Abstract
Since we still know very little about stem cells in their natural environment, it is useful to explore their dynamics through modelling and simulation, as well as experimentally. Most models of stem cell systems are based on deterministic differential equations that ignore the natural heterogeneity of stem cell populations. This is not appropriate at the level of individual cells and niches, when randomness is more likely to affect dynamics. In this paper, we introduce a fast stochastic method for simulating a metapopulation of stem cell niche lineages, that is, many sub-populations that together form a heterogeneous metapopulation, over time. By selecting the common limiting timestep, our method ensures that the entire metapopulation is simulated synchronously. This is important, as it allows us to introduce interactions between separate niche lineages, which would otherwise be impossible. We expand our method to enable the coupling of many lineages into niche groups, where differentiated cells are pooled within each niche group. Using this method, we explore the dynamics of the haematopoietic system from a demand control system perspective. We find that coupling together niche lineages allows the organism to regulate blood cell numbers as closely as possible to the homeostatic optimum. Furthermore, coupled lineages respond better than uncoupled ones to random perturbations, here the loss of some myeloid cells. This could imply that it is advantageous for an organism to connect together its niche lineages into groups. Our results suggest that a potential fruitful empirical direction will be to understand how stem cell descendants communicate with the niche and how cancer may arise as a result of a failure of such communication.
Highlights
Stem cells offer exciting potential for regenerative therapy, with ultimate possibilities being the ability to regenerate limbs and heal genetic diseases [1,2]
By implementing a stochastic model of stem cell dynamics, generically based on the bone marrow system, in a novel, fast and computationally efficient way, we show how different couplings of stem cell niche lineages lead to different predictions about homeostatic control
Understanding the demand control of stem cell systems is essential to both predicting in vivo stem cell dynamics and how its breakdown may lead to the development of cancers of the blood system
Summary
Stem cells offer exciting potential for regenerative therapy, with ultimate possibilities being the ability to regenerate limbs and heal genetic diseases [1,2]. Much of our knowledge of stem cells is derived from in vitro experiments, where the stem cells have been relocated from their native environment. In haematopoietic (blood-producing) stem cell experiments the stem cells are often isolated from a donor, expanded in vitro, and transplanted into a lethally irradiated host, with the question of interest being how the stem cells respond to this new environment (e.g., [5]). It is difficult to draw conclusions about the role and behaviour of stem cells in vivo, when experimentally we must investigate them in foreign environments [6,7]. Theoretical models of stem cell systems are valuable tools, allowing us to think about stem cells in their native environments when this cannot yet be done experimentally
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
