Integrated Metabolomics and Proteomics Analysis of Urine in a Mouse Model of Posttraumatic Stress Disorder

Abstract

Posttraumatic stress disorder (PTSD) is a serious stress disorder that occurs in individuals who have experienced major traumatic events. The underlying pathological mechanisms of PTSD are complex, and the related predisposing factors are still not fully understood. In this study, label-free quantitative proteomics and untargeted metabolomics were used to comprehensively characterize changes in a PTSD mice model. Differential expression analysis showed that 12 metabolites and 27 proteins were significantly differentially expressed between the two groups. Bioinformatics analysis revealed that the differentiated proteins were mostly enriched in: small molecule binding, transporter activity, extracellular region, extracellular space, endopeptidase activity, zymogen activation, hydrolase activity, proteolysis, peptidase activity, sodium channel regulator activity. The differentially expressed metabolites were mainly enriched in Pyrimidine metabolism, D-Glutamine and D-glutamate metabolism, Alanine, aspartate and glutamate metabolism, Arginine biosynthesis, Glutathione metabolism, Arginine, and proline metabolism. These results expand the existing understanding of the molecular basis of the pathogenesis and progression of PTSD, and also suggest a new direction for potential therapeutic targets of PTSD. Therefore, the combination of urine proteomics and metabolomics explores a new approach for the study of the underlying pathological mechanisms of PTSD.

Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry

“…Hence, it is becoming increasingly important to combine multiple layers of ‘omics data when assessing the underlying causative changes that lead to disease [ 4 , 5 ]. Furthermore, there have been several strategies developed to determine the relationship between proteomic and metabolomic data from the same samples [ 6 , 7 , 8 , 9 , 10 ].…”