Community State Types of Vaginal Microbiota and Four Types of Abnormal Vaginal Microbiota in Pregnant Korean Women

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 imp...

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Published inFrontiers in public health Vol. 8; p. 507024
Main Authors Lee, Sunghee, Oh, Kwan Young, Hong, Heeji, Jin, Chan Hee, Shim, Eunjung, Kim, Seung Hyun, Kim, Byung-Yong
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 22.10.2020
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ISSN2296-2565
2296-2565
DOI10.3389/fpubh.2020.507024

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Abstract 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 spp. in the NF group. Meanwhile, the IF and BV groups were dominated by the genera , and . These two groups also showed higher alpha diversity than the NF group ( < 0.05). Principal coordinate analysis (PCoA) indicated that the NF group was significantly different from the AVM groups ( < 0.05), whereas no significant difference was observed between IF and BV groups ( = 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 -dominated), BV2-1 ( -dominated), BV2-2 ( s1 or s2 and -dominated), and BV3 [mixed population of , and other bacteria ( < 0.05)]. Collectively, these findings could serve to advance the current understanding regarding AVM pathophysiology.
AbstractList 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 spp. in the NF group. Meanwhile, the IF and BV groups were dominated by the genera , and . These two groups also showed higher alpha diversity than the NF group ( < 0.05). Principal coordinate analysis (PCoA) indicated that the NF group was significantly different from the AVM groups ( < 0.05), whereas no significant difference was observed between IF and BV groups ( = 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 -dominated), BV2-1 ( -dominated), BV2-2 ( s1 or s2 and -dominated), and BV3 [mixed population of , and other bacteria ( < 0.05)]. Collectively, these findings could serve to advance the current understanding regarding AVM pathophysiology.
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.
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.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.
Author Shim, Eunjung
Jin, Chan Hee
Kim, Seung Hyun
Kim, Byung-Yong
Lee, Sunghee
Oh, Kwan Young
Hong, Heeji
AuthorAffiliation 1 Research Laboratories, ILDONG Pharmaceutical Co., Ltd. , Hwaseong-si , South Korea
3 Microbiome Research Center, ChunLab, Inc. , Seocho-gu , South Korea
2 Department of Obstetrics and Gynecology, School of Medicine, Eulji University , Daejeon , South Korea
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Keywords Gardnerella vaginalis
pregnant Korean women
bacterial vaginosis
next-generation sequencing
Lactobacillus spp
abnormal vaginal flora
Bifidobacterium breve
intermediate flora
Language English
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Snippet Abnormal vaginal microbiota (AVM), including bacterial vaginosis (BV), is caused by a microbiota imbalance. Nugent scoring is the gold standard for the...
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SubjectTerms abnormal vaginal flora
Actinobacteria
bacterial vaginosis
Female
Humans
intermediate flora
Lactobacillus
Lactobacillus spp
Microbiota - genetics
next-generation sequencing
Pregnancy
pregnant Korean women
Public Health
Republic of Korea - epidemiology
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Title Community State Types of Vaginal Microbiota and Four Types of Abnormal Vaginal Microbiota in Pregnant Korean Women
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