Increase the accessibility and scale of targeted metabolomics: Construction of a human urinary metabolome-wide multiple reaction monitoring library using directly-coupled reversed-phase and hydrophilic interaction chromatography

• Increase metabolite coverage by directly-coupled RPLC-HILIC.
• Combine data-dependent and data-independent strategies for deep MS/MS acquisition.
• Build a human urinary MRM library in negative-ion mode with 749 refined MRM tags.

Multiple reaction monitoring (MRM) is wildly employed to research drug absorption, distribution, metabolism, excretion and pharmacokinetics in pharmaceutical and clinical laboratories. Recently, scientists in these areas have shown great interest in utilization of metabolomics to evaluate drug efficacy and toxicity. MRM-based targeted metabolomics is intrinsically more sensitive and selective than MS based untargeted metabolomics in complex biological samples. MRM also minimizes data complexity for fast and focused analysis of core metabolites. Nevertheless, to mitigate the intrinsic targeted nature of MRM and promote it as a discovery toolbox for metabolomics, larger scale MRM assays providing more comprehensive biological information are highly desirable. Here, we employed data-dependent and data-independent strategies to perform extensive MS/MS mapping of human urinary metabolome with the assistance of a directly-coupled reversed-phase liquid chromatography and hydrophilic interaction chromatography (RPLC-HILIC) for simultaneous profiling of hydrophilic and hydrophobic metabolites. RPLC-HILIC enables to save time, limit sample consumption and facilitate data interpretation by removing data redundancy occurring between separate RPLC and HILIC methods. Major product ions in the raw MS/MS spectra were used to build a human urinary metabolome-wide MRM library which contains 749 refined MRM tags in negative ion mode with 198 of them being unambiguously or tentatively assigned for particular metabolites. The library relieves researchers from the most time-consuming setup of massive MRM transitions and making an important step toward large-scale targeted urinary metabolomics.

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