Biology subjects

Tsugawa, H.

Publications and source records attributed to Tsugawa, H..

At least 19 recordsLinked to original sources

bioRxiv2026

MassBank Human: The annotated human metabolome

Mass spectrometry-based metabolomics is essential for deciphering human metabolic functions and metabolite dark matter. However, the dark matter of the human metabolome is intricately hidden. Therefore, we developed MassBank Human, a curated library that distills 36,512,540 MS2 spectra from 76 public human datasets into 203,886 high-quality spectra via spectral averaging, recalibration, and filtering to achieve high mass accuracy. We further used three metabolite annotation tools and developed a Zipf-Bayesian rank aggregation framework to aggregate their rankings with false discovery rate control. This framework assigned molecular formulas, chemical classes, and planar structures to 55,564, 22,619, and 14,198 spectra, respectively. Approximately half of the annotated structures potentially originated from food, pollutants, or gut microbiota. In a metabolome analysis of colorectal cancer cells, MassBank Human doubled structural annotation coverage (10.6% to 21.2%), identifying acetylated polyamines as markers of metabolic rewiring. This community resource provides an annotated foundation for exploring human metabolomes.

bioinformatics↗

bioRxiv2026

MSLipidMapper: a pathway-centered lipidome analysis environment linking lipid class, acyl-chain subsets, and multi-omics data

Lipids exhibit extensive structural diversity arising from variation in lipid classes, subclasses, and acyl-chain compositions, making systematic interpretation of lipidomics data challenging. Although untargeted lipidomics enables the quantification of hundreds to thousands of lipid molecular species, downstream analyses often treat pathway-level summaries, molecular-species visualization, structural subsetting, and multi-omics interpretation as separate steps. Here, we present MSLipidMapper, an R/Shiny-based lipidomics data exploration environment for pathway-centered and structure-aware analysis of annotated lipidomics datasets. MSLipidMapper reconstructs annotated lipid peak tables as Bioconductor SummarizedExperiment objects, thereby organizing quantitative lipid abundance values, sample metadata, lipid subclass annotations, and parsed acyl-chain features within a unified data structure. Lipid molecular species are summarized on static, curated lipid metabolic pathway maps at the subclass level while retaining direct links to the underlying molecular species and acyl-chain annotations. This design enables users to inspect molecular-species patterns underlying each pathway node, define lipid subsets based on structural features such as specific acyl chains, and re-project these subsets onto the same pathway context. Gene or protein expression data can also be overlaid on pathway-associated reactions to support multi-layer interpretation of lipid metabolism. The program is showcased using publicly available aging lipidome datasets of mice, illustrating how subclass-level pathway summaries can be connected to molecular-species heatmaps, acyl-chain-defined subsets, and transcriptome or proteome information.

bioinformatics↗

bioRxiv2026

OAC-PCA: orthogonal adjustment of confounding effects in principal component analysis for metabolomics data mining

Principal component analysis (PCA) is widely used in mass spectrometry-based metabolomics for exploratory data mining. Statistical testing of loading values can extract metabolite features associated with score patterns, but this approach requires principal components (PCs) to remain orthogonal while loadings are defined as correlation coefficients between PC scores and variables. Adjustment for Confounding PCA (AC-PCA) was previously developed to explore biologically meaningful components from data matrices affected by biological and technical confounders. However, AC-PCA does not simultaneously ensure PC orthogonality and a correlation-coefficient definition of loadings, limiting the statistical interpretation of its loadings. Here, we reformulated AC-PCA as Orthogonal Adjustment for Confounding effects in PCA (OAC-PCA). In OAC-PCA, PCs remain orthogonal, and loadings retain this correlation-coefficient interpretation. These properties enable statistical testing of metabolite associations while accounting for confounding effects.

bioinformatics↗

bioRxiv2026

Elucidation of the anti-inflammatory mechanism of isoliquiritigenin from Glycyrrhiza uralensis using activity-based protein profiling

Glycyrrhiza uralensis is a widely used medicinal plant present in more than 70% of Kampo formulations in Japan owing to its diverse pharmacological activities, including immunomodulatory, antitumor, and antioxidant effects. Isoliquiritigenin (ILG), a major chalcone constituent of G. uralensis, exhibits anti-inflammatory activity; however, its molecular mechanism remains unclear. Here, we employed an activity-based protein profiling approach to identify the molecular targets of ILG. Given that the ,{beta}-unsaturated carbonyl moiety of ILG can covalently react with reactive cysteine residues via nucleophilic addition, we used an iodoacetamide-based probe to globally profile cysteine-reactive proteomes. The comparative analysis between ILG- and vehicle-treated RAW 264.7 macrophages identified cysteine 65 (Cys65) of lipocalin-type prostaglandin D2 synthase (L-PGDS) as a potential covalent target. ILG treatment did not alter L-PGDS expression levels, indicating that reduced probe labeling reflects direct covalent competition rather than changes in expression. Consistently, ILG significantly suppressed prostaglandin D2 (PGD2) production, comparable to the selective L-PGDS inhibitor AT-56. Although both ILG and AT-56 reduced interleukin-6 expression, ILG exerted a stronger inhibitory effect. Our results demonstrate that covalent inhibition of L-PGDS and subsequent suppression of PGD2 production represent a key mechanism underlying the anti-inflammatory activity of ILG.

biochemistry↗

bioRxiv2026

Stable isotope-assisted computational mass spectrometry reveals root-specific alkaloids in Glycyrrhiza species

Licorice (Glycyrrhiza) is a medicinal plant widely used in approximately 70% of traditional Japanese Kampo formulations and is known to produce a wide array of specialized metabolites with diverse pharmacological properties. Although hundreds of metabolites have been reported, the overall chemical diversity of Glycyrrhiza remains poorly characterized. Here, using mass spectrometry data obtained from fully 13C-labeled leaves and roots of Glycyrrhiza uralensis and Glycyrrhiza glabra, we determined the carbon number, followed by molecular formula and substructure prediction in combination with MS/MS similarity-based molecular networking. After excluding redundant ions, including isotopic peaks, adducts, and in-source fragments, we extracted 3,060 unique metabolite features with assigned carbon numbers. Among these, substructure information was assigned to 1,015 features (33%) across the four plant tissues, revealing the tissue-specific metabolome profiles. Furthermore, we discovered five previously unreported alkaloids, homopipecolic acid-conjugated flavonoids, in the roots of G. uralensis and G. glabra, and Glycine max, another member of the Fabaceae family. Two of these structures were validated using nuclear magnetic resonance spectroscopy. We further proposed a biosynthetic route involving a spontaneous reaction between 1-piperideine and malonyl glycoside substrates and confirmed the formation of the conjugated product using authentic standards.

biochemistry↗

bioRxiv2026

Ether lipid remodeling during neuronal differentiation prevents ferroptosis

Ferroptosis is a form of cell death driven by iron-dependent lipid peroxidation, with specific lipid species playing key roles in modulating susceptibility. Among these, ether lipids have shown conflicting effects, being linked to both protection and sensitization. Here, we dissect the relationship between lipid structure and ferroptosis sensitivity and explain how ether lipids exert context-dependent effects. Ether lipids can promote ferroptosis through a metabolic bias towards the accumulation of polyunsaturated acyl chains and ethanolamine head groups, whereas this pro-ferroptotic tendency is counterbalanced by the anti-ferroptotic vinyl ether moiety introduced by plasmanylethanolamine desaturase 1. We show that this protective effect is critical for preventing ferroptosis in hiPSC-derived neurons, which accumulate otherwise pro-ferroptotic ether lipids during differentiation. This effect is not solely due to its antioxidant properties but also stems from the reprogramming of mitochondrial respiration. The lack of vinyl ether bonds leads to multiple mitochondrial defects, including increased mitochondrial reactive oxygen species (ROS), lower membrane potential, and abnormal cristae structures. These findings indicate that vinyl ether bonds in ether lipids offer dual ferroptosis resistance by scavenging ROS and minimizing its production at the mitochondrial level. The disruption of this system in Caenorhabditis elegans leads to iron-induced death and impaired motility. Thus, our study reveals ether lipid structural remodeling as a key regulator of ferroptosis sensitivity in neurons.

cell biology↗

bioRxiv2026

Integrated omics analysis reveals reorganization of nitrogen and lipids metabolism in a toluene-degrading bacterium

Gas-phase bioprocesses that immobilize microbial cells on solid carriers enable the efficient conversion of poorly water-soluble gaseous substrates, thereby offering significant potential to advance bioremediation and bioproduction. However, microorganisms in the gas phase are exposed to various environmental stresses, mainly due to the absence of bulk water. While survival strategies of microorganisms in gaseous environments have been studied in environmental microbiology, the metabolic adaptations that sustain bacterial cell activity remain poorly understood. In this study, we elucidated the comprehensive metabolic alterations of a highly adhesive bacterium Acinetobacter sp. Tol 5 degrading toluene under gas- and aqueous-phase conditions. An integrated approach combining metabolomics, lipidomics, and transcriptomics revealed significant differences in metabolic profiles between cells under these conditions. Under the gas-phase condition, the degradation of amino acids and nucleic acids was significantly promoted, and the intracellular glutamate pool was maintained at high levels. Notably, citrulline was found to accumulate specifically under the gas-phase condition, representing a stress response similar to that reported in Cucurbitaceae plants during drought. Furthermore, lipidomics revealed the lipid composition of Tol 5 and demonstrated a shift in response to environmental conditions. Specifically, the degradation of intracellular storage lipids was promoted under gas-phase conditions, suggesting a crucial link to bacterial survival in water-limited environments. These findings provide critical insights into the adaptation strategies of bacteria adapting to gaseous environments, offering fundamental information for the rational design of robust gas-phase bioprocesses and a deeper understanding of environmental microbiology.

microbiology↗

bioRxiv2026

Sodium ion-assisted structural lipidomics for sphingolipid profiling

Sphingolipids are diverse lipids with sphingobases and N-acyl fatty acids as the hydrophobic moieties. While the importance of the in-depth elucidation of hydrophobic structures is widely recognized in lipid biology, mass spectrometry-based annotation of ceramides in the commonly used protonated form is often hindered by in-source dehydration during electrospray ionization in the heated state and variable water losses in the product ion spectrum. In this study, we investigated the sodium ion form and its product ions in ceramides with the use of electron-activated dissociation tandem mass spectrometry (EAD MS/MS) in addition to collision-induced dissociation to facilitate indepth structural elucidation. While dehydrated ions from the protonated form were frequently observed, the sodium adduct ions remained stable because of their higher activation energy compared with the protonated form, which was validated using quantum chemical calculations. Using the three adduct forms under optimized conditions increased confidence in annotating the ceramide peaks through retention-time matching. Furthermore, EAD MS/MS of the sodium adduct ions facilitated the positional determination of double bonds and hydroxyl groups in the ceramide hydrophobic moiety. Our approach is showcased by the annotation of phytoceramides with N-acyl 2- and 3-hydroxyl groups in mouse feces and ceramides with N-acyl n-6 very long-chain polyunsaturated 2-hydroxy fatty acids in mouse testis.

bioengineering↗

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↗

bioRxiv2025

Unraveling anti-inflammatory metabolic signatures of Glycyrrhiza uralensis and isoliquiritigenin through multiomics

Glycyrrhiza uralensis, known for its diverse pharmacological effects, including immunoregulation, anti-tumor, and antioxidant properties, is a widely used medicinal plant found in more than 70% of traditional herbal medicines (Kampo) in Japan. Although over 300 compounds have been discovered in G. uralensis, the molecular mechanisms underlying its bioactivity remain largely unknown due to the chemical diversity of its compounds. Here, we performed a multiomics analysis incorporating untargeted hydrophilic metabolomics, lipidomics, and phosphoproteomics to elucidate the molecular mechanisms distinguishing the effects of a single bioactive compound, isoliquiritigenin (ILG), and the extract of G. uralensis (GU). Multiomics time-course data were obtained for lipopolysaccharide (LPS)-stimulated RAW264.7 cells under four experimental conditions: control, LPS(+), LPS(+)/ILG(+), and LPS(+)/GU(+), where 182 hydrophilic metabolites, 381 lipids, and 13,211 phosphopeptides were characterized. The metabolic signatures of inflammatory macrophages, including increased levels of glycolytic intermediates, succinate, citrulline, triacylglycerols, and cholesteryl esters, were attenuated in both the GU(+) and ILG(+) groups. Using a multivariate approach based on a partial least squares algorithm with an imposed inflammation level order information, we identified upregulated phosphorylation of sirtuin 1 and 2 (SIRT1/2) along with alterations in nicotinamide adenine dinucleotide metabolism in the ILG(+) group. The inhibition of SIRT2 suppressed the anti-inflammatory effect of ILG, as indicated by a reduction in interleukin-6 (IL-6) levels. Furthermore, we discovered a substantial increase in {gamma}-aminobutyric acid (GABA) and its downstream metabolite, 4-guanidinobutyric acid, in the GU(+) group. These increases were attributed to endogenous GABA production through glutamic acid decarboxylase rather than uptake via GABA transporters. Exogenous GABA administration significantly suppressed IL-6 and IL-1{beta} expression in LPS-stimulated cells, and the simultaneous administration of GABA and ILG enhanced the anti-inflammatory effects. Consequently, this study presents an approach to elucidating the importance of traditional herbal formulations and demonstrates the utility of multiomics in uncovering that endogenous GABA production would facilitate anti-inflammatory effects with ILG in GU administration.

systems biology↗

bioRxiv2024

Data-independent acquisition coupled with electron-activated dissociation for in-depth structure elucidation of fatty acid ester of hydroxy fatty acids

Fatty acid esters of hydroxy fatty acid (FAHFAs) are a biologically important class of lipids known for their anti-inflammatory and anti-diabetic effects in animals. The physiological activity of FAHFAs varies depending on the length of the carbon chain, number and position of double bonds (DBs), and the position of the hydroxyl (OH) group. Moreover, gut bacteria produce FAHFAs with more diverse structures than those produced by the host, which necessitates a FAHFA-lipidomics approach grasping their diverse structures to fully understand the physiological and metabolic significance of FAHFAs. In this study, we developed a methodology for in-depth structural elucidation of FAHFAs. First, FAHFAs were enriched using a solid-phase extraction (SPE) system coated with titanium and zirconium dioxide, which separated these analytes from neutral lipids and phospholipids. The fractionated metabolites were then derivatized using N,N-dimethylethylenediamine (DMED) to facilitate FAHFA detection in the positive ion mode of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) system. A data-independent acquisition technique known as sequential window acquisition of all theoretical mass spectra (SWATH-DIA) was used to collect sequential MS/MS spectra of the DMED-derivatized fatty acid metabolites. Structural elucidation was based on the fragment ions generated by electron-activated dissociation (EAD). DMED-FAHFAs were annotated using the newly updated MS-DIAL program, and FAHFA isomers were quantified using the MRMPROBS program, which quantifies lipids based on SWATH-MS/MS chromatograms. This procedure was applied to profile the FAHFAs present in mouse fecal samples, characterizing seven structures at the molecular species level, 63 structures at the OH position-resolved level, and 15 structures at both the DB and OH position-resolved levels using the MS-DIAL program. In the MRMPROBS analysis, 2OH and 3OH hydroxy fatty acids with more than 20 carbon atoms were predominantly expressed, while 5OH-13OH hydroxy fatty acids with 16 or 18 carbon atoms were the major components, abundant at positions 5, 7, 9, and 10. Furthermore, age-related changes in FAHFA isomers were also observed, where FAHFA 4:0/2O(FA 26:0) and FAHFA 16:0/10O(FA 16:0) significantly increased with age. In conclusion, our study offers a novel LC-SWATH-EAD-MS/MS technique with the updates of computational MS to facilitate in-depth structural lipidomics of FAHFAs. TOC graphics O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/627939v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@1d33c09org.highwire.dtl.DTLVardef@10a97b5org.highwire.dtl.DTLVardef@6e2c35org.highwire.dtl.DTLVardef@1186da5_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

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

Formation of giant ER sheets by pentadecanoic acid causes lipotoxicity in fission yeast

Excess amounts of saturated fatty acids are toxic to organisms, a condition termed lipotoxicity, which is often accompanied by pleiotropic cellular and tissue dysfunction. Here we show that pentadecanoic acid (C15:0) exerts toxicity on the fission yeast Schizosaccharomyces pombe by generating an aberrantly planar endoplasmic reticulum (ER) structure, which we named a "giant ER sheet." Untargeted lipidomics revealed that C15:0 is incorporated into complex lipids depending on an acyl-CoA ligase Lcf1 and an acyl-CoA transferase Slc1, thereby increasing the saturation level of the acyl chains. The toxicity and giant ER sheet formation were abolished by deleting Lcf1 or Slc1, indicating that the incorporation of C15:0 into glycerophospholipids causes giant ER sheet formation. The giant ER sheets disrupted the correct migration of Mid1, a protein determining the cell division site, and physically blocked septum formation, hindering correct cell separation. Our results suggest that the ER is the primary site targeted by saturated fatty acids, leading to lipotoxicity.

cell biology↗

bioRxiv2024

MS2Lipid: a lipid subclass prediction program using machine learning and curated tandem mass spectral data

Untargeted lipidomics using collision-induced dissociation-based tandem mass spectrometry (CID-MS/MS) is essential for biological and clinical applications. However, annotation confidence is still guaranteed by manual curation by analytical chemists, although various software tools have been developed for automatic spectral processing based on rule-based fragment annotations. In this study, we provide a novel machine learning model, MS2Lipid, for the prediction of lipid subclasses from MS/MS queries to provide an orthogonal decision of lipidomics software programs to determine the lipid subclass of ion features, in which a new descriptor, MCH (mode of carbon and hydrogen), was designed to increase the specificity of lipid subclasses in nominal mass resolution MS data. The model trained with 5,224 and 5,408 manually curated MS/MS spectra for the positive- and negative-ion modes mapped the query into one or several categories of 97 lipid subclasses, with an accuracy of 95.5% queries in the test set. Our program outperformed the CANOPUS ontology prediction program, providing correct annotations for 38.7% of the same test set. The program was further validated using various datasets from different machines and curators, and the average accuracy exceeded 87.4 %. Furthermore, the function of MS2Lipid was showcased by the annotation of novel esterified bile acids, whose abundance was significantly increased in obese patients in a human cohort study, suggesting that the machine learning model provides an independent criterion for lipid subclass classification, in addition to an environment for annotating lipid metabolites that have been previously unknown.

bioinformatics↗

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↗

bioRxiv2024

Using variable data independent acquisition for capillary electrophoresis-based untargeted metabolomics

Capillary electrophoresis coupled with tandem mass spectrometry (CE-MS/MS) offers advantages in peak capacity and sensitivity for metabolic profiling, owing to the electroosmotic flow-based separation. However, the utilization of data-independent MS/MS acquisition (DIA) is restricted due to the absence of an optimal procedure for analytical chemistry and its related informatics framework. We assessed the mass spectral quality using two DIA techniques, namely, all-ion fragmentation (AIF) and variable DIA (vDIA), to isolate 60[~]800 Da precursor ions with respect to annotation rates. Our findings indicate that vDIA, coupled with the updated MS-DIAL chromatogram deconvolution algorithm, yields higher spectral matching scores and annotation rates compared to AIF. Additionally, we evaluated a linear migration time (MT) correction method using internal standards to accurately align chromatographic peaks in a dataset. After the correction, the peaks exhibited less than 0.1 min MT drifts, a difference mostly equivalent to that of conventional reverse-phase liquid chromatography techniques. Moreover, we conducted MT prediction for metabolites recorded in mass spectral libraries and metabolite structure databases containing a total of 469,870 compounds, achieving an accuracy of less than 1.5 min root mean squares. Thus, our platform provides a peak annotation platform utilizing MT information, accurate precursor m/z, and the MS/MS spectrum recommended by the metabolomics standards initiative. Applying this procedure, we investigated metabolic alterations in lipopolysaccharide (LPS)-induced macrophages, characterizing 170 metabolites. Furthermore, we assigned metabolite information to unannotated peaks using an in-silico structure elucidation tool, MS-FINDER. The results were integrated into the nodes in the molecular spectrum network based on the MS/MS similarity score. Consequently, we identified a significantly increased amount of metabolites in the LPS-administration group, glycinamide ribonucleotide, not present in any spectral libraries. Additionally, we retrieved metabolites of false-negative hits in the initial spectral annotation procedure. Overall, our study underscores the potential of CE-MS/MS with DIA and computational mass spectrometry techniques for metabolic profiling.

biochemistry↗

bioRxiv2023

A procedure for solid phase extractions using metal oxide coated silica column in lipidomics

Lipid enrichment is indispensable for enhancing the coverage of targeted molecules in mass spectrometry (MS)-based lipidomics studies. In this study, we developed a simple stepwise fractionation method using a titanium- and zirconium-dioxide-coated solid-phase extraction (SPE) silica column that separates neutral lipids, phospholipids, and other lipids, including fatty acids (FAs) and glycolipids. Chloroform was used to dissolve the lipids, and neutral lipids, including steryl esters and di- and triacylglycerols, were collected in the loading fraction. Second, methanol with formic acid (99:1, v/v) was used to retrieve FAs, ceramides, and glycolipids, including glycosylated ceramides and glycosylated diacylglycerols, by competing for affinity with the Lewis acid sites on the metal oxide surface. Finally, phospholipids strongly retained via chemoaffinity interactions were eluted using a solution containing 5% ammonia and high water content (45:50 v/v, 2-propanol:water), which canceled the electrostatic and chelating interactions with the SPE column. High average reproducibility of <10% and coverage of [~]100% compared to those of the non-SPE samples were demonstrated by untargeted lipidomics of human plasma and mouse brain, testis, and feces. The advantage of our procedure was showcased by characterizing minor lipid subclasses, including dihexosylceramides containing very long-chain polyunsaturated FA in the testis, mono- and digalactosyl monoacylglycerols in feces, and acetylated and glycolylated derivatives of gangliosides in the brain that were not detected using conventional solvent extraction methods. Likewise, the value of our method in biology is maximized during glycolipidome profiling in the absence of neutral lipids and phospholipids that cover more than 80% of the chromatographic peaks. Table of Contents artwork O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/562428v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@170b451org.highwire.dtl.DTLVardef@4e4d3forg.highwire.dtl.DTLVardef@b1a1d4org.highwire.dtl.DTLVardef@1f77b31_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2023

Using data-dependent and independent hybrid acquisitions for fast liquid chromatography-based untargeted lipidomics

Untargeted lipidomics using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has become an essential technique for large cohort studies. When a fast LC gradient of less than 10 min is used for the rapid screening of lipids, the annotation rate decreases because of the lower coverage of the MS/MS spectra caused by the narrow peak width. We propose a systematic procedure to achieve a high annotation rate in fast LC-based untargeted lipidomics by integrating data-dependent acquisition (DDA), and sequential window acquisition of all theoretical mass spectra data-independent acquisition (SWATH-DIA) techniques with the updated MS-DIAL program. Our strategy uses variable SWATH-DIA methods for quality control (QC) samples, which are a mixture of biological samples analyzed multiple times to correct MS signal drifts. In contrast, biological samples are analyzed using DDA to facilitate the structural elucidation of lipids using the pure spectrum to the maximum extent. We demonstrate our workflow using an 8.6 min LC gradient, where QCs are analyzed using five different SWATH-DIA methods. The results indicated that using both DDA and SWATH-DIA achieves 2.0-fold annotation coverage from publicly available benchmark data obtained by a fast LC-DDA-MS technique and offers 94.5% lipid coverage compared with the benchmark dataset from a 25 min LC gradient. Our study demonstrated that harmonized improvements in the analytical conditions and informatics tools provide a comprehensive lipidome in fast LC-based untargeted lipidomics, not only for large-scale studies but also for small-scale experiments, contributing to both clinical applications and basic biology.

bioinformatics↗