Lactobacillus Iners and Vaginal Microbiome Diversity as Risk Factors of Uterine Cervix Dysplasia: A Prospective Study

Lactobacillus Iners and Vaginal Microbiome Diversity as Risk Factors of Uterine Cervix Dysplasia: A Prospective Study | 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 Lactobacillus Iners and Vaginal Microbiome Diversity as Risk Factors of Uterine Cervix Dysplasia: A Prospective Study Tomas Rokos, Veronika Holubekova, Lucia Mackova, Erik Kozubik, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7861075/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Increasing evidence has suggested that changes in the physiological composition of the human vaginal microbiome are associated with cervical cytological abnormalities. The aim of this study was to observe the vaginal microbiome composition in patients with cervical dysplasia. Methods In this prospective study, 91 samples of the vaginal microbiome taken from the cervix and posterior vaginal fornix were included. Eighteen bacterial species, including Lactobacillus species, were identified by real-time PCR. Relative bacterial quantities (RQs) were calculated, and log2-transformed RQs were visualised with boxplots. The relationships between cytological abnormalities and bacterial species were calculated by nonparametric one-way ANOVA (Kruskal‒Wallis test). For determination of bacterial diversity, the Shannon index was used. Results We demonstrated an increase in the abundance of vaginal microbiome samples dominated by L. iners with increasing severity of cytologically and histologically confirmed cervical lesions, while HPV infection was present in 73.1% of community state type 3 samples. The presence of G. vaginalis and U. parvum in combination with L. iners was statistically significant. Our study also revealed considerably higher bacterial diversity in the community state type IV category. An increasing trend of bacterial diversity with increasing cytological severity of cervical lesions was also observed, although the difference was nonsignificant. Conclusion This study suggests that L. iners has adverse effects on the development of cervical dysplasia, while L. gasseri and L. crispatus may play protective roles. We also demonstrated the association of L. iners with anaerobic bacteria, and we suggest the potential role of bacterial diversity in cervical carcinogenesis. Trial registration number is EK 85/2020, the date of registration is 14 December 2020. vaginal microbiome cervical dysplasia lactobacilli HPV Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background The human body is colonised by a vast array of microorganisms that collectively form the human microbiome. It comprises approximately 500 to 1,000 bacterial species (spp.) [ 1 ], with a total gene content that exceeds that of the human genome [ 2 ]. The vaginal microbiome, which is predominantly composed of Lactobacillus spp., plays a crucial role in preventing urinary tract infections [ 3 ], urogenital disorders, and sexually transmitted infections [ 4 ]. The vaginal microbiota of healthy, sexually active women can be classified into five distinct community state types (CSTs). Four of these (CSTs I, II, III, and V) are dominated by Lactobacillus species— Lactobacillus crispatus (CST I), L. gasseri (CST II), L. iners (CST III), and L. jensenii (CST V). In contrast, CST IV is characterised by a depletion of lactobacilli and a dominance of strict anaerobes [ 5 ]. Lactobacillus species are considered protective against colonisation by vaginal pathogens because of their production of organic acids, hydrogen peroxide (H₂O₂), and antimicrobial peptides such as bacteriocins [ 6 ]. Conversely, the overgrowth of anaerobic bacteria—a condition referred to as bacterial vaginosis (BV) —is associated with reduced lactate levels and increased concentrations of short-chain fatty acids (SCFAs) and their anions. Unlike those in the intestinal microbiota, elevated SCFA levels in the vaginal environment are indicative of dysbiosis [ 7 ]. A shift from Lactobacillus -dominant vaginal microbiota to pathogen-dominant communities—indicative of vaginal dysbiosis—leads to disruptions in immune function and epithelial homeostasis. This transition is associated with increased production of proinflammatory cytokines and chemokines, activation of immune pathways, and reduced viscosity of cervicovaginal secretions due to mucin-degrading enzyme activity. These changes compromise mucosal barrier integrity, thereby increasing susceptibility to sexually transmitted infections, including high-risk human papillomavirus (hrHPV) infections [ 8 ]. Interestingly, not all Lactobacillus species play a clearly protective role. Lactobacillus iners , first described in 1999 [ 9 ], is among the most prevalent vaginal species [ 10 ]. However, its presence is not consistently associated with a healthy microbiota. Srinivasan et al. [ 11 ] reported that women with high levels of L. crispatus rarely have BV, whereas those with high levels of L. iners could be either BV-negative or BV-positive. These findings suggest that L. iners may not provide sufficient protection against BV [ 11 ]. Nonetheless, L. iners has been demonstrated to have an inhibitory effect on Gardnerella vaginalis growth, indicating that it may still play a nuanced role in microbial interactions [ 12 ]. Various aspects of vaginal health have been associated with Lactobacillus iners dominance in the vaginal microbiome, as well as with the detrimental effects of vaginal dysbiosis. In our study, we focused on the relationship between variations in the vaginal microbiome composition and the potential development of cervical dysplasia—a topic of continued relevance due to its risk of progression to cervical cancer. Materials and methods 1. Sample collection Samples were collected from patients with cervical cytological abnormalities who underwent expert colposcopic examination and from healthy controls at the Ambulance of Expert Colposcopy at the Department of Gynaecology and Obstetrics, Jessenius Faculty of Medicine, Comenius University in Bratislava and University Hospital Martin. The examined group included 20 patients with atypical squamous cells with undetermined significance (ASCUS), 25 patients with low-grade squamous intraepithelial lesions (LSILs), and 26 patients with high-grade squamous intraepithelial lesions (HSILs); 20 samples from women who were negative for intraepithelial lesions or malignancies (NILM) constituted the control group. During the examination, a cervical swab was taken from the exocervix and posterior vaginal fornix. The samples were transported to the Laboratory of Genomics and Prenatal Diagnostics, Biomedical Centre Martin, Jessenius Faculty of Medicine, Comenius University, in Bratislava and stored at -80°C in viral/bacterial transport medium (Jiangsu Mole Bioscience, Taizhou, China) until further processing. The study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava no. EK 85/2020. 2. Nucleic acid extraction The collected samples were thawed and mixed before processing. The samples were subsequently centrifuged at 3000 revolutions per minute (rpm) for 10 minutes at 4°C. The supernatant was removed, and the cells were washed twice with phosphate-buffered saline (pH 7.0). Subsequently, 100 µl of the cell suspension was used for DNA extraction with the MasterPure Complete DNA and RNA Purification Kit (Biosearch Technologies, Hoddesdon, UK) according to the manufacturer's instructions. The extracted DNA was incubated with RNase A for 30 minutes at 37°C. The deoxyribonucleic acid (DNA) was diluted in 35 µl of TE (Tris + EDTA, pH 8) buffer. The quality and quantity of the DNA were measured with a Qubit dsDNA HS assay kit (Invitrogen, Thermo Fisher Scientific, Carlsbad, CA, USA) on a Qubit 4.0 instrument (Invitrogen). 3. Detection of selected microbial strains We tested 120 ng of DNA by real-time polymerase chain reaction (qPCR) to identify eighteen microbial strains according to the manufacturer's instructions (Custom Microbial DNA qPCR Array, Qiagen, Hilden, Germany). The PCR plate contained microbial DNA arrays of 18 bacterial species ( Lactobacillus crispatus , Lactobacillus gasseri , Lactobacillus jensenii , Lactobacillus iners , Aerococcus christensenii , Atopobium vaginae , Fusobacterium nucleatum , Gardnerella vaginalis , Leptotrichia amnionii , Mobiluncus spp., Mycoplasma hominis , Parvimonas micra , Prevotella bivia , Prevotella disiens , Sneathia sanguinegens , Streptococcus agalactiae , Streptococcus mitis , and Ureaplasma parvum ), bacterial 16S rRNA (Pan B1 and Pan B3) and fungal ribosomal rRNA genes (Pan Asp/Can), and a positive PCR control (PPC). One plate allowed the examination of four patients. In total, 25 microliters (µl) of a solution consisting of 12.5 µl of microbial qPCR master mix, primer/probe depending on the position on the plate, and 11.5 µl of microbial DNA-free water (Qiagen) together with 5 ng of DNA was applied to the wells of a 96-well plate. The microbial strains were detected with a QuantStudio 5 (Applied Biosystems) with thermal cycling with initial denaturation at 95°C for 10 min, an additional 40 cycles of denaturation at 95°C for 15 s and annealing and elongation at 60°C for 2 min. All the samples were analysed with the instrument software according to the manufacturer's recommendations. HPV infection was identified according to a well-established method published in our previous study [ 13 ]. 4. Statistical analysis For data analysis, R (version 4.4.2) [ 14 ] was used. For this purpose, values were summarised using counts and percentages for categorical variables; for continuous variables, medians with lower and upper quartiles were reported. The threshold for a positive Ct result was set to 37 cycles according to the manufacturer’s recommendations. To inspect the co-occurrence (prevalence) of L. iners with other variables across all CST types, Fisher’s exact test was used. A subset of CST type 4 was subsequently used to examine the co-occurrence of G. vaginalis with other bacterial taxa using Fisher’s exact test. A one-sample binomial test was applied to examine whether the prevalence of each bacterial taxon differed significantly from the threshold value of 0.5. Owing to multiple testing in this section, Benjamini‒Hochberg correction for p value adjustment was applied. The prevalence of HPV infection between CST type 3 and other types (1, 2, and 5) and between CST type 4 and other types (1, 2, and 5) was examined. For this purpose, owing to the sufficient number of observations (n > 5 in each group), Pearson’s chi-square test was used. The Shannon diversity index was computed from relative abundances (abundances were calculated as 2^(-ΔCt), where the average Ct of 16S RNA genes was subtracted from the Ct of the selected bacterium in a given sample). The results were visualised via boxplots at the lesion and CST type levels. First, the Kruskal‒Wallis test was applied to assess differences among all levels; subsequently, pairwise comparisons between levels were performed using the Wilcoxon rank-sum test. For the CST type, level 5 was excluded from pairwise comparisons because of the low number of observations. Finally, heatmaps of relative abundances were generated for each sample at each level of the CST type. Results Analysis of clinicopathological data Among the 91 samples, the average age was 36.2 ± 9.61 years. The presence of HPV infection was detected in 55% (50/91) of the cervical cytological samples and increased with increasing severity of squamous intraepithelial lesions (p<0.05) (Table 1). In this study, we examined the selected microbial strains frequently present in the cervical cytological smears of women in the Zilina region in Slovakia. On the basis of the results of the PCR analysis, the cervical swab samples were classified into community state types (CSTs) according to the lowest delta Ct number, which was calculated as the Ct of average 16S rRNA genes subtracted from the Ct of the selected bacterium. In our cohort, 19 samples were classified into the CST 1 category with a dominance of L. crispatus , 11 samples were classified into the CST 2 category with a dominance of L. gasseri , 26 samples were classified into the CST 3 category with a dominance of L. iners , 5 samples were classified into the CST 5 category with a dominance of L. jensenii , and 30 samples were classified into the CST 4 category with dominance of bacteria other than Lactobacillus spp. There were no significant differences in age among the patients in the categories of CST 1–5 (p>0.9). The division of samples into CST classes with other monitored parameters is shown in Table 1. The proportions of bacterial strains across CST classes are listed in Table 2. Table 1. Classification of samples in the CST classes with other monitored parameters. Characteristic n CST 1 CST 2 CST 3 CST 4 CST 5 n 91 1 9 1 1 2 6 3 0 5 Age 1 m edian (Q1, Q3) 91 35 (29, 43) 33 (31, 40) 37 (29, 44) 36 (29, 45) 33 (30, 34) 1 m ean (SD) 91 37.11 ± 10.75 36.45 ± 8.74 36.08 ± 9.78 38.48 ± 14.37 33.40 ± 9.42 HPV absent, n (%) 42 10 (53%) 7 (64%) 7 (27%) 15 (50%) 3 (60%) present, n (%) 49 9 (47%) 4 (36%) 19 (73%) 15 (50%) 2 (40%) Lesion NILM, n (%) 20 5 (26%) 5 (45%) 2 (7.6%) 7 (23%) 1 (20%) ASCUS, n (%) 20 4 (21%) 1 (9.1%) 6 (23%) 7 (23%) 2 (40%) LSIL, n (%) 25 7 (37%) 2 (18.2%) 8 (31%) 8 (27%) 0 (0%) HSIL, n (%) 26 3 (16%) 3 (27.3%) 10 (38.4%) 8 (27%) 2 (40%) Biopsy negative, n (%) 14 8 (42%) 0 (0%) 2 (8%) 3 (10%) 1 (20%) CIN1, n (%) 10 1 (5%) 0 (0%) 4 (15%) 4 (13%) 1 (20%) CIN2, n (%) 22 2 (11%) 2 (18%) 10 (38%) 8 (27%) 0 (0%) CIN3/CIS, n (%) 13 0 (0%) 2 (18%) 5 (19%) 4 (13%) 2 (40%) not investigated, n (%) 32 8 (42%) 7 (64%) 5 (19%) 11 (37%) 1 (20%) Abbreviations: n, number of samples; CST, community state type; Q, quartile; SD, standard deviation; HPV, human papillomavirus; %, percentage; NILM, negative for intraepithelial lesion or malignancy; ASCUS, atypical squamous cells of undetermined significance; LSIL, low-grade squamous intraepithelial lesion; HSIL, high-grade squamous intraepithelial lesion; CIN, cervical intraepithelial neoplasia Table 2. Representation of bacterial strains among community state type (CST) classes with the number of samples and percentage representations. Characteristic CST 1 n (%) CST 2 n (%) CST 3 n (%) CST 4 n (%) CST 5 n (%) n 19 11 26 30 5 Lactobacillus crispatus 19 (100%) 3 (27%) 12 (46%) 9 (30%) 1 (20%) Lactobacillus gasseri 7 (37%) 11 (100%) 8 (31%) 4 (13%) 2 (40%) Lactobacillus jensenii 9 (47%) 1 (9%) 14 (54%) 5 (17%) 5 (100%) Lactobacillus iners 9 (47%) 3 (27%) 26 (100%) 17 (57%) 3 (60%) Aerococcus christensenii 1 (5%) 0 (0%) 5 (19%) 11 (37%) 1 (20%) Atopobium vaginae 2 (11%) 3 (27%) 6 (23%) 20 (67%) 2 (40%) Fusobacterium nucleatum 1 (5%) 1 (9%) 1 (3.8%) 10 (33%) 0 (0%) Gardnerella vaginalis 8 (42%) 3 (27%) 18 (69%) 25 (83%) 2 (40%) Leptotrichia amnionii 0 (0%) 0 (0%) 3 (12%) 12 (40%) 0 (0%) Mobiluncus spp. 2 (11%) 0 (0%) 2 (8%) 10 (33%) 0 (0%) Mycoplasma hominis 0 (0%) 1 (9%) 1 (4%) 6 (20%) 0 (0%) Parvimonas micra 1 (5%) 0 (0%) 2 (8%) 15 (50%) 1 (20%) Prevotella bivia 6 (32%) 3 (27%) 8 (31%) 16 (53%) 3 (60%) Prevotella disiens 3 (16%) 0 (0%) 2 (8%) 13 (43%) 2 (40%) Sneathia sanguinegens 0 (0%) 0 (0%) 2 (8%) 13 (43%) 0 (0%) Streptococcus agalactiae 0 (0%) 5 (45%) 3 (12%) 7 (23%) 3 (60%) Streptococcus mitis 4 (21%) 1 (9%) 4 (15%) 4 (13%) 0 (0%) Ureaplasma parvum 7 (37%) 2 (18%) 15 (58%) 8 (27%) 3 (60%) Pan Aspergillus/Candida 3 (16%) 2 (18%) 5 (19%) 8 (27%) 1 (20%) Abbreviations: n, number of samples; CST, community state type, %, percentage Analysis of selected bacterial strains in protective cervical flora (CST 1, CST 2 and CST 5) Overall, 19 samples that were dominated by L. crispatus were categorised as CST 1. In terms of cytological classification, for the CST 1, the results were as follows: normal cytological samples (NILM), 26.3%; ASCUS samples, 21.1%; LSIL samples, 36.8%; and HSIL samples, 15.8%. HPV infection was present in 47.4% of the samples. In patients who underwent biopsy (57.9%), most biopsies were negative (42.1%) for any morphological changes, or CIN1 or CIN2 histological findings (15.8%) were present. L. gasseri was dominant in 11 cytological samples, which were categorised as CST 2. In terms of cytological classification, 45.4% of the samples were NILM, 9.1% were ASCUS samples, 18.2% were LSIL samples, and 27.3% were HSIL samples. HPV infection was present in 36.4% of the samples. In patients who underwent biopsy (36.4%), moderate or severe histological outcomes were equally common in both groups in 18.2% of the samples. The CST 5 category, dominated by L. jensenii , was the smallest group, with 5 samples. Therefore, this group was excluded from further analysis because the sample size was too small. Analysis of selected bacterial strains in the CST 3 category A total of 26 cervical swab samples were assigned to the CST 3 category on the basis of having the lowest deltaCt of L. iners . The median age of patients in the CST 3 category was 36 years, with lower and upper quartiles of 29 and 44 years, respectively. The mean age of patients was 36.08 years, with a standard deviation of 9.78 years. HPV infection was present in 73.1% of the CST 3 samples; this result was significantly different (p=0.019) from those of the CST 1, 2 and 5 categories, the bacterial flora of which are dominated by protective Lactobacillus spp. In terms of cytological classification, 7.6% of the samples were NILM, 23.1% were ASCUS samples, 30.7% were LSIL samples, and 38.4% were HSIL samples; these results indicate that the CST 3 category is associated with increased lesion severity. Biopsy was investigated in 80.8% of the CST 3 cervical samples, where 7.7% of the samples were negative for any morphological changes. CIN1 histological findings were present in 15.2% of the samples, CIN2 was present in 38.4% of the samples, and severe histological changes (CIN3/CIS) were present in 19.2% of the CST 3 samples. We also tested the presence of other bacteria in the CST 3 group. Other bacteria, such as G. vaginalis (69%), U. parvum (58%), L. jensenii (54%), L. crispatus (46%), L. gasseri (31%) and P. bivia (31%), were present in more than 30% of the CST3 samples. Among these bacteria, the presence of L. gasseri , G. vaginalis and P. bivia was marginally significant in the raw (p=0.076) and adjusted (p=0.091) p values in more than 30% of the tested samples. Analysis of selected bacterial strains in the CST4 category A total of 30 cervical samples were classified into the CST 4 category on the basis of having the lowest deltaCt of bacteria other than Lactobacillus spp. The median age of patients in the CST 4 category was 36 years, with lower and upper quartiles of 29 and 45 years, respectively. The mean age of patients was 38.48 years, with a standard deviation of 14.37 years. Overall, fifty percent of CST 4 samples were positive for HPV infection, which was not significantly different (p=0.6) from the positivity rates of the CST 1, 2 and 5 categories, which had protective cervical flora. NILM or ASCUS were present in 23.3% of the CST4 samples in both groups (HPV-infected and non-HPV-infected). LSIL or HISL cytological findings were detected in 26.7% of the CST4 samples in both groups. Biopsy was investigated in 63.4% of the CST 4 cervical samples, and 10.0% of the samples were negative for any morphological changes, 13.4% of the samples were classified as CIN1, CIN2 was identified in 26.7% of the samples, and severe histological changes (CIN3/CIS) were identified in 13.3% of the samples. The most common bacterium in the CST 4 samples was G. vaginalis , which was dominant in 56.7% (17/30) of samples and present in 83.3% (25/30) of samples. Other bacterial strains were also dominant in the remaining CST4 samples: L. amnionii (13.3%, 4 of 30 samples), S. agallactiae (10.0%, 3 of 30 samples), A. vaginae (6.7%, 2 of 30 samples), Candida spp. (6.7%, 2 of 30 samples), P. bivia (3.3%, one of 30 samples) and S. mitis (3.3%, one of 30 samples). The bacterial strains present in at least 30% of the CST4 samples included A . vaginae (67%), L. iners (57%), P. bivia (53%), P. micra (50%), P. disiens (43%), S. sanguinegens (43%), L. amnionii (40%), A. christensenii (37%), F. nucleatum (33%), Mobiluncus spp. (33%) and L. crispatus (30%). We also investigated how other bacteria co-occur with G. vaginalis . Its presence was linked to an approximately 11.5-fold greater chance of detecting A. vaginae (raw p value = 0.0058; adjusted p value = 0.1043). On the other hand, samples with G. vaginalis presented a 25-fold lower chance (OR=0.041) of containing S. agalactiae (raw p value = 0.0312; adjusted p value = 0.2812). These findings suggest possible positive and negative associations, which should be confirmed in a larger patient cohort. The bacterial composition of CST4 is listed in Table 2. Diversity of bacterial strains across the CST categories In accordance with our previous study [13], we selected bacterial strains that are frequently present in the cervical swabs of Slovak women in the Zilina region. The strain was evaluated as positive when the Cycte threshold (Ct) was lower than 37 according to the manufacturer's recommendations. A representation of the bacterial strains in the CST classes is shown in Table 2. To reach our goal, we performed a prevalence analysis of L. iners with other bacteria across all CST types to investigate the relationships among the bacterial species. Overall, we found a more than four-fold (OR = 4.33) greater coexistence with G. vaginalis (p=0.0016), which was also a significant difference after p value adjustment (p=0.03). We also found more than a three-fold (OR = 3.42) greater (p=0.014) coexistence of U. parvum and three-fold (OR = 0.333) lower (p=0.022) coexistence of L. gasseri with L. iners . The coexistence of both bacteria did not significantly differ after p value adjustment (p=0.123 and p=0.131, respectively). The bacterial diversity of all the CST classes in the cytological samples was also estimated using the Shannon diversity index. The diversity was significantly greater (p=0.0006) in the CST4 class (Table 3). With respect to cytological abnormalities, we observed an increasing trend in the severity of lesions, although the increase was not significant (Table 3). Boxplots with calculated p values between the CST classes and lesions are shown in Figure 1. The relative abundances of selected bacterial species across samples in the CST classes are visualised in Figures 2–6. Table 3. Shannon diversity index Category n Shannon diversity index (median, Q1, Q3) P value CST class CST1 19 0.19 (0.01, 0.56) 0.0006 CST2 11 0.34 (0.16, 0.68) CST3 26 0.47 (0.17, 0.75) CST4 30 0.98 (0.53, 1.30) CST5 5 0.11 (0.09, 0.71) excluded Cytology NILM 20 0.35 (0.16, 0.71) 0.2776 ASCUS 20 0.42 (0.01, 0.82) LSIL 25 0.45 (0.09, 0.84) HSIL 26 0.68 (0.30, 0.98) Abbreviations: n, number of samples; CST, community state type; Q, quartile; SD, standard deviation; HPV, human papillomavirus; %, percentage; NILM, negative for intraepithelial lesion or malignancy; ASCUS, atypical squamous cells of undetermined significance; LSIL, low-grade squamous intraepithelial lesion; HSIL, high-grade squamous intraepithelial lesion; CIN, cervical intraepithelial neoplasia Discussion Lactobacillus spp. present in the vaginal flora are regarded as bacteria with a protective effect on epithelial integrity. As mentioned in the introduction, vaginal/cervical samples can be divided into categories according to microbial composition, and these categories potentially have different risks of squamous intraepithelial lesion development. The aims of our study were to examine the microbial composition and compare CST and cytological classification. An additional aim was to explore the relationship between L. iners and other selected bacteria. Our study involved the use of cervical swabs/samples taken from Slovak women with abnormal results and from those with normal results of cervical cytology. After investigating the cervical microbiome composition, we categorised the samples into main classes: CST 1, CST 2, CST 3, CST 4 and CST 5. The most common class was CST 4 (30/91, 33.0%), followed by CST3 (26/91, 28.6%), CST1 (19/91, 20.9%), CST2 (11/91, 12.1%) and CST5 (5/91, 5.5%). The same order of abundance of CST categories was found in a study with a Chinese cohort, although the CST 2 and CST5 categories were less common, making up in 2.18% and 1.75% of the vaginal samples, respectively [15]. L. crispatus strains in the vaginal microbiome, referred to as CST 1, seem to have protective effects through bacteriocin, toxin‒antitoxin systems, and other functional elements in vaginal secretions, increasing the susceptibility of the vaginal barrier to genital infections [10]. The dominance of L. crispatus in the vaginal microbiome is associated with a lower prevalence of HPV, human immunodeficiency virus (HIV) and herpes simplex virus type 2 (HSV-2) infection [16]. We found a slightly lower number of HPV-positive samples in the CST 1 group. In terms of cytological classification, in the CST 1 category, negative cytology was found in 26.3% of samples, followed by ASCUS in 21.1% of samples, LSIL in 36.8% of samples, and HSIL in 15.8% of samples. Among the eleven biopsies from the CST 1 group, eight were negative for the presence of cervical precancerous conditions. Despite the small number of biopsies performed, these findings also suggest a protective role of L. crispatus in cervical carcinogenesis. Indeed, L. gasseri , referring to the CST 2 category, can play a role in maintaining vaginal health and might be helpful in HPV clearance [17]. Its possible protective rolein the vaginal microbiome was also noted in our study. We confirmed the dominance of NILM cytology in the CST 2 category, while negative cytology was present in 45.4% of cervicovaginal samples from patients with L. gasseri dominance. The remaining cytological categories were found in descending order of lesion severity: HSIL in 27.3% of samples, LSIL in 18.2% of samples, and ASCUS in 9.1% of samples. Most CST2 samples were HPV negative (63.6%). Analysis of the coexistence of L. iners with other bacteria across all CST types revealed a three-fold (OR = 0.333) lower significance (p=0.022) of coexistence of L. gasseri with L. iners , which may highlight the protective role of L. gasseri . However, the cohort of patients in the CST 2 category was not large enough to draw specific conclusions. The CST3 group is known to be dominated by L. iners . Owing to probable rapid evolution events, with large-scale gene loss, L. iners has the smallest genome on a single chromosome among Lactobacillus spp. It is speculated that the small size of the genome may be indicative of a symbiotic or parasitic lifestyle in comparison with other Lactobacilli and that this species cannot adequately adapt to changes in environmental conditions [10, 18]. Some researchers have revealed a tendency of the L. crispatus- dominated vaginal microbiome to change to L. iners dominance. Researchers also analysed the similarity between the L. crispatus and L. iners genomes. Some genes in the L. iners genome, such as Chlamydia , Streptococcus , Parvimonas , Gardnerella and Atopobium , are likely acquired horizontally from bacterial species. Researchers have also speculated that L. crispatus may be able to grow under sufficient nutrient conditions, that the vaginal microbiome switches from L. crispatus - dominated to L. iners - dominated when nutrients become insufficient and that cytolysin is essential for liberating L. iners from host tissues [18]. We detected the coexistence of L. iners with L. crispatus in 46.2% (12/26) of samples in the CST3 group and in 47.4% (9/19) of samples in the CST1 group.TheCST3 group typically presented greater bacterial diversity (Shannon index, 0.47) and more HPV-positive samples (73.1%), confirming that the cervical epithelium of L. iners was less protected. This finding corresponds with the known abundance of L. iners in HPV-infected women, and its presence may contribute to the maintenance of vaginal dysbiosis [19]. Owing to the absence of genes, L. iners is unable to produce the D-lactic acid isoform, which could be one of the possible explanations for its relationship with increased BV prevalence [10]. L. iners may increase the adhesion of G. vaginalis , thereby facilitating BV [20]. In our work, G. vaginalis was present in 69% of the CST3 samples. Other bacteria associated with BV, such as U. parvum and P. bivia ,were confirmed in more than 30% of the CST 3 samples. We found that L. iners more likely coexisted with G. vaginalis and U. parvum when bacteria were analysed across all CST types. These results suggest that L. iners is associated with BV, which can play a role in cervical carcinogenesis, while a positive association between BV and cervical precancerous lesions is known [21]. Corresponding with the findings of Norenhag J. et al. [22], our work revealed the presence of HPV infection in 73.1% of CST 3 samples, which was significantly different (p=0.019) from those of the CST 1, 2 and 5 categories, indicating the presence of protective vaginal microbiota in these 3 categories. We also demonstrated that the number of patients in cytological categories increased with increasing severity of cervical dysplasia among women with L. iners vaginal microbiome dominance. An investigation of biopsies from the CST3 category revealed an increasing trend in lesion severity, which may highlight the potential role of L. iners in cervical carcinogenesis. This finding is also in line with other studies that considered L. iners in the vaginal microbiome as a risk factor for cervical dysplasia [23, 24]. Similarly, Oh H.Y. et al. [25] demonstrated an increased risk of CIN in women whose vaginal microbiome was dominated by L. iners and in which other bacteria, such as A. vaginae and G. vaginalis , which are associated with BV, were present [25]. Cervical samples with no Lactobacillus dominance are categorised into the CST 4 class, also known as BV, which is the most common vaginal disorder among reproductive-aged women. It is associated with the presence of anaerobic bacteria, depletion of lactobacilli and increased bacterial species diversity [26]. A systematic review of a Latina population revealed 24 unique bacteria associated with abnormal cervical cytology. Sneathia spp., Chlamydia trachomatis , and G. vaginalis were consistently enriched in women with abnormal cervical cytology [27]. The CST 4 class in our study was characterised by the dominance of more bacterial strains in the samples. The most dominant bacterium was G. vaginalis , which was less abundant in 26% of the CST4 samples. Other dominant strains were L. amnionii (13%), S. agallactiae (10%), A. vaginae (7%), Candida spp. (7%), P. bivia (7%), and S. mitis (7%). We did not confirm any associations with HPV infection or worse biopsy outcomes. The CST4 group in our study was characterised by high relative bacterial abundance (Shannon index, 0.98; p=0.0006). We also observed a trend of increasing cytological severity of cervical lesions, although the increase was not significant. L. amnionii can be found in normal vaginal flora and in women with BV [28]. However, its high prevalence, along with the presence of A. vaginae and S. sanguinegens , is linked to spontaneous abortion in women [29]. S. agalactiae , or Group B Streptococcus (GBS), is a commensal bacterium typical in the vaginal flora. Some authors have shown its ability to promote G. vaginalis biofilm formation in coculture scenarios [30]. When GBS is present in the vaginal secretions of pregnant women, it may cause severe neonatal infections that can lead to early illness, such as pneumonia, sepsis or meningitis. Maternal GBS carriage is associated with ectocervical inflammation and contact bleeding [31]. Furthermore, Candida spp. is also frequently present in the mucosal flora of healthy women and can develop into vulvovaginal candidiasis (VVc) under suitable conditions. VVc can be reduced by recolonisation of the vaginal microflora by probiotic cultures, such as Lactobacillus spp. [32]. Like G. vaginalis , P. bivia also produces multiple bacterial sialidase enzymes that were also isolated from the genera Bacteroidales , Bacteroides , Bifidobacterium , Corynebacterium (Actinomycetia), and Streptococcus and are linked to negative health outcomes, such as BV and preterm birth [33]. One of the most typical bacteria of the BV environment is G. vaginalis [34]. According to the VALENCIA classifier, CST 4 can be divided into CST 4-A, with a high relative abundance of Candidatus Lachnocurva vaginae and a moderate relative abundance of G. vaginalis , and CST 4-B, characterised by a high relative abundance of G. vaginalis and a low relative abundance of Ca. L. vaginae ; CST 4-A and CST 4-B are both characterised by moderate relative abundances of A. vaginae [35]. Furthermore, VALENCIA splits CST 4-C, characterised by a low relative abundance of Lactobacillus spp ., G. vaginalis , A. vaginae , and Ca. L. vaginae , into 5 sub-CSTs, whereas CST IV-C1 is dominated by Streptococcus [35]. According to the VALENCIA classification, G. vaginalis dominated 57% of the CST4 samples, and these samples should be classified as CST4-B. The coexistence of A. vaginae was approximately 11.5-fold greater (raw p value = 0.0058; adjusted p value = 0.1043) in the presence of G. vaginalis than in the absence of G. vaginalis . There was a 25-fold (OR=0.041) lower chance of the presence of S. agallactiae (raw p value = 0.0312; adjusted p value = 0.2812) when G. vaginalis was present in the sample than when G. vaginalis was absent. This finding is inversely correlated with the results of the VALENCIA CST IV-C1 subgroup, which was characterised by low S. agallactiae abundance in the presence of G. Vaginalis . Our study suggests that L. crispatus and L. gasseri play protective roles in maintaining vaginal health. On the other hand, we noted the presence of HPV infection in 73.1% of the CST 3 samples, and the abundance of severe cytologically and histologically confirmed cervical lesions increased with the increasing abundance of vaginal microbiome samples dominated by L. iners . Therefore, we suggest that despite the classification of L. iners into the genus Lactobacillus , which is generally considered protective, its presence may have a negative impact on the development of cervical dysplasia. Our work also revealed statistically significant G. vaginalis and U. urealyticum coexistence with L. iners , whereas other bacterial species were also present in the CST 3 category. We found significantly greater bacterial diversity in the CST4 class. An increasing trend of bacterial diversity with increasing cytological severity of cervical lesions was also observed, although the increase was not significant. This study also determined the microbial composition of cervical swabs across CST categories and tested its associations with HPV. These findings may indicate that the vaginal microbiome is a modifiable factor of cervical carcinogenesis. Conclusion This study highlights the possible role of L. iners in the development of cervical dysplasia. We also found the association of L. iners with anaerobic bacteria and indicate the potential role of bacterial diversity in cervical carcinogenesis. We suggest that a correct vaginal microbiome composition can be a protective factor against the development of cervical dysplasia. Current knowledge also highlights the role of the vaginal microbiome in other aspects of health, such as the association of vaginal dysmicrobia with adverse perinatal outcomes and its impact on postnatal development. Abbreviations ASCUS – Atypical Squamous Cells of Undetermined Significance BV – Bacterial Vaginosis CIN – Cervical Intraepithelial Neoplasia CST – Community State Types Ct – Cycle Threshold DNA – Deoxyribonucleic Acid FC – Fold Change GAPDH – Glyceraldehyde-3-phosphate Dehydrogenase HBB1 – Haemoglobin Subunit Beta-1 HPV – Human Papillomavirus HSIL High-grade Squamous Intraepithelial Lesion hrHPV – High-risk Human Papillomavirus LSIL – Low-grade Squamous Intraepithelial Lesion NILM – Negative for Intraepithelial Lesion Malignancy PCR – Polymerase Chain Reaction RNA – Ribonucleic Acid rRNA – Ribosomal Ribonucleic Acid RQ – Relative Quantification SCFAs – Short-chain Fatty Acids Spp. – Species Declarations Consent for publication Not applicable. Availability of data and material The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing interests The authors declare no competing interests. Funding This research was funded by Project VEGA 1/0398/21: “Immune system and vaginal microbiome as important mediator in the process of cervical carcinogenesis,” and co-financed by the Ministry of Education, Science, Research, and Sport of the Slovak Republic, by Project APVV-23-0428 “The role of the vaginal microbiome and the immune systemin the HPV-induced cervical carcinogenesis.” Authors' contributions EK, VH, and TR had conceptualized the study. EK, EK, TP and TR played primary role in samples collection. VH, LM, AH, and ZK performed laboratory samples processing. MG, LK and VH did analysis, and interpretation of the data. TR, EK, and VH did the manuscript preparation, and KB, TR and EN edited the manuscript. All the authors take complete responsibility for the content of the manuscript, read, and approved final version of the manuscript. Ethics approval and consent to participate The ethical review committee of the Jessenius Faculty of Medicine in Martin, Comenius University had approved the study 14 December 2020 with registration number EK 85/2020. The principles of the Helsinki Declaration were followed. Informed consent was obtained from all individual participants included in the study. Corresponding author Correspondence to Veronika Holubekova. Acknowledgments We would like to express our special gratitude to all employees of Biomedical Center Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava for their willingness and professionalism during the realization of the study. References Turnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight R, et al. The Human Microbiome Project. Nature. 2007;449:804–10. Gilbert JA, Blaser MJ, Caporaso JG, Jansson JK, Lynch SV, et al. Current understanding of the human microbiome. Nat Med. 2018; 4:392–400. Stapleton AE. 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Ngom NS, Gassama O, Dieng A, Diakhaby EB, Ndiaye SML, Tine A, Karam F, Lo G, Ba-Diallo A, Boye CSB, Toure-Kane C, Seck A, Diop-Ndiaye H, Camara M. Vaginal Carriage of Group B Streptococcus (GBS) in Pregnant Women, Antibiotic Sensitivity and Associated Risk Factors in Dakar, Senegal. Microbiol Insights. 2023;16:11786361231174419. Sun Z, Ge X, Qiu B, Xiang Z, Jiang C, Wu J, Li Y. Vulvovaginal candidiasis and vaginal microflora interaction: Microflora changes and probiotic therapy. Front Cell Infect Microbiol. 2023 Feb 3;13:1123026. doi: 10.3389/fcimb.2023.1123026. PMID: 36816582; PMCID: PMC9936092. Pelayo P, Hussain FA, Werlang CA, Wu CM, Woolston BM, Xiang CM, Rutt L, France MT, Ravel J, Ribbeck K, Kwon DS, Balskus EP. Prevotella are major contributors of sialidases in the human vaginal microbiome. Proc Natl Acad Sci U S A. 2024;121:e2400341121. Abou Chacra L, Fenollar F, Diop K. Bacterial Vaginosis: What Do We Currently Know? Front Cell Infect Microbiol. 2022;11:672429. France MT, Ma B, Gajer P, Brown S, Humphrys MS, Holm JB, Waetjen LE, Brotman RM, Ravel J. VALENCIA: a nearest centroid classification method for vaginal microbial communities based on composition. Microbiome. 2020;8:166. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-7861075","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":552342728,"identity":"c600cbc7-e0cb-4539-a92e-abba2a89a9bd","order_by":0,"name":"Tomas Rokos","email":"","orcid":"","institution":"Comenius University in Bratislava (JFMCU)","correspondingAuthor":false,"prefix":"","firstName":"Tomas","middleName":"","lastName":"Rokos","suffix":""},{"id":552342729,"identity":"8b946b50-7e56-4b66-9c3e-f0b402c2f6bd","order_by":1,"name":"Veronika 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14:49:22","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37040,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/fc2463b6a7bc06828188ef20.png"},{"id":97268923,"identity":"3247d119-6cd3-4ad6-a4c9-db81e1f6fe3d","added_by":"auto","created_at":"2025-12-02 14:49:22","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":84041,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/cba60dd59a05b10d433da93d.png"},{"id":97368042,"identity":"59a8871a-a0a1-419f-8887-73dedb95e0b2","added_by":"auto","created_at":"2025-12-03 16:21:25","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":66052,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/87399af749a139e3030166eb.png"},{"id":97369193,"identity":"e888bacd-7683-48f8-b0ae-596575e43e1d","added_by":"auto","created_at":"2025-12-03 16:23:50","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":135523,"visible":true,"origin":"","legend":"","description":"","filename":"45f73d365d764a5a9ea08fd6950144191structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/15ea67c8f6e6ebf0a1a85f10.xml"},{"id":97268932,"identity":"08dd8419-c97f-4f14-a0e4-26d1941a2af6","added_by":"auto","created_at":"2025-12-02 14:49:22","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":148120,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/493b8dcb8bec30c9f0873c40.html"},{"id":97368014,"identity":"17ba1c72-4cba-4b1c-a76a-89e98734daa8","added_by":"auto","created_at":"2025-12-03 16:21:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47782,"visible":true,"origin":"","legend":"\u003cp\u003eThe Shannon diversity index was used to calculate the \u0026nbsp;\u0026nbsp;relative bacterial abundance across CST types and lesions (0 means NILM, 1 means ASCUS, 2 means LSIL, and 3 means HSIL)\u0026nbsp;\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/bdf4b8711a19de3fe47bc78f.jpg"},{"id":97368382,"identity":"3ebeb33e-399d-47cd-9f6e-ea8bb51527e8","added_by":"auto","created_at":"2025-12-03 16:22:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":69858,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap showing the relative abundance of selected bacterial strains and the presence of HPV infection in the CST 1 category. The more intense the red colour means the higher the abundance.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/31f609990e38f2b5e091dc82.jpg"},{"id":97268908,"identity":"ce305a67-a81d-4f18-a0e3-02daa682a8d1","added_by":"auto","created_at":"2025-12-02 14:49:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":64974,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap showing the relative abundance of selected bacterial strains and the presence of HPV infection in the CST 2 category. The more intense the red colour means the higher the abundance.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/4c4430ca2524517c0d306bfd.jpg"},{"id":97369136,"identity":"69c8e6f6-1271-4988-b31e-e296b39439b7","added_by":"auto","created_at":"2025-12-03 16:23:45","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":76605,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap showing the relative abundance of selected bacterial strains and the presence of HPV infection in the CST 3 category. The more intense the red colour means the higher the abundance.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/c55d9811601c8660c4cc57ea.jpg"},{"id":97367603,"identity":"fe56c2e8-071a-49aa-9c73-0c5fc7319b1a","added_by":"auto","created_at":"2025-12-03 16:19:45","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":83537,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap showing the relative abundance of selected bacterial strains and the presence of HPV infection in the CST 4 category. The more intense the red colour means the higher the abundance.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/aa3ff074dbd56b07a4acbfd5.jpg"},{"id":97268912,"identity":"ae168c18-cfc4-463f-9d2f-309f9fe88828","added_by":"auto","created_at":"2025-12-02 14:49:22","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":53188,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap showing the relative abundance of selected bacterial strains and the presence of HPV infection in the CST 5 category. The more intense the red colour means the higher the abundance.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/4a2e05d11db70adc596f6ad1.jpg"},{"id":100963576,"identity":"95380fe9-6727-479e-a052-6017c1cdff77","added_by":"auto","created_at":"2026-01-23 08:56:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1363167,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7861075/v1/f806ad9c-a4a9-4edb-afe2-1bf4f137fa23.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Lactobacillus Iners and Vaginal Microbiome Diversity as Risk Factors of Uterine Cervix Dysplasia: A Prospective Study","fulltext":[{"header":"Background","content":"\u003cp\u003eThe human body is colonised by a vast array of microorganisms that collectively form the human microbiome. It comprises approximately 500 to 1,000 bacterial species (spp.) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], with a total gene content that exceeds that of the human genome [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The vaginal microbiome, which is predominantly composed of \u003cem\u003eLactobacillus\u003c/em\u003e spp., plays a crucial role in preventing urinary tract infections [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], urogenital disorders, and sexually transmitted infections [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe vaginal microbiota of healthy, sexually active women can be classified into five distinct community state types (CSTs). Four of these (CSTs I, II, III, and V) are dominated by Lactobacillus species\u0026mdash;\u003cem\u003eLactobacillus crispatus\u003c/em\u003e (CST I), \u003cem\u003eL. gasseri\u003c/em\u003e (CST II), \u003cem\u003eL. iners\u003c/em\u003e (CST III), and \u003cem\u003eL. jensenii\u003c/em\u003e (CST V). In contrast, CST IV is characterised by a depletion of lactobacilli and a dominance of strict anaerobes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Lactobacillus species are considered protective against colonisation by vaginal pathogens because of their production of organic acids, hydrogen peroxide (H₂O₂), and antimicrobial peptides such as bacteriocins [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Conversely, the overgrowth of anaerobic bacteria\u0026mdash;a condition referred to as \u003cem\u003ebacterial vaginosis (BV)\u003c/em\u003e\u0026mdash;is associated with reduced lactate levels and increased concentrations of short-chain fatty acids (SCFAs) and their anions. Unlike those in the intestinal microbiota, elevated SCFA levels in the vaginal environment are indicative of dysbiosis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA shift from \u003cem\u003eLactobacillus\u003c/em\u003e-dominant vaginal microbiota to pathogen-dominant communities\u0026mdash;indicative of vaginal dysbiosis\u0026mdash;leads to disruptions in immune function and epithelial homeostasis. This transition is associated with increased production of proinflammatory cytokines and chemokines, activation of immune pathways, and reduced viscosity of cervicovaginal secretions due to mucin-degrading enzyme activity. These changes compromise mucosal barrier integrity, thereby increasing susceptibility to sexually transmitted infections, including high-risk human papillomavirus (hrHPV) infections [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eInterestingly, not all \u003cem\u003eLactobacillus\u003c/em\u003e species play a clearly protective role. \u003cem\u003eLactobacillus iners\u003c/em\u003e, first described in 1999 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], is among the most prevalent vaginal species [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, its presence is not consistently associated with a healthy microbiota. Srinivasan et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] reported that women with high levels of \u003cem\u003eL. crispatus\u003c/em\u003e rarely have BV, whereas those with high levels of \u003cem\u003eL. iners\u003c/em\u003e could be either BV-negative or BV-positive. These findings suggest that \u003cem\u003eL. iners\u003c/em\u003e may not provide sufficient protection against BV [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Nonetheless, \u003cem\u003eL. iners\u003c/em\u003e has been demonstrated to have an inhibitory effect on \u003cem\u003eGardnerella vaginalis\u003c/em\u003e growth, indicating that it may still play a nuanced role in microbial interactions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eVarious aspects of vaginal health have been associated with \u003cem\u003eLactobacillus iners\u003c/em\u003e dominance in the vaginal microbiome, as well as with the detrimental effects of vaginal dysbiosis. In our study, we focused on the relationship between variations in the vaginal microbiome composition and the potential development of cervical dysplasia\u0026mdash;a topic of continued relevance due to its risk of progression to cervical cancer.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e1. Sample collection\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eSamples were collected from patients with cervical cytological abnormalities who underwent expert colposcopic examination and from healthy controls at the Ambulance of Expert Colposcopy at the Department of Gynaecology and Obstetrics, Jessenius Faculty of Medicine, Comenius University in Bratislava and University Hospital Martin. The examined group included 20 patients with atypical squamous cells with undetermined significance (ASCUS), 25 patients with low-grade squamous intraepithelial lesions (LSILs), and 26 patients with high-grade squamous intraepithelial lesions (HSILs); 20 samples from women who were negative for intraepithelial lesions or malignancies (NILM) constituted the control group. During the examination, a cervical swab was taken from the exocervix and posterior vaginal fornix. The samples were transported to the Laboratory of Genomics and Prenatal Diagnostics, Biomedical Centre Martin, Jessenius Faculty of Medicine, Comenius University, in Bratislava and stored at -80\u0026deg;C in viral/bacterial transport medium (Jiangsu Mole Bioscience, Taizhou, China) until further processing. The study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava no. EK 85/2020.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e2. Nucleic acid extraction\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe collected samples were thawed and mixed before processing. The samples were subsequently centrifuged at 3000 revolutions per minute (rpm) for 10 minutes at 4\u0026deg;C. The supernatant was removed, and the cells were washed twice with phosphate-buffered saline (pH 7.0). Subsequently, 100 \u0026micro;l of the cell suspension was used for DNA extraction with the MasterPure Complete DNA and RNA Purification Kit (Biosearch Technologies, Hoddesdon, UK) according to the manufacturer's instructions. The extracted DNA was incubated with RNase A for 30 minutes at 37\u0026deg;C. The deoxyribonucleic acid (DNA) was diluted in 35 \u0026micro;l of TE (Tris\u0026thinsp;+\u0026thinsp;EDTA, pH 8) buffer. The quality and quantity of the DNA were measured with a Qubit dsDNA HS assay kit (Invitrogen, Thermo Fisher Scientific, Carlsbad, CA, USA) on a Qubit 4.0 instrument (Invitrogen).\u003c/p\u003e\u003cp\u003e3. Detection of selected microbial strains\u003c/p\u003e\u003cp\u003eWe tested 120 ng of DNA by real-time polymerase chain reaction (qPCR) to identify eighteen microbial strains according to the manufacturer's instructions (Custom Microbial DNA qPCR Array, Qiagen, Hilden, Germany). The PCR plate contained microbial DNA arrays of 18 bacterial species (\u003cem\u003eLactobacillus crispatus\u003c/em\u003e, \u003cem\u003eLactobacillus gasseri\u003c/em\u003e, \u003cem\u003eLactobacillus jensenii\u003c/em\u003e, \u003cem\u003eLactobacillus iners\u003c/em\u003e, \u003cem\u003eAerococcus christensenii\u003c/em\u003e, \u003cem\u003eAtopobium vaginae\u003c/em\u003e, \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e, \u003cem\u003eGardnerella vaginalis\u003c/em\u003e, \u003cem\u003eLeptotrichia amnionii\u003c/em\u003e, \u003cem\u003eMobiluncus\u003c/em\u003e spp., \u003cem\u003eMycoplasma hominis\u003c/em\u003e, \u003cem\u003eParvimonas micra\u003c/em\u003e, \u003cem\u003ePrevotella bivia\u003c/em\u003e, \u003cem\u003ePrevotella disiens\u003c/em\u003e, \u003cem\u003eSneathia sanguinegens\u003c/em\u003e, \u003cem\u003eStreptococcus agalactiae\u003c/em\u003e, \u003cem\u003eStreptococcus mitis\u003c/em\u003e, and \u003cem\u003eUreaplasma parvum\u003c/em\u003e), bacterial 16S rRNA (Pan B1 and Pan B3) and fungal ribosomal rRNA genes (Pan Asp/Can), and a positive PCR control (PPC). One plate allowed the examination of four patients. In total, 25 microliters (\u0026micro;l) of a solution consisting of 12.5 \u0026micro;l of microbial qPCR master mix, primer/probe depending on the position on the plate, and 11.5 \u0026micro;l of microbial DNA-free water (Qiagen) together with 5 ng of DNA was applied to the wells of a 96-well plate.\u003c/p\u003e\u003cp\u003eThe microbial strains were detected with a QuantStudio 5 (Applied Biosystems) with thermal cycling with initial denaturation at 95\u0026deg;C for 10 min, an additional 40 cycles of denaturation at 95\u0026deg;C for 15 s and annealing and elongation at 60\u0026deg;C for 2 min. All the samples were analysed with the instrument software according to the manufacturer's recommendations.\u003c/p\u003e\u003cp\u003eHPV infection was identified according to a well-established method published in our previous study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e4. Statistical analysis\u003c/p\u003e\u003cp\u003eFor data analysis, R (version 4.4.2) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] was used.\u003c/p\u003e\u003cp\u003eFor this purpose, values were summarised using counts and percentages for categorical variables; for continuous variables, medians with lower and upper quartiles were reported. The threshold for a positive Ct result was set to 37 cycles according to the manufacturer\u0026rsquo;s recommendations.\u003c/p\u003e\u003cp\u003eTo inspect the co-occurrence (prevalence) of \u003cem\u003eL. iners\u003c/em\u003e with other variables across all CST types, Fisher\u0026rsquo;s exact test was used. A subset of CST type 4 was subsequently used to examine the co-occurrence of \u003cem\u003eG. vaginalis\u003c/em\u003e with other bacterial taxa using Fisher\u0026rsquo;s exact test. A one-sample binomial test was applied to examine whether the prevalence of each bacterial taxon differed significantly from the threshold value of 0.5. Owing to multiple testing in this section, Benjamini‒Hochberg correction for p value adjustment was applied.\u003c/p\u003e\u003cp\u003eThe prevalence of HPV infection between CST type 3 and other types (1, 2, and 5) and between CST type 4 and other types (1, 2, and 5) was examined. For this purpose, owing to the sufficient number of observations (n\u0026thinsp;\u0026gt;\u0026thinsp;5 in each group), Pearson\u0026rsquo;s chi-square test was used.\u003c/p\u003e\u003cp\u003eThe Shannon diversity index was computed from relative abundances (abundances were calculated as 2^(-ΔCt), where the average Ct of 16S RNA genes was subtracted from the Ct of the selected bacterium in a given sample). The results were visualised via boxplots at the lesion and CST type levels. First, the Kruskal‒Wallis test was applied to assess differences among all levels; subsequently, pairwise comparisons between levels were performed using the Wilcoxon rank-sum test. For the CST type, level 5 was excluded from pairwise comparisons because of the low number of observations. Finally, heatmaps of relative abundances were generated for each sample at each level of the CST type.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eAnalysis of clinicopathological data\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 91 samples, the average age was 36.2\u0026nbsp;\u0026plusmn; 9.61\u0026nbsp;years. The presence\u0026nbsp;of\u0026nbsp;HPV infection\u0026nbsp;was detected in 55% (50/91) of the cervical cytological samples and increased with increasing severity of squamous intraepithelial lesions (p\u0026lt;0.05) (Table 1).\u003c/p\u003e\n\u003cp\u003eIn this study, we examined the selected microbial strains frequently present in the cervical cytological smears of women in the Zilina region in Slovakia. On the basis of the results of the PCR analysis, the cervical swab samples were classified into community state types (CSTs) according to the lowest delta Ct number, which was calculated as the Ct of average 16S rRNA genes subtracted from the Ct of the selected bacterium.\u003c/p\u003e\n\u003cp\u003eIn our cohort, 19 samples were classified into the CST 1 category with a dominance of \u003cem\u003eL. crispatus\u003c/em\u003e, 11 samples were classified into the CST 2 category with a dominance of \u003cem\u003eL. gasseri\u003c/em\u003e, 26 samples were classified into the CST 3 category with a dominance of \u003cem\u003eL. iners\u003c/em\u003e,\u003cem\u003e\u0026nbsp;\u003c/em\u003e5 samples were classified into the CST 5 category with a dominance of \u003cem\u003eL. jensenii\u003c/em\u003e, and 30 samples were classified into the CST 4 category with dominance of bacteria other than \u003cem\u003eLactobacillus\u003c/em\u003e spp. There were no significant differences in age among the patients in the categories of CST 1\u0026ndash;5 (p\u0026gt;0.9). The division of samples into CST classes with other monitored parameters is shown in Table 1. The proportions of bacterial strains across CST classes are listed in Table 2.\u003c/p\u003e\n\u003cp\u003eTable 1. Classification of samples in the CST classes with other monitored parameters.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e91\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003em\u003cstrong\u003eedian (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e35 (29, 43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e33 (31, 40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e37 (29, 44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e36 (29, 45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e33 (30, 34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003em\u003cstrong\u003eean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e37.11\u0026nbsp;\u0026plusmn;\u0026nbsp;10.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e36.45\u0026nbsp;\u0026plusmn;\u0026nbsp;8.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e36.08\u0026nbsp;\u0026plusmn;\u0026nbsp;9.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e38.48\u0026nbsp;\u0026plusmn;\u0026nbsp;14.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e33.40\u0026nbsp;\u0026plusmn;\u0026nbsp;9.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; absent, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e10 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e15 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; present, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e9 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e19 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e15 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLesion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; NILM, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e5 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e5 (45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; ASCUS, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e4 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e6 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; LSIL, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e7 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e8 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; HSIL, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e3 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e3 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e10 (38.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e8 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiopsy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; negative, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e8 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e3 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; CIN1, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; CIN2, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e2 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e2 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e10 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e8 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; CIN3/CIS, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e2 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e5 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; not investigated, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e8 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e5 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e11 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: n, number of samples; CST, community state type; Q, quartile; SD, standard deviation; HPV, human papillomavirus; %, percentage; NILM, negative for intraepithelial lesion or malignancy; ASCUS, atypical squamous cells of undetermined significance; LSIL, low-grade squamous intraepithelial lesion; HSIL, high-grade squamous intraepithelial lesion; CIN, cervical intraepithelial neoplasia\u003c/p\u003e\n\u003cp\u003eTable 2. Representation of bacterial strains among community state type (CST) classes with the number of samples and percentage representations.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"580\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCST 5\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eLactobacillus crispatus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eLactobacillus gasseri\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eLactobacillus jensenii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eLactobacillus iners\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eAerococcus christensenii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eAtopobium vaginae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20 (67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eFusobacterium nucleatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eGardnerella vaginalis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18 (69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25 (83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eLeptotrichia amnionii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eMobiluncus\u003c/em\u003e spp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eMycoplasma hominis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eParvimonas micra\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ePrevotella bivia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ePrevotella disiens\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eSneathia sanguinegens\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eStreptococcus agalactiae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eStreptococcus mitis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eUreaplasma parvum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15 (58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePan Aspergillus/Candida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: n, number of samples; CST, community state type, %, percentage\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnalysis of selected bacterial strains in protective cervical flora (CST 1, CST 2 and CST 5)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOverall, 19 samples that were dominated by \u003cem\u003eL. crispatus\u003c/em\u003e were categorised as CST 1. In terms of cytological classification, for the CST 1, the results were as follows: normal cytological samples (NILM), 26.3%; ASCUS samples, 21.1%; LSIL samples, 36.8%; and HSIL samples, 15.8%. HPV infection was present in 47.4% of the samples. In patients who underwent biopsy (57.9%), most biopsies were negative (42.1%) for any morphological changes, or CIN1 or CIN2 histological findings (15.8%) were present.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eL. gasseri\u003c/em\u003e was dominant in 11 cytological samples, which were categorised as CST 2. In terms of cytological classification, 45.4% of the samples were NILM, 9.1% were ASCUS samples, 18.2% were LSIL samples, and 27.3% were HSIL samples. HPV infection was present in 36.4% of the samples. In patients who underwent biopsy (36.4%), moderate or severe histological outcomes were equally common in both groups in 18.2% of the samples.\u003c/p\u003e\n\u003cp\u003eThe CST 5 category, dominated by \u003cem\u003eL. jensenii\u003c/em\u003e, was the smallest group, with 5 samples. Therefore, this group was excluded from further analysis because the sample size was too small.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnalysis of selected bacterial strains in the CST 3 category\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 26 cervical swab samples were assigned to the CST 3 category on the basis of having the lowest deltaCt of \u003cem\u003eL. iners\u003c/em\u003e. The median age of patients in the CST 3 category was 36 years, with lower and upper quartiles of 29 and 44 years, respectively. The mean age of patients was 36.08 years, with a standard deviation of 9.78 years.\u003c/p\u003e\n\u003cp\u003eHPV infection was present in 73.1% of the CST 3 samples; this result was significantly different (p=0.019) from those of the CST 1, 2 and 5 categories, the bacterial flora of which are dominated by protective \u003cem\u003eLactobacillus\u003c/em\u003e spp. In terms of cytological classification, 7.6% of the samples were NILM, 23.1% were ASCUS samples, 30.7% were LSIL samples, and 38.4% were HSIL samples; these results indicate that the CST 3 category is associated with increased lesion severity.\u003c/p\u003e\n\u003cp\u003eBiopsy was investigated in 80.8% of the CST 3 cervical samples, where 7.7% of the samples were negative for any morphological changes. CIN1 histological findings were present in 15.2% of the samples, CIN2 was present in 38.4% of the samples, and severe histological changes (CIN3/CIS) were present in 19.2% of the CST 3 samples.\u003c/p\u003e\n\u003cp\u003eWe also tested the presence of other bacteria in the CST 3 group. Other bacteria, such as \u003cem\u003eG. vaginalis\u003c/em\u003e (69%), \u003cem\u003eU. parvum\u003c/em\u003e (58%), \u003cem\u003eL. jensenii\u003c/em\u003e (54%), \u003cem\u003eL. crispatus\u003c/em\u003e (46%), \u003cem\u003eL. gasseri\u003c/em\u003e (31%) and \u003cem\u003eP. bivia\u003c/em\u003e (31%), were present in more than 30% of the CST3 samples. Among these bacteria, the presence of \u003cem\u003eL. gasseri\u003c/em\u003e, \u003cem\u003eG. vaginalis\u003c/em\u003e and \u003cem\u003eP. bivia\u003c/em\u003e was marginally significant in the raw (p=0.076) and adjusted (p=0.091) p values in more than 30% of the tested samples.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnalysis of selected bacterial strains in the CST4 category\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 30 cervical samples were classified into the CST 4 category on the basis of having the lowest deltaCt of bacteria other than \u003cem\u003eLactobacillus\u0026nbsp;\u003c/em\u003espp. The median age of patients in the CST 4 category was 36 years, with lower and upper quartiles of 29 and 45 years, respectively. The mean age of patients was 38.48 years, with a standard deviation of 14.37 years.\u003c/p\u003e\n\u003cp\u003eOverall, fifty percent of CST 4 samples were positive for HPV infection, which was not significantly different (p=0.6) from the positivity rates of the CST 1, 2 and 5 categories, which had protective cervical flora. NILM or ASCUS were present in 23.3% of the CST4 samples in both groups (HPV-infected and non-HPV-infected). LSIL or HISL cytological findings were detected in 26.7% of the CST4 samples in both groups.\u003c/p\u003e\n\u003cp\u003eBiopsy was investigated in 63.4% of the CST 4 cervical samples, and 10.0% of the samples were negative for any morphological changes, 13.4% of the samples were classified as CIN1, CIN2 was identified in 26.7% of the samples, and severe histological changes (CIN3/CIS) were identified in 13.3% of the samples.\u003c/p\u003e\n\u003cp\u003eThe most common bacterium in the CST 4 samples was \u003cem\u003eG. vaginalis\u003c/em\u003e, which was dominant in 56.7% (17/30) of samples and present in 83.3% (25/30) of samples. Other bacterial strains were also dominant in the remaining CST4 samples: \u003cem\u003eL.\u003c/em\u003e amnionii (13.3%, 4 of 30 samples), \u003cem\u003eS. agallactiae\u003c/em\u003e (10.0%, 3 of 30 samples), \u003cem\u003eA. vaginae\u003c/em\u003e (6.7%, 2 of 30 samples), \u003cem\u003eCandida\u003c/em\u003e spp. (6.7%, 2 of 30 samples), \u003cem\u003eP. bivia\u003c/em\u003e (3.3%, one of 30 samples) and \u003cem\u003eS. mitis\u003c/em\u003e (3.3%, one of 30 samples). The bacterial strains present in at least 30% of the CST4 samples included A\u003cem\u003e. vaginae\u003c/em\u003e (67%), \u003cem\u003eL. iners\u003c/em\u003e (57%), \u003cem\u003eP. bivia\u003c/em\u003e (53%), \u003cem\u003eP. micra\u003c/em\u003e (50%), \u003cem\u003eP. disiens\u003c/em\u003e (43%), \u003cem\u003eS. sanguinegens\u003c/em\u003e (43%), \u003cem\u003eL. amnionii\u003c/em\u003e (40%), \u003cem\u003eA. christensenii\u003c/em\u003e (37%), \u003cem\u003eF. nucleatum\u003c/em\u003e (33%), \u003cem\u003eMobiluncus\u003c/em\u003e spp. (33%) and \u003cem\u003eL. crispatus\u003c/em\u003e (30%).\u003c/p\u003e\n\u003cp\u003eWe also investigated how other bacteria co-occur with \u003cem\u003eG. vaginalis\u003c/em\u003e. Its presence was linked to an approximately 11.5-fold greater chance of detecting \u003cem\u003eA. vaginae\u003c/em\u003e (raw p value = 0.0058; adjusted p value = 0.1043). On the other hand, samples with\u003cem\u003e\u0026nbsp;G. vaginalis\u003c/em\u003e presented a 25-fold lower chance (OR=0.041) of containing \u003cem\u003eS. agalactiae\u003c/em\u003e (raw p value = 0.0312; adjusted p value = 0.2812). These findings suggest possible positive and negative associations, which should be confirmed in a larger patient cohort. The bacterial composition of CST4 is listed in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDiversity of bacterial strains across the CST categories\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn accordance with our previous study [13], we selected bacterial strains that are frequently present in the cervical swabs of Slovak women in the Zilina region. The strain was evaluated as positive when the Cycte threshold (Ct) was lower than 37 according to the manufacturer\u0026apos;s recommendations. A representation of the bacterial strains in the CST classes is shown in Table 2.\u003c/p\u003e\n\u003cp\u003eTo reach our goal, we performed a prevalence analysis of \u003cem\u003eL. iners\u003c/em\u003e with other bacteria across all CST types to investigate the relationships among the bacterial species.\u003c/p\u003e\n\u003cp\u003eOverall, we found a more than four-fold (OR = 4.33) greater coexistence with \u003cem\u003eG. vaginalis\u003c/em\u003e (p=0.0016), which was also a significant difference after p value adjustment (p=0.03). We also found more than a three-fold (OR = 3.42) greater (p=0.014) coexistence of \u003cem\u003eU. parvum\u003c/em\u003e and three-fold (OR = 0.333) lower (p=0.022) coexistence of \u003cem\u003eL. gasseri\u003c/em\u003e with \u003cem\u003eL. iners\u003c/em\u003e. The coexistence of both bacteria did not significantly differ after p value adjustment (p=0.123 and p=0.131, respectively).\u003c/p\u003e\n\u003cp\u003eThe bacterial diversity of all the CST classes in the cytological samples was also estimated using the Shannon diversity index. The diversity was significantly greater (p=0.0006) in the CST4 class (Table 3). With respect to cytological abnormalities, we observed an increasing trend in the severity of lesions, although the increase was not significant (Table 3). Boxplots with calculated p values between the CST classes and lesions are shown in Figure 1. The relative abundances of selected bacterial species across samples in the CST classes are visualised in Figures 2\u0026ndash;6.\u003c/p\u003e\n\u003cp\u003eTable 3. Shannon diversity index\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eShannon diversity index\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(median, Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003eCST class\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eCST1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e0.19 (0.01, 0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eCST2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e0.34 (0.16, 0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eCST3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e0.47 (0.17, 0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eCST4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e0.98 (0.53, 1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eCST5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e0.11 (0.09, 0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eexcluded\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003eCytology\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eNILM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e0.35 (0.16, 0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e0.2776\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eASCUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e0.42 (0.01, 0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eLSIL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e0.45 (0.09, 0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eHSIL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e0.68 (0.30, 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: n, number of samples; CST, community state type; Q, quartile; SD, standard deviation; HPV, human papillomavirus; %, percentage; NILM, negative for intraepithelial lesion or malignancy; ASCUS, atypical squamous cells of undetermined significance; LSIL, low-grade squamous intraepithelial lesion; HSIL, high-grade squamous intraepithelial lesion; CIN, cervical intraepithelial neoplasia\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cem\u003eLactobacillus\u003c/em\u003e spp. present in the vaginal flora are regarded as bacteria with a protective effect on epithelial integrity. As mentioned in the introduction, vaginal/cervical samples can be divided into categories according to microbial composition, and these categories potentially have different risks of squamous intraepithelial lesion development. The aims of our study were to examine the microbial composition and compare CST and cytological classification. An additional aim was to explore the relationship between \u003cem\u003eL. iners\u003c/em\u003e and other selected bacteria.\u003c/p\u003e\n\u003cp\u003eOur study involved the use of cervical swabs/samples taken from Slovak women with abnormal results and from those with normal results of cervical cytology. After investigating the cervical microbiome composition, we categorised the samples into main classes: CST 1, CST 2, CST 3, CST 4 and CST 5. The most common class was CST 4 (30/91, 33.0%), followed by CST3 (26/91, 28.6%), CST1 (19/91, 20.9%), CST2 (11/91, 12.1%) and CST5 (5/91, 5.5%). The same order of abundance of CST categories was found in a study with a Chinese cohort, although the CST 2 and CST5 categories were less common, making up in 2.18% and 1.75% of the vaginal samples, respectively [15].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eL. crispatus\u003c/em\u003e strains in the vaginal microbiome, referred to as CST 1, seem to have protective effects through bacteriocin, toxin‒antitoxin systems, and other functional elements in vaginal secretions, increasing the susceptibility of the vaginal barrier to genital infections [10]. The dominance of \u003cem\u003eL. crispatus \u003c/em\u003ein the vaginal microbiome is associated with a lower prevalence of HPV, human immunodeficiency virus (HIV) and herpes simplex virus type 2 (HSV-2) infection [16]. We found a slightly lower number of HPV-positive samples in the CST 1 group. In terms of cytological classification, in the CST 1 category, negative cytology was found in 26.3% of samples, followed by ASCUS in 21.1% of samples, LSIL in 36.8% of samples, and HSIL in 15.8% of samples. Among the eleven biopsies from the CST 1 group, eight were negative for the presence of cervical precancerous conditions. Despite the small number of biopsies performed, these findings also suggest a protective role of \u003cem\u003eL. crispatus\u003c/em\u003e in cervical carcinogenesis.\u003c/p\u003e\n\u003cp\u003eIndeed, \u003cem\u003eL. gasseri\u003c/em\u003e, referring to the CST 2 category, can play a role in maintaining vaginal health and might be helpful in HPV clearance [17]. Its possible protective rolein the vaginal microbiome was also noted in our study. We confirmed the dominance of NILM cytology in the CST 2 category, while negative cytology was present in 45.4% of cervicovaginal samples from patients with \u003cem\u003eL. gasseri \u003c/em\u003edominance. The remaining cytological categories were found in descending order of lesion severity: HSIL in 27.3% of samples, LSIL in 18.2% of samples, and ASCUS in 9.1% of samples. Most CST2 samples were HPV negative (63.6%). Analysis of the coexistence of \u003cem\u003eL. iners\u003c/em\u003e with other bacteria across all CST types revealed a three-fold (OR = 0.333) lower significance (p=0.022) of coexistence of \u003cem\u003eL. gasseri\u003c/em\u003e with \u003cem\u003eL. iners\u003c/em\u003e, which may highlight the protective role of \u003cem\u003eL. gasseri\u003c/em\u003e. However, the cohort of patients in the CST 2 category was not large enough to draw specific conclusions.\u003c/p\u003e\n\u003cp\u003eThe CST3 group is known to be dominated by \u003cem\u003eL. iners\u003c/em\u003e. Owing to probable rapid evolution events, with large-scale gene loss, \u003cem\u003eL. iners\u003c/em\u003e has the smallest genome on a single chromosome among \u003cem\u003eLactobacillus\u003c/em\u003e spp. It is speculated that the small size of the genome may be indicative of a symbiotic or parasitic lifestyle in comparison with other Lactobacilli and that this species cannot adequately adapt to changes in environmental conditions [10, 18]. Some researchers have revealed a tendency of the \u003cem\u003eL. crispatus-\u003c/em\u003edominated vaginal microbiome to change to \u003cem\u003eL. iners\u003c/em\u003e dominance. Researchers also analysed the similarity between the \u003cem\u003eL. crispatus \u003c/em\u003eand \u003cem\u003eL. iners\u003c/em\u003e genomes. Some genes in the \u003cem\u003eL. iners\u003c/em\u003e genome, such as \u003cem\u003eChlamydia\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eParvimonas\u003c/em\u003e, \u003cem\u003eGardnerella\u003c/em\u003e and \u003cem\u003eAtopobium\u003c/em\u003e, are likely acquired horizontally from bacterial species. Researchers have also speculated that \u003cem\u003eL. crispatus\u003c/em\u003e may be able to grow under sufficient nutrient conditions, that the vaginal microbiome switches from \u003cem\u003eL. crispatus\u003c/em\u003e\u003cem\u003e-\u003c/em\u003edominated to \u003cem\u003eL. iners\u003c/em\u003e\u003cem\u003e-\u003c/em\u003edominated when nutrients become insufficient and that cytolysin is essential for liberating \u003cem\u003eL. iners\u003c/em\u003e from host tissues [18]. We detected the coexistence of \u003cem\u003eL. iners\u003c/em\u003e with \u003cem\u003eL. crispatus\u003c/em\u003e in 46.2% (12/26) of samples in the CST3 group and in 47.4% (9/19) of samples in the CST1 group.TheCST3 group typically presented greater bacterial diversity (Shannon index, 0.47) and more HPV-positive samples (73.1%), confirming that the cervical epithelium of \u003cem\u003eL. iners\u003c/em\u003e was less protected. This finding corresponds with the known abundance of \u003cem\u003eL. iners\u003c/em\u003e in HPV-infected women, and its presence may contribute to the maintenance of vaginal dysbiosis [19].\u003c/p\u003e\n\u003cp\u003eOwing to the absence of genes, \u003cem\u003eL. iners\u003c/em\u003e is unable to produce the D-lactic acid isoform, which could be one of the possible explanations for its relationship with increased BV prevalence [10]. \u003cem\u003eL. iners\u003c/em\u003e may increase the adhesion of \u003cem\u003eG. vaginalis\u003c/em\u003e, thereby facilitating BV [20]. In our work,\u003cem\u003e G. vaginalis\u003c/em\u003e was present in 69% of the CST3 samples. Other bacteria associated with BV, such as \u003cem\u003eU. parvum\u003c/em\u003e and \u003cem\u003eP. bivia\u003c/em\u003e,were confirmed in more than 30% of the CST 3 samples. We found that \u003cem\u003eL. iners\u003c/em\u003e more likely coexisted with \u003cem\u003eG. vaginalis\u003c/em\u003e and \u003cem\u003eU. parvum\u003c/em\u003e when bacteria were analysed across all CST types. These results suggest that \u003cem\u003eL. iners\u003c/em\u003e is associated with BV, which can play a role in cervical carcinogenesis, while a positive association between BV and cervical precancerous lesions is known [21].\u003c/p\u003e\n\u003cp\u003eCorresponding with the findings of Norenhag J. et al. [22], our work revealed the presence of HPV infection in 73.1% of CST 3 samples, which was significantly different (p=0.019) from those of the CST 1, 2 and 5 categories, indicating the presence of protective vaginal microbiota in these 3 categories. We also demonstrated that the number of patients in cytological categories increased with increasing severity of cervical dysplasia among women with \u003cem\u003eL. iners\u003c/em\u003e vaginal microbiome dominance. An investigation of biopsies from the CST3 category revealed an increasing trend in lesion severity, which may highlight the potential role of \u003cem\u003eL. iners\u003c/em\u003e in cervical carcinogenesis. This finding is also in line with other studies that considered \u003cem\u003eL. iners\u003c/em\u003e in the vaginal microbiome as a risk factor for cervical dysplasia [23, 24]. Similarly, Oh H.Y. et al. [25] demonstrated an increased risk of CIN in women whose vaginal microbiome was dominated by \u003cem\u003eL. iners\u003c/em\u003e and in which other bacteria, such as \u003cem\u003eA. vaginae\u003c/em\u003e and \u003cem\u003eG. vaginalis\u003c/em\u003e, which are associated with BV, were present [25].\u003c/p\u003e\n\u003cp\u003eCervical samples with no Lactobacillus dominance are categorised into the CST 4 class, also known as BV, which is the most common vaginal disorder among reproductive-aged women. It is associated with the presence of anaerobic bacteria, depletion of lactobacilli and increased bacterial species diversity [26]. A systematic review of a Latina population revealed 24 unique bacteria associated with abnormal cervical cytology. \u003cem\u003eSneathia\u003c/em\u003e spp., \u003cem\u003eChlamydia trachomatis\u003c/em\u003e, and \u003cem\u003eG. vaginalis\u003c/em\u003e were consistently enriched in women with abnormal cervical cytology [27]. The CST 4 class in our study was characterised by the dominance of more bacterial strains in the samples. The most dominant bacterium was \u003cem\u003eG. vaginalis\u003c/em\u003e, which was less abundant in 26% of the CST4 samples. Other dominant strains were \u003cem\u003eL. amnionii\u003c/em\u003e (13%), \u003cem\u003eS. agallactiae\u003c/em\u003e (10%), \u003cem\u003eA. vaginae\u003c/em\u003e (7%), \u003cem\u003eCandida\u003c/em\u003e spp. (7%), \u003cem\u003eP. bivia\u003c/em\u003e (7%), and \u003cem\u003eS. mitis\u003c/em\u003e (7%). We did not confirm any associations with HPV infection or worse biopsy outcomes. The CST4 group in our study was characterised by high relative bacterial abundance (Shannon index, 0.98; p=0.0006). We also observed a trend of increasing cytological severity of cervical lesions, although the increase was not significant.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eL. amnionii\u003c/em\u003e can be found in normal vaginal flora and in women with BV [28]. However, its high prevalence, along with the presence of \u003cem\u003eA. vaginae\u003c/em\u003e and \u003cem\u003eS. sanguinegens\u003c/em\u003e, is linked to spontaneous abortion in women [29].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. agalactiae\u003c/em\u003e, or Group B Streptococcus (GBS), is a commensal bacterium typical in the vaginal flora. Some authors have shown its ability to promote \u003cem\u003eG. vaginalis\u003c/em\u003e biofilm formation in coculture scenarios [30]. When GBS is present in the vaginal secretions of pregnant women, it may cause severe neonatal infections that can lead to early illness, such as pneumonia, sepsis or meningitis. Maternal GBS carriage is associated with ectocervical inflammation and contact bleeding [31]. Furthermore, \u003cem\u003eCandida\u003c/em\u003e spp. is also frequently present in the mucosal flora of healthy women and can develop into vulvovaginal candidiasis (VVc) under suitable conditions. VVc can be reduced by recolonisation of the vaginal microflora by probiotic cultures, such as Lactobacillus spp. [32]. Like \u003cem\u003eG. vaginalis\u003c/em\u003e, \u003cem\u003eP. bivia\u003c/em\u003e also produces multiple bacterial sialidase enzymes that were also isolated from the genera \u003cem\u003eBacteroidales\u003c/em\u003e, \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eCorynebacterium\u003c/em\u003e (Actinomycetia), and \u003cem\u003eStreptococcus\u003c/em\u003e and are linked to negative health outcomes, such as BV and preterm birth [33].\u003c/p\u003e\n\u003cp\u003eOne of the most typical bacteria of the BV environment is \u003cem\u003eG. vaginalis \u003c/em\u003e[34]. According to the VALENCIA classifier, CST 4 can be divided into CST 4-A, with a high relative abundance of \u003cem\u003eCandidatus Lachnocurva vaginae\u003c/em\u003e and a moderate relative abundance of \u003cem\u003eG. vaginalis\u003c/em\u003e, and CST 4-B, characterised by a high relative abundance of \u003cem\u003eG. vaginalis\u003c/em\u003e and a low relative abundance of \u003cem\u003eCa. L. vaginae\u003c/em\u003e; CST 4-A and CST 4-B are both characterised by moderate relative abundances of \u003cem\u003eA. vaginae\u003c/em\u003e [35]. Furthermore, VALENCIA splits CST 4-C, characterised by a low relative abundance of \u003cem\u003eLactobacillus spp\u003c/em\u003e., \u003cem\u003eG. vaginalis\u003c/em\u003e, \u003cem\u003eA. vaginae\u003c/em\u003e, and \u003cem\u003eCa. L. vaginae\u003c/em\u003e, into 5 sub-CSTs, whereas CST IV-C1 is dominated by \u003cem\u003eStreptococcus \u003c/em\u003e[35].\u003c/p\u003e\n\u003cp\u003eAccording to the VALENCIA classification, \u003cem\u003eG. vaginalis\u003c/em\u003e dominated 57% of the CST4 samples, and these samples should be classified as CST4-B. The coexistence of \u003cem\u003eA. vaginae \u003c/em\u003ewas approximately 11.5-fold greater (raw p value = 0.0058; adjusted p value = 0.1043) in the presence of \u003cem\u003eG. vaginalis \u003c/em\u003ethan in the absence of \u003cem\u003eG. vaginalis\u003c/em\u003e. There was a 25-fold (OR=0.041) lower chance of the presence of \u003cem\u003eS. agallactiae\u003c/em\u003e (raw p value = 0.0312; adjusted p value = 0.2812) when \u003cem\u003eG. vaginalis\u003c/em\u003e was present in the sample than when \u003cem\u003eG. vaginalis\u003c/em\u003e was absent. This finding is inversely correlated with the results of the VALENCIA CST IV-C1 subgroup, which was characterised by low \u003cem\u003eS. agallactiae \u003c/em\u003eabundance in the presence of \u003cem\u003eG. Vaginalis\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eOur study suggests that \u003cem\u003eL. crispatus\u003c/em\u003e and \u003cem\u003eL. gasseri\u003c/em\u003e play protective roles in maintaining vaginal health. On the other hand, we noted the presence of HPV infection in 73.1% of the CST 3 samples, and the abundance of severe cytologically and histologically confirmed cervical lesions increased with the increasing abundance of vaginal microbiome samples dominated by \u003cem\u003eL. iners\u003c/em\u003e. Therefore, we suggest that despite the classification of \u003cem\u003eL. iners\u003c/em\u003e into the genus \u003cem\u003eLactobacillus\u003c/em\u003e, which is generally considered protective, its presence may have a negative impact on the development of cervical dysplasia. Our work also revealed statistically significant \u003cem\u003eG. vaginalis\u003c/em\u003e and \u003cem\u003eU. urealyticum\u003c/em\u003e coexistence with \u003cem\u003eL. iners\u003c/em\u003e, whereas other bacterial species were also present in the CST 3 category. We found significantly greater bacterial diversity in the CST4 class. An increasing trend of bacterial diversity with increasing cytological severity of cervical lesions was also observed, although the increase was not significant. This study also determined the microbial composition of cervical swabs across CST categories and tested its associations with HPV. These findings may indicate that the vaginal microbiome is a modifiable factor of cervical carcinogenesis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the possible role of \u003cem\u003eL. iners\u003c/em\u003e in the development of cervical dysplasia. We also found the association of \u003cem\u003eL. iners\u003c/em\u003e with anaerobic bacteria and indicate the potential role of bacterial diversity in cervical carcinogenesis. We suggest that a correct vaginal microbiome composition can be a protective factor against the development of cervical dysplasia. Current knowledge also highlights the role of the vaginal microbiome in other aspects of health, such as the association of vaginal dysmicrobia with adverse perinatal outcomes and its impact on postnatal development.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eASCUS \u0026ndash; Atypical Squamous Cells of Undetermined Significance\u003c/p\u003e\n\u003cp\u003eBV \u0026ndash; Bacterial Vaginosis\u003c/p\u003e\n\u003cp\u003eCIN \u0026ndash; Cervical Intraepithelial Neoplasia\u003c/p\u003e\n\u003cp\u003eCST \u0026ndash; Community State Types\u003c/p\u003e\n\u003cp\u003eCt \u0026ndash; Cycle Threshold\u003c/p\u003e\n\u003cp\u003eDNA \u0026ndash; Deoxyribonucleic Acid\u003c/p\u003e\n\u003cp\u003eFC \u0026ndash; Fold Change\u003c/p\u003e\n\u003cp\u003eGAPDH\u0026nbsp;\u0026ndash; Glyceraldehyde-3-phosphate Dehydrogenase\u003c/p\u003e\n\u003cp\u003eHBB1\u0026nbsp;\u0026ndash; Haemoglobin Subunit Beta-1\u003c/p\u003e\n\u003cp\u003eHPV \u0026ndash; Human Papillomavirus\u003c/p\u003e\n\u003cp\u003eHSIL High-grade Squamous Intraepithelial Lesion\u003c/p\u003e\n\u003cp\u003ehrHPV \u0026ndash; High-risk Human Papillomavirus\u003c/p\u003e\n\u003cp\u003eLSIL \u0026ndash; Low-grade Squamous Intraepithelial Lesion\u003c/p\u003e\n\u003cp\u003eNILM \u0026ndash; Negative for Intraepithelial Lesion Malignancy\u003c/p\u003e\n\u003cp\u003ePCR \u0026ndash; Polymerase Chain Reaction\u003c/p\u003e\n\u003cp\u003eRNA \u0026ndash; Ribonucleic Acid\u003c/p\u003e\n\u003cp\u003erRNA \u0026ndash; Ribosomal Ribonucleic Acid\u003c/p\u003e\n\u003cp\u003eRQ \u0026ndash; Relative Quantification\u003c/p\u003e\n\u003cp\u003eSCFAs \u0026ndash; Short-chain Fatty Acids\u003c/p\u003e\n\u003cp\u003eSpp. \u0026ndash; Species\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by Project VEGA 1/0398/21: \u0026ldquo;Immune system and vaginal microbiome as important mediator in the process of cervical carcinogenesis,\u0026rdquo; and co-financed by the Ministry of Education, Science, Research, and Sport of the Slovak Republic, by Project APVV-23-0428 \u0026ldquo;The role of the vaginal microbiome and the immune systemin the HPV-induced cervical carcinogenesis.\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEK, VH, and TR had conceptualized the study. EK, EK, TP and TR played primary role in samples collection. VH, LM, AH, and ZK performed laboratory samples processing. MG, LK and VH did analysis, and interpretation of the data. TR, EK, and VH did the manuscript preparation, and KB, TR and EN edited the manuscript. All the authors take complete responsibility for the content of the manuscript, read, and approved final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethical review committee of the Jessenius Faculty of Medicine in Martin, Comenius University had approved the study 14 December 2020 with registration number EK 85/2020. The principles of the Helsinki Declaration were followed. Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Veronika Holubekova.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our special gratitude to all employees of Biomedical Center Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava for their willingness and professionalism during the realization of the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTurnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight R, et al. The Human Microbiome Project. Nature. 2007;449:804\u0026ndash;10. \u003c/li\u003e\n\u003cli\u003eGilbert JA, Blaser MJ, Caporaso JG, Jansson JK, Lynch SV, et al. Current understanding of the human microbiome. 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Bacterial communities in women with bacterial vaginosis: high resolution phylogenetic analyses reveal relationships of microbiota to clinical criteria. PLoS One. 2012;7:e37818. \u003c/li\u003e\n\u003cli\u003eZhou R, Lu J, Wang J, Xiao B. Vaginal Lactobacillus iners abundance is associated with outcome in antibiotic treatment of bacterial vaginosis and capable of inhibiting Gardnerella. Front Cell Infect Microbiol. 2022;12:1033431. \u003c/li\u003e\n\u003cli\u003eRokos T, Holubekova V, Kolkova Z, Hornakova A, Pribulova T, Kozubik E, Biringer K, Kudela E. Is the Physiological Composition of the Vaginal Microbiome Altered in High-Risk HPV Infection of the Uterine Cervix? Viruses. 2022; 14(:2130. \u003c/li\u003e\n\u003cli\u003eR Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2024.\u003c/li\u003e\n\u003cli\u003eChen Y, Qiu X, Wang W, Li D, Wu A, Hong Z, Di W, Qiu L. 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Does the vaginal microbiota play a role in the development of cervical cancer? Transl Res. 2017;179:168-182.\u003c/li\u003e\n\u003cli\u003eMancilla V, Jimenez NR, Bishop NS, Flores M, Herbst-Kralovetz MM. The Vaginal Microbiota, Human Papillomavirus Infection, and Cervical Carcinogenesis: A Systematic Review in the Latina Population. J Epidemiol Glob Health. 2024;14:480-497.\u003c/li\u003e\n\u003cli\u003eNawrot R, Kamieniarz K, Malinowska M, J\u0026oacute;zefiak A, Kedzia W, Kwaśniewska A, Kuźma D, Goździcka-J\u0026oacute;zefiak A. The prevalence of leptotrichia amnionii in cervical swabs of HPV positive and negative women. Eur J Gynaecol Oncol. 2010;31:425-8. \u003c/li\u003e\n\u003cli\u003eSeo SS, Arokiyaraj S, Kim MK, Oh HY, Kwon M, Kong JS, Shin MK, Yu YL, Lee JK. High Prevalence of Leptotrichia amnionii, Atopobium vaginae, Sneathia sanguinegens, and Factor 1 Microbes and Association of Spontaneous Abortion among Korean Women. 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PMID: 36816582; PMCID: PMC9936092.\u003c/li\u003e\n\u003cli\u003ePelayo P, Hussain FA, Werlang CA, Wu CM, Woolston BM, Xiang CM, Rutt L, France MT, Ravel J, Ribbeck K, Kwon DS, Balskus EP. Prevotella are major contributors of sialidases in the human vaginal microbiome. Proc Natl Acad Sci U S A. 2024;121:e2400341121. \u003c/li\u003e\n\u003cli\u003eAbou Chacra L, Fenollar F, Diop K. Bacterial Vaginosis: What Do We Currently Know? Front Cell Infect Microbiol. 2022;11:672429. \u003c/li\u003e\n\u003cli\u003eFrance MT, Ma B, Gajer P, Brown S, Humphrys MS, Holm JB, Waetjen LE, Brotman RM, Ravel J. VALENCIA: a nearest centroid classification method for vaginal microbial communities based on composition. Microbiome. 2020;8:166. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"vaginal microbiome, cervical dysplasia, lactobacilli, HPV","lastPublishedDoi":"10.21203/rs.3.rs-7861075/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7861075/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIncreasing evidence has suggested that changes in the physiological composition of the human vaginal microbiome are associated with cervical cytological abnormalities. The aim of this study was to observe the vaginal microbiome composition in patients with cervical dysplasia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this prospective study, 91 samples of the vaginal microbiome taken from the cervix and posterior vaginal fornix were included. Eighteen bacterial species, including \u003cem\u003eLactobacillus\u003c/em\u003e species, were identified by real-time PCR. Relative bacterial quantities (RQs) were calculated, and log2-transformed RQs were visualised with boxplots. The relationships between cytological abnormalities and bacterial species were calculated by nonparametric one-way ANOVA (Kruskal‒Wallis test). For determination of bacterial diversity, the Shannon index was used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe demonstrated an increase in the abundance of vaginal microbiome samples dominated by \u003cem\u003eL. iners\u003c/em\u003e with increasing severity of cytologically and histologically confirmed cervical lesions, while HPV infection was present in 73.1% of community state type 3 samples. The presence of \u003cem\u003eG. vaginalis\u003c/em\u003e and \u003cem\u003eU. parvum\u003c/em\u003e in combination with \u003cem\u003eL. iners \u003c/em\u003ewas statistically significant. Our study also revealed considerably higher bacterial diversity in the community state type IV category. An increasing trend of bacterial diversity with increasing cytological severity of cervical lesions was also observed, although the difference was nonsignificant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study suggests that \u003cem\u003eL. iners\u003c/em\u003ehas adverse effects on the development of cervical dysplasia, while \u003cem\u003eL. gasseri\u003c/em\u003e and \u003cem\u003eL. crispatus\u003c/em\u003e may play protective roles. We also demonstrated the association of \u003cem\u003eL. iners\u003c/em\u003e with anaerobic bacteria, and we suggest the potential role of bacterial diversity in cervical carcinogenesis.\u003c/p\u003e\n\u003cp\u003eTrial registration number is EK 85/2020, the date of registration is 14 December 2020.\u003c/p\u003e","manuscriptTitle":"Lactobacillus Iners and Vaginal Microbiome Diversity as Risk Factors of Uterine Cervix Dysplasia: A Prospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 14:49:17","doi":"10.21203/rs.3.rs-7861075/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8dd3799c-6f93-4cd7-a00e-18f71b48f5fc","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-23T08:56:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-02 14:49:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7861075","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7861075","identity":"rs-7861075","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}