High-Resolution Transcriptomic Landscape of the Human Submandibular Gland. (May 2023)

• Record Type: Journal Article
• Authors: Horeth, E.; Bard, J.; Che, M.; Wrynn, T.; Song, E.A.C.; Marzullo, B.; Burke, M.S.; Popat, S.; Loree, T.; Zemer, J.; Tapia, J.L.; Frustino, J.; Kramer, J.M.; Sinha, S.; Romano, R.A.
• Is Part Of: Journal of dental research. Volume 102:Number 5(2023)
• Page Start: 525
• Page End: 535
• Publication Date: 2023-05
• Subjects: salivary glands -- single-cell RNA-sequencing -- transcriptomics -- gene expression -- transcription factors; Dentistry -- Periodicals; Dentistry -- Social aspects -- Periodicals; Dentistry -- Periodicals; Research -- Periodicals; 617.6005
• DOI: 10.1177/00220345221147908
• Languages: English
• ISSNs: 0022-0345

Abstract

Saliva-secreting and transporting cells are part of the complex cellular milieu of the human salivary gland, where they play important roles in normal glandular physiology and diseased states. However, comprehensive molecular characterization, particularly at single-cell resolution, is still incomplete, in part due to difficulty in procuring normal human tissues. Here, we perform an in-depth analysis of male and female adult human submandibular gland (SMG) samples by bulk RNA sequencing (RNA-seq) and examine the molecular underpinnings of the heterogeneous cell populations by single-cell (sc) RNA-seq. Our results from scRNA-seq highlight the remarkable diversity of clusters of epithelial and nonepithelial cells that reside in the SMG that is also faithfully recapitulated by deconvolution of the bulk-RNA data sets. Our analyses reveal complex transcriptomic heterogeneity within both the ductal and acinar subpopulations and identify atypical SMG cell types, such as mucoacinar cells that are unique to humans and ionocytes that have been recently described in the mouse. We use CellChat to explore ligand–receptor interactome predictions that likely mediate crucial cell–cell communications between the various cell clusters. Finally, we apply a trajectory inference method to investigate specific cellular branching points and topology that offers insights into the dynamic and complex differentiation process of the adult SMG. The data sets and the analyses herein comprise an extensive wealth of high-resolution information and a valuable resource for a deeper mechanistic understanding of human SMG biology and pathophysiology.