Deciphering maternal-fetal cross-talk in the human placenta during parturition using single-cell RNA sequencing.
Valeria Garcia-FloresRoberto RomeroAdi Laurentiu TarcaAzam PeyvandipourYi XuJose GalazDerek MillerTinnakorn ChaiworapongsaPiya ChaemsaithongStanley M BerryAwoniyi O AwonugaDavid R BryantRoger Pique-RegiNardhy Gomez-LopezPublished in: Science translational medicine (2024)
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.
Keyphrases
- single cell
- birth weight
- gestational age
- rna seq
- preterm birth
- pregnancy outcomes
- high throughput
- endothelial cells
- preterm infants
- low birth weight
- genome wide
- induced pluripotent stem cells
- induced apoptosis
- weight gain
- electronic health record
- machine learning
- metabolic syndrome
- dna methylation
- stem cells
- body mass index
- acute myeloid leukemia
- mesenchymal stem cells
- signaling pathway
- polycystic ovary syndrome
- data analysis
- abdominal aortic aneurysm
- deep learning
- weight loss