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3D Lung Tissue Models for Studies on SARS-CoV-2 Pathophysiology and Therapeutics

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing the coronavirus disease 2019 (COVID-19), has provoked more than six million deaths worldwide and continues to pose a major threat to global health. Enormous efforts have been made by researchers around the world to elucidate COVID...

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Detalles Bibliográficos
Autores principales: Plebani, Roberto, Bai, Haiqing, Si, Longlong, Li, Jing, Zhang, Chunhe, Romano, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9456220/
https://www.ncbi.nlm.nih.gov/pubmed/36077471
http://dx.doi.org/10.3390/ijms231710071
Descripción
Sumario:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing the coronavirus disease 2019 (COVID-19), has provoked more than six million deaths worldwide and continues to pose a major threat to global health. Enormous efforts have been made by researchers around the world to elucidate COVID-19 pathophysiology, design efficacious therapy and develop new vaccines to control the pandemic. To this end, experimental models are essential. While animal models and conventional cell cultures have been widely utilized during these research endeavors, they often do not adequately reflect the human responses to SARS-CoV-2 infection. Therefore, models that emulate with high fidelity the SARS-CoV-2 infection in human organs are needed for discovering new antiviral drugs and vaccines against COVID-19. Three-dimensional (3D) cell cultures, such as lung organoids and bioengineered organs-on-chips, are emerging as crucial tools for research on respiratory diseases. The lung airway, small airway and alveolus organ chips have been successfully used for studies on lung response to infection by various pathogens, including corona and influenza A viruses. In this review, we provide an overview of these new tools and their use in studies on COVID-19 pathogenesis and drug testing. We also discuss the limitations of the existing models and indicate some improvements for their use in research against COVID-19 as well as future emerging epidemics.