Integration of Chemical Derivatization and in-Source Fragmentation Mass Spectrometry for High-Coverage Profiling of Submetabolomes

Abstract

In-source fragmentation-based high-resolution mass spectrometry (ISF-HRMS) is a potential analytical technique, which is usually used to profile some specific compounds that can generate diagnostic neutral loss (NL) or fragment ion (FI) in ion source inherently. However, the ISF-HRMS method does not work for those compounds that cannot inherently produce diagnostic NL or FI in ion source. In this study, a derivatization-based in-source fragmentation-information-dependent acquisition (DISF-IDA) strategy was proposed for profiling the metabolites with easily labeled functional groups (submetabolomes) by liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry (LC-ESI-Q-TOF MS). As a proof-of-concept study, 36 carboxylated compounds labeled with N,N-dimethylethylenediamine (DMED) were selected as model compounds to examine performance of DISF-IDA strategy in screening the carboxylated metabolites and acquiring their MSn spectra. In ESI source, the DEMD-derived carboxylated compounds were fragmented to produce characteristic neutral losses of 45.0578, 63.0684, and/or 88.1000 Da that were further used as diagnostic features for screening the carboxylated metabolites by DISF-IDA-based LC-Q-TOF MS. Furthermore, high-resolution MSn spectra of the model compounds were also obtained within a single run of DISF-IDA-based LC-Q-TOF MS analysis, which contributed to the improvement of the annotation confidence. To further verify its applicability, DISF-IDA strategy was used for profiling carboxylated submetabolome in mice feces. Using this strategy, a total of 351 carboxylated metabolites were detected from mice feces, of which 178 metabolites (51% of the total) were positively or putatively identified. Moreover, DISF-IDA strategy was also demonstrated to be applicable for profiling other submetabolomes with easily labeled functional groups such as amino, carbonyl, and cis-diol groups. Overall, our proposed DISF-IDA strategy is a promising technique for high-coverage profiling of submetabolomes with easily labeled functional groups in biological samples.

Profiling of Urine Carbonyl Metabolic Fingerprints in Bladder Cancer Based on Ambient Ionization Mass Spectrometry

“…N , N -dimethylethylenediamine (DMED) has been previously employed as a derivatization reagent for carboxyl compounds. , Here, we extend DMED to the derivatization and differentiation of carboxyl, aldehyde, and ketone compounds. Scheme shows the predicted derivatization reaction and the fragmentation of the derivatives in collision-induced dissociation (CID).…”

“…Additionally, derivatization was commonly used in the biofluid analysis − since the signal of components with low concentration would be greatly suppressed by that with high concentration (such as creatinine in urine, which has a high concentration and high ionization efficiency). For example, N , N -dimethylethylenediamine (DMED) was used for the derivatization of carboxyl compounds in plant tissue extract, human serum, and mice feces. , A (4-(2-(trimethylammonio)­ethoxy)­benzenaminium) halide was used as a labeling reagent for the analysis of aldehydes in urine . These reagents increase the detection sensitivity of a specific kind of compound.…”

Liquid Chromatography-Mass Spectrometry (LC-MS) Derivatization-Based Methods for the Determination of Fatty Acids in Biological Samples

“…Recently, the same team established a derivatization-based in-source fragmentation-information-dependent acquisition (DISF-IDA) strategy for the profiling of submetabolomes by LC-ESI-Q-TOF MS. In particular, 36 carboxylated compounds labeled with DMED were used as model compounds for the profiling of carboxylated submetabolome in mice feces [ 39 ]. In 2020, DMED was also utilized for the labeling of short chain fatty acid esters of hydroxy fatty acids (SFAHFAs).…”

Evaluation of Untargeted Metabolomic Strategy for the Discovery of Biomarker of Breast Cancer

“…Its coupling with chromatographic separation, such as gas chromatography and liquid chromatography (LC), has been widely used for metabolomic analysis by providing both molecular weight and structural information ( Liu et al, 2013 ; Alonso et al, 2015 ; Nash and Dunn, 2019 ; Hou et al, 2020 ; Harrieder et al, 2022 ). Efforts have been done in method development for sample preparation, chromatographic separation and derivatization-based detection to improve the metabolome coverage ( Yuan et al, 2018 ; An et al, 2021 ; Meng et al, 2021 ). Besides, computational approaches are also dramatically developed to assist data interpretation and metabolite global annotation ( Bonini et al, 2020 ; Chen et al, 2021 ; Duehrkop et al, 2021 ).…”