皮肤表面是代谢组学社区刚刚开始探索的重要样本来源。皮脂的变化,富含脂质的混合物覆盖皮肤表面,与年龄相关,性别,种族,饮食,锻炼,和疾病状态,使皮肤表面成为未来非侵入性生物标志物探索的理想样本来源,疾病诊断,和法医调查。皮脂采样的潜力主要通过电喷雾电离质谱(ESI-MS)实现,一种理想的方法来评估皮肤表面的脂质。然而,在常规分析中实施皮肤表面采样之前,需要更好地了解皮脂收集和随后的ESI-MS分析.挑战包括明确的脂质鉴定含糊不清,皮脂生产中固有的生物变异性,和方法论,分析中的技术变异性。为了克服这些障碍,避免常见的陷阱,并实现可重现性,强劲的结果,工作流程的每一部分-从样本收集到数据分析-都应该仔细考虑具体的应用。这篇评论详细介绍了皮脂采样的当前做法,样品制备,ESI-MS数据采集,和数据分析,它提供了从皮肤表面获取有意义的脂质组学数据集的重要考虑因素。法医研究人员调查皮脂作为消除嫌疑人的手段,而不是足够的指纹脊细节或数据库匹配,以及对非侵入性生物标志物探索感兴趣的临床研究人员,疾病诊断,和治疗监测,可以将此评论用作开发最佳实践方法的指南。
The skin surface is an important sample source that the metabolomics community has only just begun to explore. Alterations in
sebum, the lipid-rich mixture coating the skin surface, correlate with age, sex, ethnicity, diet, exercise, and disease state, making the skin surface an ideal sample source for future noninvasive biomarker exploration, disease diagnosis, and forensic investigation. The potential of
sebum sampling has been realized primarily via electrospray ionization mass spectrometry (ESI-MS), an ideal approach to assess the skin surface lipidome. However, a better understanding of
sebum collection and subsequent ESI-MS analysis is required before skin surface sampling can be implemented in routine analyses. Challenges include ambiguity in definitive lipid identification, inherent biological variability in
sebum production, and methodological, technical variability in analyses. To overcome these obstacles, avoid common pitfalls, and achieve reproducible, robust outcomes, every portion of the workflow-from sample collection to data analysis-should be carefully considered with the specific application in mind. This review details current practices in
sebum sampling, sample preparation, ESI-MS data acquisition, and data analysis, and it provides important considerations in acquiring meaningful lipidomic datasets from the skin surface. Forensic researchers investigating sebum as a means for suspect elimination in lieu of adequate fingerprint ridge detail or database matches, as well as clinical researchers interested in noninvasive biomarker exploration, disease diagnosis, and treatment monitoring, can use this review as a guide for developing methods of best-practice.