Protocol for a Longitudinal Analysis of the Vaginal Microbiome from a Pregnant Cohort of African Women in Nigeria

Abstract

Background:

The vaginal microbiota is an important component of the reproductive health of women as it offers protection against urogenital infection. African women are reported to have a vaginal microbiota colonized with high proportions of strict anaerobes rather than lactobacillus- dominated microbes. These strict anaerobes have been associated with pre-term birth and neonatal disease. The prevalence of pre-term birth (PTB) in Africa poses a major challenge to reproductive healthcare, hence the clinical and scientific attention focused on understanding the causative mechanisms of PTB. A pragmatic approach to curbing PTB requires the identification of the vaginal microbiome during various stages of a healthy pregnancy (the ‘normal’). This information will provide baseline data for future investigations of vaginal microbiome that may cause PTB (the ‘abnormal’). We present a protocol for the longitudinal analysis of vaginal microbiome in a cohort of pregnant women in Southwest Nigeria.

Methods:

We propose to recruit 51 pregnant Nigerian women, enrolling them into the study at 17-21 gestational weeks. Two vaginal swab samples and three milliliters of blood would be collected at enrollment. Sample collection will be repeated at 27-31 weeks’ gestation, ≥36 weeks’ gestation, 24-48 hours after birth and 6 weeks post-partum. DNA will be extracted from the vaginal samples and 16S rRNA sequencing would be performed. Blood samples collected would be assayed by ELISA technique for placental steroid hormones. Data will be statistically analyzed and considered in the light of vaginal microbial diversity, clinical, nutrition and other health data.

Conclusion and Global Health Implication:

Our data set will bring new insights into the vaginal microbiome of apparently healthy African women in pregnancy and postpartum, which should serve as a baseline for the investigation of vaginal microbes that may provide useful information for the prediction and management of preterm birth. It is anticipated that these data will facilitate future personalized therapeutic management and consequently improve the reproductive health fitness of women in Africa.