Untargeted metabolomics and quantitative label-free proteomics analysis of whole milk protein from Chinese native buffaloes

IF 2.1 4区农林科学

Cyta-Journal of Food Pub Date : 2023-10-31 DOI:10.1080/19476337.2023.2264953

Adhita Sri Prabakusuma, Yanan Shi, Qiong Zhao, Hamzah Aleryani, Xiaoyan Kong, Xianwei Shi, Aixiang Huang

{"title":"Untargeted metabolomics and quantitative label-free proteomics analysis of whole milk protein from Chinese native buffaloes","authors":"Adhita Sri Prabakusuma, Yanan Shi, Qiong Zhao, Hamzah Aleryani, Xiaoyan Kong, Xianwei Shi, Aixiang Huang","doi":"10.1080/19476337.2023.2264953","DOIUrl":null,"url":null,"abstract":"This study aimed to analyze metabolite abundances and proteome differences between buffalo milk from Binglangjiang (BBM) and Dehong (DBM). Untargeted UPLC-MS/MS, label-free proteomics approach, and bioinformatics analyses including GO, KEGG, and PPI were performed. The results revealed that catechol, L-proline, γ-aminobutyric acid, hippuric acid, creatinine, and betaine were detected in BBM and DBM as the major metabolites. One hundred thirteen proteins, mainly within the molecular weight range of 20–80 kDa, were identified, and the differential protein numbers of BBM were higher than those of DBM. These proteins were primarily involved in cholesterol metabolism, Staphylococcus aureus and Salmonella infections, the peroxisome proliferator-activated receptor signaling pathway, and coagulation cascades. Relative abundances of α-s1-casein, α-s2-casein, and β-casein were plentiful in BBM, while κ-casein, albumin, and α-lactalbumin were in DBM. PPI network analysis indicated that the identified proteins were highly interconnected. These findings promote a better understanding of quality biomarkers in dairy product improvements.","PeriodicalId":49084,"journal":{"name":"Cyta-Journal of Food","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cyta-Journal of Food","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19476337.2023.2264953","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

Abstract

This study aimed to analyze metabolite abundances and proteome differences between buffalo milk from Binglangjiang (BBM) and Dehong (DBM). Untargeted UPLC-MS/MS, label-free proteomics approach, and bioinformatics analyses including GO, KEGG, and PPI were performed. The results revealed that catechol, L-proline, γ-aminobutyric acid, hippuric acid, creatinine, and betaine were detected in BBM and DBM as the major metabolites. One hundred thirteen proteins, mainly within the molecular weight range of 20–80 kDa, were identified, and the differential protein numbers of BBM were higher than those of DBM. These proteins were primarily involved in cholesterol metabolism, Staphylococcus aureus and Salmonella infections, the peroxisome proliferator-activated receptor signaling pathway, and coagulation cascades. Relative abundances of α-s1-casein, α-s2-casein, and β-casein were plentiful in BBM, while κ-casein, albumin, and α-lactalbumin were in DBM. PPI network analysis indicated that the identified proteins were highly interconnected. These findings promote a better understanding of quality biomarkers in dairy product improvements.

查看原文本刊更多论文

中国本土水牛全脂牛奶蛋白的非靶向代谢组学和定量无标记蛋白质组学分析

本研究旨在分析冰浪江(BBM)和德宏(DBM)水牛奶代谢物丰度和蛋白质组学差异。进行了非靶向UPLC-MS/MS、无标记蛋白质组学方法和生物信息学分析，包括GO、KEGG和PPI。结果显示，BBM和DBM的主要代谢产物为儿茶酚、l -脯氨酸、γ-氨基丁酸、马尿酸、肌酐和甜菜碱。鉴定出113个蛋白，主要在20 ~ 80 kDa的分子量范围内，BBM的差异蛋白数高于DBM。这些蛋白主要参与胆固醇代谢、金黄色葡萄球菌和沙门氏菌感染、过氧化物酶体增殖物激活受体信号通路和凝血级联反应。BBM中α-s1-酪蛋白、α-s2-酪蛋白和β-酪蛋白相对丰度较高，DBM中κ-酪蛋白、白蛋白和α-乳白蛋白相对丰度较高。PPI网络分析表明，所鉴定的蛋白具有高度的互联性。这些发现促进了对乳制品质量生物标志物改进的更好理解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Cyta-Journal of Food FOOD SCIENCE & TECHNOLOGY-

CiteScore

4.40

自引率

0.00%

发文量

期刊介绍： CyTA – Journal of Food is an Open Access journal that publishes original peer-reviewed research papers dealing with a wide range of subjects which are essential to the food scientist and technologist. Topics include: chemical analysis of food; additives and toxins in food; sensory, nutritional and physiological aspects of food; food microbiology and biotechnology; changes during the processing and storage of foods; effect of the use of agrochemicals in foods; quality control in food; and food engineering and technology.