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bioRxiv · 10.1101/305367

Hematopoietic Stem Cell Dynamics are Regulated by Progenitor Demand: Lessons from a Quantitative Modeling Approach

Abstract

The prevailing view on murine hematopoiesis and on hematopoietic stem cells (HSC) in particular derives from experiments that are related to regeneration after irradiation and HSC transplantation. However, over the past years, different experimental techniques have been developed to investigate hematopoiesis under homeostatic conditions, thereby providing access to proliferation and differentiation rates of hematopoietic stem and progenitor cells in the unperturbed situation. Moreover, it has become clear that hematopoiesis undergoes distinct changes during aging with large effects on HSC abundance, lineage contribution, asymmetry of division and self-renewal potential. However, it is currently not fully resolved how stem and progenitor cells interact to respond to varying demands and how this balance is altered by an aging-induced shift in HSC polarity.\n\nHere, we present an in-silico model to investigate the dynamics of HSC response to varying demand. By introducing an internal feedback between stem and progenitor cells, the model is suited to consistently describe both hematopoietic homeostasis and regeneration, including the limited regulation of HSCs in the homeostatic situation. The model further explains the age-dependent increase in phenotypic HSCs as a consequence of the cells inability to preserve divisional asymmetry.\n\nOur model suggests a dynamically regulated population of intrinsically asymmetrically dividing HSCs as suitable control mechanism that adheres with many qualitative and quantitative findings on hematopoietic recovery after stress and aging. The modeling approach thereby illustrates how a mathematical formalism can support the conceptual and the quantitative understanding of regulatory principles in HSC biology.

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Klose, M., Florian, M. C., Geiger, H., Glauche, I.. 2018-04-20. Hematopoietic Stem Cell Dynamics are Regulated by Progenitor Demand: Lessons from a Quantitative Modeling Approach. https://doi.org/10.1101/305367

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