Metabolomic Coverage of Chemical-Group-Submetabolome Analysis: Group Classification and Four-Channel Chemical Isotope Labeling LC-MS

Abstract

Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) is a powerful technique for in-depth metabolome analysis with high quantification accuracy. Unlike conventional LC-MS, it analyzes chemical-group-based submetabolomes and uses the combined results to represent the whole metabolome. Due to analysis time and cost constraint, not all submetabolomes can be profiled and thus knowledge of chemical group classification is important in guiding submetabolome selection. Herein we report a study of determining the distribution of functional groups of compounds in a database and then examine how well we can experimentally analyze the major chemical groups in two representative samples (i.e., human plasma and yeast). We developed a computer algorithm to classify chemical structures according to their functional groups. After removing lipids which are targeted molecules in lipidomic analysis, inorganic species and other molecules that are unique to drug, food, plant, and environmental origins, five groups (i.e., amine, phenol, hydroxyl, carboxyl, and carbonyl) are found to be the dominant classes. In the databases of MCID (2683 filtered metabolites), HMDB (5506), KEGG (11598), YMDB (1107), and ECMDB (1462), 94.7%, 85.7%, 86.4%, 85.7%, and 95.8% of the filtered metabolites belong to one or more of the five groups, respectively. These groups can be analyzed in four-channel CIL LC-MS where hydroxyls (H), amines and phenols (A), carboxyls (C), and carbonyls or ketones/aldehydes (K) are separately profiled as individual channels using dansyl and DmPA labeling reagents. A total of 7431 peak pairs were detected with 6109 unique-mass pairs from plasma, while 5629 pairs with 4955 unique-mass pairs were detected in yeast. Compared to group distributions of database compounds, hydroxylcontaining metabolites were severely underdetected, which might indicate that the current method is less than optimal for analyzing this group of metabolites. As a result, the overall experimental coverage is likely significantly lower than the databasederived coverage. In short, this study has shown that high metabolome coverage is theoretically attainable by analyzing only the H, A, C, and K submetabolomes and the group classification information should be helpful in guiding future analytical method development and choices of submetabolomes to be analyzed.

Average daily gain divergence in beef steers is associated with altered plasma metabolome and whole blood immune-related gene expression

“…Identification of peak pairs was done using a labeled metabolite library (CIL Library; amine/phenol and carbonyl (ketone and aldehyde) channel) based on accurate mass and retention time ( Huan and Li, 2015 ). This label standard library contains 1060 unique human endogenous metabolites including 711 amines/phenols and 77 carbonyls ( Zhao et al, 2019 ). Linked identity library was used to identify some of the peak pairs that could not be identified using CIL library based on accurate mass and predicted retention time matches ( Li et al, 2013 ).…”

“…In recent years, advent of metabolomics technologies has provided an opportunity to comprehensively analyze multiple metabolites in biofluids such as blood ( Zhang et al, 2015 ). Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC–MS) is a powerful metabolomics technique to analyze metabolites based on chemical groups ( Zhao et al, 2019 ). This technique provides comprehensive analysis, with high accuracy, of metabolites containing amine/phenol group, which are common intermediate products of amino acid metabolism, and carbonyl group, which are common intermediate products of energy metabolism ( Zhao et al, 2019 ).…”

“…Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC–MS) is a powerful metabolomics technique to analyze metabolites based on chemical groups ( Zhao et al, 2019 ). This technique provides comprehensive analysis, with high accuracy, of metabolites containing amine/phenol group, which are common intermediate products of amino acid metabolism, and carbonyl group, which are common intermediate products of energy metabolism ( Zhao et al, 2019 ). In this study, we hypothesized that beef steers with divergent average daily gain (ADG) would have different concentrations of plasma metabolites associated with amino acid and energy metabolism.…”

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

“…Interestingly, 211 fecal metabolites were found to show a significant difference between the Alzheimer's disease mice model and wild‐type mice, thus providing new potential biomarkers for the diagnosis of Alzheimer's disease. Very recently, Zhao, Li, Han, Chan, and Li () designed a four‐channel chemical isotope labeling LC–MS strategy for profiling of hydroxyl, amine/phenol, carboxyl, and carbonyl submetabolomes individually. In this approach, 13 C 0 / 13 C 2 ‐DmPA was used for labeling carboxylic acid‐containing metabolites, whereas dansylation, base‐activated dansylation, and dansyl hydrazine labeling were used for derivatization of amine/phenol, hydroxyl‐, and carbonyl‐containing metabolites, respectively, using 13 C 0 / 13 C 2 reagents.…”

Recent progresses of derivatization approaches in the targeted lipidomics analysis by mass spectrometry

“…Chemical derivatization is a good way to solve these problems on the LC-MS-based metabolites analysis [32][33][34][35]. Recently, chemical derivatization, including stable isotope-labeling derivatization (SILD), has shown significant advantages in improving analytical performance for targeted metabolomics aiming at its shortcomings mentioned above [36][37][38][39]. Besides, in 2016, Ryan E and Reid GE summarized the combined strategy of chemical derivatization and ultrahigh-resolution and accurate mass spectrometry (UHRAMS) for shotgun lipidome analysis in their laboratory, whereby certain lipid classes or subclasses, namely, aminophospholipids and O-alk-1 ′ -enyl(i.e., plasmalogen)ether-containing lipids, were shifted in mass following selective chemical derivatization reactions prior to shotgun nano-ESI UHRAMS analysis [40].…”