近年來，代謝體學已被視為最新穎的體學技術，成功打開了解生物機制和尋找生物指標的途徑並提供新的見解，已有多種生物樣品被應用於代謝體研究，例如血液和尿液。然而，雖然這些生物樣本富含許多化學物質，但其高度動態性使得樣本收集的時間點成為挑戰。因此，頭髮具有長期及回顧性分析的特性，已成為研究外在暴露和內生性代謝變化的分析樣本。儘管已有許多研究指出樣品製備在代謝體研究中扮演關鍵的角色，但目前仍尚未建立標準化的頭髮萃取程序。
本研究利用非標的代謝體學方法，系統性的評估了用於頭髮代謝體的萃取程序，透過比較訊號數目、訊號強度、及涵蓋的代謝物類型等，進一步比較不同萃取程序，包括：三種pH值（酸性、中性和鹼性）、六種萃取溶液（甲醇、乙腈、丙酮、磷酸鹽緩衝鹽溶液、去離子水和二氯甲烷）、不同比例之萃取溶液及序列萃取，並評估了萃取時間（15、45、60、120、240和480分鐘）。最佳化的頭髮萃取程序為利用甲醇：磷酸鹽緩衝鹽溶液50:50（v / v）在 55°C下進行超音波萃取240分鐘。進一步利用此最佳化的萃取程序結合結構鑑定軟體，探討頭髮代謝體組成，根據不同鑑定等級分別鑑定出171和853個可能的代謝物結構、及414個化學式，並包含多種類型的化學物質，實現了頭髮代謝體分析的潛力。在本研究中，我們利用非標的代謝體學策略建立了一個最佳化的頭髮萃取程序，以提高訊號數目、訊號強度、涵蓋廣泛的代謝物類型，並進一步探討頭髮代謝體的組成。

Metabolomics has been featured as the state-of-the-art technology that successfully opens the paths to understanding biological mechanisms and facilitating biomarker discovery over recent years. A variety of biological samples has been applied to profile the metabolome, such as blood and urine. However, the metabolome of these biofluids includes a wide array of chemical compounds that are subject to very rapid changes. The fluctuations are often preserved merely for a short span of time. Hair has thus emerged as a valuable analytical specimen for the long-term and retrospective analysis of both xenobiotic exposure and endogenous perturbations. Although sample preparation had been known to play a crucial role in metabolomics analysis, there is currently no standardized extraction procedure for hair analysis. Here, we systemically evaluated the extraction procedures for investigating hair metabolome using an untargeted metabolomics approach. Three pH values (acidic, neutral, and basic) in aqueous solution, six extraction solvents (methanol, acetonitrile, acetone, phosphate-buffered saline, deionized water, and dichloromethane), different compositions of selected solvent mixtures and their sequential extraction, and a series of extraction times (15, 45, 60, 120, 240, and 480 min) were evaluated by comparing the features and the identified compounds. The ideal condition for hair extraction is ultrasonic-assisted extraction with methanol:phosphate-buffered saline 50:50 (v/v) under 55°C for 240 min. The optimized extraction strategy was then coupled with structure annotation tools for hair metabolome profiling. Hair metabolite identification was achieved as the annotations of 171 probable structures and 853 tentative structures as well as the assignments of 414 unequivocal molecular formulae. In conclusion, we established an optimized extraction strategy to investigate the composition of the metabolome, maximize the signal abundance, and guarantee broader coverages of detected metabolites in a straightforward approach.

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