INTRODUCTION

Human lifestyle shifts do not only impact the health of the biosphere but likely affect our health as a result of changes in our microbial ecology. In the microscopic world, it is well known that humans are ecological harbors. The female genital tract is increasingly becoming one of the important habitats for human microbiota because the vaginal tract contains remarkably complex microbial communities¹.

Vaginal illnesses are among the most frequent gynecological issues. The vaginal microbiota’s stability is influenced by a variety of variables. Age, menses, menarche, diseases, pregnancy, birth control, and sexual practices all affect the composition of the vaginal microbiota². Infections are a common occurrence in vaginal disorders. The human vaginal microbiota tends to play a crucial role in avoiding a variety of urogenital diseases, including bacterial vaginosis, yeast infections, sexually transmitted diseases, urinary tract, and HIV-related infections³. A significant number of cases of vulvitis, cervicitis, and pelvic infections are associated with urogenital diseases⁴. The healthy vaginal microbiota is dominated by the hydrogen peroxide-forming Lactobacillus spp.^5-7, such as Lb. crispatus, Lb. acidophilus, Lacticaseibacillus rhamnosus, and others (except Lb. iners). This feature suppresses the growth of other organisms and excludes other bacteria unable to synthesize catalase⁷. Both healthy habitat and vaginal dysbiosis are often identified in the vaginal habitat of Lb. iners. It seems representative of a symbiotic or parasitic lifestyle, as opposed to other niche-flexible lactobacilli^8,9. Except for 9% of the strains¹⁰, Lb. iners are unable to produce hydrogen peroxide^11,12. However, facultative or obligate anaerobic bacteria, which are 100 to 1000 times more abundant than hydrogen peroxide-producing Lactobacillus spp., dominate a typical unhealthy vaginal flora^13,14. Furthermore, some non-infectious diseases, such as intrauterine adhesions, preterm birth, induced abortions, polycystic ovarian syndrome, miscarriage, uterine fibroid, infertility, and menstrual disorders, have been linked to microbial dysbiosis, represent a major threat to women’s reproductive health¹⁵.

The function of many bacteria that are assumed “normal” within the vagina has been redefined thanks to the introduction of NGS technology. Scientists are concerned not only about potentially “harmful” bacteria but also about changes in the organization of the vaginal microbiota as a whole¹⁶. Although there are some disadvantages using this method, such as a lot of technical difficulties which need to be thoroughly studied and solved, and high costs, time-consuming protocols, NGS has managed to solve the drawbacks of conventional DNA sequencing approaches and find the use in a wide variety of applications¹⁷. NGS could also be applied effectively to classify a large variety of taxonomic species that would not be possible with other methods.

The present study aimed to identify bacterial vaginal microbiota using the NGS method and metagenomic approach at different taxonomic levels from the kingdom to the species level. Furthermore, the relationships of identified bacterial communities present in vaginal microbiota with age and marital status were determined by canonical correspondence analysis (CCA).

MATERIALS AND METHODS

Samples

In this study, a total of 38 vaginal swab samples were collected from patients admitted to Yeditepe University Hospital, Department of Obstetrics and Gynecology in June 2021, using the DNA/RNA shield collection tubes with a swab (R1107, Zymo Research, USA). The swabs were stored at -20 °C till DNA extraction. The information related to patients’ age, marital status, preliminary diagnosis, and anamnesis status is given at Table 1.

The collection of all human materials was approved by Yeditepe University Clinical Research Ethics Committee (approval number: 1274, date: 20.08.2020).

DNA Extraction

Total DNA extraction was carried out using a ZymoBIOMICS DNA miniprep kit (D4300, Zymo Research, USA). The DNA samples were quantitated spectrophotometrically by the Take3 plate of the microplate reader (Epoch-2, BioTek, USA). Then, DNA samples were stored at -20 °C up to amplicon PCR experiments for NGS.

NGS and Metagenomic Analysis

DNA library was prepared according to the 16S metagenomic sequencing library preparation guide instructions (Illumina, Inc., California, USA). In 16S rRNA amplicon PCR, the primer pairs F-primer:5’-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3’ and R-primer5’-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3’ were used. In total extracted DNA of vaginal swab samples, bacterial 16S rRNA V3–V4 regions were amplified by PCR using KAPA HiFi HS Mix (Roche, Germany). Then, the amplicons of each swab sample were indexed with dual indexes by the Nextera XT index Kit v2 Set-A (Illumina). All PCR products and indexed samples were cleaned using AMPure XP beads (Beckman Coulter, USA) in a magnetic rack (DynaMag™-96 Side, Invitrogen, Norway). The equimolar (10 nM) proportions of the samples were pooled in a tube, then it was diluted to 1 nM, and it was finally diluted to a 35 pM DNA library. The diluted library (20 µl) containing 5% (v/v) PhiX control DNA (Illumina) was loaded into an iSeq100 v1 cartridge (Illumina). The sequencing was performed in the iSeq100 system (Illumina) with a pair-end read type and two reads of 151 bp read length of the sequence.

The NGS data were analyzed using the 16S Metagenomics, Version: 1.1.0 software (Illumina). The sequence identity of clustered sequences by NGS was determined by an operational taxonomic unit (OTU) approach. Alpha diversity values (Shannon species diversity index), the number of species, evenness, and taxonomic distributions of bacterial communities were determined by the 16S Metagenomics software Version 1.1.0 (Illumina) using RefSeq RDP 16S v3 May 2018 DADA2 32 bp taxonomical interference and the Ribosomal Database Project (RDP) Classifier¹⁸. CCA was applied using the PAleontological STatistics Software version 4.06b package (2021) to consider the variables of the patients’ age and marriage status¹⁹.

RESULTS

In the present study, the swab samples for vaginal bacterial microbiota taken from 38 Turkish patients were evaluated. The patients’ ages ranged between 22 and 46 years. Out of 38 patients, 21 of them were married, and 17 of the patients were single (Table 1). In addition, five of the patients applied for general control and no symptoms related to any diseases was observed (v2, v11, v22, v29, and v30) and they were considered healthy controls. A preliminary diagnosis of acute vaginitis was made only in one patient with pregnancy status (v35). Moreover, HPV with mild cervical dysplasia was prediagnosed in two patients (v7 and v13). Mastodynia with acute vaginitis was prediagnosed in three patients (v4, v5, and v10). Abnormal uterine and vaginal bleeding were prediagnosed in five patients (v3, v15, v16, v32, and v39). The remaining 22 patients were prediagnosed with acute vaginitis. Patient information with age, marital status, preliminary diagnosis, and anamnesis are given in Table 1.

The vaginal microbiota analysis was generated from a total of 2,047,376 high-quality NGS reads obtained from the total DNA of 38 vaginal swab samples and all belonged to the bacteria kingdom. The percentages of OTUs allocated to each bacterial phylum are given in Figure 1. Vaginal swab samples revealed the percent abundance of the top six phyla at the phylum level. The dominant phylum Firmicutes was followed by Proteobacteria, Actinobacteria, Tenericutes, Fusobacteria, and Synergistetes in the vaginal samples (Figure 1).

The percentages of bacterial OTUs assigned to the genus level were given in Figure 2. At the genus level, vaginal swab samples revealed the percent abundance of the top twenty genera. In addition, Lactobacillus was the most abundant genus in the vaginal swab samples, followed by Prevotella, Enterobacter, Gardnerella, and Dialister. The percent abundance of the top twenty species was shown in Figure 3. Lb. iners was the most abundant species in vaginal swab samples, followed by Gardnerella vaginalis, Enterobacter tabaci, Prevotella timonensis, P. bivia, and Lb. jensenii.

The alpha diversity of the samples determined by Shannon species diversity index values and evenness is presented in Table 2. The lower evenness indicates the diverse vaginal microbiota. In this context, the highest diversity was found in v38 and v19 samples. The preliminary diagnosis of the v19 and v38 samples was acute vaginitis with vaginal discharge for 2 days. The lowest diversity was found in v39 and v36 samples. The preliminary diagnosis of the v36 sample was acute vaginitis with smelly vaginal discharge for 2 days and menstrual irregularity for 2 months, and the v39 sample was abnormal uterine and vaginal bleeding with menstrual irregularity for 4 months (Tables 1 and 2). In the vaginal samples, the number of identified bacterial species ranged from 32 to 175 (Table 2).

CCA is a correspondence analysis extension that uses direct gradient analysis²⁰. CCA was used to determine the associations between vaginal swab samples and their bacterial populations at the phylum, the genus, and the species levels, as well as their variables like marital status and age of examined patients.

The phylum points were presented in Figure 4A. In combination with the arrows for variables, it was accounted for 99.75% of the weighted averages of the 6 phyla of bacteria regarding the two variables. The sum of all eigenvalues was 0.03. Proteobacteria and Fusobacteria were mainly found in variable married/single with the highest percentages, whereas Actinobacteria and Tenericutes were found in variable age with the highest percentages. At the phylum level, a negative correlation was found between variables married/single status and age (Figure 4A).

The genus points were shown in Figure 4B. In combination with the arrows for variables, it was accounted for 99.69% of the weighted averages of the 20 genera of bacteria about the two variables, the sum of all eigenvalues being 0.10. Campylobacter, Atopobium, Enterobacter, and Lactococcus were mainly found in variable married/single with the highest percentages, whereas Gardnerella was found in the lowest percentages. Anaerococcus, Streptococcus, Sutterella, and Veillonella were mainly found in variable age with the highest percentages, whereas Staphylococcus and Escherichia/Shigella were found in the lowest percentages. In addition, a positive correlation was found between variables married/single and age at the genus level (Figure 4B).

It was accounted for 99.42% of the weighted averages of the 20 species of bacteria regarding the two variables, the sum of all eigenvalues being 0.33. Campylobacter ureolyticus, Lb. jensenii, and Atopobium vaginae were mainly found in variable married/single with the highest percentages, whereas Lb. johnsonii and Gardnerella vaginalis were mainly found in variable age with the highest percentages. In addition, at the species level, a negative correlation was found between variables married/single and age (Figure 4C).

DISCUSSION

The human vaginal microbiome is complex, and researchers are only now beginning to understand its role in health and disease. The human microbiome is a collection of microorganisms like viruses, bacteria, and fungi that live in a symbiotic relationship with the human body²¹. The microbiome profile of each anatomical component of the body is unique. In the female vaginal tract, virus and bacterial profiles are complex, with a substantial inter-individual variation²².

Hočevar et al.²³ studied preterm delivery with 155 Caucasian women and they found the dominant phyla in the vaginal microbiota were Firmicutes and Actinobacteria, with lower contributions from Fusobacteria, Proteobacteria, and Tenericutes. At the genus level, the dominant members were Lactobacillus, Gardnerella, Atopobium, Streptococcus, and Sneathia. At the species level, Lb. iners and Lb. crispatus were most abundant bacteria. Their results were similar to our findings in the current study in which Firmicutes were the dominant phyla. However, we found Proteobacteria as the second dominant phyla, and Fusobacteria and Synergistetes were found to be the lower contributors for bacterial microbiota profile (Figure 1). Similarly, we found Lactobacillus was the most abundant genus. Indeed, in our study, Atopobium and Streptococcus were detected, but Sneathia was not found in our metagenomics study (Figure 2). At the species level, similarly, we found Lb. iners was the most abundant species. Indeed, we did not identify Lb. crispatus in our study (Figure 3). Many studies have detected that having Lb. crispatus in the vaginal area is connected with fine health; however, having Lb. iners in the vaginal area does not provide adequate protection against vaginal dysbiosis^24-26. Exogenous bacteria are inhibited more effectively by D-lactic acid than by L-lactic acid. As a result, it appears that L-lactic acid makes Lb. iners less effective at preventing pathogen invasion²⁷. A recent study has reported that bacterial vaginosis patients exhibit vaginal colonization with a wide range of bacteria, including numerous previously uncultivated species that appear to be highly specific for bacterial vaginosis, as well as the absence of Lb. crispatus²⁸.

In a recent study, the microbiota of asymptomatic bacterial vaginosis patients was compared with that of healthy women using NGS in India. Their results showed that Lactobacillus was dominant especially in normal healthy vaginal microbiota compared to dysbiotic microbiota with the abundance of Gardnerella, Sneathia, Prevotella, Atopobium, Ureaplasma, and Dialister genera²⁹. Similar to our results, Prevotella, Gardnerella, and Dialister were also identified with high read numbers. Furthermore, Atopobium vaginae, Sneathia amnii, Mycoplasma hominis, and Prevotella disiens were significantly demonstrated as biomarkers for dysbiosis, and Lb. jensenii as a biomarker for a healthy microbiota²⁹. The decrease in the number of protective Lactobacillus population in bacterial vaginosis patients leads to an increase Gardnerella vaginalis and Prevotella species³⁰. Indeed, G. vaginalis is the most isolated bacteria in bacterial vaginosis patients¹³. Prevotella spp. are associated with menopause, bacterial vaginosis, and body mass index (obesity), as well as they are the most heritable vaginal microbiota members among twins. Moreover, Prevotella spp. are negatively correlated with Lactobacilli and obese individuals have an abundance of Prevotella populations in their vaginal microbiota³¹.

The link between ethnicity and health is gaining attention in global health studies. Varied ethnic origins as Algerian women³², South African women³³, large North American cohorts consisting of four ethnic groups (Caucasian, African, Hispanic, and Asian)³⁴, Dutch, African Surinamese, South-Asian, Surinamese, Ghanaian, Turkish, and Moroccan women³⁵ have been documented in earlier research to have different geographical settlements and vaginal flora. The causes of these differences within ethnic groups are unknown, but they could be linked to genetic variations in innate and adaptive immune systems³¹.

In a prior study, Komesu et al.³⁶ discovered that Lactobacillus had the greatest connection with age. Lactobacillus content in vaginal microbiota was shown to be decreased as people became older, according to their research. The quantity of Lactobacillus has therefore been demonstrated to be age-dependent. Similarly, according to our CCA result related to the genus level (Figure 4B), we did not find a positive relationship with the genus Lactobacillus. In addition, Anaerococcus, Streptococcus, Sutterella, and Veillonella were mainly found to have a positive relationship with age variable. Dysbiosis, or changes in the microbiota, has been linked to reproductive failure, and changes in the microbiota may affect susceptibility to gynecological problems. For example, Anaerococcus, Streptococcus, and Veillonella were found in abnormal vaginal bacterial microbiota³⁷. Sutterella is a major component of the intestinal microbiota and plays an important role in the dysfunction of human microbiota³⁸. Previous results showed that marital status was significantly associated with vaginal bacterial microbiota and the incidence of vaginitis was shown to be more common in married women than in unmarried women³⁹. Likewise, we also found the relationships between vaginal bacterial microbiota and marital status by using CCA in the present study (Figures 4A-C).

Study Limitations

The small number of patients in our study is a constraint. More research with a larger number of patients is required.

CONCLUSION

In conclusion, vaginal diseases continue to be a significant public health issue. Thanks to technological developments, it has been seen that the vaginal microbiota, which has been examined in more detail in recent years, is more complex than previously thought. It is critical to swiftly and precisely identify the bacteria involved in the etiology of vaginal diseases for proper therapy. Further studies are needed in more patients to confirm and develop current findings.

Acknowledgements

The authors would like to thank Prof. Dr. Rukset Attar (Yeditepe University Hospital, Department of Obstetrics and Gynecology) and Kit-ARGEM R&D Center Konya Food and Agriculture University.

Ethics

Ethics Committee Approval: All procedures used in studies involving human volunteers complied with the institutional and/or national research committee’s ethical requirements, as well as the 1964 Helsinki Statement and its subsequent revisions or comparable ethical standards. The collection of all human materials was approved by Yeditepe University Clinical Research Ethics Committee (approval number: 1274, date: 20.08.2020).

Informed Consent: Consent form was filled out by all participants.

Peer-review: Externally peer-reviewed.

Authorship Contributions

Concept: S.U., B.G.T., S.D., V.C.Ö., Design: S.U., M.S., B.G.T., S.D., V.C.Ö., Data Collection or Processing: S.U., M.N.Z.Y., B.B.T., E.E.A., B.G.T., S.D., Analysis or Interpretation: S.U., M.S., M.N.Z.Y., B.B.T., E.E.A., Literature Search: S.U., Writing: S.U., M.S., V.C.Ö.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: This study was financially supported by Atılım University Research Fund with a project number ATÜ-ADP-2021-02.