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ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Livestock Issues Research » Research » Publications at this Location » Publication #413850
Research Project: Environmental and Management Influences on Animal Productivity and Well-Being Phenotypes

Location: Livestock Issues Research

Title: Metabolomic profile of plasma from cattle challenged with lipopolysaccharide (LPS)

Author
item BARKER, SAMANTHA - Texas Tech University
item Carroll, Jeffery - Jeff Carroll
item Sanchez, Nicole
item Broadway, Paul
item KERTH, CHRIS - Texas Tech University
item LEGAKO, JERRAD - Texas Tech University

Submitted to: Journal of Animal Science Supplement
Publication Type: Abstract Only
Publication Acceptance Date: 5/1/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: The objective of this study was to evaluate metabolomic differences at 3 major time points in cattle subjected to a lipopolysaccharide challenge. Steers (n = 10; 379 kg ± 30.7) were challenged intravenously with LPS (0.25 µg/kg BW), and plasma was isolated from blood at -2, 0, 2, 4, 6, 8, 10, 12, 18, 24, 36, and 48 h relative to the LPS challenge at 0 h. Samples were selected for metabolomic analysis at -2, 2, and 8 h of the challenge based on oxidative stress markers present in companion studies. Liquid chromatography-electrospray ionization-high resolution mass spectrometry was used to separate and detect metabolites (50 to 1,400 m/z). Mass spectral features were annotated using MS-DIAL. Total ion count intensities were log10 transformed and analyzed using MetaboAnalyst v.5. An initial 1428 compounds were discovered within samples. In addition to multidimensional statistical analyses (Partial Least Squares-Discriminant Analysis and Hierarchal Clustering), an analysis of variance (ANOVA) with a false discovery rate (FDR) of P < 0.05 was used to determine 822 significant compounds. Partial Least Squares- Discriminant Analysis (PLS-DA) and variable importance in projection plot were used to visualize treatments and identify compounds driving discrimination between groups. Hierarchical clustering using the Ward method was also used to determine metabolite differences during an acute phase response in cattle at -2, 2, and 8 h of the challenge. Metabolites determined across these time points were most similar at 2 and 8 h, with a clear separation of -2 h from 2 and 8 h. A PLS-DA explained the majority of variation across Component 1 (76.8% variation) within the model, showing clear distinction between metabolites present at -2 h versus those present at 2 and 8 h post challenge. The data suggest that metabolites change drastically following an immune response, suggesting changes in pathways in vitro, which may contribute to oxidative stress and, potentially, post-mortem meat quality.