Please use this identifier to cite or link to this item:
|Title:||Systematic experimental design for bioprocess characterization: elucidating transient effects of multi-cytokine contributions on erythroid differentiation||Authors:||Lim, Mayasari
Mantalaris, Athanasios (Sakis)
|Issue Date:||2012||Source:||Lim, M., Shunjie, C., Panoskaltsis, N.,& Mantalaris, A. (2012). Systematic experimental design for bioprocess characterization: Elucidating transient effects of multi-cytokine contributions on erythroid differentiation. Biotechnology and Bioprocess Engineering, 17(1), 218-226.||Series/Report no.:||Biotechnology and bioprocess engineering||Abstract:||In vitro differentiation of hematopoietic stem cells (HSCs) is a highly dynamic process whereby contributions of exogenous cytokines vary at each stage of differentiation. In this study, we present erythroid differentiation as three progressive yet independent stages and aim to elucidate transient contributions from stem cell factor (SCF), insulin-growth factor II (IGF-II), and erythropoietin (EPO). This will be accomplished using the Taguchi design and response surface methodology (RSM). We found that cultures with high process variability (noise factors), such as those in primary cell cultures, pose limitations on the effectiveness of RSM and result in inconsistencies in empirical models developed for elucidating transient effects. However, the Taguchi design—which showed greater robustness in accommodating for noise factors—successfully identified significant main and interactive contributions at each differentiation stage, thus highlighting the dynamic roles of each cytokine. The Taguchi analysis suggested high IGF-II dependency during early erythroid differentiation, with an antagonistic effect in the presence of EPO. At mid-stage differentiation, the roles of SCF and EPO dominate those of IGF-II, and the former act independently. Finally, toward erythroid maturation, only EPO plays a significant role. Although process outcomes from the Taguchi analysis were semi-quantitative, this approach provides a path for overcoming cell culture and sample-to-sample variability and can therefore be utilized with many cell culture applications in order to understandcomplex and intricate process relationships.||URI:||https://hdl.handle.net/10356/99471
|DOI:||10.1007/s12257-011-0422-y||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||SCBE Journal Articles|
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.