SUMMARY
Hematopoiesis provides an accessible system for studying the principles underlying cell-fate decisions in stem cells. Proposed models of hematopoiesis suggest that quantitative changes in lineage-specific transcription factors (LS-TFs) underlie cell-fate decisions. However, evidence for such models is lacking as TF levels are typically measured via RNA expression rather than by analyzing temporal changes in protein abundance. Here, we used single-cell mass cytometry and absolute quantification by mass spectrometry to capture the temporal dynamics of TF protein expression in individual cells during human erythropoiesis. We found that LS-TFs from alternate lineages are co-expressed, as proteins, in individual early progenitor cells and quantitative changes of LS-TFs occur gradually rather than abruptly to direct cell-fate decisions. Importantly, upregulation of a megakaryocytic TF in early progenitors is sufficient to deviate cells from an erythroid to a megakaryocyte trajectory, showing that quantitative changes in protein abundance of LS-TFs in progenitors can determine alternate cell fates.
Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete understanding of potentially druggable immune mediators of disease. To advance this, we present a comprehensive multi-omic blood atlas in patients with varying COVID-19 severity and compare with influenza, sepsis and healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity revealed cells, their inflammatory mediators and networks as potential therapeutic targets, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Tensor and matrix decomposition of the overall dataset revealed feature groupings linked with disease severity and specificity. Our systems-based integrative approach and blood atlas will inform future drug development, clinical trial design and personalised medicine approaches for COVID-19.
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