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The cellular immune response to COVID-19 deciphered by single cell multi-omics across three UK centres

Updated January 28, 2022

The COVID-19 pandemic, caused by SARS coronavirus 2 (SARS-CoV-2), has resulted in excess morbidity and mortality as well as economic decline. To characterise the systemic host immune response to SARS-CoV-2, we performed single-cell RNA-sequencing coupled with analysis of cell surface proteins, providing molecular profiling of over 800,000 peripheral blood mononuclear cells from a cohort of 130 patients with COVID-19. Our cohort, from three UK centres, spans the spectrum of clinical presentations and disease severities ranging from asymptomatic to critical. Three control groups were included: healthy volunteers, patients suffering from a non-COVID-19 severe respiratory illness and healthy individuals administered with intravenous lipopolysaccharide to model an acute inflammatory response. Full single cell transcriptomes coupled with quantification of 188 cell surface proteins, and T and B lymphocyte antigen receptor repertoires have provided several insights into COVID-19: 1. a new non-classical monocyte state that sequesters platelets and replenishes the alveolar macrophage pool; 2. platelet activation accompanied by early priming towards megakaryopoiesis in immature haematopoietic stem/progenitor cells and expansion of megakaryocyte-primed progenitors; 3. increased clonally expanded CD8+ effector:effector memory T cells, and proliferating CD4+ and CD8+ T cells in patients with more severe disease; and 4. relative increase of IgA plasmablasts in asymptomatic stages that switches to expansion of IgG plasmablasts and plasma cells, accompanied with higher incidence of BCR sharing, as disease severity increases. All data and analysis results are available for interrogation and data mining through an intuitive web portal. Together, these data detail the cellular processes present in peripheral blood during an acute immune response to COVID-19, and serve as a template for multi-omic single cell data integration across multiple centers to rapidly build powerful resources to help combat diseases such as COVID-19.

Muzlifah HaniffaNewcastle Universitym.a.haniffa@newcastle.ac.uk
Muzlifah Haniffa (Principal Investigator)1
Emily Stephenson (Experimental Scientist)1
Gary Reynolds (Experimental Scientist)1
Rachel Botting (Experimental Scientist)1
Fernando Calero-Nieto (Experimental Scientist)2
Michael Morgan (Experimental Scientist)3
Zewen Kelvin Tuong (Experimental Scientist)4
Karsten Bach (Experimental Scientist)3
Waradon Sungnak (Experimental Scientist)5
1Newcastle University
2Wellcome - University of Cambridge
3EMBL-EBI
4University of Cambridge
5Wellcome Sanger Institute
Wei Kheng Teh

To reference this project, please use the following link:

https://explore.data.humancellatlas.org/projects/b963bd4b-4bc1-4404-8425-69d74bc636b8
None
EGA Accessions:Array Express Accessions:

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Analysis Portals

CZ CELLxGENECZ CELLxGENE
UCSC Cell BrowserUCSC Cell Browser

Project Label

Covid19PBMC

Species

Homo sapiens

Sample Type

specimens

Anatomical Entity

blood

Organ Part

Unspecified

Selected Cell Types

peripheral blood mononuclear cell

Disease Status (Specimen)

7 disease statuses

Disease Status (Donor)

6 disease statuses

Development Stage

human adult stage

Library Construction Method

4 library construction methods

Nucleic Acid Source

single cell

Paired End

true

Analysis Protocol

Combined_AnalysisProt

File Format

2 file formats

Cell Count Estimate

800.0k

Donor Count

120
csv1 file(s)h5ad1 file(s)