone antibiotic resistance gene PatA and the lincosamide antibiotic resistance gene lmrD was lower in the AV group than in the healthy group. This indicates that the possibility of resistance in the vaginal microbiota of AV women through this mechanism is lower than in healthy women.\u003c/p\u003e \u003cp\u003eThe lipooligosaccharide (LOS) is a molecule that provides critical protection to the bacterium against host defenses, may act as an adhesin, and is an endotoxin that signals through toll-like receptor 4 and NF-κB to cause inflammation.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e The relative abundance of the virulence factor LOS in the healthy group was significantly lower than in the AV, AV_BV and the BV groups. Therefore, the LOS is a critical component that enables pathogenic microorganisms in vaginitis to resist host defenses and cause disease.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e In conclusion, our study provided valuable insights into the characteristics of the vaginal flora in AV and BV combined with AV (AV_BV). We found that the vaginal flora of patients in the AV_BV and VVC_BV groups exhibited structural similarities to that of the BV group. This finding emphasizes the complexity of mixed vaginal infections and may have clinical implications for treatment strategies. Metagenomic technology offers a valuable tool for investigating the composition and function of vaginal microbiota in cases of vaginitis. In this study, we preliminarily explored ARGs and virulence factors, elucidated the functional status of vaginal microbiota in vaginitis, and provided insights into the treatment of vaginitis.\u003c/p\u003e"},{"header":"Declarations","content":"\n\u003cp\u003e\u003cem\u003eAcknowledgments:\u003c/em\u003e Thanks for support by the gynecology clinic of Peking University People\u0026apos;s Hospital. \u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eData availability:\u003c/em\u003e All the data generated or analyzed during this study are included in this published article (and its supplementary information files).\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eAuthor contributions:\u003c/em\u003e Ruichen Wang arranged the samples, did the experiment, analyzed the data, and wrote the article; Ruichen Wang and Siqi Li collected the data; Xiao Yang contributed to the sample collection and data analysis; Honglan Zhu collected the references; Jianliu Wang and Xudong Liang conceived and designed the study; and all the authors read and approved the final manuscript.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorkowski KA, Bachmann LH, Chan PA et al (2021) Sexually Transmitted Infections Treatment Guidelines, 2021. 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Curr Top Microbiol Immunol 396:131\u0026ndash;148. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/82_2015_5020\u003c/span\u003e\u003cspan address=\"10.1007/82_2015_5020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"current-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Current Microbiology","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"Vaginal microbiota, metagenomic sequencing, vaginal inflammatory diseases, aerobic vaginitis, mixed vaginitis","lastPublishedDoi":"10.21203/rs.3.rs-9061730/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9061730/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eOBJECTIVE\u003c/h2\u003e \u003cp\u003eTo investigate whether different types of vaginitis have distinct microbiota in the female reproductive tract, and whether bacteria may have specific functions.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e \u003cp\u003eThis is a cross-sectional study involving 53 patients who visited the gynecology clinic of Peking University People's Hospital for examination. Vaginal secretions were collected from each participant Samples were used for metagenomic sequencing.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eOur results identified that patients with various types of vaginitis exhibited increased vaginal microbiota diversity. The vaginal microbiota of patients with AV is mainly composed of \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, and \u003cem\u003ePrevotella\u003c/em\u003e. \u003cem\u003eMobiluncus.mulieris\u003c/em\u003e is an important biomarker for patients in the AV_BV group. CARD analysis showed that the relative abundance of resistance gene efrB in the healthy group was significantly higher than in the other vaginitis groups. The relative abundance of the immune modulation-related virulence factor LOS (VF0044) in the healthy group was significantly lower than in the AV group, AV_BV group, and the BV group.\u003c/p\u003e\u003ch2\u003eCONCLUSION\u003c/h2\u003e \u003cp\u003eThe vaginal flora of patients in the AV_BV and VVC_BV groups exhibited structural similarities to that of the BV group. The antibiotic resistance genes in the microbiota urgently require clinical attention.\u003c/p\u003e","manuscriptTitle":"Analysis of metagenomic sequencing characteristics of vaginal microbiota in vaginal inflammatory diseases","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 15:10:32","doi":"10.21203/rs.3.rs-9061730/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-16T06:26:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-14T13:34:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-10T16:39:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Current Microbiology","date":"2026-03-08T03:20:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"","identity":"current-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Current Microbiology","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1dc0774b-6862-40df-888c-50212bada70b","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T15:10:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 15:10:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9061730","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9061730","identity":"rs-9061730","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}