Single-cell resolution uncovers neighboring cell subtypes that share steroidogenic capacity during fetal testis development
Abstract
Historically, endocrine cells were perceived to coordinate their output in a uniform manner. Recently however, single-cell technologies have uncovered heterogeneity within these populations, indicating that individual cells may operate as independently regulated units. Using high-resolution tools such as single-molecule fluorescent in situ hybridization (sm-FISH) and single-cell RNA sequencing (scRNA-seq), we investigated the contributions of individual and the collective of fetal Leydig cells to androgen production over time during mouse testis development. Temporal profiles of intratesticular androgens alongside the expression of steroidogenic pathway genes ( Star, Cyp11a1, Cyp17a1, and Hsd3b1 ) from prenatal to perinatal testes demonstrated that the peak in gene expression preceded the peak in androgen production. Spatially, steroidogenic cells were initially observed to be concentrated toward the anterior–posterior poles along the center of the dorsal–ventral axis of the fetal testis at embryonic day (E) 13 and then expanded to a uniform distribution by E16. Next, sm-FISH using probes for individual steroidogenic pathway genes exposed the following findings: gene transcription and processing of individual and combinations of steroidogenic pathway genes are not synchronized among fetal Leydig cells; and some fetal Leydig cells express incomplete sets of genes. Further, sm-FISH and scRNA-seq data corroborated the presence of fetal Leydig and other interstitial cell types harboring incomplete sets of steroidogenic pathway genes throughout developmental stages. Taken together, these findings highlight that fetal steroidogenic gene expression is tightly regulated and that transcript presence among interstitial cell types promotes the possibility that optimal androgen biosynthesis results from a cooperative effort among neighboring steroidogenic cells.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (9)
Keer Jiang
Department of Comparative Biosciences, School of Veterinary Medicine, University of Wisconsin
Zirui Fu
Department of Comparative Biosciences, School of Veterinary Medicine, University of Wisconsin
Philippos Tsourkas
Cancer Informatics Shared Resource, Carbone Cancer Center, University of Wisconsin
Anbarasi Kothandapani
Department of Comparative Biosciences, School of Veterinary Medicine, University of Wisconsin
Tyler Kearse
Department of Comparative Biosciences, School of Veterinary Medicine, University of Wisconsin
Sean J. McIlwain
Cancer Informatics Shared Resource, Carbone Cancer Center, University of Wisconsin
Chloé Mayère
Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva
Serge Nef
Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva
Joan S. Jorgensen
Department of Comparative Biosciences, School of Veterinary Medicine, University of Wisconsin