Using Untargeted LC-MS Metabolomics to Identify the Association of Biomarkers in Cattle Feces with Marbling Standard Longissimus Lumborum

  • Animals (Basel). 2022 Aug 30;12(17):2243. doi: 10.3390/ani12172243.
Dong Chen  1 ,  Minchao Su  1 ,  He Zhu  2  3  4 ,  Gang Zhong  1 ,  Xiaoyan Wang  1 ,  Weimin Ma  4 ,  Metha Wanapat  5 ,  Zhiliang Tan  6
Affiliations
  • 1. College of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China.
  • 2. College of Food Science and Engineering, Shandong Agriculture and Engineering University, Jinan 250100, China.
  • 3. National Engineering Laboratory for Rice and By-Products Further Processing, College of Food Science and Engineering, Central South University of Forestry & Technology, Changsha 410004, China.
  • 4. Technology Center of Gaoqing Black Cattle Product Processing and Quality Improvement, Zibo 255000, China.
  • 5. Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Facully of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand.
  • 6. Institute of Subtropical Agriculture of the Chinese Academy of Sciences, Changsha 410125, China.
PMID: 36077963 DOI: 10.3390/ani12172243
Abstract

Background: To improve the grade of beef marbling has great economic value in the cattle industry since marbling has the traits of high quality and comprehensive nutrition. And because of the marbling’s importance and complexity, it is indispensable to explore marbled beef at multiple levels. This experiment studied the relationship between fecal metabolites and marbling characters, and further screened biomarkers. Results: We performed fecal metabolomics analysis on 30 individuals selected from 100 crossbreed cattle (Luxi Yellow cattle ♀ × Japanese Wagyu cattle ♂), 15 with an extremely high-grade marbling beef and 15 with an extremely low-grade marbling beef. A total of 9959 and 8389 m/z features were detected in positive ionization and negative ionization mode by liquid chromatography-mass spectrometry (LC-MS). Unfortunately, the sample separation in the PCA is not obvious, and the predictive ability of the orthogonal partial least squares discrimination analysis (OPLS-DA) model is not good. However, we got six differential metabolites filtered by VIP > 1 and p < 0.05. After that, we used weighted correlation network analysis (WGCNA) and found out a module in each positive and negative mode most related to the trait of marbling beef, and then identified three metabolites in positive mode. By further annotation of the Kyoto encyclopedia of genes and genomes (KEGG), it was found that these metabolites involved a variety of metabolic ways, including sphingomyelin metabolism, linoleic acid metabolism, glycerophospholipid metabolism, and so on. Finally, receiver operating characteristic (ROC) analysis was used to evaluate the predictability of metabolites, and the result showed that SM(d18:0/16:1(9Z)) (AUC = 0.72), PC(15:0/18:2(9Z,12Z)) (AUC = 0.72), ADP (AUC = 0.71), PC(16:0/16:0) (AUC = 0.73), and 3-O-Sulfogalactosylceramide (d18:1/18:0) (AUC = 0.69) have an accuracy diagnosis. Conclusions: In conclusion, this study supports new opinions for the successive evaluation of marbling beef through metabolites. Furthermore, six non-invasive fecal metabolites that can evaluate beef marbling grade were found, including SM(d18:0/16:1(9Z)), PC(15:0/18:2(9Z,12Z)), ADP, PC(16:0/16:0), and 3-O-Sulfogalactosylceramide.

Keywords
biomarker; intramuscular fat; marbling beef; metabonomics.
Products