Comparison of Metabolomic Signatures Between Low and Heavy Parasite Burden of Haemonchus contortus in Meat Goats Fed with Cynodon dactylon (Bermudagrass) and Crotalaria juncea L. (Sunn Hemp)

<b>Background/Objectives:</b> Animal health remains a critical issue that directly impacts economic sustainability through animal welfare and production. In small ruminants, the gastrointestinal parasite <i>Haemonchus contortus</i> can lead to anemia and possibly mortality, since parasite burden can be considerable and is challenging to control. Small ruminant health can be affected by poor diet and environmental conditions that lead to changes in the metabolic balance. The link between animal health and metabolic profiles has been investigated in the past. These studies have shed important light on physiological changes by identifying dietary and disease biomarkers. This study aimed to correlate the metabolite signature of feces from goats, having two levels of <i>Haemonchus contortus</i> infection, grazing on two different forages (Bermudagrass and Sunn Hemp). <b>Methods:</b> Fecal samples were taken from goats grazing either Sunn Hemp or Bermudagrass pastures, with naturally variable <i>Haemonchus contortus</i> loads. Samples were evaluated using ¹H-NMR and LC/MS methods to describe and compare metabolic patterns under varied forage conditions between low and high Fecal Egg Count (FEC). <b>Results:</b> Our findings indicated no significant difference using univariate analyses but identified 10 discriminatory features using multivariate analyses for Bermudagrass and Sunn Hemp using ¹H-NMR. With LC-MS, we found 14 significantly different features (<i>p</i> < 0.05, FC > 2), 115 discriminatory features for Bermudagrass and 113 in Sunn Hemp from multivariate analyses. Combining the findings of the two approaches suggested that <i>Haemonchus contortus</i> influenced several pathways associated with the metabolism of amino acids and energy conversion. <b>Conclusions:</b> The analysis of metabolome changes across both forages may help in revealing novel knowledge and accurate identification of possible biomarkers for gastrointestinal parasites. Further study is needed to validate the potential biomarker before deploying diagnostic tools based on the metabolomics indicators for early parasite diagnosis.