Deciphering maternal-fetal cross-talk in the human placenta during parturition using single-cell RNA sequencing

Abstract

Labor is a complex physiological process requiring a well-orchestrated dialogue between the mother and fetus. However, the cellular contributions and communications that facilitate maternal-fetal cross-talk in labor have not been fully elucidated. Here, single-cell RNA sequencing (scRNA-seq) was applied to decipher maternal-fetal signaling in the human placenta during term labor. First, a single-cell atlas of the human placenta was established, demonstrating that maternal and fetal cell types underwent changes in transcriptomic activity during labor. Cell types most affected by labor were fetal stromal and maternal decidual cells in the chorioamniotic membranes (CAMs) and maternal and fetal myeloid cells in the placenta. Cell-cell interaction analyses showed that CAM and placental cell types participated in labor-driven maternal and fetal signaling, including the collagen, C-X-C motif ligand (CXCL), tumor necrosis factor (TNF), galectin, and interleukin-6 (IL-6) pathways. Integration of scRNA-seq data with publicly available bulk transcriptomic data showed that placenta-derived scRNA-seq signatures could be monitored in the maternal circulation throughout gestation and in labor. Moreover, comparative analysis revealed that placenta-derived signatures in term labor were mirrored by those in spontaneous preterm labor and birth. Furthermore, we demonstrated that early in gestation, labor-specific, placenta-derived signatures could be detected in the circulation of women destined to undergo spontaneous preterm birth, with either intact or prelabor ruptured membranes. Collectively, our findings provide insight into the maternal-fetal cross-talk of human parturition and suggest that placenta-derived single-cell signatures can aid in the development of noninvasive biomarkers for the prediction of preterm birth.

Homeostatic macrophages prevent preterm birth and improve neonatal outcomes by mitigatingin uterosterile inflammation

“…However, we sought to test our hypothesis using an unbiased discovery approach. To do this, we leveraged our previously generated single-cell atlases of the myometrium and maternal-fetal interface 44–46 . The maternal-fetal interface includes key sites of contact between maternal and fetal tissues: the fetal placenta embedded in the maternal decidua basalis adjacent to the myometrium, and the fetal extraplacental membranes enclosing the amniotic cavity and attached to the maternal decidua parietalis, next to the myometrium (Figure 1A).…”

“…The maternal-fetal interface includes key sites of contact between maternal and fetal tissues: the fetal placenta embedded in the maternal decidua basalis adjacent to the myometrium, and the fetal extraplacental membranes enclosing the amniotic cavity and attached to the maternal decidua parietalis, next to the myometrium (Figure 1A). Our myometrial single-cell atlas includes samples collected from women with term labor as well as term non-labor controls 45 , whereas our single-cell atlases of the placenta and extraplacental membranes also include samples from women with preterm labor in addition to the term groups 44,46 . Given that preterm non-labor deliveries are only performed due to pregnancy complications, such cases are not suited for use as gestational age controls for preterm labor and thus historically have not been utilized in our studies.…”

“…Data from three of our previously generated human scRNA-seq datasets 44–46 were combined and re-analyzed to specifically investigate macrophage populations at the maternal-fetal interface. All datasets were pre-processed and normalized with a comparable pipeline.…”

“…Furthermore, any cells with less than 100 or more than 10,000 genes were filtered out, as well as those with > 25% mitochondrial reads. Cells annotated as macrophages (details regarding the annotation process can be found in the original publications 44–46 ) were extracted and combined into a new Seurat object.…”

“…Single-cell RNA-sequencing data were previously reported 44–46 and are deposited in the NIH dbGAP database (phs001886.v5.p1). 16S rRNA gene sequencing files and associated metadata have been uploaded to the National Center for Biotechnology Information’s Sequence Read Archive (PRJNA925285).…”