Chemometrics-assisted optimization of liquid chromatography-quadrupole-time-of-flight mass spectrometry analysis for targeted metabolomics.

Mass spectrometry-based metabolomics is characterized by a vast number of variables leading to a great degree of complexity. In this work, we aimed to simplify this process with a stepped chemometric optimization of the both funnel technology (funnel exit DC, FDC; funnel RF LP, FLC; funnel RF HP, FRP) and ion source parameters (Octopolo, Oct; and Fragmentor, Frag) of a quadrupole-time of flight (qTOF) for a human urinary metabolites. The workflow comprised a Box-Behnken experimental design with 47 experiments followed by the identification and quantification of a set of metabolites using high-resolution full-scan MS mode and feature extraction with an inclusion list. Metabolite peak areas were grouped according to abundance (high and low) and modeled by Random Forest regression (variance explained >85%). The full three-level factorial design consisting in 243 experiments was predicted and top 10 solutions for desirability function and those comprising the Pareto front were extracted and investigated. To guarantee the quality of results, we compared the Pareto front solutions with those achieved by standard instrumental parameters suggested by the manufacturer. A set of five solutions were identified that increased the mean peak area by 56-59% and 17%, for high- and low-abundance metabolites, respectively. The optimal parameters were determined to be: FLP, 100 V; FDC, 40 and 30 V; Frag, 275 and 400 V; and Oct, 600 and 800 V. The methodology applied throughout this work represents a flexible strategy to optimize instrumental parameters and exploit the performance of a qTOF MS detector.