Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begins when the viral spike protein binds angiotensin-converting enzyme 2 (ACE2) on airway and alveolar epithelial cells and is activated by transmembrane serine protease 2 (TMPRSS2) or endosomal cathepsins, enabling membrane fusion and viral entry. Following cytoplasmic release, the viral genome replicates within endoplasmic reticulum–derived membranous webs, promoting epithelial dysfunction and inflammatory signaling. Although these steps have been extensively characterized in 2-dimensional cell lines and animal models, limited representation of human epithelial diversity, polarity, and maturation restricts accurate modeling of viral tropism and host responses. Lung organoids provide 3-dimensional platforms that reconstruct essential features of the human respiratory epithelium. Induced pluripotent stem cell–derived lung organoids recapitulate early developmental trajectories and allow interrogation of how fetal-like epithelial states influence viral susceptibility. In contrast, adult stem cell–derived airway and alveolar organoids, including alveolar type II–enriched models, display more mature phenotypes with endogenous ACE2 and TMPRSS2 expression. Together, these complementary systems enable analyses of entry pathways, replication dynamics, innate immune activation, and variant-specific shifts in epithelial tropism. Despite these advances, current lung organoid platforms lack key physiological components, including immune cell populations, vascular interfaces, and biomechanical forces, and remain constrained by incomplete epithelial maturation, donor variability, and limited scalability. Methodological innovations—immune–epithelial co-culture, vascular integration, mechanical stimulation, microfluidic organ-on-chip systems, and standardized differentiation protocols—are poised to improve physiological fidelity and translational relevance for studying SARS-CoV-2 infection and emerging respiratory pathogens.
Building similarity graph...
Analyzing shared references across papers
Loading...
Geon-Woo Kim
Yong-Hee Cho
Organoid
University of California, San Diego
Korea Research Institute of Chemical Technology
Building similarity graph...
Analyzing shared references across papers
Loading...
Kim et al. (Fri,) studied this question.
www.synapsesocial.com/papers/6975b350feba4585c2d6ec79 — DOI: https://doi.org/10.51335/organoid.2026.6.e1