Identification of metabolite biomarkers in Salmonella enteritidis-contaminated chickens using UHPLC-QTRAP-MS-based targeted metabolomics
文献类型： 外文期刊
作者： Chen, Lan 1 ; Zhang, Tao 2 ; Ding, Hao 1 ; Xie, Xing 4 ; Zhu, Yali 2 ; Dai, Guojun 2 ; Gao, Yushi 1 ; Zhang, Genxi 2 ; Xie, Kaizhou 1 ;
作者机构： 1.Yangzhou Univ, Coll Vet Med, Yangzhou 225009, Peoples R China
2.Yangzhou Univ, Coll Anim Sci & Technol, Yangzhou 225009, Peoples R China
3.Yangzhou Univ, Joint Int Res Lab Agr & Agriprod Safety MOE, Yangzhou 225009, Peoples R China
4.Jiangsu Acad Agr Sci, Inst Vet Med, Key Lab Vet Biol Engn & Technol, Minist Agr, Nanjing 210000, Peoples R China
5.Chinese Acad Agr Sci, Poultry Inst, Yangzhou 225009, Peoples R China
6.Yangzhou Univ, Coll Anim Sci & Technol, 48 East Wenhui Rd, Yangzhou 225009, Jiangsu, Peoples R China
关键词： S. enteritidis; Chicken; UHPLC-QTRAP-MS; Metabolite biomarkers
期刊名称：FOOD CHEMISTRY-X （ 影响因子：6.1； 五年影响因子：6.4 ）
ISSN： 2590-1575
年卷期： 2023 年 20 卷
页码：
收录情况： SCI
摘要： This study aimed to characterize the metabolic profile of Salmonella enteritidis (S. enteritidis) in chicken matrix and to identify metabolic biomarkers of S. enteritidis in chicken. The UHPLC-QTRAP-MS high-throughput targeted metabolomics approach was employed to analyze the metabolic profiles of contaminated and control group chickens. A total of 348 metabolites were quantified, and the application of deep learning least absolute shrinkage and selection operator (LASSO) modelling analysis obtained eight potential metabolite biomarkers for S. enteritidis. Metabolic abundance change analysis revealed significantly enriched abundances of anthranilic acid, l-pyroglutamic acid, 5-hydroxylysine, n,n-dimethylarginine, 4-hydroxybenzoic acid, and menatetrenone in contaminated chicken samples. The receiver operating characteristic (ROC) curve analysis demonstrated the strong ability of these six metabolites as biomarkers to distinguish S. enteritidis contaminated and fresh chicken samples. The findings presented in this study offer a theoretical foundation for developing an innovative approach to identify and detect foodborne contamination caused by S. enteritidis.
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