{"title":"An Improved Metabolomics Workflow Enables Untargeted Data Acquisition and Targeted Data Analysis Using Liquid Chromatography–Mass Spectrometry","authors":"Yi Wu, and , Yang Wang*, ","doi":"10.1021/acs.jproteome.5c00427","DOIUrl":null,"url":null,"abstract":"<p >In this study, we present an improved metabolomics methodological framework that synergistically integrates untargeted data acquisition with targeted data analysis using chemical derivatization combined with ultrahigh performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF MS) analysis. Data-independent acquisition (DIA)-based mass spectrometry (MS1) data were used to conduct conventional untargeted analysis for biomarker discovery. The data-dependent acquisition (DDA) method was applied to obtain high-quality tandem mass spectrometry (MS2) information for quantitative data analysis. 1-Aminopiperidine (1AP) served as the derivatization reagent for sample preparation, which selectively reacts with carboxyl-containing compounds. Fatty acid (FA) standards were used to examine the derivatization reaction, and the results of LC-MS analysis showed that protonated FA + 1AP-H<sub>2</sub>O was the precursor. The ion at <i>m</i>/<i>z</i> 84.08, along with the product ion from a neutral loss of 45.02 Da, emerged as characteristic fragments, facilitating compound annotation and quantitative analysis. Method validation results demonstrated the proposed method with excellent repeatability, stability, and linearity. The lung tissue samples were successfully analyzed using this method, which was further employed to evaluate the therapeutic efficacy of Zhuye Shigao Decoction (ZSD) against lipopolysaccharide (LPS)-induced acute pneumonia in mice.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"24 9","pages":"4734–4743"},"PeriodicalIF":3.6000,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Proteome Research","FirstCategoryId":"99","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jproteome.5c00427","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, we present an improved metabolomics methodological framework that synergistically integrates untargeted data acquisition with targeted data analysis using chemical derivatization combined with ultrahigh performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF MS) analysis. Data-independent acquisition (DIA)-based mass spectrometry (MS1) data were used to conduct conventional untargeted analysis for biomarker discovery. The data-dependent acquisition (DDA) method was applied to obtain high-quality tandem mass spectrometry (MS2) information for quantitative data analysis. 1-Aminopiperidine (1AP) served as the derivatization reagent for sample preparation, which selectively reacts with carboxyl-containing compounds. Fatty acid (FA) standards were used to examine the derivatization reaction, and the results of LC-MS analysis showed that protonated FA + 1AP-H2O was the precursor. The ion at m/z 84.08, along with the product ion from a neutral loss of 45.02 Da, emerged as characteristic fragments, facilitating compound annotation and quantitative analysis. Method validation results demonstrated the proposed method with excellent repeatability, stability, and linearity. The lung tissue samples were successfully analyzed using this method, which was further employed to evaluate the therapeutic efficacy of Zhuye Shigao Decoction (ZSD) against lipopolysaccharide (LPS)-induced acute pneumonia in mice.
期刊介绍:
Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".