He Yuchen, Rashan Edrees H, Linke Vanessa, Shishkova Evgenia, Hebert Alexander S, Jochem Adam, Westphall Michael S, Pagliarini David J, Overmyer Katherine A, Coon Joshua J
Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States.
Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States.
Anal Chem. 2021 Mar 9;93(9):4217-4222. doi: 10.1021/acs.analchem.0c04764. Epub 2021 Feb 22.
Mass spectrometry (MS) serves as the centerpiece technology for proteome, lipidome, and metabolome analysis. To gain a better understanding of the multifaceted networks of myriad regulatory layers in complex organisms, integration of different multiomic layers is increasingly performed, including joint extraction methods of diverse biomolecular classes and comprehensive data analyses of different omics. Despite the versatility of MS systems, fractured methodology drives nearly all MS laboratories to specialize in analysis of a single ome at the exclusion of the others. Although liquid chromatography-mass spectrometry (LC-MS) analysis is similar for different biomolecular classes, the integration on the instrument level is lagging behind. The recent advancements in high flow proteomics enable us to take a first step towards integration of protein and lipid analysis. Here, we describe a technology to achieve broad and deep coverage of multiple molecular classes simultaneously through multi-omic single-shot technology (MOST), requiring only one column, one LC-MS instrument, and a simplified workflow. MOST achieved great robustness and reproducibility. Its application to a study consisting of 20 conditions revealed 2842 protein groups and 325 lipids and potential molecular relationships.
质谱(MS)是蛋白质组、脂质组和代谢组分析的核心技术。为了更好地理解复杂生物体中众多调控层的多方面网络,越来越多地进行不同多组学层的整合,包括不同生物分子类别的联合提取方法和不同组学的综合数据分析。尽管质谱系统具有通用性,但破碎的方法使得几乎所有质谱实验室都专注于单一组学的分析而排除其他组学。虽然液相色谱 - 质谱(LC - MS)分析对于不同生物分子类别来说是相似的,但仪器层面的整合却滞后了。高流量蛋白质组学的最新进展使我们能够朝着蛋白质和脂质分析的整合迈出第一步。在这里,我们描述了一种通过多组学单次技术(MOST)同时实现对多种分子类别的广泛而深入覆盖的技术,该技术仅需要一根柱子、一台LC - MS仪器和简化的工作流程。MOST具有很高的稳健性和重现性。将其应用于一项包含20种条件的研究中,发现了2842个蛋白质组、325种脂质以及潜在的分子关系。