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  • Title: A Comprehensive LC-QTOF-MS Metabolic Phenotyping Strategy: Application to Alkaptonuria.
    Author: Norman BP, Davison AS, Ross GA, Milan AM, Hughes AT, Sutherland H, Jarvis JC, Roberts NB, Gallagher JA, Ranganath LR.
    Journal: Clin Chem; 2019 Apr; 65(4):530-539. PubMed ID: 30782595.
    Abstract:
    BACKGROUND: Identification of unknown chemical entities is a major challenge in metabolomics. To address this challenge, we developed a comprehensive targeted profiling strategy, combining 3 complementary liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) techniques and in-house accurate mass retention time (AMRT) databases established from commercial standards. This strategy was used to evaluate the effect of nitisinone on the urinary metabolome of patients and mice with alkaptonuria (AKU). Because hypertyrosinemia is a known consequence of nitisinone therapy, we investigated the wider metabolic consequences beyond hypertyrosinemia. METHODS: A total of 619 standards (molecular weight, 45-1354 Da) covering a range of primary metabolic pathways were analyzed using 3 liquid chromatography methods-2 reversed phase and 1 normal phase-coupled to QTOF-MS. Separate AMRT databases were generated for the 3 methods, comprising chemical name, formula, theoretical accurate mass, and measured retention time. Databases were used to identify chemical entities acquired from nontargeted analysis of AKU urine: match window theoretical accurate mass ±10 ppm and retention time ±0.3 min. RESULTS: Application of the AMRT databases to data acquired from analysis of urine from 25 patients with AKU (pretreatment and after 3, 12, and 24 months on nitisinone) and 18 HGD -/- mice (pretreatment and after 1 week on nitisinone) revealed 31 previously unreported statistically significant changes in metabolite patterns and abundance, indicating alterations to tyrosine, tryptophan, and purine metabolism after nitisinone administration. CONCLUSIONS: The comprehensive targeted profiling strategy described here has the potential of enabling discovery of novel pathways associated with pathogenesis and management of AKU.
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