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This project compares the human vaginal microbiota of mothers and their adolescent daughters.
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README.md

README.md

Mother Daughter Vaginal Microbiota study

Repository Description

This repository contains details in support of the submitted manuscript entitled, "Evidence that vertical transmission of the vaginal microbiota can persist into adolescence" by Christine M. Bassis, Kaylie A. Bullock, Daniel E. Sack, Katie Saund, Ali Pirani, Evan S. Snitkin, Veronica I. Alaniz, Elisabeth H. Quint, Vincent B. Young and Jason D. Bell.

This repository includes:

  • the mothur batch file with steps used to process and analyze 16S rRNA gene sequences

  • mothur output files used in final bacterial community analysis and figures

  • R code for manuscript figures, statistics and genomic analysis

Manuscript Abstract

Background: Factors that influence vaginal microbiota composition, including its source, are not well understood. To determine if vaginal microbiota transmission from mother to daughter at birth influences the human vaginal microbiota composition in adolescence, we investigated the relationship between the vaginal microbiota of 13 mother/daughter pairs and the daughter’s birth mode.

Results: Based on analysis of bacterial 16S rRNA gene sequences, the vaginal microbiotas of mother/daughter pairs were more similar to each other if the daughter was born by vaginal delivery rather than by C-section. Additionally, genome sequences from an important member of the vaginal microbiota, Lactobacillus crispatus, isolated from one mother/daughter pair in which the daughter was born by vaginal delivery, were highly similar.

Conclusions: Both community-level analysis and isolate genome sequence analysis provide evidence of birth-mode dependent transmission and persistence of at least some members of the vaginal microbiota.

Raw sequence data

Bacterial 16S rRNA gene sequences: NCBI BioProject PRJNA547595

Lactobacillus crispatus genome sequences: NCBI BioProject PRJNA547620

Contributors

Christine M. Bassis (cbassis@umich.edu), Kaylie A. Bullock and Katie Saund contributed to this code. Please email cbassis@umich.edu with questions.

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