Nature CommunicationsCell BiologyPeer-reviewed journal article
Clonal memory of cell division in humans diverges between healthy haematopoiesis and acute myeloid leukaemia
Alessandro DonadaiD, Gurvan HermangeiD, Tiziana TocciiD, Adil MidouniD, Giulio PrevedelloiD, Louisa Hadj AbediD, Délia Dupré, Wenjie SuniD, Idan MiloiD, Sabrina Tenreira Bento, Constandina PosporiiD, Andrew J. InnesiD, Christophe WillekensiD, Jacques VargaftigiD, David MichonneauiD, Cristina Lo CelsoiD, Nicolas ServantiD, Ken R. DuffyiD, Hervé IsambertiD, Paul-Henry CournèdeiD, Lucie LaplaneiD, Leïla PeriéiD
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Abstract
Clonal memory, a cellular property inherited across at least two divisions, has emerged as a key driver of cell heterogeneity. To uncover its roles in human haematopoiesis, we developed high-resolution ex vivo tools that track both division and fate commitment of individual primary human haematopoietic stem and progenitor cells (HSPCs). We show that human HSPCs display a clonal memory of division, as cells descending from the same ancestor cell divide synchronously over multiple generations. In parallel, HSPCs inherit a clonal memory of fate commitment, independently of lineage identity. Both forms of clonal memory persist over at least two divisions, across different HSPC commitment stages and cell culture conditions. In contrast, malignant haematopoiesis exhibits lower synchronicity, revealing a disruption of clonal memory in leukemic cells. Epigenetic remodelling using a bromodomain inhibitor partially restores the clonal memory in division in leukemic HSPCs, highlighting the plasticity of this trait and its potential for therapeutic modulation. Our findings position clonal memory as a key regulator of human haematopoietic stem cell behaviour. Demonstrating that clonal memory can be modulated opens new avenues for tuning cell heterogeneity in healthy and pathological tissues.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
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