Purdue Metabolite Profiling Facility, Purdue University, West Lafayette, IN 47907, USA.
Sao Paulo State University Julio de Mesquita Filho, Institute of Chemistry, Araraquara, Sao Paulo, Brazil.
Mol Omics. 2024 Jun 10;20(5):296-321. doi: 10.1039/d3mo00214d.
Omics analyses collectively refer to the possibility of profiling genetic variants, RNA, epigenetic markers, proteins, lipids, and metabolites. The most common analytical approaches used for detecting molecules present within biofluids related to metabolism are vibrational spectroscopy techniques, represented by infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies and mass spectrometry (MS). Omics-based assessments utilizing MS are rapidly expanding and being applied to various scientific disciplines and clinical settings. Most of the omics instruments are operated by specialists in dedicated laboratories; however, the development of miniature portable omics has made the technology more available to users for field applications. Variations in molecular information gained from omics approaches are useful for evaluating human health following environmental exposure and the development and progression of numerous diseases. As MS technology develops so do statistical and machine learning methods for the detection of molecular deviations from personalized metabolism, which are correlated to altered health conditions, and they are intended to provide a multi-disciplinary overview for researchers interested in adding multiomic analysis to their current efforts. This includes an introduction to mass spectrometry-based omics technologies, current state-of-the-art capabilities and their respective strengths and limitations for surveying molecular information. Furthermore, we describe how knowledge gained from these assessments can be applied to personalized medicine and diagnostic strategies.
组学分析通常是指对遗传变异、RNA、表观遗传标记物、蛋白质、脂质和代谢物进行分析。用于检测与代谢相关的生物体液中存在的分子的最常见分析方法是振动光谱技术，包括红外、拉曼和核磁共振（NMR）光谱学和质谱（MS）。基于 MS 的组学评估正在迅速扩展，并应用于各种科学领域和临床环境。大多数组学仪器都由专门实验室的专家操作；然而，微型便携式组学的发展使得该技术更易于用户在现场应用。从组学方法获得的分子信息变化可用于评估人类在环境暴露后的健康状况以及许多疾病的发展和进展。随着 MS 技术的发展，用于检测个性化代谢中与健康状况改变相关的分子偏差的统计和机器学习方法也在发展，这旨在为有兴趣将多组学分析添加到其当前工作中的研究人员提供多学科概述。这包括介绍基于质谱的组学技术、当前的最新技术水平以及它们各自在调查分子信息方面的优势和局限性。此外，我们还描述了如何将这些评估中获得的知识应用于个性化医疗和诊断策略。
