Abstract
Annually, millions of people are affected by mosquito-borne Orthoflavivirus infections. These include diseases caused by the Dengue virus (DENV), Japanese encephalitis virus (JEV), and Zika virus (ZIKV), posing a formidable challenge to global public health. This research aims to explore the potential role of the Gut-Brain Axis (GBA) in Orthoflavivirus infection, particularly focusing on key metabolites involved in the process of viral invasion into the central nervous system. Given the advantages of metabolomics technology in metabolite identification. Therefore, we employed an untargeted Liquid Chromatography-Mass Spectrometry (LC-MS) metabolomics platform to examine alterations in metabolite concentrations within the feces and brain tissues of mice infected with DENV, JEV, or ZIKV, as well as uninfected controls. The results showed that 225, 240, and 252 differential metabolites were identified in the fecal metabolome of DENV, JEV, and ZIKV infections, respectively, with amino acid metabolism and lipid metabolism being significantly disrupted. In the brain metabolome, 37, 81, and 18 differential metabolites were identified for DENV, JEV, and ZIKV infections, respectively, with lipid metabolism and purine metabolism being significantly disrupted. Amino acids with low abundance in viral proteins are significantly disrupted in the amino acid metabolism pathway, suggesting that Orthoflaviviruses adapt to its needs for synthesizing viral proteins by regulating the host's amino acid composition. The disruption of purine metabolism also implies the viral genome replication process occurring in the brain. Moreover, the disturbance of lipid metabolism is highly correlated with the biological function of the Orthoflavivirus envelope, where Sphingosine 1-phosphate (S1P) may be the key for Orthoflaviviruses to enter the human central nervous system via the GBA. This research is the first to explore the potential role of GBA in Orthoflavivirus infection through joint metabolomic analysis of fecal and brain tissue samples, providing new insights into viral invasion of the central nervous system. The findings not only elucidate the characteristics of viral infection from complementary perspectives of fecal and brain tissue samples, revealing associated metabolic changes, but also establish a foundation for subsequent identification of biomarkers to diagnose disease states-particularly for predicting central nervous system infection risks. The specific patterns revealed by fecal metabolomics analysis provide the theoretical basis for developing non-invasive predictive approaches to assess brain infection status in the future.