Metabolic response to anthelmintic treatment in beef cattle with subclinical gastrointestinal nematode infection.

Gastrointestinal nematodes (GINs) represent a recurring challenge for beef cattle production, because infections are predominantly subclinical and current diagnostic tools have limited ability to detect affected animals before significant losses to the production chain occur. With the advent of new technologies, it has become possible to obtain a wide range of information from animal serum. Through metabolomics, it is possible to expand knowledge of the host-parasite relationship, identify biomarkers with diagnostic potential, and prospect new molecules that may aid in treatment. Thus, the present study aimed to examine the serum metabolome of asymptomatic beef cattle naturally infected with GINs, predominantly Cooperia spp., comparing animals treated with an anthelmintic to untreated controls, in order to identify metabolic alterations. A total of 20 Nellore cattle in the growing phase, naturally infected, were used and allocated into two groups (n = 10): control (CON) and treated weekly with fenbendazole (TRAT). Treatment efficacy was confirmed by the fecal egg count reduction test, and pooled coprocultures indicated a predominance of Cooperia spp. Metabolomic analysis was performed on day 42 (D42) using ^1H NMR spectroscopy (600 MHz) on filtered serum (3 kDa), with metabolite identification and quantification. A total of 43 metabolites were identified, 11 of which exhibited VIP scores > 1 and were considered relevant for group discrimination: 1-methylhistidine, lactic acid, aspartate, carnitine, ethanol, glycine, glutamate, glycerol, isoleucine, methionine, and ornithine. The TRAT group showed a metabolic profile consistent with greater anabolism and increased utilization of aerobic energy pathways, whereas the CON group indicated greater mobilization of lipid reserves. These findings elucidate relevant aspects of the host-parasite relationship, as well as the physiological impacts of subclinical infection, and highlight metabolites with potential use as biomarkers, which should be validated in future studies.