Single cell profiling of COVID-19 patients: an international data resource from multiple tissues

Chan Zuckerberg Initiative Single-Cell COVID-19 Consortia, Esteban Ballestar, Donna L. Farber, Sarah Glover, Bruce Horwitz, Kerstin Meyer, Marko Nikolić, Jose Ordovas-Montanes, Peter Sims, Alex Shalek, Niels Vandamme, Linos Vandekerckhove, Roser Vento-Tormo, Alexandra Chloe Villani

Abstract

In late 2019 and through 2020, the COVID-19 pandemic swept the world, presenting both scientific and medical challenges associated with understanding and treating a previously unknown disease. To help address the need for great understanding of COVID-19, the scientific community mobilized and banded together rapidly to characterize SARS-CoV-2 infection, pathogenesis and its distinct disease trajectories. The urgency of COVID-19 provided a pressing use-case for leveraging relatively new tools, technologies, and nascent collaborative networks. Single-cell biology is one such example that has emerged over the last decade as a powerful approach that provides unprecedented resolution to the cellular and molecular underpinnings of biological processes. Early foundational work within the single-cell community, including the Human Cell Atlas, utilized published and unpublished data to characterize the putative target cells of SARS-CoV-2 sampled from diverse organs based on expression of the viral receptor ACE2 and associated entry factors TMPRSS2 and CTSL (Muus et al., 2020; Sungnak et al., 2020; Ziegler et al., 2020). This initial characterization of reference data provided an important foundation for framing infection and pathology in the airway as well as other organs. However, initial community analysis was limited to samples derived from uninfected donors and other previously-sampled disease indications. This report provides an overview of a single-cell data resource derived from samples from COVID-19 patients along with initial observations and guidance on data reuse and exploration.

Datasets

1. PBMC
Metadata
Annotation
donor_id
time_point
age
assay_ontology_term_id
cell_type_ontology_term_id
development_stage_ontology_term_id
disease_ontology_term_id
preexisting_heartdisease
preexisting_lungdisease
preexisting_kidneydisease
preexisting_diabetes
preexisting_hypertension
preexisting_immunocompromisedcondition
respiratory_symptoms
fever_symptoms
gastrointestinal_symptoms
self_reported_ethnicity_ontology_term_id
organism_ontology_term_id
sex_ontology_term_id
tissue_ontology_term_id
suspension_type
tissue_type
cell_type
assay
disease
organism
sex
tissue
self_reported_ethnicity
development_stage
Monocyte 112211 cells
Monocyte 29407 cells
CD8 T cell 17271 cells
CD4 T cell 16726 cells
Monocyte 35383 cells
B cell 13874 cells
NK cell3248 cells
B cell 22257 cells
T cell1659 cells
Monocyte 41599 cells
CD8 T cell 21387 cells
Monocyte 51278 cells
Dendritic Cell1038 cells
Platelet1007 cells
Plasmablast586 cells
pDC575 cells
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Single cell profiling of COVID-19 patients: an international data resource from multiple tissues

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Source data

https://cellxgene.cziscience.com/collections/0434a9d4-85fd-4554-b8e3-cf6c582bb2fa

Alias names

Acute COVID-19 cohort across a range of WHO categories seen at the Department of Emergency Medicine at MGH

Cite this study

Chan Zuckerberg Initiative Single-Cell COVID-19 Consortia, Ballestar, E., Farber, D.L., Glover, S., Horwitz, B., Meyer, K., Nikolić, M., Ordovas-Montanes, J., Sims, P., Shalek, A. and Vandamme, N., 2020. Single cell profiling of COVID-19 patients: an international data resource from multiple tissues. MedRxiv, pp.2020-11. https://doi.org/10.1101/2020.11.20.20227355