Directed differentiation of human pluripotent stem cells into diverse organ-specific mesenchyme of the digestive and respiratory systems

人类多能干细胞定向分化为消化系统和呼吸系统的多种器官特异性间充质

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作者:Keishi Kishimoto, Kentaro Iwasawa, Alice Sorel, Carlos Ferran-Heredia, Lu Han, Mitsuru Morimoto, James M Wells, Takanori Takebe, Aaron M Zorn

Abstract

Development of visceral organs such as the esophagus, lung, liver and stomach are coordinated by reciprocal signaling interactions between the endoderm and adjacent mesoderm cells in the fetal foregut. Although the recent successes in recapitulating developmental signaling in vitro has enabled the differentiation of human pluripotent stem cells (hPSCs) into various types of organ-specific endodermal epithelium, the generation of organ-specific mesenchyme has received much less attention. This is a major limitation in ongoing efforts to engineer complex human tissue. Here, we describe a protocol to differentiate hPSCs into different types of organ-specific mesoderm, leveraging signaling networks and molecular markers elucidated from single-cell transcriptomics of mouse foregut organogenesis. Building on established methods, hPSC-derived lateral plate mesoderm treated with either retinoic acid (RA) or RA together with a Hedgehog (HH) agonist generates posterior or anterior foregut splanchnic mesoderm, respectively, after 4-d cultures. These are directed into organ-specific mesenchyme lineages by the combinatorial activation or inhibition of WNT, BMP, RA or HH pathways from days 4 to 7 in cultures. By day 7, the cultures are enriched for different types of mesoderm with distinct molecular signatures: 60-90% pure liver septum transversum/mesothelium-like, 70-80% pure liver-like fibroblasts and populations of ~35% respiratory-like mesoderm, gastric-like mesoderm or esophageal-like mesoderm. This protocol can be performed by anyone with moderate experience differentiating hPSCs, provides a novel platform to study human mesoderm development and can be used to engineer more complex foregut tissue for disease modeling and regenerative medicine.

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