Hematopoietic stem cell heterogeneity in non-human primates revealed by five-lineage output bias analysis.
Blood Sci
; 6(1): e00176, 2024 Jan.
Article
in En
| MEDLINE
| ID: mdl-38213824
ABSTRACT
Understanding hematopoietic stem cell (HSC) heterogeneity is crucial for treating malignant blood disorders. Compared with mice, we have limited knowledge of the heterogeneity of human HSCs. Fortunately, non-human primates (NHPs) have become the best animal models for studying human HSCs. Here, we employed a public dataset derived from NHP autologous bone marrow transplantation, and focused on a total of 820 HSC clones with reconstitution capacity of all available five lineages (granulocyte, monocyte, B cell, T cell, and natural killer cell) at two time points (11/12 and/or 42/43 months). Intriguingly, unsupervised clustering on these clones revealed six HSC subtypes, including a lymphoid/myeloid balanced (LM-balanced) subtype and five single-lineage-biased subtypes. We also observed that the subtypes of these HSC clones might change over time, and a given subtype could transition into any one of the other five subtypes, albeit with a certain degree of selectivity. Particularly, each of the six subtypes was more likely to turn into lymphoid-biased rather than myeloid-biased ones. Additionally, our five-lineage classification method exhibited strong correlation with traditional lymphoid/myeloid bias classification method. Specifically, our granulocyte- and monocyte-biased subtypes were predominantly attributed to α-HSCs, while LM-balanced, B cell-biased, and T cell-biased subtypes were primarily associated with ß-HSCs. The γ-HSCs were composed of a small subset of B cell-biased and T cell-biased subtypes. In summary, our five-lineage classification identifies more finely tuned HSC subtypes based on lineage output bias. These findings enrich our understanding of HSC heterogeneity in NHPs and provide important insights for human research.
Full text:
1
Database:
MEDLINE
Type of study:
Prognostic_studies
Language:
En
Journal:
Blood Sci
Year:
2024
Type:
Article
Affiliation country:
China