bioRxivGenomicsPreprint
Chromatin remodeling in peripheral blood cells reflects COVID-19 symptom severity
Nicholas S. GirouxiD, Shengli DingiD, Micah T. McClainiD, Thomas W. BurkeiD, Elizabeth PetzoldiD, Hong A. Chung, Grecia R. Palomino, Ergang WangiD, Rui XiiD, Shree BoseiD, Tomer Rotstein, Bradly P. NicholsoniD, Tianyi CheniD, Ricardo HenaoiD, Gregory D. SempowskiiD, Thomas N. DennyiD, Emily R. KoiD, Geoffrey S. GinsburgiD, Bryan D. KraftiD, Ephraim L. TsalikiD, Christopher W. WoodsiD, Xiling SheniD
Abstract
SARS-CoV-2 infection triggers highly variable host responses and causes varying degrees of illness in humans. We sought to harness the peripheral blood mononuclear cell (PBMC) response over the course of illness to provide insight into COVID-19 physiology. We analyzed PBMCs from subjects with variable symptom severity at different stages of clinical illness before and after IgG seroconversion to SARS-CoV-2. Prior to seroconversion, PBMC transcriptomes did not distinguish symptom severity. In contrast, changes in chromatin accessibility were associated with symptom severity. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif occupancy for individual PBMC cell types. The most extensive remodeling occurred in CD14+ monocytes where sub-populations with distinct chromatin accessibility profiles were associated with disease severity. Our findings indicate that pre-seroconversion chromatin remodeling in certain innate immune populations is associated with divergence in symptom severity, and the identified transcription factors, regulatory elements, and downstream pathways provide potential prognostic markers for COVID-19 subjects. One sentence summaryChromatin accessibility in immune cells from COVID-19 subjects is remodeled prior to seroconversion to reflect disease severity.
- organism: human
- assay: ATAC-seq
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 9
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