Abstract
Lower urinary tract symptoms (LUTS) is common in aging males. Disease etiology is largely unknown but likely includes inflammation and age-related changes in steroid hormones. Diagnosis is currently based on subjective symptom scores, and mainstay treatments can be ineffective and bothersome. Biomarker discovery efforts could facilitate objective diagnostic criteria for personalized medicine and new potential druggable pathways. To identify urine metabolite markers specific to hormone-induced bladder outlet obstruction, we applied our custom synthesized multiplex isobaric tags to monitor the development of bladder outlet obstruction across time in an experimental mouse model of LUTS. Mouse urine samples were collected before treatment and after 2, 4, and 8 weeks of steroid hormone treatment and subsequently analyzed by nanoflow ultrahigh-performance liquid chromatography coupled to tandem mass spectrometry. Accurate and high-throughput quantification of amine-containing metabolites was achieved by 12-plex DiLeu isobaric labeling. Metandem, a novel online software tool for large-scale isobaric labeling-based metabolomics, was used for identification and relative quantification of labeled metabolites. A total of 59 amine-containing metabolites were identified and quantified, 9 of which were changed significantly by the hormone treatment. Metabolic pathway analyses showed that three metabolic pathways were potentially disrupted. Among them, the arginine and proline metabolism pathway was significantly dysregulated both in this model and in a prior analysis of LUTS patient samples. Proline and citrulline were significantly changed in both samples and serve as attractive candidate biomarkers. The 12-plex DiLeu isobaric labeling with Metandem data processing presents an accessible and efficient workflow for an amine-containing metabolome study in biological specimens.