Dataset Information

Leveraging 16S rRNA data to uncover vaginal microbial signatures in women with cervical cancer.

ABSTRACT: Microbiota-relevant signatures have been investigated for human papillomavirus-related cervical cancer (CC), but lack consistency because of study- and methodology-derived heterogeneities. Here, four publicly available 16S rRNA datasets including 171 vaginal samples (51 CC versus 120 healthy controls) were analyzed to characterize reproducible CC-associated microbial signatures. We employed a recently published clustering approach called VAginaL community state typE Nearest CentroId clAssifier to assign the metadata to 13 community state types (CSTs) in our study. Nine subCSTs were identified. A random forest model (RFM) classifier was constructed to identify 33 optimal genus-based and 94 species-based signatures. Confounder analysis revealed confounding effects on both study- and hypervariable region-associated aspects. After adjusting for confounders, multivariate analysis identified 14 significantly changed taxa in CC versus the controls (P < 0.05). Furthermore, predicted functional analysis revealed significantly upregulated pathways relevant to the altered vaginal microbiota in CC. Cofactor, carrier, and vitamin biosynthesis were significantly enriched in CC, followed by fatty acid and lipid biosynthesis, and fermentation of short-chain fatty acids. Genus-based contributors to the differential functional abundances were also displayed. Overall, this integrative study identified reproducible and generalizable signatures in CC, suggesting the causal role of specific taxa in CC pathogenesis.

SUBMITTER: Wu M

PROVIDER: S-EPMC9892946 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Leveraging 16S rRNA data to uncover vaginal microbial signatures in women with cervical cancer.

Wu Ming M Yu Hongfei H Gao Yueqian Y Li Huanrong H Wang Chen C Li Huiyang H Ma Xiaotong X Dong Mengting M Li Bijun B Bai Junyi J Dong Yalan Y Fan Xiangqin X Zhang Jintian J Yan Ye Y Qi Wenhui W Han Cha C Fan Aiping A Xue Fengxia F

Frontiers in cellular and infection microbiology 20230119

Microbiota-relevant signatures have been investigated for human papillomavirus-related cervical cancer (CC), but lack consistency because of study- and methodology-derived heterogeneities. Here, four publicly available 16S rRNA datasets including 171 vaginal samples (51 CC versus 120 healthy controls) were analyzed to characterize reproducible CC-associated microbial signatures. We employed a recently published clustering approach called VAginaL community state typE Nearest CentroId clAssifier t ...[more]

PMID: 36743303

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Project description:BackgroundThe incidence of preterm birth (PTB) in India is around 13%. Specific bacterial communities or individual taxon living in the vaginal milieu of pregnant women is a potential risk factor for PTB and may play an important role in its pathophysiology. Besides, bacterial taxa associated with PTB vary across populations.ObjectiveConduct a comparative analysis of vaginal microbiome composition and microbial genomic repertoires of women who enrolled in the Interdisciplinary Group for Advanced Research on Birth Outcomes - A DBT India Initiative (GARBH-Ini) pregnancy cohort to identify bacterial taxa associated with term birth (TB) and PTB in Indian women.MethodsVaginal swabs were collected during all three trimesters from 38 pregnant Indian women who delivered spontaneous term (n=20) and preterm (n=18) neonates. Paired-end sequencing of V3-V4 region of 16S rRNA gene was performed using the metagenomic DNA isolated from vaginal swabs (n=115). Whole genome sequencing of bacterial species associated with birth outcomes was carried out by shotgun method. Lactobacillus species were grown anaerobically in the De Man, Rogosa and Sharpe (MRS) agar culture medium for isolation of genomic DNA and whole genome sequencing.ResultsVaginal microbiome of both term and preterm samples reveals similar alpha diversity indices. However, significantly higher abundance of Lactobacillus iners (p-value All_Trimesters<0.02), Megasphaera sp (p-value1st_Trimester <0.05), Gardnerella vaginalis (p-value2nd_Trimester= 0.01) and Sneathia sanguinegens (p-value2nd_Trimester <0.0001) were identified in preterm samples whereas higher abundance of L. gasseri (p-value3rd_Trimester =0.010) was observed in term samples by Wilcoxon rank-sum test. The relative abundance of L. iners, and Megasphaera sp. were found to be significantly different over time between term and preterm mothers. Analyses of the representative genomes of L. crispatus and L. gasseri indicate presence of secretory transcriptional regulator and several ribosomally synthesized antimicrobial peptides correlated with anti-inflammatory condition in the vagina. These findings indicate protective role of L. crispatus and L. gasseri in reducing the risk of PTB.ConclusionOur findings indicate that the dominance of specific Lactobacillus species and few other facultative anaerobes are associated with birth outcomes.

Project description:BackgroundMolecular methods such as next-generation sequencing are actively being employed to characterize the vaginal microbiota in health and disease. Previous studies have focused on characterizing the biological variation in the microbiota, and less is known about how factors related to sampling contribute to the results. Our aim was to investigate the impact of a sampling device and anatomical sampling site on the quantitative and qualitative outcomes relevant for vaginal microbiota research. We sampled 10 Finnish women representing diverse clinical characteristics with flocked swabs, the Evalyn® self-sampling device, sterile plastic spatulas and a cervical brush that were used to collect samples from fornix, vaginal wall and cervix. Samples were compared on DNA and protein yield, bacterial load, and microbiota diversity and species composition based on Illumina MiSeq sequencing of the 16S rRNA gene. We quantified the relative contributions of sampling variables versus intrinsic variables in the overall microbiota variation, and evaluated the microbiota profiles using several commonly employed metrics such as alpha and beta diversity as well as abundance of major bacterial genera and species.ResultsThe total DNA yield was strongly dependent on the sampling device and to a lesser extent on the anatomical site of sampling. The sampling strategy did not affect the protein yield or the bacterial load. All tested sampling methods produced highly comparable microbiota profiles based on MiSeq sequencing. The sampling method explained only 2% (p-value = 0.89) of the overall microbiota variation, markedly surpassed by intrinsic factors such as clinical status (microscopy for bacterial vaginosis 53%, p = 0.0001), bleeding (19%, p = 0.0001), and the variation between subjects (11%, p-value 0.0001).ConclusionsThe results indicate that different sampling strategies yield comparable vaginal microbiota composition and diversity. Hence, past and future vaginal microbiota studies employing different sampling strategies should be comparable in the absence of other technical confounders. The Evalyn® self-sampling device performed equally well compared to samples taken by a clinician, and hence offers a good-quality microbiota sample without the need for a gynecological examination. The amount of collected sample as well as the DNA and protein yield varied across the sampling techniques, which may have practical implications for study design.

Dataset Information

Leveraging 16S rRNA data to uncover vaginal microbial signatures in women with cervical cancer.

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Leveraging 16S rRNA data to uncover vaginal microbial signatures in women with cervical cancer.

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