Application of Screening Experimental Designs to Assess Chromatographic Isotope Effect upon Isotope-Coded Derivatization for Quantitative Liquid Chromatography–Mass Spectrometry

Abstract

Isotope effect may cause partial chromatographic separation of labeled (heavy) and unlabeled (light) isotopologue pairs. Together with a simultaneous matrix effect, this could lead to unacceptable accuracy in quantitative liquid chromatography–mass spectrometry assays, especially when electrospray ionization is used. Four biologically relevant reactive aldehydes (acrolein, malondialdehyde, 4-hydroxy-2-nonenal, and 4-oxo-2-nonenal) were derivatized with light or heavy (d3-, 13C6-, 15N2-, or 15N4-labeled) 2,4-dinitrophenylhydrazine and used as model compounds to evaluate chromatographic isotope effects. For comprehensive assessment of retention time differences between light/heavy pairs under various gradient reversed-phase liquid chromatography conditions, major chromatographic parameters (stationary phase, mobile phase pH, temperature, organic solvent, and gradient slope) and different isotope labelings were addressed by multiple-factor screening using experimental designs that included both asymmetrical (Addelman) and Plackett–Burman schemes followed by statistical evaluations. Results confirmed that the most effective approach to avoid chromatographic isotope effect is the use of 15N or 13C labeling instead of deuterium labeling, while chromatographic parameters had no general influence. Comparison of the alternate isotope-coded derivatization assay (AIDA) using deuterium versus 15N labeling gave unacceptable differences (>15%) upon quantifying some of the model aldehydes from biological matrixes. On the basis of our results, we recommend the modification of the AIDA protocol by replacing d3-2,4-dinitrophenylhydrazine with 15N- or 13C-labeled derivatizing reagent to avoid possible unfavorable consequences of chromatographic isotope effects.

Ion Mobility Separation of Peptide Isotopomers

“…As with all MS analyses of complex samples, prior fractionation of mixtures is desired. The traditional tools of gas or liquid chromatography and electrophoresis broadly separate structural isomers, but never isotopomers (though LC can resolve non-isobaric isotopologues for various compounds, including labeled peptides) [13–14]. …”

Current trends in isotope‐coded derivatization liquid chromatographic‐mass spectrometric analyses with special emphasis on their biomedical application

“…Placing deuterium atoms in close proximity to a hydrophilic group decreases the chromatographic isotopic effect according to the solvophobic theory (Zhang, Sioma, Thompson, Xiong, & Regnier, ). By contrast, the chromatographic isotopic effect is insignificant in the case of 12 C/ 13 C, 16 O/ 18 O, and 14 N/ 15 N labeling because the chromatographic behavior of each pair of derivatives is the same (Szarka et al, ). Moreover, ICD is a labeling process, and thus, it carries the same disadvantage of any chemical derivatization process such as contamination of the ion source in the LC–MS system with the excess reagents or their by‐products, which may lead to ion suppression.…”

“…The IS (heavy labeled derivatives) is mixed with the sample before LC-MS analysis, and so the recovery of the analyte is not corrected. As a consequence, the extraction and pre-treatment should be highly efficient (Hewavitharana, 2011;Szarka, Prokai-Tatrai, & Prokai, 2014;Yang, Mirzaei, Liu, & Regnier, 2006). In addition, the introduction of many 2 H atoms into the target compound causes a decrease in the retention behavior of the heavy isotope derivatized analytes in RPLC, exposing them to different matrix effects.…”

Enhanced Metabolome Coverage and Evaluation of Matrix Effects by the Use of Experimental-Condition-Matched 13C-Labeled Biological Samples in Isotope-Assisted LC-HRMS Metabolomics

“…The application of native and labeled sample mixtures in LC-HRMS-based untargeted metabolomics is implemented in many laboratories and is described as an effective method for detecting biology-derived metabolites and to improve (absolute, relative, or differential) quantification in metabolomics studies [5,[21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36]. To exemplify a few alternative approaches, the MIRACLE (Mass isotopomer ratio analysis of U 13 C-labeled extracts) approach, IROA (isotope ratio outlier analysis), and feature credentialing shall briefly be mentioned.…”