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. 2016:2016:8054219.
doi: 10.1155/2016/8054219. Epub 2016 Jun 2.

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis

Manish Kurhekar  1 , Umesh Deshpande  1
Affiliations

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis

Manish Kurhekar et al. Adv Bioinformatics. 2016.

Abstract

Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.

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Figures

Figure 1
Figure 1
Bone marrow graph in two dimensions (each vertex is a cell that has eight immediate neighbors and the label denotes its type).
Figure 2
Figure 2
Comparison of Agur et al.'s model and the model proposed in this paper.
Figure 3
Figure 3
Stem cells proliferation shown progressively from images (a) to (d), with directional component moving clockwise.
Figure 4
Figure 4
Initial state with a single stem cell.
Figure 5
Figure 5
After 20 time steps, 0% stem cells quiescent.
Figure 6
Figure 6
After 50 time steps, 12.2% stem cells quiescent.
Figure 7
Figure 7
After 100 time steps, 43.32% stem cells quiescent.
Figure 8
Figure 8
After 200 time steps, 60.56% stem cells quiescent.
Figure 9
Figure 9
After 500 time steps, 59.22% stem cells quiescent.
Figure 10
Figure 10
Starting with 20% evenly distributed stem cells.
Figure 11
Figure 11
After 500 time steps, 58.95% stem cells quiescent.
Figure 12
Figure 12
Number of differentiated cells (y-axis) against (Φ/Ψ) ratio (x-axis) over 1000 time steps.
See this image and copyright information in PMC

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