Neural Network Analysis of Ex-vivo Expansion of Hematopoietic Stem Cells

Robust, quantitative tools for modelling ex-vivo expansion of haematopoietic stem cells and progenitors

Despite substantial research activity on bioreactor design and experiments, there are very few reports of modelling tools that can be used to generate predictive models describing how bioreactor parameters affect performance. New developments in mathematics, such as sparse Bayesian feature selection methods and nonlinear model-free modelling regression methods, offer considerable promise for modelling diverse types of data. The utility of these mathematical tools in stem cell biology are demonstrated by analysis of a large set of bioreactor data derived from the literature. In spite of the diversity of the data sources, and the inherent difficulty in representing bioreactor variables, these modelling methods were able to develop robust, quantitative, predictive models. These models relate bioreactor operational parameters to the degree of expansion of haematopoietic stem cells or their progenitors, and also identify the bioreactor variables that are most likely to affect performance across many experiments. These methods show substantial promise in assisting the design and optimisation of stem cell bioreactors.

Optimization of primary culture condition for mesenchymal stem cells derived from umbilical cord blood with factorial design

Mesenchymal stem cells (MSCs) can not only support the expansion of hematopoietic stem cells in vitro, but also alleviate complications and accelerate recovery of hematopoiesis during hematopoietic stem cell transplantation. However, it proved challenging to culture MSCs from umbilical cord blood (UCB) with a success rate of 20-30%. Many cell culture parameters contribute to this outcome and hence optimization of culture conditions is critical to increase the probability of success. In this work, fractional factorial design was applied to study the effect of cell inoculated density, combination and dose of cytokines, and presence of serum and stromal cells. The cultured UCB-MSC-like cells were characterized by flow cytometry and their multilineage differentiation potentials were tested. The optimal protocol was identified achieving above 90% successful outcome: 2 x 10(6) cells/mL mononuclear cells inoculated in Iscove's modified Dulbecco's medium supplied with 10% FBS, 15 ng/mL IL-3, and 5 ng/mL Granulocyte-macrophage colony-stimulating factor (GM-CSF). Moreover, the UCB-MSC-like cells expressed MSC surface markers of CD13, CD29, CD105, CD166, and CD44 positively, and CD34, CD45, and human leukocyte antigens-DR (HLA-DR) negatively. Meanwhile, these cells could differentiate into osteoblasts, chondrocytes, and adipocytes similarly to MSCs derived from bone marrow. In conclusion, we have developed an efficient protocol for the primary culture of UCB-MSCs by adding suitable cytokines into the culture system.