Human lung organoid: Models for respiratory biology and diseases

A prospects tool in virus research: Analyzing the applications of organoids in virus studies

Organoids have emerged as a powerful tool for understanding the biology of the respiratory, digestive, nervous as well as urinary system, investigating infections, and developing new therapies. This article reviews recent progress in the development of organoid and advancements in virus research. The potential applications of these models in studying virul infections, pathogenesis, and antiviral drug discovery are discussed.

Organoids in COVID-19: can we break the glass ceiling?

COVID-19 emerged in September 2020 as a disease caused by the virus SARS-CoV-2. The disease presented as pneumonia at first but later was shown to cause multisystem infections and long-term complications. Many efforts have been put into discovering the exact pathogenesis of the disease. In this review, we aim to discuss an emerging tool in disease modeling, organoids, in the investigation of COVID-19. This review will introduce some methods and breakthroughs achieved by organoids and the limitations of this system.

Generation of 3D lung organoids from human induced pluripotent stem cells for modeling of lung development and viral infection

The lack of physiologically relevant in vitro models has hampered progress in understanding human lung development and disease. Here, we describe a protocol in which human induced pluripotent stem cells (hiPSCs) undergo stepwise differentiation into definitive endoderm (>88% population) to three-dimensional (3D) lung organoids (LORGs), which contain both epithelial and mesenchymal cellular architecture and display proximal and distal airway patterning. These LORGs can maintained for more than 90 days by re-embedding in the Matrigel. We show the utility of LORGs for disease modeling and drug screening by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and treatment with antiviral drugs.

Multiomic Investigations into Lung Health and Disease

Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions.