Wang Hong-Xun, Yi Yang, Sun Jie, Lamikanra Olusola, Min Ting
College of Biology & Pharmaceutical Engineering, Wuhan Polytechnic University Wuhan 430023 PR China
College of Food Science & Engineering, Wuhan Polytechnic University Wuhan 430023 PR China
RSC Adv. 2018 May 4;8(30):16574-16584. doi: 10.1039/c8ra01104d. eCollection 2018 May 3.
Thirty-nine polysaccharides isolated from different parts of 13 lotus root varieties were characterized with fingerprint and chemometrics analyses to explore their similarity and diversity. The physicochemical features of lotus root polysaccharides (LRPs) were found to be the following: LRPs contained mainly polysaccharides (5.94 kDa) and polysaccharide-protein complexes (11.57 kDa and 5.30 kDa); their carbohydrates were composed of mannose, rhamnose, glucuronic acid, galacturonic acid, glucose, galactose and arabinose approximately in the molar ratio of 0.19 : 0.14 : 0.08 : 0.17 : 6.49 : 1.00 : 0.16; and node LRPs possessed more binding proteins and uronic acids than both flesh and peel LRPs. Their fingerprints based on Fourier-transform infrared spectroscopy, pre-column derivatization high-performance liquid chromatography and high performance size-exclusion chromatography all exhibited relatively high similarities, contributing to the common figerprint models which could be utilized as references for the identification of LPRs. In addition, the fingerprint characteristics associated with the between-group variability of LRPs in the score plots derived from multivariate analytical models might indicate which variety or part of lotus root they were isolated from. Therefore, multi-fingerprinting techniques have the potential to be applied to the identification and quality control of LRPs.
对从13个莲藕品种不同部位分离得到的39种多糖进行指纹图谱和化学计量学分析,以探究它们的相似性和多样性。发现莲藕多糖(LRP)的理化特性如下:LRP主要包含多糖(5.94 kDa)和多糖 - 蛋白质复合物(11.57 kDa和5.30 kDa);其碳水化合物由甘露糖、鼠李糖、葡萄糖醛酸、半乳糖醛酸、葡萄糖、半乳糖和阿拉伯糖组成,摩尔比约为0.19∶0.14∶0.08∶0.17∶6.49∶1.00∶0.16;并且节点LRP比果肉和果皮LRP拥有更多的结合蛋白和糖醛酸。基于傅里叶变换红外光谱、柱前衍生化高效液相色谱和高效尺寸排阻色谱的指纹图谱均表现出较高的相似性,有助于建立通用指纹图谱模型,可作为鉴定LPR的参考。此外,在多变量分析模型的得分图中,与LRP组间变异性相关的指纹特征可能表明它们是从哪个莲藕品种或部位分离得到的。因此,多指纹技术有潜力应用于LPR的鉴定和质量控制。