[关键词]
[摘要]
目的 采用糖谱法,通过完全酸水解、部分酸水解和果胶酶酶解建立不同批次清半夏多糖的单糖组成和寡糖组成指纹图谱,为其质量评价提供新的思路与方法。方法 收集26批清半夏,提取非淀粉多糖。多糖经完全酸水解后,1-苯基-3-甲基-5-吡唑啉酮(1-phenyl-3-methyl-5-pyrazolone,PMP)衍生化-HPLC法建立指纹图谱,色谱条件:ODS-AQ C18色谱柱,流动相为乙腈-0.05 mol/L磷酸盐缓冲液(pH 6.8)(18∶82)等度洗脱,体积流量为1.0 mL/min,进样体积为10 μL,柱温为30 ℃,检测波长为245 nm。多糖采用部分酸水解和果胶酶酶解后,HILIC-HPLC-ELSD法建立指纹图谱,色谱条件:Pei HILIC色谱柱,流动相为乙腈-水,梯度洗脱:0~25 min,85%~65%乙腈;25~40 min,65%~50%乙腈;体积流量1.0 mL/min,柱温35 ℃,进样量10 μL。ELSD漂移管温度115 ℃,载气体积流量3.2 L/min。采用中药色谱指纹图谱相似度评价系统分析,并结合化学计量学分析样品间的差异。结果 单糖组成指纹图谱分析结果表明,样品相似度在0.781~1.000,化学计量学分析表明样品分类与药材产地有潜在的相关性,筛选出L-鼠李糖、D-甘露糖、D-半乳糖醛酸、D-葡萄糖为潜在差异标记物。寡糖指纹图谱分析结果显示,部分酸水解指纹图谱相似度为0.888~1.000,层次聚类分析(hierarchical cluster analysis,HCA)和主成分分析(principal component analysis,PCA)结果表明,甘肃与河北样品聚为一类,河南、四川、山西样品聚为另一类,甘肃S11号样品独立成类;变量重要性投影(variable importance projection,VIP)筛选出DP6、DP7、DP1和DP5作为潜在差异标记物。果胶酶酶解样品的指纹图谱相似度0.991~1.000,比部分酸水解一致性更好,进一步分析结果表明,甘肃和河南样品均呈现跨类分布;VIP值筛选得到DP5、DP2和DP4作为潜在差异标记物。结论 基于糖谱法建立的多糖的单糖和寡糖指纹图谱分析方法稳定、可靠,可为清半夏的质量评价提供重要依据。
[Key word]
[Abstract]
Objective To establish monosaccharide and oligosaccharide fingerprints of polysaccharides from different batches of Qingbanxia (Pinelliae Rhizoma Praeparatum cum Alumine, PRPCA) using sugar profiling method, including complete acid hydrolysis, partial acid hydrolysis, and pectinase digestion, thereby providing a new ideas and methods for the quality evaluation of PRPCA. Methods Non-starch polysaccharides were extracted from 26 batches of PRPCA. For monosaccharide fingerprinting, the polysaccharides were subjected to complete acid hydrolysis followed by 1-phenyl-3-methyl-5-pyrazolone (PMP) pre-column derivatization and HPLC analysis. The separation was performed on an ODS-AQ C18 column with isocratic elution using acetonitrile-0.05 mol/L phosphate buffer (pH 6.8) (18:82) at a flow rate of 1.0 mL/min. The injection volume was 10 μL, column temperature was 30 ℃, and detection wavelength was 245 nm. For oligosaccharide fingerprinting, polysaccharides were treated by partial acid hydrolysis or pectinase digestion, and then analyzed by HILIC-HPLC-ELSD on a Pei HILIC column with gradient elution (0—25 min, 85%—65% acetonitrile; 25—40 min, 65%—50% acetonitrile) at 1.0 mL/min, column temperature of 35 ℃, and injection volume of 10 μL. The ELSD drift tube temperature was set at 115 ℃ with a gas flow rate of 3.2 L/min. The differences between samples were analyzed by using the similarity evaluation system of chromatographic fingerprint of traditional Chinese medicine, and combined with chemometrics. Results The results of monosaccharide fingerprint analysis showed that the sample similarity ranged from 0.781 to 1.000. Chemometric analysis revealed a potential correlation between sample clustering and geographic origin. L-Rhamnose, D-mannose, D-galacturonic acid, and D-glucose were identified as potential differential markers. For the partial acid hydrolysis-derived oligosaccharide fingerprints, similarities ranged from 0.888 to 1.000. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) showed that samples from Gansu and Hebei clustered together, while those from Henan, Sichuan, and Shanxi formed another cluster, the Gansu S11 sample was distinctly separated. DP6, DP7, DP1, and DP5 were screened as potential differential markers via variable importance projection (VIP) analysis. The similarity of the fingerprint spectra of the samples hydrolyzed by pectinase ranged from 0.991 to 1.000, which was better than the consistency of partial acid hydrolysis. Further analysis indicated cross-cluster distribution of samples from Gansu and Henan. DP5, DP2, and DP4 were identified as potential differential markers based on VIP values. Conclusion The established monosaccharide and oligosaccharide fingerprint based on sugar profiling method is stable and reliable, offering a robust basis for the quality evaluation of PRPCA.
[中图分类号]
R283.6
[基金项目]
国家自然科学基金项目(82104547);山西省科技厅基础研究计划面上项目(202503021211214);山西省高等学校青年学术带头人项目(2024Q029);山西省科技厅青年创新人才团队(202304051001044);山西中医药大学“杏林英才计划”科技创新领域人才项目(2025XK09);山西中医药大学“杏林英才计划”科技创新领域人才项目(2025XK13);山西中医药大学科技创新能力培育计划“基础与临床合作研究专项”(2024PY-JL-3-01);山西中医药大学科技创新能力培育计划“基础与临床合作研究专项”(2024PY-JL-3-02)