RNA profiling of laser microdissected human trophoblast subtypes at mid-gestation reveals a role for cannabinoid signaling in invasion.
Matthew J GormleyOliver OliverioMirhan KapidzicKatherine OnaSteven C HallSusan J FisherPublished in: Development (Cambridge, England) (2021)
Human placental architecture is complex. Its surface epithelium, specialized for transport, forms by fusion of cytotrophoblast progenitors into multinucleated syncytiotrophoblasts. Near the uterine surface, these progenitors assume a different fate, becoming cancer-like cells that invade its lining and blood vessels. The latter process physically connects the placenta to the mother and shunts uterine blood to the syncytiotrophoblasts. Isolation of trophoblast subtypes is technically challenging. Upon removal, syncytiotrophoblasts disintegrate and invasive cytotrophoblasts are admixed with uterine cells. We used laser capture to circumvent these obstacles. This enabled isolation of syncytiotrophoblasts and two subpopulations of invasive cytotrophoblasts from cell columns and the endovascular compartment of spiral arteries. Transcriptional profiling revealed numerous genes, the placental or trophoblast expression of which was not known, including neurotensin and C4ORF36. Using mass spectrometry, discovery of differentially expressed mRNAs was extended to the protein level. We also found that invasive cytotrophoblasts expressed cannabinoid receptor 1. Unexpectedly, screening agonists and antagonists showed that signals from this receptor promote invasion. Together, these results revealed previously unseen gene expression patterns that translate to the protein level. Our data also suggested that endogenous and exogenous cannabinoids can affect human placental development.
Keyphrases
- gene expression
- endothelial cells
- single cell
- mass spectrometry
- induced pluripotent stem cells
- liquid chromatography
- dna methylation
- poor prognosis
- binding protein
- pluripotent stem cells
- induced apoptosis
- stem cells
- small molecule
- protein protein
- machine learning
- cell proliferation
- electronic health record
- bone marrow
- amino acid
- ms ms
- cell therapy
- artificial intelligence
- heat shock
- heat stress