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| Status |
Public on Apr 05, 2021 |
| Title |
Single-Cell Omics Reveals Dyssynchrony of the Innate and Adaptive Immune System in Progressive COVID-19 [CITE-seq] |
| Organism |
Homo sapiens |
| Experiment type |
Other
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| Summary |
A dysregulated immune response against the SARS-CoV-2 virus plays a critical role in severe COVID-19. However, the molecular and cellular mechanisms by which the virus causes lethal immunopathology are poorly understood. Here, we utilize multi-omics single-cell analysis to probe dynamic immune responses in patients with stable or progressive manifestations of COVID-19, and assess the effects of tocilizumab, an anti-IL-6 receptor monoclonal antibody. Coordinated profiling of gene expression and cell lineage protein markers reveals a prominent type-1 interferon response across all immune cells, especially in progressive patients. An anti-inflammatory signature in monocytes and a pre-exhaustion phenotype in activated T cells are hallmarks of progressive disease. Single-cell T and B cell receptor repertoire analysis reveal a skewed clonal distribution of CD8 T cells and a primary B cell response with possible contribution from memory B cells. Our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19, which may contribute to delayed virus clearance and has implications for therapeutic intervention.
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| Overall design |
18 PBMC samples from 10 patients at various time points were studied. Age and sex matched healthy subjects (n=13) whose samples were collected before the COVID-19 pandemic were used as controls. Single-cell RNA sequencing (scRNA-seq) was performed, as well as surface protein libraries (CITE-seq), T cell receptor (TCR) libraries and B cell receptor (BCR) libraries. Detailed sample metadata are included in the tar archive with the processed data. The processed data for the control samples exist solely within the Seurat Rds file. There are no additional metadata or processed data files for the control samples, as there are for the COVID-19 samples.
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| Contributor(s) |
Unterman A, Sumida T, Hafler DA, Kaminski N, Dela Cruz CS |
| Citation(s) |
35064122, 36596303 |
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| Submission date |
Jul 27, 2020 |
| Last update date |
Jan 05, 2023 |
| Contact name |
Steven Kleinstein |
| Organization name |
Yale University
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| Department |
Pathology
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| Lab |
Kleinstein
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| Street address |
300 George St.
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| City |
New Haven |
| State/province |
Ct |
| ZIP/Postal code |
06511 |
| Country |
USA |
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| Platforms (1) |
| GPL24676 |
Illumina NovaSeq 6000 (Homo sapiens) |
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| Samples (6)
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| GSM4697605 |
CITE1_Samples NS1A, NS1B, TS5A, TS5B, TP7A, TP7B |
| GSM4697606 |
CITE2_Samples NS1A, NS1B, TS5A, TS5B, TP7A, TP7B |
| GSM4697607 |
CITE3_Samples NS0A, NS0B, TS2A, TS2B, TP6A |
| GSM4697608 |
CITE4_Samples NS0A, NS0B, TS2A, TS2B, TP6A, TP6B |
| GSM4697609 |
CITE5_Samples TS3A, TS3B, TS4A, TS4B, TP9B |
| GSM4697610 |
CITE6_Samples TS3A, TS3B, TS4A, TS4B, TP9B |
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| This SubSeries is part of SuperSeries: |
| GSE155224 |
Single-Cell Omics Reveals Dyssynchrony of the Innate and Adaptive Immune System in Progressive COVID-19 |
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| Relations |
| BioProject |
PRJNA648992 |
| SRA |
SRP345663 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE155222_CITE-seq_deshashing_table.txt.gz |
279 b |
(ftp)(http) |
TXT |
| GSE155222_RAW.tar |
327.7 Mb |
(http)(custom) |
TAR (of TAR) |
| GSE155222_feature_reference.csv.gz |
3.0 Kb |
(ftp)(http) |
CSV |
SRA Run Selector |
| Processed data provided as supplementary file |
| Processed data are available on Series record |
| Raw data are available in SRA |
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