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| Status |
Public on Mar 24, 2021 |
| Title |
IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 lungs and inflammatory diseases with tissue inflammation |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
We explored how the human macrophages response to different inflammatory factors, focusing particularly on the effects of antiviral interferons (IFN-β and IFN-γ), pro-inflammatory cytokines such as TNF-α, and other mediators like IL-4. Co-cultured fibroblasts were a component in some conditions to generate factors produced by resident stroma. We used a single-cell antibody-based hashing strategy to multiplex samples from different stimulatory conditions in one sequencing run. This macrophage transcriptomic data reveals distinct macrophage activation states and polarizations shaped by different tissue-related inflammatory conditions at single-cell resolution. We further performed an unbiased integration between tissue-level macrophages and this stimulated human blood-derived macrophages, which pinpoint an IFN-γ and TNF-α synergistically driven inflammatory macrophage phenotype expanded in severe COVID-19 lungs and other inflamed disease tissues.
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| Overall design |
We isolated CD14+ monocytes from each of the 4 healthy blood samples using human CD14 microbeads (Miltenyi Biotec) and differentiated these cells into blood-derived macrophages. Human CD14+ MCSF-differentiated macrophages were cultured with or without synovial fibroblasts in trans-well chambers. In total, we created 9 wells per donor. We added either IFN-β (200 pg/mL), IL-4 (20 ng/ mL), TNF-α (20 ng/mL), and/ or IFN-γ (5 ng/mL) to each trans-well and underlying plate per donor. All plates were incubated at 37° C for 19 hours. We applied a modified version of the staining protocol from CITE-seq, using only Totalseq-A Hashing antibodies from Biolegend. We followed the Chromium Single Cell 3' v3 kit (10x Genomics) processing instructions and super-loaded 30,000 cells per lane. We used one lane per donor, with 9 conditions multiplexed per donor sample. Pairs of libraries were pooled and sequenced per lane on an Illumina NovaSeq S2 with paired-end 150 base-pair reads. We quantified mRNA and antibody unique molecular identifiers (UMI) counts, respectively. Cellranger v3.1.0 was used to process the raw BCL files. Then, raw BCL files were demultiplexed using cellranger mkfastq to generate FASTQ files. FASTQ files were aligned to the GRCh38 human reference genome. Gene/antibody reads were quantified simultaneously using cellranger count.
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Authors state the following:
These are human blood samples that required control for access. We will put the raw sequencing data to dbGap.
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| Contributor(s) |
Zhang F, Donlin L, Raychaudhuri S |
| Citation(s) |
33879239 |
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| Submission date |
Mar 11, 2021 |
| Last update date |
Apr 21, 2021 |
| Contact name |
Soumya Raychaudhuri |
| E-mail(s) |
soumya@broadinstitute.org
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| Organization name |
Brigham and Women's Hospital, Harvard Medical School
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| Street address |
77 Avenue Louis Pasteur
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| City |
Boston |
| State/province |
MA |
| ZIP/Postal code |
02115 |
| Country |
USA |
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| Platforms (1) |
| GPL24676 |
Illumina NovaSeq 6000 (Homo sapiens) |
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| Samples (4)
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| Relations |
| BioProject |
PRJNA713777 |
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