Novel Human Lung Tissue Model for the Study of SARS-CoV-2 Entry, Inflammation and New Therapeutics

Grau-Expósito, Judith; Perea, David; Suppi, Marina; Massana, Núria; Vergara, Ander; José Soler, Maria; García-Pérez, Javier; Alcamí, José; Serrano-Mollar, Anna; Rosado, Joel; Falcó, Vicenç; Genescà , Meritxell; Buzon, Maria J.

The development of physiological models that reproduce SARS-CoV-2 infection in primary human cells will be instrumental to identify host-pathogen interactions and potential therapeutics. Here, using cell suspensions from primary human lung tissues (HLT), we have developed a platform for the identification of viral targets and the expression of viral entry factors, as well as for the screening of viral entry inhibitors and anti-inflammatory compounds. We show that the HLT model preserves its main cell populations, maintains the expression of proteins required for SARS-CoV-2 infection, and identifies alveolar type II (AT-II) cells as the most susceptible cell targets for SARS-CoV-2 in the human lung. Antiviral testing of 39 drug candidates revealed a highly reproducible system, and provided the identification of new compounds missed by conventional systems such as VeroE6. Using this model, we also show that interferons do not modulate ACE2 expression, and that stimulation of local inflammatory responses can be modulated by different compounds with antiviral activity. Overall, we present a novel and relevant physiological model for the study of SARS-CoV-2. Synopsis Ex vivo physiological systems for the study of SARS-CoV-2-host interactions are scarce. Here, we establish a novel model using primary human lung tissue (HLT) for the analysis of cell tropism and identification of therapeutics. The HLT model preserves main cell subpopulations, including alveolar type-2 cells, and expression of SARS-CoV-2 entry factors ACE2, CD147, and TMPRSS2. The HLT model is readily susceptible to SARS-CoV-2 entry. Antiviral testing in the HLT model allows the identification of new candidates missed by conventional systems. Local inflammation is supported in the HLT model and offers the identification of relevant anti-inflammatory compounds for SARS-CoV-2 infection.