BACKGROUND: Analyte annotation confidence in untargeted liquid chromatography mass-spectrometry (LC-MS) based chemical analysis can be enhanced by leveraging retention time information. For this, the chromatographic characteristics of the analytical system used should be well characterized. In this study, we measured 604 diverse chemical standards to characterize a dual LC setup consisting of pentabromobenzyl (PBr) and type-C silica hydride (SiH) columns operating in reversed-phase (RP) and aqueous normal-phase (ANP) mode, respectively. RESULTS: ANP and RP separations individually retained 40 % and 64 % of standards in cLogP range from -6.60 to 8.67 and -3.34 to 12.95, respectively. Using both columns, the coverage increased to 79 % of standards with cLogP range from -6.60 to 12.95 (median cLogP = 1.63). Retention selectivity follows the number of basic nitrogen atoms in the molecule on SiH column and polarity (cLogP) on PBr column. Column repeatability and reproducibility were tested in triplicate using a chemically diverse subset of 108 standards. Repeatability of retention times, peak widths and peak areas was 0.3 %, 14 %, 4 % for SiH column and 0.2 %, 12 %, 4 % for PBr column. Similarly, reproducibility was 15 %, 34 %, 30 % for SiH column and 9 %, 18 % and 34 % for PBr column. Predictive RT models were developed based on experimental RT data, achieving R2 values of 0.92 and 0.96, with mean absolute errors of 0.29 min and 0.27 min for SiH and PBr columns, respectively. SIGNIFICANCE: As proof of concept, 129 metabolites were annotated in pooled human serum and plasma by matching standard or predicted RT on one or both columns. The RT models and MS2 spectra of standards are openly available, facilitating uptake of this well-characterized chromatographic system to increase confidence in analyte annotation.

RECETOX Faculty of Science Masaryk University Brno Czech Republic

RECETOX Faculty of Science Masaryk University Brno Czech Republic; Department of Environmental Sciences Jožef Stefan Institute Ljubljana Slovenia

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