Communications BiologyImmunologyPeer-reviewed journal article
G-CSF and IL-6 drive myeloid dysregulation during severe viral infection
Kimberly K. KajiharaiD, Donghong YaniD, Gretchen L. SeimiD, Hannah Little-Hooy, Jing‐Qiong KangiD, Cynthia CheniD, Marco Claudio De SimoneiD, Tim DelemarreiD, Spyros DarmanisiD, Haridha ShivramiD, Rebecca N. BaueriD, Carrie M. RosenbergeriD, Sharookh B. KapadiaiD, Min Jian XuiD, Miguel ReyesiD
Abstract
Dysregulated myeloid states are associated with disease severity in both sepsis and COVID-19. However, their relevance in non-COVID-19 viral infection, the factors driving their induction, and their role in tissue injury remain poorly understood. We performed a meta-analysis of 1,622,180 myeloid cells from 890 COVID-19 or sepsis patients and controls across 19 published blood scRNA-seq datasets, which revealed severity-associated gene programs in both neutrophils and monocytes pointing to emergency myelopoiesis (EM). Using published bulk transcriptional data from 562 individuals with non-COVID-19 viral disease, we show that these signatures are similarly upregulated during severe influenza and RSV infection. Analysis of transcriptional and proteomic responses in tocilizumab-treated COVID-19 patients show that IL-6 signaling blockade results in a partial reduction of EM signatures and a compensatory increase in the growth factor G-CSF. Using a cellular model of human myelopoiesis, we show that both IL-6 and G-CSF stimulate the production of myeloid cells that express EM signatures in vitro. Using a mouse model of severe influenza infection, we demonstrate the effect of IL-6 and G-CSF signaling blockade on EM-associated myeloid cells, and highlight the opposing effects of EM-induced neutrophils and monocytes on tissue injury. Our study demonstrates the link between systemic cytokines and myeloid dysregulation during severe infection in humans, and highlights the cooperative role of IL-6 and G-CSF signaling in driving infection-induced myelopoiesis.
- organism: human
- organism: mouse
- assay: scRNA-seq
- assay: bulk RNA-seq
- assay: proteomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: statistical model
- approach: experimental assay
- approach: wet-lab / biochemical assay
- Citations
- 8
- FWCI
- 0.65
- Field percentile
- top 42%
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