Neutrophils Dominate the Cervical Immune Cell Population in Pregnancy and Their Transcriptome Correlates With the Microbial Vaginal Environment

The cervicovaginal environment in pregnancy is proposed to influence risk of spontaneous preterm birth. The environment is shaped both by the resident microbiota and local inflammation driven by the host response (epithelia, immune cells and mucous). The contributions of the microbiota, metabolome and host defence peptides have been investigated, but less is known about the immune cell populations and how they may respond to the vaginal environment. Here we investigated the maternal immune cell populations at the cervicovaginal interface in early to mid-pregnancy (10–24 weeks of gestation, samples from N = 46 women), we confirmed neutrophils as the predominant cell type and characterised associations between the cervical neutrophil transcriptome and the cervicovaginal metagenome (N = 9 women). In this exploratory study, the neutrophil cell proportion was affected by gestation at sampling but not by birth outcome or ethnicity. Following RNA sequencing (RNA-seq) of a subset of neutrophil enriched cells, principal component analysis of the transcriptome profiles indicated that cells from seven women clustered closely together these women had a less diverse cervicovaginal microbiota than the remaining three women. Expression of genes involved in neutrophil mediated immunity, activation, degranulation, and other immune functions correlated negatively with Gardnerella vaginalis abundance and positively with Lactobacillus iners abundance; microbes previously associated with birth outcome. The finding that neutrophils are the dominant immune cell type in the cervix during pregnancy and that the cervical neutrophil transcriptome of pregnant women may be modified in response to the microbial cervicovaginal environment, or vice versa, establishes the rationale for investigating associations between the innate immune response, cervical shortening and spontaneous preterm birth and the underlying mechanisms.