Vaginal Microbiota in Pregnancy: Evaluation Based on Vaginal Flora, Birth Outcome, and Race
Objective This study aims to evaluate vaginal microbiota differences by bacterial vaginosis (BV), birth timing, and race, and to estimate parameters to power future vaginal microbiome studies. Methods Previously, vaginal swabs were collected at 21 to 25 weeks (stored at -80°C), and vaginal smears evaluated for BV (Nugent criteria). In a blinded fashion, 40 samples were selected, creating 8 equal-sized groups stratified by race (black/white), BV (present/absent), and birth timing (preterm/term). Samples were thawed, DNA extracted, and prepared. Polymerase chain reaction (PCR) with primers targeting the 16S rDNA V4 region was used to prepare an amplicon library. PCR products were sequenced and analyzed using quantitative insight into microbial ecology; taxonomy was assigned using ribosomal database program classifier (threshold 0.8) against the modified Greengenes database. Results After quality control, 97,720 sequences (mean) per sample, single-end 250 base-reads, were analyzed. BV samples had greater microbiota diversity (p < 0.05)-with BVAB1, Prevotella, and unclassified genus, Bifidobacteriaceae family (all p < 0.001) more abundant; there was minimal content of Gardnerella or Mobiluncus. Microbiota did not differ by race or birth timing, but there was an association between certain microbial clusters and preterm birth (p = 0.07). To evaluate this difference, 159 patients per group are needed. Conclusions There are differences in the vaginal microbiota between patients with and without BV. Larger studies should assess the relationship between microbiota composition and preterm birth..
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2016 |
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| Erschienen: |
2016 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:33 |
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| Enthalten in: |
American journal of perinatology - 33(2016), 4, Seite 401 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Subramaniam, Akila [VerfasserIn] |
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| Links: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
OLC1973345781 |
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| 520 | |a Objective This study aims to evaluate vaginal microbiota differences by bacterial vaginosis (BV), birth timing, and race, and to estimate parameters to power future vaginal microbiome studies. Methods Previously, vaginal swabs were collected at 21 to 25 weeks (stored at -80°C), and vaginal smears evaluated for BV (Nugent criteria). In a blinded fashion, 40 samples were selected, creating 8 equal-sized groups stratified by race (black/white), BV (present/absent), and birth timing (preterm/term). Samples were thawed, DNA extracted, and prepared. Polymerase chain reaction (PCR) with primers targeting the 16S rDNA V4 region was used to prepare an amplicon library. PCR products were sequenced and analyzed using quantitative insight into microbial ecology; taxonomy was assigned using ribosomal database program classifier (threshold 0.8) against the modified Greengenes database. Results After quality control, 97,720 sequences (mean) per sample, single-end 250 base-reads, were analyzed. BV samples had greater microbiota diversity (p < 0.05)-with BVAB1, Prevotella, and unclassified genus, Bifidobacteriaceae family (all p < 0.001) more abundant; there was minimal content of Gardnerella or Mobiluncus. Microbiota did not differ by race or birth timing, but there was an association between certain microbial clusters and preterm birth (p = 0.07). To evaluate this difference, 159 patients per group are needed. Conclusions There are differences in the vaginal microbiota between patients with and without BV. Larger studies should assess the relationship between microbiota composition and preterm birth. | ||
| 540 | |a Nutzungsrecht: © Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA. | ||
| 700 | 1 | |a Kumar, Ranjit |4 oth | |
| 700 | 1 | |a Cliver, Suzanne P |4 oth | |
| 700 | 1 | |a Zhi, Degui |4 oth | |
| 700 | 1 | |a Szychowski, Jeff M |4 oth | |
| 700 | 1 | |a Abramovici, Adi |4 oth | |
| 700 | 1 | |a Biggio, Joseph R |4 oth | |
| 700 | 1 | |a Lefkowitz, Elliot J |4 oth | |
| 700 | 1 | |a Morrow, Casey |4 oth | |
| 700 | 1 | |a Edwards, Rodney K |4 oth | |
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| 856 | 4 | 2 | |u http://www.ncbi.nlm.nih.gov/pubmed/26479170 |
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