Dataset Information

Changes in vaginal community state types reflect major shifts in the microbiome.

ABSTRACT: Background: Recent studies of various human microbiome habitats have revealed thousands of bacterial species and the existence of large variation in communities of microorganisms in the same habitats across individual human subjects. Previous efforts to summarize this diversity, notably in the human gut and vagina, have categorized microbiome profiles by clustering them into community state types (CSTs). The functional relevance of specific CSTs has not been established. Objective: We investigate whether CSTs can be used to assess dynamics in the microbiome. Design: We conduct a re-analysis of five sequencing-based microbiome surveys derived from vaginal samples with repeated measures. Results: We observe that detection of a CST transition is largely insensitive to choices in methods for normalization or clustering. We find that healthy subjects persist in a CST for two to three weeks or more on average, while those with evidence of dysbiosis tend to change more often. Changes in CST can be gradual or occur over less than one day. Upcoming CST changes and switches to high-risk CSTs can be predicted with high accuracy in certain scenarios. Finally, we observe that presence of Gardnerella vaginalis is a strong predictor of an upcoming CST change. Conclusion: Overall, our results show that the CST concept is useful for studying microbiome dynamics.

SUBMITTER: Brooks JP

PROVIDER: S-EPMC5443090 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Changes in vaginal community state types reflect major shifts in the microbiome.

Brooks J Paul JP Buck Gregory A GA Chen Guanhua G Diao Liyang L Edwards David J DJ Fettweis Jennifer M JM Huzurbazar Snehalata S Rakitin Alexander A Satten Glen A GA Smirnova Ekaterina E Waks Zeev Z Wright Michelle L ML Yanover Chen C Zhou Yi-Hui YH

Microbial ecology in health and disease 20170410 1

<b>Background</b>: Recent studies of various human microbiome habitats have revealed thousands of bacterial species and the existence of large variation in communities of microorganisms in the same habitats across individual human subjects. Previous efforts to summarize this diversity, notably in the human gut and vagina, have categorized microbiome profiles by clustering them into community state types (CSTs). The functional relevance of specific CSTs has not been established. <b>Objective</b>: ...[more]

PMID: 28572753

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Project description:Abnormal vaginal microbiota (AVM), including bacterial vaginosis (BV), is caused by a microbiota imbalance. Nugent scoring is the gold standard for the laboratory diagnosis of BV; however, it is somewhat subjective to interpret, and challenging to distinguish bacteria. Hence, there is a need for improved technologies for the accurate diagnosis of AVM. To this end, next-generation sequencing (NGS) technology has been shown to yield comprehensive information on the pathophysiology of AVM. Hence, to evaluate the relationship between microbiota composition and the pathophysiology of AVM and its clinical significance, we characterized vaginal swab samples from 212 pregnant Korean women using both Nugent scoring and NGS analysis. Of these, the Nugent scoring identified 175 subjects (82.5%; 175/212) with normal flora (NF), 20 (9.4%; 20/212) with intermediate flora (IF), and 17 (8.0%; 17/212) with BV. NGS analysis followed by the characterization of vaginal microbiota composition, as represented by alpha and beta diversity, revealed the relative abundance of specific bacterial taxa at the genus and species level. Moreover, we identified all five predominant community state types (CSTs) along with three smaller CSTs. Analysis of the vaginal microbiota revealed the dominance of one or two Lactobacillus spp. in the NF group. Meanwhile, the IF and BV groups were dominated by the genera Gardnerella, Prevotella, and Atopobium. These two groups also showed higher alpha diversity than the NF group (p < 0.05). Principal coordinate analysis (PCoA) indicated that the NF group was significantly different from the AVM groups (p < 0.05), whereas no significant difference was observed between IF and BV groups (p = 0.25). Lastly, to investigate the characteristics of vaginal microbiota based on taxonomic composition, the IF and BV groups (AVM groups) were reclassified using the unweighted pair group method with arithmetic mean (UPGMA) clustering. Consequently, they were reclassified into BV1 (Lactobacillus iners-dominated), BV2-1 (Bifidobacterium breve-dominated), BV2-2 (Gardnerella vaginalis s1 or s2 and Atopobium vaginae-dominated), and BV3 [mixed population of G. vaginalis, L. iners, and other bacteria (p < 0.05)]. Collectively, these findings could serve to advance the current understanding regarding AVM pathophysiology.

Project description:Polycystic ovary syndrome (PCOS) is a complex endocrine disorder that affects women. It can be accompanied by many clinical manifestations that can vary between individuals. Previous studies have found that there are specific changes in the intestinal flora of PCOS patients, and interventions to modify the intestinal flora can significantly improve the symptoms of PCOS. Women with PCOS have a higher incidence of vaginitis compared to healthy women. Few studies to-date have focused on investigating vaginal flora. Here, we aimed to explore distribution changes of the vaginal microbiome in PCOS patients. We recruited 42 PCOS patients (T-PCOS) and 24 healthy controls (T-control). 16s rRNA gene sequencing was used to sequence their vaginal microbiome. Normally, Lactobacillus was dominated in vaginal. Lactobacillus-dominated-type vaginal microbiome in T-PCOS and T-control (L-PCOS and L-control) and non-Lactobacillus-dominated-type vaginal microbiome in T-PCOS and T-control (N-PCOS and N-control) were analyzed separately. A total of 655 operational taxonomic units were detected in this sequencing, including 306 unique to T-PCOS, 202 unique to T-control, and 147 common between the two groups. At the genus level, Lactobacillus accounted for more than 70% of the total microbiome. Observed species (P = 0.021), Chao1 index (P = 0.020), and ACE index (P = 0.023) decreased significantly in L-PCOS. Principal component analysis showed no statistically significant differences among the subgroups. There were significant statistical differences in principal coordinate analysis in the Jaccard distance between the T-PCOS and T-control groups and between the L-PCOS and L-control groups. Linear discriminant analysis effect size found that Enterococcus and Actinomycetes were significantly different in the T-PCOS group. Atopobium and Actinomyces were statistically significantly different in patients with L-PCOS and N-PCOS group, respectively. Environmental factor analysis found that Ezakiella was significantly negatively correlated with age, while Streptococcus was significantly negatively correlated with follicle stimulating hormone. There were statistically significant differences between PCOS patients and healthy women in the vaginal microbiome, regardless of the abundance of Lactobacillus. Alpha diversity of vaginal microbiome decreased markedly in PCOS patients when it was dominated by Lactobacillus spp. Actinomyces could be a potential biomarker to identify PCOS. Streptococcus may have an impact on the pathological changes in PCOS by affecting the female reproductive endocrine environment.

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Changes in vaginal community state types reflect major shifts in the microbiome.

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Changes in vaginal community state types reflect major shifts in the microbiome.

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