Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, 46556-5670, United States.
Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, 46556-5670, United States.
Talanta. 2020 Apr 1;210:120645. doi: 10.1016/j.talanta.2019.120645. Epub 2019 Dec 17.
Metabolomics, the study of metabolic profiles in a biological sample, has seen rapid growth due to advances in measurement technologies such as mass spectrometry (MS). While MS metabolite reference libraries have been generated for metabolomics applications, mass spectra alone are unable to unambiguously identify many metabolites in a sample; these unidentified compounds are typically annotated as "features". Surface-enhanced Raman spectroscopy (SERS) is an interesting technology for metabolite identification based on vibrational spectra. However, no reports have been published that present SERS metabolite spectra from chemical libraries. In this paper, we demonstrate that an untargeted approach utilizing citrate-capped silver nanoparticles yields SERS spectra for 20% of 80 compounds chosen randomly from a commercial metabolite library. Furthermore, prescreening of the metabolites according to chemical functionality allowed for the efficient identification of samples within the library that yield distinctive SERS spectra under our experimental conditions. Last, we present a reference database of 63 metabolite SERS spectra for use as an identification tool in metabolomics studies; this set includes 30 metabolites that have not had previously published SERS spectra.
代谢组学是研究生物样本中代谢物谱的一门学科,由于质谱(MS)等测量技术的进步,其得到了快速发展。虽然已经为代谢组学应用生成了 MS 代谢物参考文库,但仅凭质谱本身无法明确鉴定样品中的许多代谢物;这些未被鉴定的化合物通常被注释为“特征”。表面增强拉曼光谱(SERS)是一种基于振动光谱的代谢物鉴定的有趣技术。然而,目前还没有报道表明从化学文库中获得了 SERS 代谢物光谱。在本文中,我们证明了一种非靶向方法,利用柠檬酸封端的银纳米粒子可获得 80 种随机选择的商业代谢物文库中 20%化合物的 SERS 光谱。此外,根据化学功能对代谢物进行预筛选,可在我们的实验条件下对文库中产生独特 SERS 光谱的样品进行有效鉴定。最后,我们提供了一个包含 63 种代谢物 SERS 光谱的参考数据库,可用作代谢组学研究中的鉴定工具;这组数据包括 30 种以前没有发表过 SERS 光谱的代谢物。