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The vaginal microbiome during pregnancy and the postpartum period in a European population

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TLDR
It is shown that vaginal microbiome composition dramatically changes postpartum to become less Lactobacillus spp.
Abstract
The composition and structure of the pregnancy vaginal microbiome may influence susceptibility to adverse pregnancy outcomes. Studies on the pregnant vaginal microbiome have largely been limited to Northern American populations. Using MiSeq sequencing of 16S rRNA gene amplicons, we characterised the vaginal microbiota of a mixed British cohort of women (n = 42) who experienced uncomplicated term delivery and who were sampled longitudinally throughout pregnancy (8–12, 20–22, 28–30 and 34–36 weeks gestation) and 6 weeks postpartum. We show that vaginal microbiome composition dramatically changes postpartum to become less Lactobacillus spp. dominant with increased alpha-diversity irrespective of the community structure during pregnancy and independent of ethnicity. While the pregnancy vaginal microbiome was characteristically dominated by Lactobacillus spp. and low alpha-diversity, unlike Northern American populations, a significant number of pregnant women this British population had a L. jensenii-dominated microbiome characterised by low alpha-diversity. L. jensenii was predominantly observed in women of Asian and Caucasian ethnicity whereas L. gasseri was absent in samples from Black women. This study reveals new insights into biogeographical and ethnic effects upon the pregnancy and postpartum vaginal microbiome and has important implications for future studies exploring relationships between the vaginal microbiome, host health and pregnancy outcomes.

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Journal ArticleDOI

DADA2: High-resolution sample inference from Illumina amplicon data

TL;DR: The open-source software package DADA2 for modeling and correcting Illumina-sequenced amplicon errors is presented, revealing a diversity of previously undetected Lactobacillus crispatus variants.
Posted ContentDOI

UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing

Robert C. Edgar
- 15 Oct 2016 - 
TL;DR: UNOISE2 is described, an updated version of the UNOISE algorithm for denoising (error-correcting) Illumina amplicon reads and it is shown that it has comparable or better accuracy than DADA2.
Journal ArticleDOI

The Central Nervous System and the Gut Microbiome

TL;DR: The biological intersection of neurodevelopment and the microbiome is discussed and the hypothesis that gut bacteria are integral contributors to development and function of the nervous system and the balance between mental health and disease is explored.
Journal ArticleDOI

The microbiome in early life: implications for health outcomes

TL;DR: How prenatal and postnatal factors shape the development of both the microbiome and the immune system are described and the prospects of microbiome-mediated therapeutics and the need for more effective approaches that can reconfigure bacterial communities from pathogenic to homeostatic configurations are discussed.
References
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Journal Article

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R Core Team
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Journal ArticleDOI

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Journal ArticleDOI

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Robert C. Edgar
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Journal ArticleDOI

Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

TL;DR: The RDP Classifier can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes, and the majority of the classification errors appear to be due to anomalies in the current taxonomies.

16S/23S rRNA sequencing

D. J. Lane
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