TY  - JOUR
AU  - Dutton, Renly
AU  - Abdi, Frank
AU  - Minnetyan, Levon
AU  - Sherley, James L.
PY  - 2020
DA  - 2020/08/28
TI  - A Computational Simulation Technology for Specific Counting of Perinatal and Postnatal Human Tissue Stem Cells for Transplantation Medicine
JO  - OBM Transplantation
SP  - 117
VL  - 04
IS  - 03
AB  - Although tissue stem cells are essential for the maintenance, renewal, and repair of vertebrate organs and tissues, previously, the simple act of counting them has not been possible. For more than a half-century, progress in tissue stem cell research and medicine has been undermined by the lack of a means to determine tissue stem cell number. In particular, a major unmet need for stem cell transplantation medicine has been a way to quantify the specific dosage of tissue stem cell treatments. The counting problem persists because no biomarkers are known that identify tissue stem cells specifically, without also counting their more abundant committed progenitor progeny cells. Here, we describe integration of principles of tissue stem cell asymmetric self-renewal kinetics with computational simulation to achieve specific and accurate counting of therapeutic tissue stem cells. The asymmetric self-renewal kinetics of tissue stem cells is rate-limiting for the rate and extent of proliferation of primary tissue cell cultures. Based on this essential relationship, we show that simple total cell count data from primary cell cultures, passaged until achieving terminal proliferation arrest, are determined by tissue stem cell kinetics factors, including viability, cell cycle time, self-renewal rate, and number. We describe a Probabilistic Stem Cell Kinetics (PSCK) model and Random Input Factor Searching (RIFS) software that can be combined to discover these previously inaccessible factors. The method is validated by several orthogonal strategies, including comparisons to the currently best available method for estimating a tissue stem cell fraction, independent tests for asymmetrically self-renewing cells, tissue stem cell fractionation, and treatments with tissue stem cell-active agents. A major advance of the method is the discovery of simple algorithms that allow rapid convenient computation of the specific tissue stem cell fraction of complex human tissue cell preparations from simple population doubling time data.
SN  - 2577-5820
UR  - https://doi.org/10.21926/obm.transplant.2003117
DO  - 10.21926/obm.transplant.2003117
ID  - Dutton2020
ER  -