奶牛临床和亚临床酮病的血浆代谢组学研究

doi:10.3864/j.issn.0578-1752.2014.08.015

摘要/Abstract

摘要： 【目的】基于代谢组学的气相色谱(GC)/质谱(MS)联用技术分析临床酮病、亚临床酮病和健康的奶牛血浆代谢谱，观察奶牛体内代谢产物的变化，寻找内源性代谢分子标记物，用于发现奶牛临床和亚临床酮病的早期诊断及病情进展的特征生物标志物，并阐明该病发病机制。【方法】收集临床酮病奶牛血样24例，亚临床酮病奶牛33例，健康对照组奶牛23例，静脉采集试验奶牛血液，分离血浆，检测其β-羟丁酸、血糖等生化指标。将血浆样品预处理后，运用GC/MS联用技术检测各组奶牛血浆代谢产物，利用质谱数据库对其进行鉴定。采用主成分分析（principal component analysis, PCA）和偏最小二乘判别分析法（partial least squares discriminant analysis, PLS-DA）等多元统计方法对临床酮病组、亚临床酮病组和健康对照组奶牛检测数据进行模式识别分析。通过PLS-DA方法建立疾病诊断模型后，筛选潜在的疾病生物标记物。【结果】以80例奶牛血浆样品为分析对象,研究建立了内源性代谢物谱的GC/MS分析方法，并利用NIST（2008）商业质谱数据库对检测到的代谢物进行快速鉴定，共检测出267个变量。将代谢组数据导入SIMCA-P软件进行主成分分析和偏最小二乘法判别分析,代谢组数据可将患病组与健康组分别聚类区分，并且寻找到组间种类无差别代谢物为40种。结果显示与对照组相比，临床和亚临床酮病的差异代谢物均为32个，临床酮病与亚临床酮病组相比有13个差异代谢物。通过查找KEGG数据库，对代谢物进行分析，这些代谢物主要与氨基酸代谢、脂肪代谢和碳水化合物代谢等能量代谢途径相关。【结论】基于代谢组学的GC/MS技术对酮病奶牛血浆进行检测，并结合多元统计分析，共在临床、亚临床酮病和健康组之间发现40种代谢物（主要为脂肪酸，氨基酸和碳水化合物等物质）。证明奶牛血浆样品的GC/MS代谢谱可以有效地对临床酮病组、亚临床酮病组与健康对照组进行区分。该结果也进一步证明了利用代谢组学技术，在一定程度上可以揭示奶牛临床和亚临床酮病的发生和发展变化，而这些对组间分类有贡献的差异代谢物可能是奶牛酮病诊断的潜在代谢标记物和客观指标。通过研究可以发现奶牛临床和亚临床酮病的发生和发展过程中，其血浆内的部分代谢物的代谢模式和代谢途径发生了改变。此外，新的潜在的代谢物也为奶牛酮病的诊断和预防提供了一定的新思路。

关键词: 气相色谱/质谱联用技术 , 代谢组学 , 酮病 , 多元统计分析

Abstract: 【Objective】 This study aims to search the relational metabolites in plasma of cows with clinical and subclinical ketosis by the method of metabolomics based on the technology of gas chromatography (GC) / mass spectrometry (MS) techniques, find out molecular markers for endogenous metabolism for early diagnosis and prognosis of ketosis, and reveal the essence of ketosis. 【Method】 Total 24 dairy cows with clinical ketosis (CK), 33 dairy cows with subclinical ketosis (SK) and 23 healthy controls (C) were selected for the research. Venous blood of cows was collected, for the preparation of plasma samples, and the biochemical criterions such as β-hydroxybutyric acid, glucose and so on were detected. After the plasma samples were pretreated, cows plasma metabolites were detected by GC/MS technique. The detected metabolites were identified by mass spectral database. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of multivariate statistical methods were used for recognizing different metabolic patterns among clinical ketosis, subclinical ketosis and healthy controls. After establishing the diagnosis models of disease by partial least squares discriminant analysis, potential biomarkers of disease were selected. 【Result】 A stable and reliable GC/MS analytical method was established to obtain the metabolite profiles of the plasma samples. A commercial mass spectral database (NIST2008) was used for the rapid identification of detected metabolites and totally 267 variables were detected. The metabolomics data were imported into Simca-P 11.0 software for PCA and PLS-DA . Ketosis groups and healthy groups could be clustered and distinguished by the metabolomics data, and 40 types of metabolites without difference among 3 groups were found out. Results showed that compared with the healthy control group, different metabolites obtained in subclinical and clinical ketosis groups were 32, different metabolites obtained between clinical ketosis group and subclinical ketosis group were 13. Through seeking the KEGG database and analysis of metabolites, these metabolites primarily were related to amino acid metabolism, fat metabolism and carbohydrate metabolism.【Conclusion】 The present study is an integrated detection of dairy cattle ketosis based on plasma metabolomic profiling by GC/MS combined with multivariate statistical analysis. It was firstly discovered that 40 metabolites (i.e. fatty acids, amino acids, carbohydrates, et. al) were differentially found among CK, SK and C. It proved that the plasma GC/MS metabolite profiles can effectively distinguish clinical and subclinical ketosis groups from healthy control group. This further proved that metabolomics technology, to some extent, can reveal the development and progression of clinical and subclinical ketosis, while the substances of different content and contributing to classification may be the potential metabolic marker and objective indicators for diagnosing ketosis. To research ketosis, in the process of the occurrence and development of clinical and subclinical ketosis, parts of metabolic patterns and metabolic pathways in plasma changed. Furthermore, new potential metabolites could shed light on new strategies for the diagnosis, prognosis, and prevention of ketosis .

Key words: gas chromatography/mass spectrometry , metabonomics , ketosis , multivariate statistical analysis

孙玲伟, 包凯, 李影, 李兰, 张洪友, 夏成, 吴凌. 奶牛临床和亚临床酮病的血浆代谢组学研究[J]. 中国农业科学, 2014, 47(8): 1588-1599.

SUN Ling-Wei, BAO Kai, LI Ying, LI Lan, ZHANG Hong-You, XIA Cheng, WU Ling. Plasma Metabolomics Study of Dairy Cows with Clinical and Subclinical Ketosis[J]. Scientia Agricultura Sinica, 2014, 47(8): 1588-1599.

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