Stochastic versus deterministic in haemopoiesis: what is what?

Area of Science:

• Hematopoiesis research
• Cellular biology
• Mathematical modeling in biology

Background:

• Stochastic models are often used to explain hematopoiesis (blood cell formation).
• These models propose random processes and extrinsic control for cell development.
• Previous interpretations of experimental data favored stochastic explanations.

Purpose of the Study:

• To critically evaluate the assumptions and experimental support for stochastic models of hematopoiesis.
• To explore alternative models that can explain observed quantitative relationships in blood cell development.
• To present and validate a simple, ordered development model.

Main Methods:

• Juxtaposition of stochastic and deterministic concepts in hematopoiesis.
• Analysis of experimental data cited as evidence for stochastic models.
• Development and simulation of a simple ordered development model ('proliferation tree').

Main Results:

• Key features attributed to stochastic models, like inaccessible extrinsic control, are shown to be unsupported conjectures.
• Quantitative relationships between stem cells and in vitro colony formation are compatible with multiple models, not exclusively stochastic ones.
• The proposed ordered development model successfully reproduces experimental distributions.

Conclusions:

• The experimental basis for current stochastic models of hematopoiesis is questionable.
• Simpler models, such as ordered proliferation trees, can equally explain observed phenomena.
• Re-evaluation of control mechanisms in blood cell development is warranted.