A multi-organoid platform identifies CIART as a key factor for SARS-CoV-2 infection.

Xuming Tang, Dongxiang Xue, Tuo Zhang, Benjamin E Nilsson-Payant, Lucia Carrau, Xiaohua Duan, Miriam Gordillo, Adrian Y Tan, Yunping Qiu, Jenny Xiang, Robert E Schwartz, Benjamin R tenOever, Todd Evans, Shuibing Chen

Journal: Nature cell biology 2023;25(3):381-389

PMID: 36918693

Abstract

COVID-19 is a systemic disease involving multiple organs. We previously established a platform to derive organoids and cells from human pluripotent stem cells to model SARS-CoV-2 infection and perform drug screens. This provided insight into cellular tropism and the host response, yet the molecular mechanisms regulating SARS-CoV-2 infection remain poorly defined. Here we systematically examined changes in transcript profiles caused by SARS-CoV-2 infection at different multiplicities of infection for lung airway organoids, lung alveolar organoids and cardiomyocytes, and identified several genes that are generally implicated in controlling SARS-CoV-2 infection, including CIART, the circadian-associated repressor of transcription. Lung airway organoids, lung alveolar organoids and cardiomyocytes derived from isogenic CIART human pluripotent stem cells were significantly resistant to SARS-CoV-2 infection, independently of viral entry. Single-cell RNA-sequencing analysis further validated the decreased levels of SARS-CoV-2 infection in ciliated-like cells of lung airway organoids. CUT&RUN, ATAC-seq and RNA-sequencing analyses showed that CIART controls SARS-CoV-2 infection at least in part through the regulation of NR4A1, a gene also identified from the multi-organoid analysis. Finally, transcriptional profiling and pharmacological inhibition led to the discovery that the Retinoid X Receptor pathway regulates SARS-CoV-2 infection downstream of CIART and NR4A1. The multi-organoid platform identified the role of circadian-clock regulation in SARS-CoV-2 infection, which provides potential therapeutic targets for protection against COVID-19 across organ systems.

© 2023. The Author(s).

Address: Department of Surgery, Weill Cornell Medicine, New York, NY, USA.; Center for Genomic Health, Weill Cornell Medicine, New York, NY, USA.; Genomics Resources Core Facility, Weill Cornell Medicine, New York, NY, USA.; Department of Microbiology, New York University, New York, NY, USA.; TWINCORE Centre for Experimental and Clinical Infection Research, Hannover, Germany.; Department of Microbiology, New York University, New York, NY, USA.; Stable Isotope and Metabolomics Core Facility, The Einstein-Mount Sinai Diabetes Research Center, Albert Einstein College of Medicine, Bronx, New York, USA.; Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.; Department of Physiology, Biophysics and Systems Biology, Weill Cornell Medicine, New York, NY, USA.; Department of Surgery, Weill Cornell Medicine, New York, NY, USA. [email protected].; Center for Genomic Health, Weill Cornell Medicine, New York, NY, USA. [email protected].
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