Self-organized stem cell-derived human lung buds with proximo-distal patterning and novel targets of SARS-CoV-2
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ABSTRACT:
PROVIDER: PRJNA687221 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13289346.fastq.gz | Fastqsanger.gz | |||
| SRR13289347.fastq.gz | Fastqsanger.gz |
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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the global COVID-19 pandemic and the lack of therapeutics hinders pandemic control. Although lung disease is the primary clinical outcome in COVID-19 patients, how SARS-CoV-2 induces tissue pathology in the lung remains elusive. Here we describe a high-throughput-based platform to generate tens of thousands of self-organizing, nearly identical, and genetically matched human lung buds derived from human pluripotent stem cells (hPSCs) cultured on confined geometries on micropattern chips. Strikingly, in vitro-derived human lung buds resemble fetal human lung tissue and display in vivo-like proximo-distal coordination of alveolar and airway tissue differentiation whose 3D epithelial self-organization is directed by the levels of KGF. Single-cell transcriptomics unveiled the cell identities and ontogeny of airway and alveolar tissue and the specification of WNThi cycling alveolar stem cells from alveolar progenitors. These synthetic human lung buds are susceptible to SARS-CoV-2 infection and can be used to track cell type-dependent susceptibilities to infection, intercellular transmission and cytopathology in airway and alveolar tissue in individual synthetic lung buds. We detected an increased susceptibility to infection in alveolar cells and identified cycling alveolar stem cells as targets of SARS-CoV-2. We used this platform to test neutralizing antibodies isolated from convalescent plasma that efficiently blocked SARS-CoV-2 infection and intercellular transmission. Our platform offers unlimited, rapid and scalable access to disease-relevant lung tissue that recapitulate human lung development and can be used to track SARS-CoV-2 infection and identify pre-clinical candidate therapeutics for COVID-19.
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