Abstract

Simple SummaryTo 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. This experiment studied the relationship between fecal metabolites and marbling characters, and further screened biomarkers (including ADP, SM(d18:0/16:1(9Z)), PC(15:0/18:2(9Z,12Z)), digoxin, indoleacetaldehyde, PC(16:0/16:0), 3-O-Sulfogalactosylceramide (d18:1/18:0), and spermine).This experiment contributes to a more comprehensive understanding of the molecular mechanism and supplies an essential reference for further exploring the application of metabolite biomarkers to identify marbling beef traits.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.

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