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mSystems
mSystems
msystems
mSystems
2379-5077
American Society for Microbiology 1752 N St., N.W., Washington, DC

39120153
msystems00738-24
10.1128/msystems.00738-24
msystems.00738-24
Research Article
clinical-microbiologyClinical MicrobiologyHuman papillomavirus molecular prevalence in south China and the impact on vaginal microbiome of unvaccinated women
Wang Tingting 1 Writing – review and editing
https://orcid.org/0000-0002-8956-0164
Li Weili 2 Conceptualization Data curation Writing – review and editing
Cai Mingya 3 4 Writing – review and editing
Ji Shushen 2 Formal analysis Software
Wang Yufang 1 Writing – review and editing
Huang Nan 1 Writing – review and editing
Jiang Yancheng 3 Supervision
https://orcid.org/0009-0009-9894-5793
Zhang Zhishan 3 Funding acquisition Supervision zhishanzhang@fjmu.edu.cn

1 School of Health, Quanzhou Medical College , Quanzhou, China
2 Zhangjiang Center for Translational Medicine, Shanghai Biotecan Pharmaceuticals Co., Ltd. , Shanghai, China
3 Department of Clinical Laboratory, Quanzhou First Hospital Affiliated to Fujian Medical University , Quanzhou, China
4 Department of Clinical Laboratory, Jinjiang Hospital , Jinjiang, China
Editor Gilbert Jack A. University of California San Diego , La Jolla, California, USA

Address correspondence to Zhishan Zhang, zhishanzhang@fjmu.edu.cn
Tingting Wang, Weili Li, and Mingya Cai contributed equally to this article. Author order was determined by the order of decreasing seniority.

W.L. and S.J. are employed by Shanghai Biotecan Pharmaceuticals Company. The other authors declare no conflict of interest.

9 2024
09 8 2024
09 8 2024
9 9 e00738-2429 5 2024
30 5 2024
Copyright © 2024 Wang et al.
2024
Wang et al.
https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

ABSTRACT

The vaginal microbiome (VM) is associated with human papillomavirus (HPV) infection and progression, but a thorough understanding of the relation between HPV infection, and VM needs to be elucidated. From August to December 2022, women who underwent routine gynecological examinations were screened for HPV infection. The distribution of HPV variants and clinical characteristics were collected. Then, a total of 185 participants were enrolled and divided into HPV-negative (HC), high-risk HPV (H), low-risk HPV (L), multiple high-risk HPV (HH), and mixed high-low risk HPV (HL) groups. Samples were collected from the mid-vagina of these 185 participants and sent for 16S rDNA sequencing (V3–V4 region). Among 712 HPV-positive women, the top 3 most frequently detected genotypes were HPV52, HPV58, and HPV16. Among 185 participants in the microbiology study, the β diversity of the HC group was significantly different from HPV-positive groups (P < 0.001). LEfSe analysis showed that Lactobacillus iners was a potential biomarker for H group, while Lactobacillus crispatus was for L group. Regarding HPV-positive patients, the α diversity of cervical lesion patients was remarkably lower than those with normal cervix (P < 0.05). Differential abundance analysis showed that Lactobacillus jensenii significantly reduced in cervical lesion patients (P < 0.001). Further community state type (CST) clustering displayed that CST IV was more common than other types in HC group (P < 0.05), while CST I was higher than CST IV in H group (P < 0.05). Different HPV infections had distinct vaginal microbiome features. HPV infection might lead to the imbalance of Lactobacillus spp. and cause cervical lesions.

IMPORTANCE

In this study, we first investigated the prevalence of different HPV genotypes in south China, which could provide more information for HPV vaccinations. Then, a total of 185 subjects were selected from HPV-negative, high-risk, low-risk, multiple hr-hr HPV infection, and mixed hr-lr HPV infection populations to explore the vaginal microbiome changes. This study displayed that HPV52, HPV58, and HPV16 were the most prevalent high-risk variants in south China. In addition, high-risk HPV infection was featured by Lactobacillus iners, while low-risk HPV infection was by Lactobacillus crispatus. Further sub-group analysis showed that Lactobacillus jensenii was significantly reduced in patients with cervical lesions. Finally, CST clustering showed that CST IV was the most common type in HC group, while CST I accounted the most in H group. In a word, this study for the first time systemically profiled vaginal microbiome of different HPV infections, which may add bricks to current knowledge on HPV infection and lay the foundation for novel treatment/prevention development.

KEYWORDS

human papillomavirus
prevalence
vaginal microbiome
cervical intraepithelial neoplasia
Quanzhou Science & Technology Program 2021N131S Wang Tingting Quanzhou High-level Talents Innovation and Entrepreneurship Project 2022C037R Zhang Zhishan Natural Science Foundation of Fujian Province of China 2021J011402 Jiang Yancheng cover-dateSeptember 2024
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pmcINTRODUCTION

Human papillomavirus (HPV) are ubiquitous double-stranded DNA viruses that can be transmitted sexually. Nowadays, hundreds of HPV genotypes have been reported and many of them can infect the genital tract (1). Genital HPV infections can be asymptomatic, and most women are reported to have HPV infections at some time throughout their lives. Although over 90% can be cleared spontaneously (2), there is still a small proportion of women suffering from persistent infection, which may lead to cervical neoplastic lesions (3, 4). According to a recent largest epidemiology study in China (5), the overall prevalence of HPV was more than 20% and was increasing over the years. Though HPV vaccination is an effective prevention method (6, 7), the vaccine coverage is still low in mainland China (8). In addition, HPV vaccines only protect women from targeted HPV genotypes, leaving them still at risk of other genotypes of HPV infections. Considering that concurrent multiple HPV infections are common (9, 10) and are associated with persistent infections (11, 12), the role of multiple HPV infections in cervical cancer development should not be overlooked. In addition, based on the carcinogenicities, HPV can be divided into high-risk HPV (hr-HPV) and low-risk HPV (lr-HPV). Hr-HPV consists of at least 12 genotypes, including HPV16, HPV18, HPV52, and so on. Worldwide, the prevalence of hr-HPV genotypes demonstrated a region-specific pattern. Typically, HPV18 is reported to be the most common one in Europe, while HPV16 is one of the most frequent variant in Africa, North America, and China (13, 14). Emerging evidence showed that the biological behaviors of hr-HPV and lr-HPV were different regarding viral genome integration (15, 16), and such variance could explain the distinct outcomes of the two types of HPV infection. But, beyond these aspects, other mechanisms underneath the pathogenicity differences deserve exploring.

Like the human gut and skin microbiome, abundant microorganisms reside in the vagina, playing essential roles in regulating vaginal microecological balances. To date, extensive work has been done regarding the constitution of vaginal microbiota. For instance, Ravel et al. (17) reported that bacterial communities in asymptomatic women can be classified into five community state types (CSTs). CST I, II, III, and V were dominated by Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus iners, and Lactobacillus jensenii, respectively, while CST IV was featured by a more diverse community. Their research also showed that CST III accounted for the most proportion of the Asian women, followed by CST I and CST IV. Rapidly accumulating research showed that the vaginal microbiota was also involved in HPV acquisition and persistence (18), and the relationships between vaginal microbiome and HPV infections are increasingly understood. A systemic research that enrolled 15 prospective cohort studies found a causal link between vaginal dysbiosis and HPV infection and persistence (19). Lee et al. (20) reported a higher diversity, a lower level of Lactobacillus, especially L. iners, in the HPV-positive group. Vargas-Robles et al. (21) further investigated the cervicovaginal microbiome of Hispanic women regarding physiological stages, HPV infection types, as well as cervical lesions. In recent years, increasing studies explored the vaginal microbiome features of hr-HPV (22, 23), lr-HPV (24), and multiple HPV infections (25). A comprehensive depiction of the vaginal microbiome of patients with different types of HPV infection will provide an expanded understanding of relationships between vaginal microbiota, HPV, and cervical cancers among the Chinese population.

This study firstly investigated the distribution of different HPV genotypes among women in Quanzhou, providing an overview of HPV infections in south China. Then, further exploration of the vaginal microbiome in patients with distinct types of HPV infection was performed using next-generation sequencing. By depicting vaginal microbial profiles of the hr-/lr-/multiple HPV infections, more in-depth knowledge on the mechanisms of HPV infection could be obtained, laying the foundation for novel therapy development to prevent HPV infection and restore cervicovaginal health.

MATERIALS AND METHODS

Study design and specimen collection

From August to December 2022, a total of 6,346 women underwent routine gynecological examinations in the Department of Gynecology of the First Hospital of Quanzhou City, Fujian, China. Cervical specimens were collected with a Cytobrush and were sent for cervical Thinprep Cytology Test (TCT) (Hologic, Marlborough, MA, USA) and HPV DNA detection, respectively. HPV DNA test was performed with an HPV detection kit according to the manufacturer’s instruction (Hybribio, Chaozhou, Guangdong, China), which uses PCR + membrane hybridization technique and can qualitatively detect 21 types of HPV DNA, namely, 6, 11, 53, 16, 18, 31, 33, 58, 35, 39, 45, 51, 52, 56, 59, 66, 68, 42, 43, 44, and CP8304 (often infringes Chinese population [5]). Among these, 14 genotypes were hr-HPV, including HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68; 6 genotypes were lr-HPV, including HPV6, 11, 42, 43, 44, and CP8304, while 1 genotype, that is, HPV53, was intermediate-risk HPV. Histopathological examinations were performed on patients according to China Cervical Cancer Diagnoses and Treatment Guidelines (26). Patients with cervical lesions were further classified into low-grade squamous intraepithelial lesions (LSIL), high-grade squamous intraepithelial lesions (HSIL), and squamous-cell carcinoma (SCC) based on the WHO Classification of Female Genital Tumors (27), which indicated cervical intraepithelial neoplasia grade 1 (CIN1) to be LSIL, while CIN2 and CIN3 to be HSIL. Then, a third specimen was collected from the mid-vagina of subjects who gave informed consent (n = 354) and was immediately stored at −80°C. From these individuals, a total of 185 age-matched subjects were included in the vaginal microbiome study, containing 35 subjects with HPV-negative (HC), 50 with single hr-HPV infections (H), 50 with single lr-HPV infections (L), 36 with multiple hr-hr HPV infections (HH), and 14 with hr-lr HPV infections (HL). The respective third specimens of these participants were shipped with sufficient dry ice and were subjected to 16S rDNA sequencing. The exclusion criteria were as follows: (i) HPV vaccinated; (ii) other gynecological cancer types except cervical cancer; (iii) current pregnancy; (iv) chlamydia/gonorrhea/HIV infection; (v) sexual intercourse or vaginal lavage in 3 days before sample collection; and (vi) antibiotics or vaginal antimicrobials usage in 2 weeks before sample collection. The clinical characteristics of these participants were recorded, including age, body mass index (BMI), marital status, gravity times, parity times and vaginal discharge examination results. The flowchart of the study design can be found in Fig. 1. The study protocol was approved by the ethics committee of the First Hospital of Quanzhou City (#2021010), and the study was conducted following the principles of the Declaration of Helsinki. All participants in the microbiological study provided written informed consent before sample collection. The STORMS checklist can be found at https://doi.org/10.6084/m9.figshare.25440403.

FIG 1 The flowchart of the study design.

Bacterial DNA extraction and 16S rDNA sequencing

First, according to the manufacturer’s instructions, the total bacterial genomic DNA was extracted with the PowerMax DNA isolation kit (MoBio Laboratories, Carlsbad, CA, USA) and stored at −20°C. A NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and agarose gel electrophoresis were performed to test the quantity and quality of extracted DNA, respectively. Then, the V3–V4 region of the bacterial 16S rDNA gene was amplified using polymerase chain reaction (PCR) with the forward primers 341F (5′-CCTAYGGGRBGCASCAG-3′) and the reverse primer 806R (5′-GGACTACHVGGGTWTCTAAT-3′). The PCR was performed in a reaction system that contained 25 µL of Phusion High-Fidelity PCR Master Mix, 3 µL (10 μM) of forward primer, 3 µL (10 μM) of reverse primer, 10 µL of DNA template, 3 µL of DMSO, and 6 µL of ddH2O. The thermal cycling conditions were set as initial denaturation at 98°C for 30 s, followed by 25 cycles consisting of denaturation at 98°C for 15 s, annealing at 58°C for 15 s, and extension at 72°C for 15 s, with a final extension of 1 min at 72°C. Next, PCR amplicons were purified by Agencourt AMPure XP Beads (Beckman Coulter, Indianapolis, IN) and quantified with the PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA), followed by pooling of the amplicons in equimolar quantities. After that, pair-end 2 × 150 bp sequencing was performed on the Illumina NovaSeq 6000 platform at Shanghai Biotecan Co., Ltd (Shanghai, China).

Bioinformatic analysis

Raw sequencing reads that matched exactly to the barcodes were assigned to respective samples. Then, quality filtration of raw reads was performed following the below criteria: sequences that (i) had a length under 150 bp; (ii) had average Phred scores under 20; (iii) contained ambiguous bases; and (iv) contained mononucleotide repeats over 8 bp were removed. Next, paired-end reads were assembled using Vsearch v2.4.4, and unique sequences were assigned to operational taxonomic units (OTUs) with 97% similarity by mothur (v1.39.5). The taxonomy of these OTUs was further generated by searching against the Greengenes2 database. An OTU table recording the abundance of each OTU in a single sample was further generated. Before downstream analysis, the rarefy function from the vegan R package was used to perform rarefaction on the OTU table, normalizing it to the minimum sequence count across all samples. Moreover, to minimize the differences in sequencing depth across samples, OTUs that contained lower than 0.001% of total sequences were discarded and an averaged rarefied OTU table was generated.

The Quantitative Insights into Microbial Ecology (QIIME2, v2023.2.0) and R packages (v3.2.0) were applied to analyze sequence data. In QIIME2, the OTU table was used to calculate the α diversity indices, including the Chao1, abundance-based coverage estimator (ACE), Shannon, and Simpson indexes. Besides, β diversity analysis was also performed to explore the bacterial community’s structural differences across samples via Unifrac distance and visualized with the principal component analysis (PCA), principal coordinate analysis (PCoA), and non-metric multi-dimensional scaling (NMDS). Taxa that statistically differed in relative abundance between two groups were identified using Kruskal–Wallis test from the R stats package, and the linear discriminant analysis (LDA) effect size analysis (LEfSe) was performed with the cutoff value of the absolute LDA score (log10) being >2.0 and P < 0.05. In addition, ANCOM-BC2 was applied for differential abundance analysis. Finally, to predict the metagenome functions of microbials, PICRUSt2 (https://github.com/picrust/picrust2/) was applied and the functional pathways were enriched by Kyoto Encyclopedia of Genes and Genomes (KEGG) database, in addition to the human gut metabolic modules (GMMs) database and gut-brain modules (GBMs).

Statistical analysis

For clinical characteristics, normally distributed continuous data were presented as mean ± SD, and category variables were presented as numbers and percentages. Non-parametric Dunn’s tests with Kruskal–Wallis tests or Mann–Whitney U test were applied in comparisons between groups. For the microbial data, the Wilcoxon rank sum test, Tukey test, and permutational multivariate analysis of variance (PERMANOVA) were used to test the differences between groups. Spearman’s rank correlation analysis was performed on featured genera and biofunctions via R (v3.2.0). All P values were two-sided, and P < 0.05 was considered statistically significant.

RESULTS

Epidemiology of HPV variants

A total of 712 women with an average age of 39.34 ± 13.3 years old were reported to have HPV infections, and 533 of them had available cytological test results. The most frequently detected genotypes were HPV52 (155 cases), followed by HPV58 (104 cases), and HPV16 (103 cases) (Fig. 2A). Two peaks in frequencies of hr-HPV infections were observed among patients between 30 and 50 years old (Fig. 2B). The HPV distribution across age groups was displayed in Table 1. Among all patients, 416 (58.43%) had single hr-HPV infections, 47 (6.60%) had single intermediate-risk HPV infections, 73 (10.25%) had single lr-HPV infections, and 176 (24.72%) had multiple HPV infections. Among the multiple infections, 110 (62.50%) were multiple hr-hr HPV infection, 62 (35.23%) were mixed hr-lr HPV infections, while only 4 (2.27%) were multiple lr-lr HPV infections. Besides, most multiple HPV infection patients were concurrent of 2 HPV genotypes (71.59%), followed by 3 HPV genotypes (19.32%) (Fig. 2C). Among 533 patients with accessible cytological results, 162 (30.39%) had cervical lesions (including SCC, HSIL, and LSIL). The number and the proportion of different HPV infection types in cervical lesions were shown in Fig. 2D. However, there was no significant difference in cervical lesion types among HPV infection types (P > 0.05) (Table 2). Further analysis of the frequencies of HPV genotypes in patients with or without cervical lesions showed that HPV16 accounts for most of SCC (75%) and HSIL (48%) patients (Fig. 2E).

FIG 2 Epidemiology of HPV infections. (A) Distribution of HPV genotypes based on the present frequencies. (B) Distribution of HPV infections according to age. (C) Proportion of HPV infection types among 712 HPV-positive patients. (D) The number (bar plot) and the proportion of cases (pie graph) of HPV infection types among 162 patients with cervical lesions. (E) Frequency of HPV genotypes among patients with or without cervical lesions. H, single hr-HPV infection; HH, high-risk and high-risk multiple HPV infections; HL, high-risk and low-risk multiple HPV infections; I, single intermediate-risk HPV infection; L, single lr-HPV infection; LL, low-risk and low-risk multiple HPV infections; M, multiple HPV infections.

TABLE 1 Distribution of HPV infection types and age groupsa

Age (years)	Single hr-HPV
(n = 417) (%)	Single inter-risk HPV
(n = 46) (%)	Single lr-HPV
(n = 74) (%)	Multiple hr-hr HPV
(n = 110) (%)	Mixed hr-lr HPV
(n = 61) (%)	Multiple lr-lr HPV
(n = 4) (%)	P-value	
<25	52 (12.47)	3 (6.52)	17 (22.97)	24 (21.82)	20 (32.79)	2 (50)	0.195	
25–34	118 (28.30)	15 (32.61)	16 (21.62)	22 (20)	9 (14.75)	0	
35–44	88 (21.10)	10 (21.74)	16 (21.62)	18 (16.36)	13 (21.31)	0	
45–54	103 (24.70)	12 (26.09)	23 (31.08)	23 (20.91)	13 (21.31)	1 (25)	
>54	56 (13.43)	6 (13.04)	2 (2.70)	23 (20.91)	6 (9.84)	1 (25)	
a Data are displayed as n (%). P was calculated with Kruskal–Wallis test.

TABLE 2 Distribution of cytology types among different HPV infection typesa

Cytology type	Single hr-HPV
(n = 327) (%)	Single inter-risk HPV
(n = 35) (%)	Single lr-HPV
(n = 54) (%)	Multiple hr-hr HPV
(n = 76) (%)	Mixed hr-lr HPV
(n = 38) (%)	Multiple lr-lr HPV
(n = 3) (%)	P-value	
NILMb	230 (71.43)	26 (74.29)	41 (75.93)	48 (63.16)	23 (62.16)	3 (100)	0.315	
LSIL	73 (22.67)	9 (25.71)	11 (20.38)	22 (28.95)	12 (32.43)	0	
HSIL	14 (2.80)	0	2 (3.70)	4 (5.26)	3 (5.41)	0	
SCC	10 (3.11)	0	0	2 (2.63)	0	0	
a Data are displayed as n (%); the percentage was calculated as number of cytology type/number of a certain HPV infection type. P was calculated with Kruskal–Wallis test.

b NILM, no intraepithelial lesion or malignancy.

Clinical characteristics of participants in vaginal microbiome study

In the cohort of vaginal microbiome study, 185 subjects, including 50 hr-HPV (H group), 36 multiple hr-hr infections (HH group), 14 mixed hr-lr infections (HL group), 50 lr-HPV (L group), and 35 HPV-negative (HC group), were enrolled to investigate the features of vaginal microbiota. The average ages of the five groups were comparable, with 32.84 ± 1.63, 32.36 ± 6.05, 35.36 ± 6.44, 34.7 ± 6.17, and 31.49 ± 3.07, respectively. Besides, the five groups did not differ in terms of BMI, cigarette smoking, and contraception uses. Cervical lesions were found in 34% of HPV-positive patients and 6% of HPV-negative individuals. The details of demographic features of the study population can be found in Table 3.

TABLE 3 Clinical characteristics of 185 participants in vaginal microbiology studya

	H group
(n = 50)	HH group
(n = 36)	HL group
(n = 14)	L group
(n = 50)	HC group
(n = 35)	
Age (years, mean ± SD)	32.84 ± 1.63	32.36 ± 6.05	35.36 ± 6.44	34.7 ± 6.17	31.49 ± 3.07	
BMI (kg/m2, mean ± SD)	20.91 ± 2.89	21.55 ± 3.15	21.56 ± 3.25	21.08 ± 3.50	20.56 ± 2.64	
Current smoker (n, %)	0	0	0	2 (4)	0	
Contraception (n, %)						
 Condom	5 (10)	4 (11)	2 (14)	6 (12)	2 (6)	
 Hormonal contraception	4 (8)	3 (8)	1 (7)	9 (18)	1 (2)	
 IUD	4 (8)	2 (6)	1 (7)	3 (6)	3 (8)	
 Other	20 (40)	15 (42)	7 (50)	14 (28)	21(60)	
 Unknown	17 (34)	12 (33)	3 (21)	18 (36)	5 (14)	
Cervical lesions (n, %)						
 NILM	34 (68)	20 (56)	8 (57)	37 (74)	33 (94)	
 LSIL	10 (20)	13 (36)	4 (29)	11 (22)	2 (6)	
 HSIL	5 (10)	2 (6)	2 (14)	2 (4)	0	
 SCC	1 (2)	1 (3)	0	0	0	
Gravidity (n, %)						
 0	3 (6)	9 (25)	5 (36)	8 (16)	12 (34)	
 1	11 (22)	4 (11)	4 (29)	5 (10)	10 (28)	
 2–3	17 (34)	8 (22)	2 (14)	15 (30)	9 (26)	
 >3	4 (8)	3 (8)	0	6 (12)	1 (3)	
 Unknown	15 (30)	12 (33)	3 (21)	16 (32)	3 (9)	
Parity (n, %)						
 0	5 (10)	9 (25)	6 (43)	10 (20)	15 (43)	
 1	12 (24)	5 (14)	4 (27)	10 (20)	10 (28)	
 2	14 (28)	9 (25)	1 (7)	10 (20)	6 (17)	
 ≥3	3 (6)	1 (3)	0	4 (8)	1 (3)	
 Unknown	16 (32)	12 (33)	3 (21)	16 (32)	3 (9)	
a Missing data were recorded as “unknown.” IUD, intrauterine device.

Vaginal microbiome features with different HPV infections

The microbiota composition across samples at genus level is displayed in Fig. 3A. No significant difference was found in α-diversity among the five groups (P > 0.05) (Fig. S1A). However, there was a significant difference in β-diversity (P < 0.001), with principal co-ordinates 1 and 2 explaining 18.6% and 12.9% of the variance, respectively (Fig. 3B). Typically, the HC group differed remarkably from the H group (P < 0.05), L group (P < 0.0001), and HH group (P < 0.05) in PCo1 and was significantly higher than the other groups in PCo2 (P < 0.0001). LEfSe analysis showed that the L. iners, L. jensenii 330150, and Lactobacillus fornicalis might be potential biomarkers for H group, while L. crispatus might be for L group (Fig. 3C). According to the differential abundance analysis performed by ANCOM-BC2, L. iners was significantly more abundant in H group than that in HC group (P < 0.05), while s_Ensifer_A (P < 0.01), s_Bifidobacterium (P < 0.001), and other bacteria were significantly lower in H group compared to HC group (Fig. 3D).

FIG 3 Vaginal microbiome diversity and composition among HC, H, HH, HL, and L groups. (A) Taxon at genus level across samples. (B) Differences in β-diversity of vaginal microbiome based on PCoA analysis. (C) Lefse analysis of featured microbiota of all groups. (D) Differential abundance analysis based on ANCOM-BC2. ***P < 0.001; **P < 0.01; *P < 0.05.

Vaginal microbiome features in women with cervical lesions

Among 150 HPV-positive participants, a total of 51 subjects with cervical lesions (LSIL, HSIL, SCC) were further compared with those with normal cervix to explore the differences in the vaginal microbiome. The α diversity indexes, including ACE, observed species and Chao1, were significantly lower in cervical lesion patients than those with normal cervix (P < 0.05) (Fig. 4A). But the β-diversity between the two groups was not significant (Fig. S1B through D). LEfSe analysis indicated that L. crispatus and L. iners were associated with normal cervix in HPV-positive patients (Fig. 4B), while L. jensenii 330150 was remarkably lower in cervical lesion group according to the differential abundance analysis with ANCOMBC2 (P < 0.001) (Fig. 4C).

FIG 4 Vaginal microbiome features of patients with cervical lesions. (A) α diversity indexes of two groups. (B) Bar plot of LDA score of featured microbial (threshold LDA score > 2) based on LEfSe analysis. (C) Differential abundance analysis based on ANCOM-BC2. ***P < 0.001; **P < 0.01; *P < 0.05. P was calculated with the Wilcoxon test.

CST clustering based on vaginal microbiota composition

According to Ravel’s (17) theory, participants in the present study were clustered into CST I (L. crispatus), CST III (L. iners), and CST IV (Diversity group). However, due to the insufficient samples, CST II and CST V were not clustered (Fig. 5). There was a significant difference in CST grouping among different HPV infection types (P < 0.001). Particularly, CST I accounted for a higher proportion than CST IV in H group (42% vs 28%, P < 0.05), while CST IV (85.7%) occurred more frequently than CST I (5.7%) and CST III (8.6%) in HC group (P < 0.05) (Table 4).

FIG 5 CST clustering of all samples.

TABLE 4 HPV infection types in different CST groupsa

Group	CST I (L. crispatus)
(n = 56) (%)	CST III (L. iners)
(n = 44) (%)	CST IV (diversity group)
(n = 85) (%)	P-value	
H group	21 (37.50)	15 (34.09)	14 (16.47)	<0.001	
HH group	14 (25.00)	8 (18.18)	14 (16.47)	
HL group	6 (10.71)	3 (6.81)	5 (5.88)	
L group	13 (23.21)	15 (34.09)	22 (25.88)	
HC group	2 (3.57)	3 (6.81)	30 (35.29)	
a Data are displayed as n (%). P was calculated with χ test.

DISCUSSION

This cross-sectional study first investigated the prevalence of HPV variants in Quanzhou and then explored the vaginal microbiome features with different HPV infections. Consistent with other studies in Guangdong (5) and Taiwan (28), this study found that HPV52, HPV58, and HPV16 were the top three most common variants detected in south China. In addition, the distribution of HPV genotypes also displayed an age-specific feature. In this study, two peaks of hr-HPV infection were observed, with one peak appearing at 35 and the other at 45 years of age. Similarly, other studies also reported a “two-peak” phenomenon of HPV prevalence across ages. For example, Yang et al. (5) and Wang et al. (29) reported the two peaks of hr-HPV infection to appear at under 21 years old and around 50 years old, respectively. The underlying mechanisms for such a “two-peak” pattern remain unclear but might be the result of immunity and hormone changes over time (30). Among 533 subjects with cytological results, a total of 162 participants (30.39%) reported cervical lesions, including LSIL, HSIL, and SCC, and most of them were infected with hr-HPV or multiple hr-hr HPV infections. But there were two cases of lr-HPV infection also associated with HSIL. Furthermore, HPV16 accounted for the largest proportion of HSIL and SCC patients, which is also consistent with previous studies (1, 5, 31).

Vaginal microbiome is a dynamic “ecosystem” that maintains a healthy vaginal microenvironment. Accumulating data show that the vaginal microbiome changes under physiological and disease states (32–34). In the present study, the β diversity of HPV-positive groups, including H, L, HH, and HL groups, was remarkably different from that of HPV-negative populations, which is in agreement with other studies (24, 25). As for the bacterial taxon analysis, the abundance of Lactobacillus, especially L. iners, was higher in H group when compared to the HC group. Studies (35, 36) reported that the healthy vaginal microbiome was predominated with Lactobacillus and HPV-positive patients had less Lactobacillus spp. presence. But, not all the species of Lactobacillus are protective factors for cervicovaginal health. For example, L. crispatus, L. jensenii, and L. gasseri are noninflammatory, while L. iners is proinflammatory, which may promote the oncogenic potential of hr-HPV (37). Besides, a longitudinal study that explored the relationship between vaginal microbiota and HPV clearance, suggested that high abundance of L. iners might hinder HPV clearance in hr-HPV infections (38), highlighting the differences in bio-functions of specific Lactobacillus species and the importance of species identification. Although a series of studies identified potential biomarkers for HPV infections, for example, Prevotella, Atopobium, and Dialister were thought to be related to HPV infections (39–41), it is seldom reported about the potential biomarkers for different types of HPV infections, respectively. In this study, LEfSe analysis identified a string of featured microbiota for H, HC, HL, and L groups. To be specific, L. crispatus and Prevotella bivia might be biomarkers for L group; Fannyhessea vaginae for HL group; L. iners, L. jensenii 330150, and L. fornicalis for hr-HPV infection; and Brucella melitensis, Burkholderia lata, Ensifer A adharens, and Enterococcus H 360604 faecalis for HPV-negative individuals. Inconsistently, Wei et al. (22) reported an increased abundance of Gardnerella, Porphyromonas, and Ureaplasma in hr-HPV infections. Another study also confirmed a high abundance of Sneathia in lr-HPV infection patients (24). The underlying reasons for such discrepancies might probably be caused by different methodologies and pollution of background bacteria. Further sub-group analysis demonstrated that the α diversity was lower in cervical lesion group. Besides, the L. iners slightly but not significantly increased in cervical lesions, while L. jensenii remarkably reduced in patients with cervical lesions. Studies found L. jensenii could inhibit the viability of cervical cancer cells by regulating HPV oncogenes and cell cycle-related genes (42), and a depletion of beneficial Lactobacillus species may lead to a vulnerable microenvironment of female reproductive tract (43). Taken together, it can be speculated that hr-HPV infection might be responsible for Lactobacillus spp. imbalance, which could lead to cervical lesions.

Lactic acid, acetate, succinic acid, propionic, and butyrate composed the major microbiota metabolites in the vagina (44, 45) and play different roles under healthy or disease states. Delgado-Diaz et al. (43) reported that acetate is capable of eliciting inflammatory effect in bacterial vaginosis, which can be encountered by lactic acid produced largely by Lactobacillus, (18) except L. iners. Interestingly, Wen et al. (46) found that a blocked conversion of acetate to butyrate may induce colon epithelial barrier damage in a pig model. In gynecological oncology models, it is recorded that butyrate can inhibit HPV-positive cervical cancer and ovarian cancer by arresting cell cycles (47, 48). Although researches showed that the abundance of Lactobacillus decreases with an increased level of acetate, butyrate, and other SCFAs in vaginal dysbiosis, the species of L. iners is an exception, which may induce inflammation and dysbiosis in the vagina, and may be associated with poor outcomes of bacterial vaginosis (49, 50). In vitro study showed L. iners is cysteine-dependent and can be targeted by inhibition agents (51). This study found that L. iners dominated in the H group; therefore, insufficient lactate could be produced to encounter the inflammation caused by SCFAs. This hypothesis might throw light on developing targeted treatment options but needs more solid work to verify it.

Limitations inevitably existed in this study. First, this is an observational study that depicted the vaginal microbiota features in different HPV infections, which demands more reliable proof to explain the phenomenon observed. Second, due to the limitation of 16s rDNA sequencing technique, the annotation to detailed species of microbiota needs a more exact method to verify it, such as culture or metagenomics sequencing. Lastly, the sampling method may cause potential selection biases in this study.

Conclusions

Overall, this study investigated the prevalence of HPV genotypes in south China and for the first time identified vaginal microbiome features for hr-, lr-, and multiple HPV infections comprehensively. Each HPV group had distinct microbiome features. In particular, hr-HPV was characterized by L. iners, while lr-HPV was featured by L. crispatus. The imbalance of Lactobacillus spp., caused by HPV infection, might be associated with cervical lesions. These results might throw light on the mechanisms of genital HPV infection and pave the way for novel therapy and vaccination development.

ACKNOWLEDGMENTS

The authors would like to thank all patients for participating in the study.

This work was supported by Quanzhou Science & Technology Program (2021N131S), Quanzhou High-level Talents Innovation and Entrepreneurship Project (2022C037R), and Natural Science Foundation of Fujian Province of China (2021J011402).

DATA AVAILABILITY

Raw sequence data can be obtained from NCBI (https://www.ncbi.nlm.nih.gov/) at SRA accession number PRJNA1089804. Other data that supports the findings of this study is available from the corresponding author upon reasonable request.

ETHICS APPROVAL

This study was approved by the Ethics Committee of Quan Zhou First Hospital (#2021010).

SUPPLEMENTAL MATERIAL

The following material is available online at https://doi.org/10.1128/msystems.00738-24.

10.1128/msystems.00738-24.SuF1 Figure S1 msystems.00738-24-s0001.docx

Microbiological diversity differences.

ASM does not own the copyrights to Supplemental Material that may be linked to, or accessed through, an article. The authors have granted ASM a non-exclusive, world-wide license to publish the Supplemental Material files. Please contact the corresponding author directly for reuse.
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REFERENCES

1 de Sanjose S, Quint WG, Alemany L, Geraets DT, Klaustermeier JE, Lloveras B, Tous S, Felix A, Bravo LE, Shin H-R, et al. . 2010. Human papillomavirus genotype attribution in invasive cervical cancer: a retrospective cross-sectional worldwide study. Lancet Oncol 11 :1048–1056. doi:10.1016/S1470-2045(10)70230-8 20952254
2 Woodman CB, Collins S, Winter H, Bailey A, Ellis J, Prior P, Yates M, Rollason TP, Young LS. 2001. Natural history of cervical human papillomavirus infection in young women: a longitudinal cohort study. Lancet 357 :1831–1836. doi:10.1016/S0140-6736(00)04956-4 11410191
3 Schlecht NF, Kulaga S, Robitaille J, Ferreira S, Santos M, Miyamura RA, Duarte-Franco E, Rohan TE, Ferenczy A, Villa LL, Franco EL. 2001. Persistent human papillomavirus infection as a predictor of cervical intraepithelial neoplasia. JAMA 286 :3106–3114. doi:10.1001/jama.286.24.3106 11754676
4 Ho GY, Burk RD, Klein S, Kadish AS, Chang CJ, Palan P, Basu J, Tachezy R, Lewis R, Romney S. 1995. Persistent genital human papillomavirus infection as a risk factor for persistent cervical dysplasia. J Natl Cancer Inst 87 :1365–1371. doi:10.1093/jnci/87.18.1365 7658497
5 Yang X, Li Y, Tang Y, Li Z, Wang S, Luo X, He T, Yin A, Luo M. 2023. Cervical HPV infection in Guangzhou, China: an epidemiological study of 198,111 women from 2015 to 2021. Emerg Microbes Infect 12 :e2176009. doi:10.1080/22221751.2023.2176009 36744409
6 Shing JZ, Hu S, Herrero R, Hildesheim A, Porras C, Sampson JN, Schussler J, Schiller JT, Lowy DR, Sierra MS, Carvajal L, Kreimer AR, Costa Rica HPV Vaccine Trial Group. 2022. Precancerous cervical lesions caused by non-vaccine-preventable HPV types after vaccination with the bivalent AS04-adjuvanted HPV vaccine: an analysis of the long-term follow-up study from the randomised costa Rica HPV vaccine trial. Lancet Oncol 23 :940–949. doi:10.1016/S1470-2045(22)00291-1 35709811
7 Joura EA, Garland SM, Paavonen J, Ferris DG, Perez G, Ault KA, Huh WK, Sings HL, James MK, Haupt RM, FUTURE I and II Study Group. 2012. Effect of the human papillomavirus (HPV) quadrivalent vaccine in a subgroup of women with cervical and vulvar disease: retrospective pooled analysis of trial data. BMJ 344 :e1401. doi:10.1136/bmj.e1401 22454089
8 Yin X, Zhang M, Wang F, Huang Y, Niu Y, Ge P, Yu W, Wu Y. 2022. A national cross-sectional study on the influencing factors of low HPV vaccination coverage in mainland China. Front Public Health 10 :1064802. doi:10.3389/fpubh.2022.1064802 36726621
9 Woodman CBJ, Collins SI, Young LS. 2007. The natural history of cervical HPV infection: unresolved issues. Nat Rev Cancer 7 :11–22. doi:10.1038/nrc2050 17186016
10 Laake I, Feiring B, Jonassen CM, Pettersson JHO, Frengen TG, Kirkeleite IØ, Trogstad L. 2022. Concurrent infection with multiple human papillomavirus types among unvaccinated and vaccinated 17-year-old norwegian girls. J Infect Dis 226 :625–633. doi:10.1093/infdis/jiaa709 33205203
11 Kim M, Park NJ-Y, Jeong JY, Park JY. 2021. Multiple human papilloma virus (HPV) infections are associated with HSIL and persistent HPV infection status in Korean patients. Viruses 13 :1342. doi:10.3390/v13071342 34372548
12 Oyervides-Muñoz MA, Pérez-Maya AA, Sánchez-Domínguez CN, Berlanga-Garza A, Antonio-Macedo M, Valdéz-Chapa LD, Cerda-Flores RM, Trevino V, Barrera-Saldaña HA, Garza-Rodríguez ML. 2020. Multiple HPV infections and viral load association in persistent cervical lesions in Mexican women. Viruses 12 :380. doi:10.3390/v12040380 32244347
13 Kombe Kombe AJ, Li B, Zahid A, Mengist HM, Bounda G-A, Zhou Y, Jin T. 2020. Epidemiology and burden of human papillomavirus and related diseases, molecular pathogenesis, and vaccine evaluation. Front Public Health 8 :552028. doi:10.3389/fpubh.2020.552028 33553082
14 Bruni L, Diaz M, Castellsagué X, Ferrer E, Bosch FX, de Sanjosé S. 2010. Cervical human papillomavirus prevalence in 5 continents: meta-analysis of 1 million women with normal cytological findings. J Infect Dis 202 :1789–1799. doi:10.1086/657321 21067372
15 Frattini MG, Lim HB, Laimins LA. 1996. In vitro synthesis of oncogenic human papillomaviruses requires episomal genomes for differentiation-dependent late expression. Proc Natl Acad Sci U S A 93 :3062–3067. doi:10.1073/pnas.93.7.3062 8610168
16 Karimzadeh M, Arlidge C, Rostami A, Lupien M, Bratman SV, Hoffman MM. 2023. Human papillomavirus integration transforms chromatin to drive oncogenesis. Genome Biol 24 :142. doi:10.1186/s13059-023-02926-9 37365652
17 Ravel J, Gajer P, Abdo Z, Schneider GM, Koenig SSK, McCulle SL, Karlebach S, Gorle R, Russell J, Tacket CO, Brotman RM, Davis CC, Ault K, Peralta L, Forney LJ. 2011. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci U S A 108 Suppl 1 :4680–4687. doi:10.1073/pnas.1002611107 20534435
18 Li Y, Yu T, Yan H, Li D, Yu T, Yuan T, Rahaman A, Ali S, Abbas F, Dian Z, Wu X, Baloch Z. 2020. Vaginal microbiota and HPV infection: novel mechanistic insights and therapeutic strategies. Infect Drug Resist 13 :1213–1220. doi:10.2147/IDR.S210615 32431522
19 Brusselaers N, Shrestha S, van de Wijgert J, Verstraelen H. 2019. Vaginal dysbiosis and the risk of human papillomavirus and cervical cancer: systematic review and meta-analysis. Am J Obstet Gynecol 221 :9–18. doi:10.1016/j.ajog.2018.12.011 30550767
20 Lee JE, Lee S, Lee H, Song Y-M, Lee K, Han MJ, Sung J, Ko G. 2013. Association of the vaginal microbiota with human papillomavirus infection in a Korean twin cohort. PLoS One 8 :e63514. doi:10.1371/journal.pone.0063514 23717441
21 Vargas-Robles D, Romaguera J, Alvarado-Velez I, Tosado-Rodríguez E, Dominicci-Maura A, Sanchez M, Wiggin KJ, Martinez-Ferrer M, Gilbert JA, Forney LJ, Godoy-Vitorino F. 2023. The cervical microbiota of hispanics living in Puerto Rico is nonoptimal regardless of HPV status. mSystems 8 :e0035723. doi:10.1128/msystems.00357-23 37534938
22 Wei Z-T, Chen H-L, Wang C-F, Yang G-L, Han S-M, Zhang S-L. 2020. Depiction of vaginal microbiota in women with high-risk human papillomavirus infection. Front Public Health 8 :587298. doi:10.3389/fpubh.2020.587298 33490017
23 Mei L, Wang T, Chen Y, Wei D, Zhang Y, Cui T, Meng J, Zhang X, Liu Y, Ding L, Niu X. 2022. Dysbiosis of vaginal microbiota associated with persistent high-risk human papilloma virus infection. J Transl Med 20 :12. doi:10.1186/s12967-021-03201-w 34980148
24 Zhou Y, Wang L, Pei F, Ji M, Zhang F, Sun Y, Zhao Q, Hong Y, Wang X, Tian J, Wang Y. 2019. Patients with LR-HPV infection have a distinct vaginal microbiota in comparison with healthy controls. Front Cell Infect Microbiol 9 :294. doi:10.3389/fcimb.2019.00294 31555603
25 Liu S, Li Y, Song Y, Wu X, Baloch Z, Xia X. 2022. The diversity of vaginal microbiome in women infected with single HPV and multiple genotype HPV infections in China. Front Cell Infect Microbiol 12 :642074. doi:10.3389/fcimb.2022.642074 36601309
26 Preparation and validation expert groups. 2022. Cervical cancer diagnoses and treatment guidelines
27 WHO classification of tumours editorial board. 2020. In Female genital tumours. Vol. 4 .
28 Lin Y, Lin W-Y, Lin T-W, Tseng Y-J, Wang Y-C, Yu J-R, Chung C-R, Wang H-Y. 2015. Trend of HPV molecular epidemiology in the post-vaccine era: a 10-year study. Viruses 15 :2015. doi:10.3390/v15102015
29 Wang R, Guo X-L, Wisman GBA, Schuuring E, Wang W-F, Zeng Z-Y, Zhu H, Wu S-W. 2015. Nationwide prevalence of human papillomavirus infection and viral genotype distribution in 37 cities in China. BMC Infect Dis 15 :257. doi:10.1186/s12879-015-0998-5 26142044
30 de Sanjosé S, Diaz M, Castellsagué X, Clifford G, Bruni L, Muñoz N, Bosch FX. 2007. Worldwide prevalence and genotype distribution of cervical human papillomavirus DNA in women with normal cytology: a meta-analysis. Lancet Infect Dis 7 :453–459. doi:10.1016/S1473-3099(07)70158-5 17597569
31 Muñoz-Bello JO, Carrillo-García A, Lizano M. 2022. Epidemiology and molecular biology of HPV variants in cervical cancer: the state of the art in Mexico. Int J Mol Sci 23 :8566. doi:10.3390/ijms23158566 35955700
32 DiGiulio DB, Callahan BJ, McMurdie PJ, Costello EK, Lyell DJ, Robaczewska A, Sun CL, Goltsman DSA, Wong RJ, Shaw G, Stevenson DK, Holmes SP, Relman DA. 2015. Temporal and spatial variation of the human microbiota during pregnancy. Proc Natl Acad Sci U S A 112 :11060–11065. doi:10.1073/pnas.1502875112 26283357
33 Oh KY, Lee S, Lee M-S, Lee M-J, Shim E, Hwang YH, Ha JG, Yang YS, Hwang IT, Park JS. 2021. Composition of vaginal microbiota in pregnant women with aerobic vaginitis. Front Cell Infect Microbiol 11 :677648. doi:10.3389/fcimb.2021.677648 34568084
34 Chen X, Lu Y, Chen T, Li R. 2021. The female vaginal microbiome in health and bacterial vaginosis. Front Cell Infect Microbiol 11 :631972. doi:10.3389/fcimb.2021.631972 33898328
35 . Ravel, J. et al. . Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci U S A 108 Suppl 1 , 4680–4687 (2011).20534435
36 Valenti P, Rosa L, Capobianco D, Lepanto MS, Schiavi E, Cutone A, Paesano R, Mastromarino P. 2018. Role of lactobacilli and lactoferrin in the mucosal cervicovaginal defense. Front Immunol 9 :376. doi:10.3389/fimmu.2018.00376 29545798
37 Kyrgiou M, Mitra A, Moscicki A-B. 2017. Does the vaginal microbiota play a role in the development of cervical cancer? Transl Res 179 :168–182. doi:10.1016/j.trsl.2016.07.004 27477083
38 Shi W, Zhu H, Yuan L, Chen X, Huang X, Wang K, Li Z. 2022. Vaginal microbiota and HPV clearance: a longitudinal study. Front Oncol 12 :955150. doi:10.3389/fonc.2022.955150 36353544
39 Cheng L, Norenhag J, Hu YOO, Brusselaers N, Fransson E, Ährlund-Richter A, Guðnadóttir U, Angelidou P, Zha Y, Hamsten M, Schuppe-Koistinen I, Olovsson M, Engstrand L, Du J. 2020. Vaginal microbiota and human papillomavirus infection among young Swedish women. NPJ Biofilms Microbiomes 6 :39. doi:10.1038/s41522-020-00146-8 33046723
40 Zhang Y, Xu X, Yu L, Shi X, Min M, Xiong L, Pan J, Zhang Y, Liu P, Wu G, Gao G. 2022. Vaginal microbiota changes caused by HPV infection in Chinese women. Front Cell Infect Microbiol 12 :814668. doi:10.3389/fcimb.2022.814668 35800384
41 Santella B, Schettino MT, Franci G, De Franciscis P, Colacurci N, Schiattarella A, Galdiero M. 2022. Microbiota and HPV: the role of viral infection on vaginal microbiota. J Med Virol 94 :4478–4484. doi:10.1002/jmv.27837 35527233
42 Wang K-D, Xu D-J, Wang B-Y, Yan D-H, Lv Z, Su J-R. 2018. Inhibitory effect of vaginal Lactobacillus supernatants on cervical cancer cells. Probiotics Antimicrob Proteins 10 :236–242. doi:10.1007/s12602-017-9339-x 29071554
43 Delgado-Diaz DJ, Tyssen D, Hayward JA, Gugasyan R, Hearps AC, Tachedjian G. 2019. Distinct immune responses elicited from cervicovaginal epithelial cells by lactic acid and short chain fatty acids associated with optimal and non-optimal vaginal microbiota. Front Cell Infect Microbiol 9 :446. doi:10.3389/fcimb.2019.00446 31998660
44 Al-Mushrif S, Eley A, Jones BM. 2000. Inhibition of chemotaxis by organic acids from anaerobes may prevent a purulent response in bacterial vaginosis. J Med Microbiol 49 :1023–1030. doi:10.1099/0022-1317-49-11-1023 11073156
45 Chaudry AN, Travers PJ, Yuenger J, Colletta L, Evans P, Zenilman JM, Tummon A. 2004. Analysis of vaginal acetic acid in patients undergoing treatment for bacterial vaginosis. J Clin Microbiol 42 :5170–5175. doi:10.1128/JCM.42.11.5170-5175.2004 15528711
46 Wen Y, Yang L, Wang Z, Liu X, Gao M, Zhang Y, Wang J, He P. 2023. Blocked conversion of Lactobacillus johnsonii derived acetate to butyrate mediates copper-induced epithelial barrier damage in a pig model. Microbiome 11 :218. doi:10.1186/s40168-023-01655-2 37777765
47 Terao Y, Nishida J, Horiuchi S, Rong F, Ueoka Y, Matsuda T, Kato H, Furugen Y, Yoshida K, Kato K, Wake N. 2001. Sodium butyrate induces growth arrest and senescence-like phenotypes in gynecologic cancer cells. Int J Cancer 94 :257–267. doi:10.1002/ijc.1448 11668507
48 Park JK, Cho CH, Ramachandran S, Shin SJ, Kwon SH, Kwon SY, Cha SD. 2006. Augmentation of sodium butyrate-induced apoptosis by phosphatidylinositol 3-kinase inhibition in the human cervical cancer cell-line. Cancer Res Treat 38 :112–117. doi:10.4143/crt.2006.38.2.112 19771269
49 Amabebe E, Anumba DOC. 2020. Female gut and genital tract microbiota-induced crosstalk and differential effects of short-chain fatty acids on immune sequelae. Front Immunol 11 :2184. doi:10.3389/fimmu.2020.02184 33013918
50 Zheng N, Guo R, Wang J, Zhou W, Ling Z. 2021. Contribution of Lactobacillus iners to vaginal health and diseases: a systematic review. Front Cell Infect Microbiol 11 :792787. doi:10.3389/fcimb.2021.792787 34881196
51 Bloom SM, Mafunda NA, Woolston BM, Hayward MR, Frempong JF, Abai AB, Xu J, Mitchell AJ, Westergaard X, Hussain FA, Xulu N, Dong M, Dong KL, Gumbi T, Ceasar FX, Rice JK, Choksi N, Ismail N, Ndung’u T, Ghebremichael MS, Relman DA, Balskus EP, Mitchell CM, Kwon DS. 2022. Cysteine dependence of Lactobacillus iners is a potential therapeutic target for vaginal microbiota modulation. Nat Microbiol 7 :434–450. doi:10.1038/s41564-022-01070-7 35241796
