Nonnegative principal component analysis in thin layer fingerprint screening: A case of <i>Gentiana</i> extracts from <i>in vitro</i> cultures
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Twenty-one species of Gentiana L. were successfully grown <i>in vitro</i> in the same conditions and 72 samples of various cultures of these species (root, shoots, cotyledon callus, hypocotyl callus, and root callus) were obtained. The investigated species were as follows: <i>G. affinis</i>, <i>G. andrewsii</i>, <i>G. bhutanica</i>, <i>G. burseri</i>, <i>G. cachemirica</i>, <i>G. capitata</i>, <i>G. crassicaulis</i>, <i>G. dahurica</i>, <i>G. decumbens</i>, <i>G. freyniana</i>, <i>G. frigida</i>, <i>G. gelida</i>, <i>G. grossheimii</i>, <i>G. kurroo</i>, <i>G. macrophylla</i>, <i>G. paradoxa</i>, <i>G. robusta</i>, <i>G. scabra</i>, <i>G. septemfida</i>, <i>G. siphonantha</i>, and <i>G. tianschanica</i>. The obtained samples were extracted with methanol–acetone–water (3:1:1) mixture, evaporated to dryness, and subjected to TLC on silica gel with mobile phase ethyl acetate–methanol–water (8:2:2) in sandwich mode. Data fusion of two densitometric modes: extinction at 254 nm and fluorescence at 312 nm (emission above 370 nm) were used as a fingerprint of each sample. Densitograms were denoised, subjected to baseline removal, warped, and analyzed with principal component analysis (PCA), hierarchical cluster analysis and—the novel proposal—nonnegative PCA. This allowed to split negatively intercorrelated fingerprint features to subsequent principal components (PCs), which increases the number of PCs required to see the same information, but these PCs are much more informative.
本研究成功将21种龙胆属（Gentiana L.）植物在统一条件下进行离体（in vitro）培养，共获取对应物种的72份不同培养物样本，涵盖根、嫩枝、子叶愈伤组织、下胚轴愈伤组织及根愈伤组织。供试物种如下：近缘龙胆（G. affinis）、安德鲁龙胆（G. andrewsii）、不丹龙胆（G. bhutanica）、布尔瑟龙胆（G. burseri）、克什米尔龙胆（G. cachemirica）、头状龙胆（G. capitata）、粗茎龙胆（G. crassicaulis）、达乌里龙胆（G. dahurica）、铺地龙胆（G. decumbens）、弗赖恩龙胆（G. freyniana）、耐寒龙胆（G. frigida）、冰地龙胆（G. gelida）、格罗西海姆龙胆（G. grossheimii）、库罗龙胆（G. kurroo）、大叶龙胆（G. macrophylla）、奇异龙胆（G. paradoxa）、健壮龙胆（G. robusta）、粗糙龙胆（G. scabra）、七裂龙胆（G. septemfida）、管花龙胆（G. siphonantha）及天山龙胆（G. tianschanica）。 将获取的样本采用甲醇-丙酮-水（体积比3:1:1）混合溶剂进行萃取，经减压蒸发至干后，以硅胶为固定相、乙酸乙酯-甲醇-水（体积比8:2:2）为展开剂，采用夹心式展开模式进行薄层色谱（Thin Layer Chromatography, TLC）分离。以254 nm波长下的吸光度值与312 nm波长下的荧光强度（发射波长大于370 nm）两种密度扫描模式的数据融合结果，作为每份样本的指纹图谱。 对得到的密度扫描图谱进行去噪、基线校正及峰位扭曲校正后，分别采用主成分分析（Principal Component Analysis, PCA）、系统聚类分析以及本研究提出的非负主成分分析（nonnegative PCA）进行数据分析。该方法可将呈负相关的指纹特征分配至不同的主成分（Principal Components, PCs）中，虽会增加表征全部指纹信息所需的主成分数量，但所得主成分的信息携带量显著提升。
