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基于液相色谱-高分辨质谱的石油组学数据处理流程。

A data processing pipeline for petroleomics based on liquid chromatography-high resolution mass spectrometry.

机构信息

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China; Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, PR China.

School of Computer Science & Technology, Dalian University of Technology, Dalian 116023, PR China.

出版信息

J Chromatogr A. 2022 Jun 21;1673:463194. doi: 10.1016/j.chroma.2022.463194. Epub 2022 Jun 3.

Abstract

Online liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has attracted much attention in the molecular characterization of crude oil. Neither open access nor commercially available petroleomics tools were developed specifically to process LC-HRMS data. Here, a novel data processing pipeline was specifically designed for LC-HRMS-based petroleomics data. A customizable formula database was established deriving from the detected sample, which could avoid the interference caused by a large number of redundant molecules in a conventionally theoretical molecular database. Molecular formula candidates were assigned by the formula database using a low noise threshold, and false-positive assignments were eliminated by the chromatographic retention behaviors. Multi-dimensional information was obtained, including heteroatom class, double bond equivalent (DBE), carbon number, retention time, and MS/MS spectra. The developed method was compared with a popular petroleomics software, similar relative abundance class distribution was obtained, and much more formulas of low abundant components were uniquely extracted by the developed method. Finally, it was applied to reveal variation between feed and product oils in hydrodenitrogenation. Significantly compositional and structural differences were revealed. The developed method provides a useful pipeline for molecular data mining of petroleum samples.

摘要

在线液相色谱与高分辨质谱联用(LC-HRMS)在原油的分子特征化方面引起了广泛关注。既没有开放获取的,也没有专门为处理 LC-HRMS 数据而开发的商业可用的石油组学工具。在这里,专门为基于 LC-HRMS 的石油组学数据设计了一种新的数据处理流程。从检测到的样品中建立了一个可定制的公式数据库,该数据库可以避免通常理论分子数据库中大量冗余分子造成的干扰。使用低噪声阈值,通过公式数据库分配分子公式候选物,并通过色谱保留行为消除假阳性分配。获得了多维信息,包括杂原子族、双键等价物 (DBE)、碳原子数、保留时间和 MS/MS 光谱。所开发的方法与一种流行的石油组学软件进行了比较,得到了相似的相对丰度类分布,并且所开发的方法独特地提取了更多低丰度成分的公式。最后,它被应用于揭示加氢脱氮过程中进料油和产品油之间的变化。揭示了明显的组成和结构差异。所开发的方法为石油样品的分子数据挖掘提供了一个有用的流程。

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