Novel Method for Comprehensive Annotation of Plant Glycosides Based on Untargeted LC-HRMS/MS Metabolomics.

Glycosides are a large family of secondary metabolites in plants, which play a critical role in plant growth and development. Due to the complexity and diversity in structures and the limited availability of authentic standards, comprehensive annotation of the glycosides remains a great challenge. In this study, using maize as an example, a deep annotation method of glycosides was proposed based on untargeted liquid chromatography-high-resolution tandem mass spectrometry metabolomics analysis. First, knowledge-based in silico aglycone and glycosyl/acyl-glycosyl libraries were built. A total of 1240 known and potential aglycones from databases and literature were recorded. Next, the MS parameters beneficial to aglycone ion-rich MS/MS were explored using 1782 high-resolution MS/MS spectra of glycosides from the MassBank of North America (MoNA) and confirmed by 52 authentic glycoside standards. Then, screening rules for aglycon ions in MS/MS were recommended. Glycoside candidates were further filtered by MS/MS-based chemical classification and MS/MS similarity of aglycon-glycoside pairs. Finally, the glycosylation sites of flavonoid mono-O-glycosides were recommended by characteristic fragmentation patterns. The developed method was validated using glycosides and nonglycosides from the MoNA library. The annotation accuracy rates were 96.8, 94.9, and 98.0% in negative ion mode (ESI-), positive ion mode (ESI+), and the combined ESI- & ESI+, respectively. The annotation specificity was 99.6% (ESI-), 99.6% (ESI+), and 99.2% (ESI- & ESI+). A total of 274 glycosides (including 34 acyl-glycosides) were tentatively annotated in maize by the developed method. The method enables effective and reliable annotation for plant glycosides.

In-depth characterization of nitrogen heterocycles of petroleum by liquid chromatography-energy-resolved high resolution tandem mass spectrometry.

With the increased attention to processing heavy crude oils, a detailed description of chemical composition is critical for the petroleum refining industry. The current analytical technique such as ultrahigh resolution mass spectrometry has been successfully applied for the molecular level characterization of complex petroleum fractions. But the structural characterization of heavy petroleum feedstock is still a great challenge. In this study, a novel in-depth characterization method of nitrogen heterocycles (N-heterocycles) in heavy petroleum mixtures was proposed by online liquid chromatography coupled with electrospray ionization high resolution energy-resolved mass spectrometry. A series of typical basic aromatic, neutral aromatic and naphtheno-aromatic nitrogen heterocyclic model compounds were synthesized to investigate energy-resolved fragmentation behaviors in high energy collision-induced dissociation at 10-100 eV. Energy-dependent fragmentation pathways were elucidated. Notably, characteristic double bond equivalent (DBE) versus carbon number distributions of N1 ions and all CH ions were discovered, which were closely related to their core structure. Then a workflow to assign core structures of alkyl-substituted N-heterocycles in petroleum was proposed and validated. The developed method was applied to investigate the structural isomers in feed and product vacuum gas oil (VGO) fractions. Core structural differences in feed VGO and subtle structural variations between feed and product VGOs were recognized. This work can distinguish structural isomers of N-heterocycles with the subtle difference in their core structure in heavy petroleum fractions based on global energy dimensional fragmentation characteristics.

A data processing pipeline for petroleomics based on liquid chromatography-high resolution mass spectrometry.

Online liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has attracted much attention in the molecular characterization of crude oil. Neither open access nor commercially available petroleomics tools were developed specifically to process LC-HRMS data. Here, a novel data processing pipeline was specifically designed for LC-HRMS-based petroleomics data. A customizable formula database was established deriving from the detected sample, which could avoid the interference caused by a large number of redundant molecules in a conventionally theoretical molecular database. Molecular formula candidates were assigned by the formula database using a low noise threshold, and false-positive assignments were eliminated by the chromatographic retention behaviors. Multi-dimensional information was obtained, including heteroatom class, double bond equivalent (DBE), carbon number, retention time, and MS/MS spectra. The developed method was compared with a popular petroleomics software, similar relative abundance class distribution was obtained, and much more formulas of low abundant components were uniquely extracted by the developed method. Finally, it was applied to reveal variation between feed and product oils in hydrodenitrogenation. Significantly compositional and structural differences were revealed. The developed method provides a useful pipeline for molecular data mining of petroleum samples.