Biology subjects

Buyantogtokh, B.

Publications and source records attributed to Buyantogtokh, B..

3 recordsLinked to original sources

bioRxiv2025

Retrospective metabolomics via dual-dimensional deconvolution using ZT Scan DIA 2.0

We present a scanning data-independent acquisition (DIA) strategy, ZT Scan DIA, combined with dual-dimensional tandem mass spectrometry spectral filtering and deconvolution along both the quadrupole and retention time axes to reconstruct compound-specific MS2 spectra from complex mixtures. This approach is particularly effective for hydrophilic metabolomics data, where spectral similarity-based annotation is widely used, increasing annotation rates by 119-193% compared with conventional data-dependent acquisition (DDA) and window-based DIA methods. In lipidomics, deconvolution improved annotation precision by removing contaminant product ions and enabled separate quantification of co-eluting isomers using MS2 chromatograms, although common diagnostic ions could also be erroneously removed. Nevertheless, optimization of analysis parameters minimized this negative effect. Furthermore, we developed a practical data processing pipeline in which raw ZT Scan DIA-MS2 chromatograms are directly used for isomer separation and MS2-based quantification, covering 1,393 and 3,020 molecules for human plasma and mouse liver tissues, respectively. All data processing steps, including direct import of vendor raw data, are supported in MS-DIAL.

bioengineering↗

bioRxiv2024

Dual fragmentation via collision-induced and oxygen attachment dissociations using water and its radicals for C=C position-resolved lipidomics

Oxygen attachment dissociation (OAD) is a tandem mass spectrometry (MS/MS) technique used to annotate the positions of double bonds (C=C) in complex lipids. Although OAD has been used for untargeted lipidomics, its availability has been limited to the positive-ion mode, requiring the independent use of a collision-induced dissociation (CID) method. In this study, we demonstrated the OAD-MS/MS technique in the negative-ion mode for profiling phosphatidylserines, phosphatidylglycerols, phosphatidylinositols, and sulfatides, where the fragmentation mechanism remained consistent with that in the positive-ion mode. Furthermore, we proposed optimal conditions for the simultaneous acquisition of CID- and OAD-specific fragment ions, termed OAciD. In the collision cell for OAD, oxygen atoms and hydroxy radicals facilitate C=C position-specific fragmentation, while residual water vapor induces cleavage of low-energy covalent bonds, such as ester and peptide bonds, at higher collision energy values, preserving OAD-specific ions under high collision energy conditions. Finally, theoretical fragment ions were implemented in MS-DIAL 5 to accelerate C=C position-resolved untargeted lipidomics. The OAciD methodology was applied to lipid profiling of five marmoset brain regions: the frontal lobe, hippocampus, midbrain, cerebellum, and medulla. Region-specific marmoset lipidomes were characterized with C=C positional information, where the ratios of C=C positional isomers such as delta 9- and delta 11 of fatty acid 18:1 in phosphatidylcholine were also estimated using OAciD-MS/MS. In addition, we characterized the profiles of polyunsaturated fatty acid-containing complex lipids with C=C positional information, where lipids containing omega-3 fatty acids were enriched in the cerebellum, while those containing omega-6 fatty acids were more abundant in the hippocampus and frontal lobe.

bioengineering↗

bioRxiv2024

MS-DIAL 5 multimodal mass spectrometry data mining unveils lipidome complexities

Lipidomics and metabolomics communities comprise various informatics tools; however, software programs that can handle multimodal mass spectrometry (MS) data with structural annotations guided by the Lipidomics Standards Initiative are limited. Here, we provide MS-DIAL 5 to facilitate the in-depth structural elucidation of lipids through electron-activated dissociation (EAD)-based tandem MS, as well as determine their molecular localization through MS imaging (MSI) data using a species/tissue-specific lipidome database containing the predicted collision-cross section (CCS) values. With the optimized EAD settings using 14 eV kinetic energy conditions, the program correctly delineated the lipid structures based on EAD-MS/MS data from 96.4% of authentic standards. Our workflow was showcased by annotating the sn- and double-bond positions of eye-specific phosphatidylcholine molecules containing very-long-chain polyunsaturated fatty acids (VLC-PUFAs), characterized as PC n-3-VLC-PUFA/FA. Using MSI data from the eye and HeLa cells supplemented with n-3-VLC-PUFA, we identified glycerol 3-phosphate (G3P) acyltransferase (GPAT) as an enzyme candidate responsible for incorporating n-3 VLC-PUFAs into the sn-1 position of phospholipids in mammalian cells, which was confirmed using recombinant proteins in a cell-free system. Therefore, the MS-DIAL 5 environment, combined with optimized MS data acquisition methods, facilitates a better understanding of lipid structures and their localization, offering novel insights into lipid biology.

bioinformatics↗