Rosa Filipa, Sales Kevin C, Carmelo Joana G, Fernandes-Platzgummer Ana, da Silva Cláudia L, Lopes Marta B, Calado Cecília R C
Engineering Faculty, Catholic University of Portugal, Rio de Mouro, Portugal.
Dept. of Bioengineering and iBB-Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade De Lisboa, Av. Rovisco Pais, Lisboa, 1049-001, Portugal.
Biotechnol Prog. 2016 Mar;32(2):447-55. doi: 10.1002/btpr.2215. Epub 2016 Feb 12.
Human mesenchymal stem/stromal cells (MSCs) have received considerable attention in the field of cell-based therapies due to their high differentiation potential and ability to modulate immune responses. However, since these cells can only be isolated in very low quantities, successful realization of these therapies requires MSCs ex-vivo expansion to achieve relevant cell doses. The metabolic activity is one of the parameters often monitored during MSCs cultivation by using expensive multi-analytical methods, some of them time-consuming. The present work evaluates the use of mid-infrared (MIR) spectroscopy, through rapid and economic high-throughput analyses associated to multivariate data analysis, to monitor three different MSCs cultivation runs conducted in spinner flasks, under xeno-free culture conditions, which differ in the type of microcarriers used and the culture feeding strategy applied. After evaluating diverse spectral preprocessing techniques, the optimized partial least square (PLS) regression models based on the MIR spectra to estimate the glucose, lactate and ammonia concentrations yielded high coefficients of determination (R(2) ≥ 0.98, ≥0.98, and ≥0.94, respectively) and low prediction errors (RMSECV ≤ 4.7%, ≤4.4% and ≤5.7%, respectively). Besides PLS models valid for specific expansion protocols, a robust model simultaneously valid for the three processes was also built for predicting glucose, lactate and ammonia, yielding a R(2) of 0.95, 0.97 and 0.86, and a RMSECV of 0.33, 0.57, and 0.09 mM, respectively. Therefore, MIR spectroscopy combined with multivariate data analysis represents a promising tool for both optimization and control of MSCs expansion processes. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:447-455, 2016.
人间充质干/基质细胞（MSCs）因其高分化潜能和调节免疫反应的能力，在基于细胞的治疗领域受到了广泛关注。然而，由于这些细胞只能以非常低的数量分离出来，因此要成功实现这些治疗，需要在体外扩增MSCs以达到相关的细胞剂量。代谢活性是MSCs培养过程中经常使用昂贵的多分析方法监测的参数之一，其中一些方法耗时较长。本研究通过与多变量数据分析相关的快速且经济的高通量分析，评估了中红外（MIR）光谱法在监测无血清培养条件下在转瓶中进行的三种不同MSCs培养过程中的应用，这三种培养过程在所用微载体类型和培养补料策略上有所不同。在评估了多种光谱预处理技术后，基于MIR光谱估计葡萄糖、乳酸和氨浓度的优化偏最小二乘（PLS）回归模型具有较高的决定系数（分别为R(2)≥0.98、≥0.98和≥0.94）和较低的预测误差（RMSECV分别≤4.7%、≤4.4%和≤5.7%）。除了适用于特定扩增方案的PLS模型外，还建立了一个对这三个过程同时有效的稳健模型来预测葡萄糖、乳酸和氨，其R(2)分别为0.95、0.97和0.86，RMSECV分别为0.33、0.57和0.09 mM。因此，MIR光谱法与多变量数据分析相结合是优化和控制MSCs扩增过程的一种有前途的工具。©2016美国化学工程师学会生物技术进展，32:447 - 455，2016。
