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Efficient Generation and Transcriptomic Profiling of Human iPSC-Derived Pulmonary Neuroendocrine Cells.

Authors :
Hor P
Punj V
Calvert BA
Castaldi A
Miller AJ
Carraro G
Stripp BR
Brody SL
Spence JR
Ichida JK
Ryan Firth AL
Borok Z
Source :
IScience [iScience] 2020 May 22; Vol. 23 (5), pp. 101083. Date of Electronic Publication: 2020 Apr 21.
Publication Year :
2020

Abstract

Expansion of pulmonary neuroendocrine cells (PNECs) is a pathological feature of many human lung diseases. Human PNECs are inherently difficult to study due to their rarity (<1% of total lung cells) and a lack of established protocols for their isolation. We used induced pluripotent stem cells (iPSCs) to generate induced PNECs (iPNECs), which express core PNEC markers, including ROBO receptors, and secrete major neuropeptides, recapitulating known functions of primary PNECs. Furthermore, we demonstrate that differentiation efficiency is increased in the presence of an air-liquid interface and inhibition of Notch signaling. Single-cell RNA sequencing (scRNA-seq) revealed a PNEC-associated gene expression profile that is concordant between iPNECs and human fetal PNECs. In addition, pseudotime analysis of scRNA-seq results suggests a basal cell origin of human iPNECs. In conclusion, our model has the potential to provide an unlimited source of human iPNECs to explore PNEC pathophysiology associated with several lung diseases.<br />Competing Interests: Declaration of Interests J.K.I. is a co-founder of AcuraStem Incorporated. J.K.I. declares that he is bound by confidentiality agreements that prevent him from disclosing details of his financial interests in this work. All data needed to evaluate the conclusions in the article are present in the article paper and/or the Supplemental Information. Additional data related to this article may be requested from the authors.<br /> (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
2589-0042
Volume :
23
Issue :
5
Database :
MEDLINE
Journal :
IScience
Publication Type :
Academic Journal
Accession number :
32380423
Full Text :
https://doi.org/10.1016/j.isci.2020.101083