Natural Products Laboratory, Institute of Biology, Leiden University, Leiden 2333 BE, the Netherlands.
Horticulture and Product Physiology, Department of Plant Sciences, Wageningen University & Research, PO Box 16, 6700 AA, Wageningen, the Netherlands.
J Chromatogr A. 2023 Nov 8;1710:464425. doi: 10.1016/j.chroma.2023.464425. Epub 2023 Sep 29.
The technological advances of analytical instrumentation and techniques has laid the ground for the rapid expansion of metabolomics or in a wider sense, untargeted analysis applied to life sciences themes. However, the objective of identifying all existing metabolites within organisms remains a daunting challenge. All analytical techniques exhibit varying degrees of sensitivity and versatility for the detection of metabolites and none of the existing analytical platforms can be expected to be ideal for exhaustive chemical profiling. Planar liquid chromatography, and in particular, high performance thin layer chromatography (HPTLC), has been used for chemical profiling of natural products in conjunction with metabolomics. HPTLC has specific advantages which include its ability to generate reliable chemical fingerprinting data and facilitate preparative work for metabolite isolation during later stages of metabolomics analysis. In this study, we investigated the chemical profiles of four commercially available basil cultivars, namely Dolly, Emily, Keira, and Rosie. We used HPTLC as the primary analytical tool for the separation of basil cultivars based on detected metabolites, and then compared the results with those obtained with other analytical platforms. We identified the characteristic marker compounds of each basil cultivar from the HPTLC plates and validated their potential using LC-MS and GC-MS analyses as a metabolomics tool. Firstly, we compared the HPTLC data of the four cultivars, obtained with two systems that used silica gel 60 and two mobile phases composed of toluene-EtOAc (8:2, v/v) and EtOAc-formic acid-acetic acid-water (100:11:11:27, v/v), with H NMR data to evaluate their separation power. Despite providing lower resolution and detecting fewer compounds, the HPTLC separation power was comparable, and in some cases even better than that of H NMR. Additionally, we investigated the potential of HPTLC as a tool for chemical fingerprinting and demonstrated its suitability for preparative purposes that are essential for identifying metabolites in mixture analysis. Metabolites were easily isolated from sample mixtures, and identified with the assistance of GC-MS, LC-MS, and TLC-densitometry.. Several marker compounds were thus identified, including 2,4 di-tertbutylphenol, palmitic acid, hexadecanamide, 9-octadecenamide, squalene, hentriacontane, methyl 3-(3,5-ditert‑butyl‑4-hydroxyphenyl)propanoic acid, sagerinic acid, and cyanidin-3-O-sophoroside.
分析仪器和技术的技术进步为代谢组学或更广泛意义上的、应用于生命科学主题的非靶向分析的快速扩展奠定了基础。然而，识别生物体中所有现有代谢物的目标仍然是一个艰巨的挑战。所有分析技术对代谢物的检测都具有不同程度的灵敏度和多功能性，并且不能期望现有的任何分析平台都能理想地进行详尽的化学剖析。平面液相色谱，特别是高效薄层色谱（HPTLC），已与代谢组学一起用于天然产物的化学剖析。HPTLC 具有特定的优势，包括能够生成可靠的化学指纹数据，并为代谢组学分析后期的代谢物分离提供便利。在这项研究中，我们研究了四种市售罗勒品种（即 Dolly、Emily、Keira 和 Rosie）的化学特征。我们使用 HPTLC 作为主要分析工具，根据检测到的代谢物分离罗勒品种，然后将结果与其他分析平台的结果进行比较。我们从 HPTLC 板上鉴定出每个罗勒品种的特征标记化合物，并使用 LC-MS 和 GC-MS 分析作为代谢组学工具验证其潜在用途。首先，我们将两种使用硅胶 60 和两种由甲苯-EtOAc（8:2，v/v）和 EtOAc-甲酸-乙酸-水（100:11:11:27，v/v）组成的流动相的系统获得的四种品种的 HPTLC 数据与 H NMR 数据进行比较，以评估其分离能力。尽管分辨率较低且检测到的化合物较少，但 HPTLC 的分离能力相当，在某些情况下甚至更好。此外，我们研究了 HPTLC 作为化学指纹图谱工具的潜力，并证明了其适合于混合物分析中识别代谢物的制备目的。代谢物可以很容易地从样品混合物中分离出来，并在 GC-MS、LC-MS 和 TLC-密度计的帮助下进行鉴定。因此，确定了几个标记化合物，包括 2,4-二叔丁基苯酚、棕榈酸、十六烷酰胺、9-十八烯酰胺、角鲨烯、三十烷醇、甲基 3-(3,5-二叔丁基-4-羟基苯基)丙酸、sagerinic 酸和矢车菊素-3-O-槐糖苷。
