bioRxivImmunologyPreprint
BCG vaccination impacts the epigenetic landscape of progenitor cells in human bone marrow
S. J. Sun, R. Aguirre-Gamboa, C. J. de Bree, J. Sanz, A. Dumaine, L. A. Joosten, M. Divangahi, M. Netea, L. B. Barreiro
Abstract
While the Bacille-Calmette-Guerin (BCG) vaccine is used to prevent tuberculosis, it also offers protection against a diverse range of non-mycobacterial infections. However, the underlying protective mechanisms in humans are not yet fully understood. Here, we surveyed at single-cell resolution the gene expression and chromatin landscape of human bone marrow, aspirated before and 90 days after BCG vaccination or placebo administration. We show that BCG vaccination significantly alters both the gene expression and epigenetic profiles of human hematopoietic stem and progenitor cells (HSPCs). Changes in gene expression occur primarily on the most uncommitted stem cells and are reflective of a persistent myeloid bias. In contrast, BCG-induced changes in chromatin accessibility are most prevalent within differentiated progenitor cells at sites influenced by Kruppel-like factor (KLF)/SP and EGR transcription factors (TFs). These TFs are also activated in the most uncommitted stem cells, indicating that activated TFs, which drive persistent changes in HSC gene expression, likely also drive chromatin dynamics appearing within downstream progenitor cells. This perspective contests the prevailing notion that epigenetic modifications linked to innate immune memory transfer directly from stem cells to their differentiated derivatives. Finally, we show that alterations in gene expression and chromatin accessibility in HSPCs due to BCG vaccination were highly correlated (r>0.8) with the IL-1{beta} secretion capacity of paired PBMCs upon secondary immune challenge. Overall, our findings shed light on BCG vaccinations profound and lasting effects on HSPCs and its influence on innate immune responses.
- organism: human
- assay: scRNA-seq
- assay: ChIP-seq
- research focus: chromatin & epigenetic regulation
- approach: statistical model
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