Department of Chemistry Materials and Chemical Engineering "G. Natta", Politecnico di Milano, Milan, Italy.
Environmental Research Laboratory, National Center for Scientific Research "Demokritos", Agia Paraskevi Attikis, 15310, Greece.
Sci Rep. 2017 Nov 17;7(1):15808. doi: 10.1038/s41598-017-16043-8.
Cell metabolism is a key determinant factor for the pluripotency and fate commitment of Stem Cells (SCs) during development, ageing, pathological onset and progression. We derived and cultured selected subpopulations of rodent fetal, postnatal, adult Neural SCs (NSCs) and postnatal glial progenitors, Olfactory Ensheathing Cells (OECs), respectively from the subventricular zone (SVZ) and the olfactory bulb (OB). Cell lysates were analyzed by proton Nuclear Magnetic Resonance (H-NMR) spectroscopy leading to metabolites identification and quantitation. Subsequent multivariate analysis of NMR data by Principal Component Analysis (PCA), and Partial Least Square Discriminant Analysis (PLS-DA) allowed data reduction and cluster analysis. This strategy ensures the definition of specific features in the metabolic content of phenotypically similar SCs sharing a common developmental origin. The metabolic fingerprints for selective metabolites or for the whole spectra demonstrated enhanced peculiarities among cell types. The key result of our work is a neat divergence between OECs and the remaining NSC cells. We also show that statistically significant differences for selective metabolites characterizes NSCs of different ages. Finally, the retrived metabolome in cell cultures correlates to the physiological SC features, thus allowing an integrated bioengineering approach for biologic fingerprints able to dissect the (neural) SC molecular specificities.
细胞代谢是决定干细胞(SCs)多能性和命运的关键因素,在发育、衰老、病理发生和进展过程中都是如此。我们分别从侧脑室下区(SVZ)和嗅球(OB)中分离和培养了选定的啮齿动物胎儿、出生后、成年神经干细胞(NSCs)和出生后神经胶质前体细胞、嗅鞘细胞(OECs)的亚群。通过质子磁共振波谱(H-NMR)分析细胞裂解物,鉴定和定量代谢物。随后通过主成分分析(PCA)和偏最小二乘判别分析(PLS-DA)对 NMR 数据进行多元分析,实现数据减少和聚类分析。这种策略确保了在具有共同发育起源的表型相似的SCs 中定义代谢物内容的特定特征。选择性代谢物或整个光谱的代谢指纹显示出细胞类型之间增强的独特性。我们工作的关键结果是 OECs 和剩余 NSC 细胞之间的明显分离。我们还表明,不同年龄的 NSCs 中选择性代谢物的统计学差异特征明显。最后,细胞培养中恢复的代谢组与生理SCs 特征相关,从而允许采用集成的生物工程方法来获取生物指纹,以剖析(神经)SCs 的分子特异性。