Preliminary Proteomic and Metabolomic Analyses Reveal Potential Serum Biomarkers for Identifying Alveolar Echinococcosis in Mice

Alveolar echinococcosis (AE) is a chronic and potentially fatal zoonotic parasitic disease that seriously affects the host’s health. It is caused by the proliferation of <i>Echinococcus multilocularis</i> larvae within the liver. Due to its long incubation period following host infection, early diagnosis of the disease is currently not feasible. Treatment options are extremely limited, with the only choice being curative surgical resection combined with benzimidazole medication. Thus, the development of early, rapid, and minimally invasive diagnostic methods is crucial for enhancing patient prognosis. This study conducted proteomic and metabolomic analyses of protein and metabolite changes in the serum of a treatment group and control group, aiming to compare the differences between them. Overall, 22 proteins showed significant differences between the treatment and control groups, primarily involved in carbohydrate metabolism, lipid metabolism, and amino acid metabolism. The upregulation of genes related to immune response and enhanced glycolysis were observed, possibly associated with the reproduction of <i>E. multilocularis</i> in the liver. A total of 182 metabolites were screened to distinguish between the treatment group and control group. A significant increase in the cytochrome P450 (cP450) metabolite of arachidonic acid indicated signs of renal and splenic involvement in the treatment group. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis highlighted a strong association between amino acid metabolism and the development of AE. The observed changes in amino acid levels may provide nutrients that facilitate <i>E. multilocularis</i> colonization and contribute to the pathogenesis of AE. In summary, by investigating the different characteristics of the AE and control group through proteomic (<i>n</i> = 4/group/time point) and metabolomic (<i>n</i> = 8/group/time point) analyses, potential serum biomarkers for diagnosing mice with AE were identified.