bims-metlip 2024-12-01 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2024–12–01
33 papers selected by
Sofia Costa, Matterworks

Online Direct Infusion Mass Spectrometry of Liquid-Liquid Extraction Phases for Metabolite and Lipid Profiling with the Direct Infusion Probe.
A Comprehensive LC-MS Metabolomics Assay for Quantitative Analysis of Serum and Plasma.
A New LC-MS/MS-Based Method for the Simultaneous Detection of α-Tocopherol and Its Long-Chain Metabolites in Plasma Samples Using Stable Isotope Dilution Analysis.
Targeted Chiral Metabolomics of D-Amino Acids: Their Emerging Role as Potential Biomarkers in Neurological Diseases with a Focus on Their Liquid Chromatography-Mass Spectrometry Analysis upon Chiral Derivatization.
Four-Dimensional Lipidomic Analysis Using Comprehensive Online UHPLC × UHPSFC/Tandem Mass Spectrometry.
Comprehensive targeted profiling of multiple steroid classes in rodent plasma using liquid chromatography-mass spectrometry.
MS2Lipid: A Lipid Subclass Prediction Program Using Machine Learning and Curated Tandem Mass Spectral Data.
Validation of a sensitive bioanalytical method for metronidazole extraction from human plasma.
Application of magnetic bead-assisted liquid chromatography-tandem mass spectrometry method for analyzing serum bile acid profiles: Advancing toward automated mass spectrometry.
Determination of sacubitril and seven sartan drugs in serum samples by online solid phase extraction-liquid chromatography-tandem mass spectrometry.
rIDIMS: A novel tool for processing direct-infusion mass spectrometry data.
Tandem Mass Spectrometry in Untargeted Lipidomics: A Case Study of Peripheral Blood Mononuclear Cells.
Non-Invasive Monitoring of Corticosterone Levels in Mouse Urine with Liquid Chromatography-Electrospray Ionization-Tandem Mass Spectrometry.
Interlaboratory comparison of standardised metabolomics and lipidomics analyses in human and rodent blood using the MxP® Quant 500 kit.
Graphene Oxide/TiO2 Nanocomposite-Assisted Two-Step Ambient Liquid Extraction Mass Spectrometry Imaging for Comprehensively Enhancing Lipid Coverage in Spatial Lipidomics.
Exploratory analysis of metabolic changes using mass spectrometry data and graph embeddings.
MS-DIAL 5 multimodal mass spectrometry data mining unveils lipidome complexities.
Studying Structural Details in Complex Samples: II. High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Coupled to High Resolution Tandem Mass Spectrometry (MS/MS).
Stationary phase effects in hydrophilic interaction liquid chromatographic separation of oligonucleotides.
JESTR: Joint Embedding Space Technique for Ranking Candidate Molecules for the Annotation of Untargeted Metabolomics Data.
In Silico Mass Spectrometric Fragmentation and Liquid Chromatography with Tandem Mass Spectrometry (LC-MS/MS) Betalainic Fingerprinting: Identification of Betalains in Red Pitaya.
Metabolomic Analysis of Barley by Gas Chromatography/Mass Spectrometry.
Chromatography-Based Metabolomics as a Tool in Bioorganic Research of Honey.
Language model-guided anticipation and discovery of unknown metabolites.
Matrix Solid-Phase Dispersion Procedure for Determination of Antibiotics and Metabolites in Mussels: Application in Exposure Bioassays.
LC-MS-Based Simultaneous Determination of Biomarkers in Dried Urine Spots for the Detection of Cofactor-Dependent Metabolic Disorders in Neonates.
A Review on the Analysis of Chiral Molecules as Disease Biomarkers by LC/MS.
Comparative Metabolomic Analysis of the Nutrient Composition of Different Varieties of Sweet Potato.
iModMix : Integrative Module Analysis for Multi-omics Data.
Extraction Methods for Brain Biopsy NMR Metabolomics: Balancing Metabolite Stability and Protein Precipitation.
Spatial-resolved metabolome imaging of petals for Forsythia viridissima and Jasminum nudiflorum using online extraction (OLE) coupled to LC-Qtof-MS.
Dehydroascorbic acid quantification in human plasma: Simultaneous direct measurement of the ascorbic acid/dehydroascorbic acid couple by UPLC/MS-MS.
Metabolomics analysis reveals resembling metabolites between humanized γδ TCR mice and human plasma.

Metabolites. 2024 Oct 30. pii: 587. [Epub ahead of print]14(11):

Online Direct Infusion Mass Spectrometry of Liquid-Liquid Extraction Phases for Metabolite and Lipid Profiling with the Direct Infusion Probe.

Cátia Marques, Lena Blaase, Ingela Lanekoff.

  Background/Objectives: Profiling of metabolites and lipids in biological samples can provide invaluable insights into life-sustaining chemical processes. The ability to detect both metabolites and lipids in the same sample can enhance these understandings and connect cellular dynamics. However, simultaneous detection of metabolites and lipids is generally hampered by chromatographic systems tailored to one molecular type. This void can be filled by direct infusion mass spectrometry (MS), where all ionizable molecules can be detected simultaneously. However, in direct infusion MS, the high chemical complexity of biological samples can introduce limitations in detectability due to matrix effects causing ionization suppression. Methods: Decreased sample complexity and increased detectability and molecular coverage was provided by combining our direct infusion probe (DIP) with liquid-liquid extraction (LLE) and directly sampling the different phases for direct infusion. Three commonly used LLE methods for separating lipids and metabolites were evaluated. Results: The butanol-methanol (BUME) method was found to be preferred since it provides high molecular coverage and have low solvent toxicity. The established BUME DIP-MS method was used as a fast and sensitive analysis tool to study chemical changes in insulin-secreting cells upon glucose stimulation. By analyzing the metabolome at distinct time points, down to 1-min apart, we found high dynamics of the intracellular metabolome. Conclusions: The rapid workflow with LLE DIP-MS enables higher sensitivity of phase separated metabolites and lipids. The application of BUME DIP-MS provides novel information on the dynamics of the intracellular metabolome of INS-1 during the two phases of insulin release for both metabolite and lipid classes.

Keywords:  INS-1 cells; direct infusion probe; glucose stimulation; high-resolution mass spectrometry; liquid–liquid extraction; time-dependent analysis; untargeted metabolomics

DOI:  https://doi.org/10.3390/metabo14110587
Metabolites. 2024 Nov 14. pii: 622. [Epub ahead of print]14(11):

A Comprehensive LC-MS Metabolomics Assay for Quantitative Analysis of Serum and Plasma.

Lun Zhang, Jiamin Zheng, Mathew Johnson, Rupasri Mandal, Meryl Cruz, Miriam Martínez-Huélamo, Cristina Andres-Lacueva, David S Wishart.

  Background/Objectives: Targeted metabolomics is often criticized for the limited metabolite coverage that it offers. Indeed, most targeted assays developed or used by researchers measure fewer than 200 metabolites. In an effort to both expand the coverage and improve the accuracy of metabolite quantification in targeted metabolomics, we decided to develop a comprehensive liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay that could quantitatively measure more than 700 metabolites in serum or plasma. Methods: The developed assay makes use of chemical derivatization followed by reverse phase LC-MS/MS and/or direct flow injection MS (DFI-MS) in both positive and negative ionization modes to separate metabolites. Multiple reaction monitoring (MRM), in combination with isotopic standards and multi-point calibration curves, is used to detect and absolutely quantify the targeted metabolites. The assay has been adapted to a 96-well plate format to enable automated, high-throughput sample analysis. Results: The assay (called MEGA) is able to detect and quantify 721 metabolites in serum/plasma, covering 20 metabolite classes and many commonly used clinical biomarkers. The limits of detection were determined to range from 1.4 nM to 10 mM, recovery rates were from 80% to 120%, and quantitative precision was within 20%. LC-MS/MS metabolite concentrations of the NIST® SRM®1950 plasma standard were found to be within 15% of NMR quantified levels. The MEGA assay was further validated in a large dietary intervention study. Conclusions: The MEGA assay should make comprehensive quantitative metabolomics much more affordable, accessible, automatable, and applicable to large-scale clinical studies.

Keywords:  LC–MS; high-throughput; plasma; quantitative metabolomics; serum; targeted metabolomics

DOI:  https://doi.org/10.3390/metabo14110622
Pharmaceuticals (Basel). 2024 Oct 22. pii: 1405. [Epub ahead of print]17(11):

A New LC-MS/MS-Based Method for the Simultaneous Detection of α-Tocopherol and Its Long-Chain Metabolites in Plasma Samples Using Stable Isotope Dilution Analysis.

Alexander Maxones, Eva Beck, Gerald Rimbach, Marc Birringer.

  Background: Our study presented a novel LC-MS/MS method for the simultaneous quantification of α-tocopherol (α-TOH) and its phase II metabolites, α-13'-COOH and α-13'-OH, in human serum using deuterium-labeled internal standards (d6-α-TOH, d6-α-13'-COOH, d6-α-13'-OH). Methods: The method addresses the analytical challenge posed by the significantly different concentration ranges of α-TOH (µmol/L) and its metabolites (nmol/L). Previous methods quantified these analytes separately, which caused an increase in workflow complexity. Results: Key features include the synthesis of stable isotope-labeled standards and the use of a pentafluorophenyl-based core-shell chromatography column for baseline separation of both α-TOH and its metabolites. Additionally, solid phase extraction (SPE) with a HybridSPE® material provides a streamlined sample preparation, enhancing analyte recovery and improving sensitivity. By utilizing deuterium-labeled standards, the method compensates for matrix effects and ion suppression. This new approach achieves precise and accurate measurements with limits of detection (LOD) and quantification (LOQ), similar to previous studies. Calibration, accuracy, and precision parameters align well with the existing literature. Conclusions: Our method offers significant advantages in the simultaneous analysis of tocopherol and its metabolites despite concentration differences spanning up to three orders of magnitude. In contrast to earlier studies, which required separate sample preparations and analytical techniques for tocopherol and its metabolites, our approach streamlines this process. The use of a solid-phase extraction procedure allows for parallel sample preparation. This not only enhances efficiency but also significantly accelerates pre-analytical workflows, making the method highly suitable for large-scale studies.

Keywords:  liquid-chromatography tandem-mass spectrometry (LC-MS/MS); long chain metabolites; stable isotope dilution analysis; vitamin E

DOI:  https://doi.org/10.3390/ph17111405
Int J Mol Sci. 2024 Nov 19. pii: 12410. [Epub ahead of print]25(22):

Targeted Chiral Metabolomics of D-Amino Acids: Their Emerging Role as Potential Biomarkers in Neurological Diseases with a Focus on Their Liquid Chromatography-Mass Spectrometry Analysis upon Chiral Derivatization.

Cinzia Lella, Liam Nestor, Dimitri De Bundel, Yvan Vander Heyden, Ann Van Eeckhaut.

  In neuroscience research, chiral metabolomics is an emerging field, in which D-amino acids play an important role as potential biomarkers for neurological diseases. The targeted chiral analysis of the brain metabolome, employing liquid chromatography (LC) coupled to mass spectrometry (MS), is a pivotal approach for the identification of biomarkers for neurological diseases. This review provides an overview of D-amino acids in neurological diseases and of the state-of-the-art strategies for the enantioselective analysis of chiral amino acids (AAs) in biological samples to investigate their putative role as biomarkers for neurological diseases. Fluctuations in D-amino acids (D-AAs) levels can be related to the pathology of neurological diseases, for example, through their role in the modulation of N-methyl-D-aspartate receptors and neurotransmission. Because of the trace presence of these biomolecules in mammals and the complex nature of biological matrices, highly sensitive and selective analytical methods are essential. Derivatization strategies with chiral reagents are highlighted as critical tools for enhancing detection capabilities. The latest advances in chiral derivatization reactions, coupled to LC-MS/MS analysis, have improved the enantioselective quantification of these AAs and allow the separation of several chiral metabolites in a single analytical run. The enhanced performances of these methods can provide an accurate correlation between specific D-AA profiles and disease states, allowing for a better understanding of neurological diseases and drug effects on the brain.

Keywords:  D-amino acids; LC-MS/MS; biomarkers; chemical derivatization; chirality; enantioselective analysis; neurological diseases

DOI:  https://doi.org/10.3390/ijms252212410
Anal Chem. 2024 Nov 27.

Four-Dimensional Lipidomic Analysis Using Comprehensive Online UHPLC × UHPSFC/Tandem Mass Spectrometry.

Zuzana Lásko, Tomáš Hájek, Robert Jirásko, Ondřej Peterka, Petr Šimek, Peter J Schoenmakers, Michal Holčapek.

Multidimensional chromatography offers enhanced chromatographic resolution and peak capacity, which are crucial for analyzing complex samples. This study presents a novel comprehensive online multidimensional chromatography method for the lipidomic analysis of biological samples, combining lipid class and lipid species separation approaches. The method combines optimized reversed-phase ultrahigh-performance liquid chromatography (RP-UHPLC) in the first dimension, utilizing a 150 mm long C18 column, with ultrahigh-performance supercritical fluid chromatography (UHPSFC) in the second dimension, using a 10 mm long silica column, both with sub-2 μm particles. A key advantage of employing UHPSFC in the second dimension is its ability to perform ultrafast analysis using gradient elution with a sampling time of 0.55 min. This approach offers a significant increase in the peak capacity. Compared to our routinely used 1D methods, the peak capacity of the 4D system is 10 times higher than RP-UHPLC and 18 times higher than UHPSFC. The entire chromatographic system is coupled with a high-resolution quadrupole-time-of-flight (QTOF) mass analyzer using electrospray ionization (ESI) in both full-scan and tandem mass spectrometry (MS/MS) and with positive- and negative-ion polarities, enabling the detailed characterization of the lipidome. The confident identification of lipid species is achieved through characteristic ions in both polarity modes, information from MS elevated energy (MSE) and fast data-dependent analysis scans, and mass accuracy below 5 ppm. This analytical method has been used to characterize the lipidomic profile of the total lipid extract from human plasma, which has led to the identification of 298 lipid species from 16 lipid subclasses.

DOI: https://doi.org/10.1021/acs.analchem.4c03946
Anal Chim Acta. 2024 Dec 15. pii: S0003-2670(24)01163-2. [Epub ahead of print]1332 343362

Comprehensive targeted profiling of multiple steroid classes in rodent plasma using liquid chromatography-mass spectrometry.

Taťána Gazárková, Hana Kočová Vlčková, Kateřina Plachká, Karla Vagnerová, Dominika Dubecová, Petra Klusoňová, Jiří Pácha, Frantisek Svec, Lucie Nováková.

   BACKGROUND: Reliable quantification of multiple steroid classes in biological fluids within a single method remains an analytical challenge despite many previously published methods. Crosstalk of positional isomers, overlap of stereoisomer fragmentation patterns, differing proton affinities, in-source fragmentation, varying stability of protonated ions in the gas phase across steroid classes, and non-existence of steroid-free matrix are the main challenges limiting the number of simultaneously profiled steroids.
RESULTS: In this study, we focused on the development of a derivatization-free, achiral, high-throughput, and cost-effective UHPLC-MS/MS approach that allows simultaneous profiling of a spectrum of 38 steroids covering progestogens, androgens, corticosteroids, and estrogens, while properly addressing the hurdles of steroid analysis. Within a 20-min method, 16 stereoisomers and 15 positional isomers were fully resolved within a single run while separated from 7 additional non-interfering steroids and matrix interferences in rodent plasma. Protein precipitation (PP) and supported liquid extraction (SLE) methods using only 40 μL of sample were developed to achieve the lowest possible limits of quantification. Nevertheless, 5α-dihydroprogesterone and 3α,5α-THDOC could be only qualitatively assessed when using PP. In contrast, DHEA-S could not be quantified or identified when using SLE. A novel surrogate matrix-background subtraction approach, using rat plasma after the animal's adrenalectomy, has been implemented into the optimized PP-UHPLC-MS/MS workflow, successfully validated according to the unified ICH/EMA M10 guidelines, and compared to the traditional quantification strategies. Moreover, the validity of the newly adopted approach has been verified by the targeted profiling of multiple biologically active endogenous steroids in more than 500 samples of mouse plasma in total.
SIGNIFICANCE: Underestimation of hurdles associated with steroid analysis often compromises the accurate steroid quantification. Our comprehensive, fully validated UHPLC-MS/MS method targeting a wide spectrum of endogenous steroids, mitigating steroid crosstalk and using a minimal sample volume together with a novel surrogate matrix-background subtraction approach significantly advances steroid analysis for research and clinical applications covering multiple biological scopes.

Keywords:  Bioanalytical method validation; Isomeric compounds; Protein precipitation; Rodent plasma; Targeted steroid profiling; UHPLC-MS/MS

DOI:  https://doi.org/10.1016/j.aca.2024.343362
Metabolites. 2024 Nov 07. pii: 602. [Epub ahead of print]14(11):

MS2Lipid: A Lipid Subclass Prediction Program Using Machine Learning and Curated Tandem Mass Spectral Data.

Nami Sakamoto, Takaki Oka, Yuki Matsuzawa, Kozo Nishida, Jayashankar Jayaprakash, Aya Hori, Makoto Arita, Hiroshi Tsugawa.

  Background: Untargeted lipidomics using collision-induced dissociation-based tandem mass spectrometry (CID-MS/MS) is essential for biological and clinical applications. However, annotation confidence still relies on manual curation by analytical chemists, despite the development of various software tools for automatic spectral processing based on rule-based fragment annotations. Methods: In this study, we present a novel machine learning model, MS2Lipid, for the prediction of known lipid subclasses from MS/MS queries, providing an orthogonal approach to existing lipidomics software programs in determining the lipid subclass of ion features. We designed a new descriptor, MCH (mode of carbon and hydrogen), to increase the specificity of lipid subclass prediction in nominal mass resolution MS data. Results: The model, trained with 6760 and 6862 manually curated MS/MS spectra for the positive and negative ion modes, respectively, classified queries into one or several of 97 lipid subclasses, achieving an accuracy of 97.4% in the test set. The program was further validated using various datasets from different instruments and curators, with the average accuracy exceeding 87.2%. Using an integrated approach with molecular spectral networking, we demonstrated the utility of MS2Lipid by annotating microbiota-derived esterified bile acids, whose abundance was significantly increased in fecal samples of obese patients in a human cohort study. This suggests that the machine learning model provides an independent criterion for lipid subclass classification, enhancing the annotation of lipid metabolites within known lipid classes. Conclusions: MS2Lipid is a highly accurate machine learning model that enhances lipid subclass annotation from MS/MS data and provides an independent criterion.

Keywords:  human fecal samples; lipid class prediction; machine learning; microbiota-dependent lipids; tandem mass spectrum; untargeted lipidomics

DOI:  https://doi.org/10.3390/metabo14110602
J Pharm Biomed Anal Open. 2024 Jun;pii: 100025. [Epub ahead of print]3

Validation of a sensitive bioanalytical method for metronidazole extraction from human plasma.

Krishna Kumar Patel, Valeria Cota, Nicole K Brogden.

  Metronidazole (MTZ) is a broad-spectrum antibiotic with numerous routes of administration, including topical. Topical application of MTZ gel or cream results in very low systemic absorption, resulting in the need for a sensitive extraction method to quantify plasma concentrations. Currently published methods are not suitable for analysis of plasma concentrations after topical application, as undetectable MTZ concentrations commonly occur. We validated a simple extraction method for MTZ recovery from plasma and quantified it using an LC-MS/MS analytical method. Methods: Plasma samples were spiked with MTZ (0.5 - 5 ng/mL) and internal standard (tinidazole, 2 ng/mL). MTZ was extracted by liquid-liquid extraction using ethyl acetate and acetonitrile mixture (4:1) as the extraction solvent. A quadrupole mass spectrometer interfaced with an Acquity H-Class HPLC was used to quantify MTZ concentrations in positive ion mode. A Kinetix C18 analytical column (150 mm × 4.6 mm i. d., 5 μm particle size) was used for separation. The plasma extraction method was validated for various parameters, including % recovery, precision, accuracy, and stability. Results: The extraction method demonstrated high MTZ recovery, ranging from 93.7 - 97.5%. The calibration curve prepared using MTZ samples extracted from plasma (0.5 - 5 ng/mL) had excellent linearity with R2 = 0.999. The extracted samples also showed higher autosampler and freeze-thaw stability over a 72-hr period. The mean intra- and inter-day accuracy and precision of the extraction assay ranged from 97 to 101.6% and 2.7 - 4.8% RSD, respectively. The assay was highly efficient, with a limit of quantification (0.53 ± 0.04 ng/mL) lower than previously published methods (≥5 ng/mL). The extraction method was successfully validated using LC-MS/MS and can be used to extract and detect trace amounts of MTZ in plasma after topical application.

Keywords:  Bioanalytical assay; Extraction; Human plasma; LC-MS/MS; Metronidazole; Validation

DOI:  https://doi.org/10.1016/j.jpbao.2024.100025
Clin Chim Acta. 2024 Nov 22. pii: S0009-8981(24)02311-8. [Epub ahead of print]566 120058

Application of magnetic bead-assisted liquid chromatography-tandem mass spectrometry method for analyzing serum bile acid profiles: Advancing toward automated mass spectrometry.

Yu Zhou, Jing Du, Yamei Liu, Jinfei Ma, Xiaofen Yuan, Jun Xia.

   BACKGROUND: Magnetic bead-assisted extraction technology offers potential for automating mass spectrometry processes, yet research in this area remains limited. Here, we developed and validated a magnetic bead extraction method to simultaneously analyze 13 bile acid profiles in human serum.
METHODS: A magnetic bead-assisted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was established for serum bile acid profiles. The linearity, accuracy, precision, matrix effect, carryover, stability test and interference test of the LC-MS/MS method were assessed. Comparative analysis involving 20 pregnant women evaluated different methodologies for diagnosing and monitoring intrahepatic cholestasis of pregnancy (ICP).
RESULTS: The magnetic bead extraction method demonstrated analytical performance comparable to the traditional protein precipitation method. The method exhibited linear responses across the clinical reference interval for all 13 bile acids. Meanwhile, the recovery rates for bile acid analytes ranged from 85.14 to 114.43%, and the repeatability was within 1.68 to 10.83%, meeting acceptance criteria. Our magnetic bead-assisted extraction method showed no obvious matrix effects and carryover effects. The extracted specimens remained stable in the autosampler for 24 h, and the interference test suggested the bile acid profile results would not be significantly affected under different interfering substances. Furthermore, comparative studies with traditional protein precipitation method showed comparable results, and our method exhibited robust clinical consistency in monitoring the efficacy of ICP patients.
CONCLUSIONS: We developed a straightforward magnetic bead extraction method coupled with LC-MS/MS for bile acid profiles. It can be applied to the clinical routine diagnosis of ICP and facilitate the automated mass spectrometry processes.

Keywords:  Automation; Intrahepatic cholestasis of pregnancy; Liquid chromatography-tandem mass spectrometry; Magnetic bead-assisted extraction; Serum bile acid profiles

DOI:  https://doi.org/10.1016/j.cca.2024.120058
J Pharm Biomed Anal. 2024 Nov 22. pii: S0731-7085(24)00622-8. [Epub ahead of print]254 116580

Determination of sacubitril and seven sartan drugs in serum samples by online solid phase extraction-liquid chromatography-tandem mass spectrometry.

Yanan Guo, Shuang Cao, Bin Geng, Juanjuan Ma, Bo Yao.

  An online solid phase extraction-ultra performance liquid chromatography-tandem mass spectrometry detection method was developed for the simultaneous determination of sacubitril and seven sartan drugs in blood serum in this study. The compounds were separated through a C18 column. Mass spectrometry of the samples was performed using a jet stream electrospray ion source (AJS, ESI+). The samples were detected via a multiple reaction monitoring (MRM) mode and quantified via a stable isotope internal standard method. 900 μL of prepared sample was injected and a run time of 12.5 minutes was obtained in this proposed method. The eight examined target compounds showed good linearity (r2＞0.994) in the corresponding mass concentration range and a lower limit of quantitation (LLOQ) was in the range of 0.05-0.1 μg/L. The recovery of the spiked serum samples ranged from 90.90 % to 106.20 % with relative standard deviations (RSDs) of 4.57 %-9.27 %. Five target compounds were detected in the actual serum samples using this method. The proposed method is simple to use, sensitive, accurate, and suitable for the trace detection of sacubitril and seven sartan drugs present in serum samples. The method can meet the needs for clinical monitoring of blood concentrations of this type of drug, while providing detection technology support for the development of compound preparations of sacubitril and other sartan drugs.

Keywords:  Blood serum; Online solid phase extraction; Sacubitril; Sartan drug; Ultraperformance liquid chromatography–tandem mass spectrometry

DOI:  https://doi.org/10.1016/j.jpba.2024.116580
Talanta. 2024 Nov 22. pii: S0039-9140(24)01652-7. [Epub ahead of print]284 127273

rIDIMS: A novel tool for processing direct-infusion mass spectrometry data.

Felipe R P Mansoldo, Iasmim Lopes de Lima, Caroline Pais de Carvalho, Adriano R J da Silva, Marcos Nogueira Eberlin, Alane Beatriz Vermelho.

  Metabolomics using mass spectrometry-only (MS) analysis either by continuous or intermittent direct infusion (DIMS) and ambient ionization techniques (AMS) has grown in popularity due to their rapid, high-throughput nature and the advantage of performing fast analysis with minimal or no sample pretreatments. But currently, end-users without programming knowledge do not find applications with Graphical User Interface (GUI) specialized in processing DIMS or AMS data. Specifically, there is a lack of standardized workflow for processing data from limited sample sizes and scans from different total ion chronograms (TIC).To address this gap, we present rIDIMS, a browser-based application that offers a straightforward and fast workflow focusing on high-quality scan selection, grouping of isotopologues and adducts, data alignment, binning, and filtering. We also introduce a novel function for selecting TIC scans that is reproducible and statistically reliable, which is a feature particularly useful for studies with limited sample sizes. After processing in rIDIMS, the result is exported in an HTML report document that presents publication-quality figures, statistical data and tables, ready to be customized and exported. We demonstrate rIDIMS functionality in three cases: (i) Classification of coffee bean species through the chemical profile obtained with Mass Spec Pen; (ii) Public repository DIMS data from lipid profiling in monogenic insulin resistance syndromes, and (iii) Lipids for lung cancer classification. We show that our implementation facilitates the processing of AMS and DIMS data through an easy and intuitive interface, contributing to reproducible and reliable metabolomic investigations. Indeed, rIDIMS function asa user-friendly GUI based Shiny web application for intuitive use by end-users (available at https://github.com/BioinovarLab/rIDIMS).

Keywords:  Ambient ionization; Direct infusion mass spectrometry; Graphical user interface for mass spectrometry data processing; MasSpec pen; Metabolomics

DOI:  https://doi.org/10.1016/j.talanta.2024.127273
Int J Mol Sci. 2024 Nov 10. pii: 12077. [Epub ahead of print]25(22):

Tandem Mass Spectrometry in Untargeted Lipidomics: A Case Study of Peripheral Blood Mononuclear Cells.

Giovanni Ventura, Mariachiara Bianco, Cosima Damiana Calvano, Ilario Losito, Tommaso R I Cataldi.

  Peripheral blood mononuclear cells (PBMCs), including lymphocytes, are important components of the human immune system. These cells contain a diverse array of lipids, primarily glycerophospholipids (GPs) and sphingolipids (SPs), which play essential roles in cellular structure, signaling, and programmed cell death. This study presents a detailed analysis of GP and SP profiles in human PBMC samples using tandem mass spectrometry (MS/MS). Hydrophilic interaction liquid chromatography (HILIC) and electrospray ionization (ESI) coupled with linear ion-trap MS/MS were employed to investigate the diagnostic fragmentation patterns that aided in determining regiochemistry in complex lipid extracts. Specifically, the study explored the fragmentation patterns of various lipid species, including phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), their plasmalogen and lyso forms, phosphatidylserines (PSs), phosphatidylinositols (PIs), phosphatidylglycerols (PGs), sphingomyelins (SMs), and dihexosylceramides (Hex2Cer). Our comprehensive analysis led to the characterization of over 200 distinct lipid species, significantly expanding our understanding of PBMC lipidome complexity. A freely available spreadsheet tool for simulating MS/MS spectra of GPs is provided, enhancing the accessibility and reproducibility of this research. This study advances our knowledge of PBMC lipidomes and establishes a robust analytical framework for future investigations in lipidomics.

Keywords:  HILIC; biomarker discovery; lipidomics; product ions; tandem MS

DOI:  https://doi.org/10.3390/ijms252212077
Molecules. 2024 Nov 15. pii: 5399. [Epub ahead of print]29(22):

Non-Invasive Monitoring of Corticosterone Levels in Mouse Urine with Liquid Chromatography-Electrospray Ionization-Tandem Mass Spectrometry.

Laura Howe-Wittek, Paul Kroschk, Kai Nieschalke, Harshadrai M Rawel, Stephanie Krämer, Jens Raila.

  An innovative method for the quantification of corticosterone in the urine of C57BL/6J mice by liquid chromatography-electrospray ionization-tandem mass spectrometry was developed. Unconjugated and glucuronidated corticosterone was detected in the urine samples using enzymatic hydrolysis following liquid-liquid extraction. After optimization of the extraction protocol and LC-MS/MS parameters, we performed a validation study using a representative urine pool of C57BL/6J and Naval Medical Research Institute mice. The method shows good linearity (1-5000 fmol/µL) and the calculated limit of quantification amounts to 0.823 fmol/µL. Both intra-day and inter-day variation was ≤10%, while their recoveries amounted to 90.4-110.6% and 99.8%, respectively. Twenty-four hour urine collection of C57BL/6J mice restrained in two different metabolic cage types for two times was used to test the validated method. To control the hydration level of mice, the corticosterone concentration in their urine was normalized to urinary creatinine concentration. Our LC-MS/MS method represents a highly specific analytical tool for the quantification of corticosterone levels in urine samples, assisting in non-invasive monitoring of acute stress levels in laboratory mice.

Keywords:  C57BL/6J mice; corticosterone; enzymatic hydrolysis; liquid chromatography-electrospray ionization-tandem mass spectrometry; liquid–liquid extraction; metabolic cage; non-invasive monitoring; stress; urine

DOI:  https://doi.org/10.3390/molecules29225399
bioRxiv. 2024 Nov 14. pii: 2024.11.13.619447. [Epub ahead of print]

Interlaboratory comparison of standardised metabolomics and lipidomics analyses in human and rodent blood using the MxP® Quant 500 kit.

Gözde Ertürk Zararsiz, Jutta Lintelmann, Alexander Cecil, Jennifer Kirwan, Gernot Poschet, Hagen M Gegner, Sven Schuchardt, Xue Li Guan, Daisuke Saigusa, David Wishart, Jiamin Zheng, Rupasri Mandal, Kendra Adams, J Will Thompson, Michael P Snyder, Kevin Contrepois, Songjie Chen, Nadia Ashrafi, Sumeyya Akyol, Ali Yilmaz, Stewart F Graham, Thomas M O'Connell, Karel Kalecký, Teodoro Bottiglieri, Alice Limonciel, Hai Tuan Pham, Therese Koal, Jerzy Adamski, Gabi Kastenmüller.

Metabolomics and lipidomics are pivotal in understanding phenotypic variations beyond genomics. However, quantification and comparability of mass spectrometry (MS)-derived data are challenging. Standardised assays can enhance data comparability, enabling applications in multi-center epidemiological and clinical studies. Here we evaluated the performance and reproducibility of the MxP® Quant 500 kit across 14 laboratories. The kit allows quantification of 634 different metabolites from 26 compound classes using triple quadrupole MS. Each laboratory analysed twelve samples, including human plasma and serum, lipaemic plasma, NIST SRM 1950, and mouse and rat plasma, in triplicates. 505 out of the 634 metabolites were measurable above the limit of detection in all laboratories, while eight metabolites were undetectable in our study. Out of the 505 metabolites, 412 were observed in both human and rodent samples. Overall, the kit exhibited high reproducibility with a median coefficient of variation (CV) of 14.3 %. CVs in NIST SRM 1950 reference plasma were below 25 % and 10 % for 494 and 138 metabolites, respectively. To facilitate further inspection of reproducibility for any compound, we provide detailed results from the in-depth evaluation of reproducibility across concentration ranges using Deming regression. Interlaboratory reproducibility was similar across sample types, with some species-, matrix-, and phenotype-specific differences due to variations in concentration ranges. Comparisons with previous studies on the performance of MS-based kits (including the AbsoluteIDQ p180 and the Lipidyzer) revealed good concordance of reproducibility results and measured absolute concentrations in NIST SRM 1950 for most metabolites, making the MxP® Quant 500 kit a relevant tool to apply metabolomics and lipidomics in multi-center studies.

DOI: https://doi.org/10.1101/2024.11.13.619447
Anal Chem. 2024 Nov 26.

Graphene Oxide/TiO2 Nanocomposite-Assisted Two-Step Ambient Liquid Extraction Mass Spectrometry Imaging for Comprehensively Enhancing Lipid Coverage in Spatial Lipidomics.

Jiawei Lei, Zhihao Zhao, Qian Wu, Hongmei Lu.

It is challenging to have comprehensive spatial lipidomic analysis by mass spectrometry imaging (MSI) due to the strong ion suppression and peak interference from high-abundance polar lipids to low-abundance poorly ionizable lipids. In this work, we proposed a new MSI approach via ambient liquid extraction techniques assisted by a new mixed-mode adsorptive material, graphene oxide (GO)/TiO2 nanocomposite. The material combines chelation affinity from TiO2 and hydrophobic interaction from GO. By finely tuning the adsorption solvent as 9% H2O-6% ammonia-85% methanol/acetonitrile (1:1, v/v), simultaneous enrichment of poorly ionizable glycolipids and glycerides with separation from high-abundance phospholipids was achieved on the material. In 10 mg/mL glucose-6% ammonia-94% methanol, all of the adsorbed glycolipids and glycerides could be desorbed from the material efficiently. Then, GO/TiO2 nanocomposite was coated onto the sample plate for thaw-mounting the tissue section, and ambient liquid extraction probe was used to have pixel-to-pixel desorption of the lipids on the section in two steps with the above two solvents. The results show that most of the phospholipids were imaged in the first step MSI, and glycolipids and glycerides were selectively imaged in the second step MSI, largely reducing ion suppression and peak interference. Compared with direct ambient liquid extraction MSI, much more glycolipid species (22 vs 9), glyceride species (10 vs 5), phosphatidylethanolamines (11 vs 3), and lysophospholipids (12 vs 2) were detected via GO/TiO2 nanocomposite-assisted two-step MSI. The ion images of most lipids show much higher signals and imaging quality with the new method than with the traditional method. Thus, comprehensive enhancement of lipid coverage in MSI by on-tissue separation was achieved here for the first time, providing more information about spatial lipidomics studies.

DOI: https://doi.org/10.1021/acs.analchem.4c03955
Sci Rep. 2024 Nov 28. 14(1): 29570

Exploratory analysis of metabolic changes using mass spectrometry data and graph embeddings.

Edwin Alvarez-Mamani, Florian Buettner, Cesar A Beltran-Castanon, Alfredo J Ibanez.

  Mass spectrometry (MS)-based metabolomics analysis is a powerful tool, but it comes with its own set of challenges. The MS workflow involves multiple steps before its interpretation in what is denominate data mining. Data mining consists of a two-step process. First, the MS data is ordered, arranged, and presented for filtering before being analyzed. Second, the filtered and reduced data are analyzed using statistics to remove further variability. This holds true particularly for MS-based untargeted metabolomics studies, which focused on understanding fold changes in metabolic networks. Since the task of filtering and identifying changes from a large dataset is challenging, automated techniques for mining untargeted MS-based metabolomic data are needed. The traditional statistics-based approach tends to overfilter raw data, which may result in the removal of relevant data and lead to the identification of fewer metabolomic changes. This limitation of the traditional approach underscores the need for a new method. In this work, we present a novel deep learning approach using node embeddings (powered by GNNs), edge embeddings, and anomaly detection algorithm to analyze the data generated by mass spectrometry (MS)-based metabolomics called GEMNA (Graph Embedding-based Metabolomics Network Analysis), for example for an untargeted volatile study on Mentos candy, the data clusters produced by GEMNA were better than the ones used traditional tools, i.e., GEMNA has [Formula: see text], vs. the traditional approach has [Formula: see text].

Keywords:  Graph embeddings; Graph neural networks; Mass spectrometry; Metabolomic networks

DOI:  https://doi.org/10.1038/s41598-024-80955-5
Nat Commun. 2024 Nov 28. 15(1): 9903

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

Hiroaki Takeda, Yuki Matsuzawa, Manami Takeuchi, Mikiko Takahashi, Kozo Nishida, Takeshi Harayama, Yoshimasa Todoroki, Kuniyoshi Shimizu, Nami Sakamoto, Takaki Oka, Masashi Maekawa, Mi Hwa Chung, Yuto Kurizaki, Saki Kiuchi, Kanako Tokiyoshi, Bujinlkham Buyantogtokh, Misaki Kurata, Aleš Kvasnička, Ushio Takeda, Haruki Uchino, Mayu Hasegawa, Junki Miyamoto, Kana Tanabe, Shigenori Takeda, Tetsuya Mori, Ryota Kumakubo, Tsuyoshi Tanaka, Tomoko Yoshino, Mami Okamoto, Hidenori Takahashi, Makoto Arita, Hiroshi Tsugawa.

Lipidomics and metabolomics communities comprise various informatics tools; however, software programs handling multimodal mass spectrometry (MS) data with structural annotations guided by the Lipidomics Standards Initiative are limited. Here, we provide MS-DIAL 5 for in-depth lipidome structural elucidation through electron-activated dissociation (EAD)-based tandem MS and determining their molecular localization through MS imaging (MSI) data using a species/tissue-specific lipidome database containing the predicted collision-cross section values. With the optimized EAD settings using 14 eV kinetic energy, the program correctly delineated lipid structures for 96.4% of authentic standards, among which 78.0% had the sn-, OH-, and/or C = C positions correctly assigned at concentrations exceeding 1 μM. We showcased our workflow by annotating the sn- and double-bond positions of eye-specific phosphatidylcholines containing very-long-chain polyunsaturated fatty acids (VLC-PUFAs), characterized as PC n-3-VLC-PUFA/FA. Using MSI data from the eye and n-3-VLC-PUFA-supplemented HeLa cells, we identified glycerol 3-phosphate acyltransferase as an enzyme candidate responsible for incorporating n-3 VLC-PUFAs into the sn1 position of phospholipids in mammalian cells, which was confirmed using EAD-MS/MS and 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 insights into lipid biology.

DOI: https://doi.org/10.1038/s41467-024-54137-w
J Am Soc Mass Spectrom. 2024 Nov 25.

Studying Structural Details in Complex Samples: II. High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Coupled to High Resolution Tandem Mass Spectrometry (MS/MS).

Alessandro Vetere, Wolfgang Schrader.

The elucidation of structural motifs in extremely complex mixtures is very difficult since the standard methods for structural elucidation are not capable to provide significant information on a single molecule. The best method for the analysis of complex mixtures is ultrahigh resolution mass spectrometry, but the utilization of this method alone does not provide significant information about structural details. Here, a combination with a separation method is necessary. While chromatography is a well-established technique, it has some disadvantages in regard to the separation of complex mixtures, as often no separation of individual isomers is possible. Therefore, here the combination of an ion mobility separation with ultrahigh resolution mass spectrometry is evaluated. As a sample matrix, crude oil is used because it is an excellent matrix to develop new analytical techniques on complex samples. Crude oil is the most complex natural sample known, but only little information is available on the structural identity or functionalities due to a high number of structural isomers or isobars. A lab-built APPI/APLI-FAIMS source was revised to optimize ion transmission and used to follow up on the ion mobility of crude oil constituents after photoionization. An MS/MS approach using collision-induced dissociation (CID) was used to elucidate structural motifs of the transmitted isomers.

DOI: https://doi.org/10.1021/jasms.4c00227
Analyst. 2024 Nov 29.

Stationary phase effects in hydrophilic interaction liquid chromatographic separation of oligonucleotides.

Scott Abernathy, Asif Rayhan, Patrick A Limbach.

The use of liquid chromatography coupled with mass spectrometry (LC-MS) for the characterization of oligonucleotides and nucleic acids is a powerful analytical method. Recently, hydrophilic interaction chromatography (HILIC) has been proposed as a reasonable alternative to ion-pair reversed phase separations of oligonucleotides prior to MS. A wide variety of HILIC stationary phase surface chemistries are currently available. Although their selectivity can be considerably different, few studies have compared these chemistries for LC-MS analysis of oligonucleotides. We evaluated ten different HILIC column chemistries to understand their capabilities for separating a variety of oligonucleotides. In general, we found that most columns were ineffective at separating larger (n > 15-mer) oligonucleotides under the mobile phase and gradient conditions evaluated here. However, several stationary phases were found to be effective for separating smaller oligonucleotides such as endonuclease digestion products. Given that early eluting oligonucleotides were found to be compatible with standard electrospray ionization conditions, several different HILIC stationary phase options are available for LC-MS studies of smaller oligonucleotides including those generated in RNA modification mapping experiments.

DOI: https://doi.org/10.1039/d4an01155d
ArXiv. 2024 Nov 25. pii: arXiv:2411.14464v2. [Epub ahead of print]

JESTR: Joint Embedding Space Technique for Ranking Candidate Molecules for the Annotation of Untargeted Metabolomics Data.

Apurva Kalia, Dilip Krishnan, Soha Hassoun.

MOTIVATION: A major challenge in metabolomics is annotation: assigning molecular structures to mass spectral fragmentation patterns. Despite recent advances in molecule-to-spectra and in spectra-to-molecular fingerprint prediction (FP), annotation rates remain low.
RESULTS: We introduce in this paper a novel paradigm (JESTR) for annotation. Unlike prior approaches that explicitly construct molecular fingerprints or spectra, JESTR leverages the insight that molecules and their corresponding spectra are views of the same data and effectively embeds their representations in a joint space. Candidate structures are ranked based on cosine similarity between the embeddings of query spectrum and each candidate. We evaluate JESTR against mol-to-spec and spec-to-FP annotation tools on three datasets. On average, for rank@[1-5], JESTR outperforms other tools by 23.6%-71.6%. We further demonstrate the strong value of regularization with candidate molecules during training, boosting rank@1 performance by 11.4% and enhancing the model's ability to discern between target and candidate molecules. Through JESTR, we offer a novel promising avenue towards accurate annotation, therefore unlocking valuable insights into the metabolome.
Molecules. 2024 Nov 20. pii: 5485. [Epub ahead of print]29(22):

In Silico Mass Spectrometric Fragmentation and Liquid Chromatography with Tandem Mass Spectrometry (LC-MS/MS) Betalainic Fingerprinting: Identification of Betalains in Red Pitaya.

Jesús Alfredo Araujo-León, Ivonne Sánchez-Del Pino, Ligia Guadalupe Brito-Argáez, Sergio R Peraza-Sánchez, Rolffy Ortiz-Andrade, Victor Aguilar-Hernández.

  Betalains, which contain nitrogen and are water soluble, are the pigments responsible for many traits of plants and biological activities in different organisms that do not produce them. To better annotate and identify betalains using a spectral library and fingerprint, a database catalog of 140 known betalains (112 betacyanins and 28 betaxanthins) was made in this work to simplify betalain identification in mass spectrometry analysis. Fragmented peaks obtained using MassFrontier, along with chemical structures and protonated precursor ions for each betalain, were added to the database. Product ions made in MS/MS and multistage MS analyses of betanin, beetroot extract, and red pitaya extract revealed the fingerprint of betalains, distinctive ions of betacyanin, betacyanin derivatives such as decarboxylated and dehydrogenated betacyanins, and betaxanthins. A distinctive ion with m/z 211.07 was found in betaxanthins. By using the fingerprint of betalains in the analysis of red pitaya extracts, the catalog of betalains in red pitaya was expanded to 86 (31 betacyanins, 36 betacyanin derivatives, and 19 betaxanthins). Four unknown betalains were detected to have the fingerprint of betalains, but further research will aid in revealing the complete structure. Taken together, we envisage that the further use of the fingerprint of betalains will increase the annotation coverage of identified molecules in studies related to revealing the biological function of betalains or making technologies based on these natural colorants.

Keywords:  LC-MS/MS; betacyanin derivatives; betacyanins; betaxanthins; fingerprint betalains; red pitaya

DOI:  https://doi.org/10.3390/molecules29225485
J Vis Exp. 2024 Nov 08.

Metabolomic Analysis of Barley by Gas Chromatography/Mass Spectrometry.

Peter J Wieber, Gabrielle Feber, Patrick J Hrdlicka, Zachary Kayler.

Climate change increases drought risk to agriculture and impacts both food nutrient content and overall food security. Metabolomics is one way to observe and quantify the impacts of drought on grain and other agricultural products. The identified metabolites may allow for the identification of the biochemical response that allows the plant to tolerate stressful environments. The methodology presented herein allowed for the total metabolomic analysis of barley flour using gas chromatography/mass spectrometry (GC/MS). Barley flour metabolite extracts were fractionated into four fractions based on polarity. To allow for analysis by GC/MS, metabolites were derivatized to increase volatility and metabolite separation: fatty acids esters were derivatized into fatty acid methyl esters; sugars were oximated into their straight chain form; and metabolites with hydroxyl groups were converted to their corresponding silyl ethers. The derivatized samples were injected into the GC/MS and the generated mass spectra were used for metabolite identification by comparing the generated spectra to the National Institute of Standards and Technology (NIST) Tandem Mass Spectra library. The method described here can also be used to examine the total metabolome for other plants, furthering our understanding of the biochemical responses of stressed plants.

DOI: https://doi.org/10.3791/67175
Metabolites. 2024 Nov 08. pii: 606. [Epub ahead of print]14(11):

Chromatography-Based Metabolomics as a Tool in Bioorganic Research of Honey.

Marina Kranjac, Piotr Marek Kuś, Saša Prđun, Renata Odžak, Carlo Ignazio Giovanni Tuberoso.

  This review presents the latest research on chromatography-based metabolomics for bioorganic research of honey, considering targeted, suspect, and untargeted metabolomics involving metabolite profiling and metabolite fingerprinting. These approaches give an insight into the metabolic diversity of different honey varieties and reveal different classes of organic compounds in the metabolic profiles, among which, key metabolites such as biomarkers and bioactive compounds can be highlighted. Chromatography-based metabolomics strategies have significantly impacted different aspects of bioorganic research, including primary areas such as botanical origins, honey origin traceability, entomological origins, and honey maturity. Through the use of different tools for complex data analysis, these strategies contribute to the detection, assessment, and/or correlation of different honey parameters and attributes. Bioorganic research is mainly focused on phytochemicals and their transformation, but the chemical changes that can occur during the different stages of honey formation remain a challenge. Furthermore, the latest user- and environmentally friendly sample preparation methods and technologies as well as future perspectives and the role of chromatography-based metabolomic strategies in honey characterization are discussed. The objective of this review is to summarize the latest metabolomics strategies contributing to bioorganic research onf honey, with emphasis on the (i) metabolite analysis by gas and liquid chromatography techniques; (ii) key metabolites in the obtained metabolic profiles; (iii) formation and accumulation of biogenic volatile and non-volatile markers; (iv) sample preparation procedures; (v) data analysis, including software and databases; and (vi) conclusions and future perspectives. For the present review, the literature search strategy was based on the PRISMA guidelines and focused on studies published between 2019 and 2024. This review outlines the importance of metabolomics strategies for potential innovations in characterizing honey and unlocking its full bioorganic potential.

Keywords:  bioorganic research; chromatography-based metabolomics; data elaboration; honey metabolites; origin traceability; sample preparation; suspect metabolomics; targeted metabolomics; untargeted metabolomics

DOI:  https://doi.org/10.3390/metabo14110606
bioRxiv. 2024 Nov 15. pii: 2024.11.13.623458. [Epub ahead of print]

Language model-guided anticipation and discovery of unknown metabolites.

Hantao Qiang, Fei Wang, Wenyun Lu, Xi Xing, Hahn Kim, Sandrine A M Merette, Lucas B Ayres, Eponine Oler, Jenna E AbuSalim, Asael Roichman, Michael Neinast, Ricardo A Cordova, Won Dong Lee, Ehud Herbst, Vishu Gupta, Samuel Neff, Mickel Hiebert-Giesbrecht, Adamo Young, Vasuk Gautam, Siyang Tian, Bo Wang, Hannes Röst, Russell Greiner, Li Chen, Chad W Johnston, Leonard J Foster, Aaron M Shapiro, David S Wishart, Joshua D Rabinowitz, Michael A Skinnider.

Despite decades of study, large parts of the mammalian metabolome remain unexplored. Mass spectrometry-based metabolomics routinely detects thousands of small molecule-associated peaks within human tissues and biofluids, but typically only a small fraction of these can be identified, and structure elucidation of novel metabolites remains a low-throughput endeavor. Biochemical large language models have transformed the interpretation of DNA, RNA, and protein sequences, but have not yet had a comparable impact on understanding small molecule metabolism. Here, we present an approach that leverages chemical language models to discover previously uncharacterized metabolites. We introduce DeepMet, a chemical language model that learns the latent biosynthetic logic embedded within the structures of known metabolites and exploits this understanding to anticipate the existence of as-of-yet undiscovered metabolites. Prospective chemical synthesis of metabolites predicted to exist by DeepMet directs their targeted discovery. Integrating DeepMet with tandem mass spectrometry (MS/MS) data enables automated metabolite discovery within complex tissues. We harness DeepMet to discover several dozen structurally diverse mammalian metabolites. Our work demonstrates the potential for language models to accelerate the mapping of the metabolome.

DOI: https://doi.org/10.1101/2024.11.13.623458
Molecules. 2024 Nov 20. pii: 5478. [Epub ahead of print]29(22):

Matrix Solid-Phase Dispersion Procedure for Determination of Antibiotics and Metabolites in Mussels: Application in Exposure Bioassays.

Carmen Mejías, Tainá G Fonseca, Noelia García-Criado, Julia Martín, Juan Luis Santos, Irene Aparicio, Esteban Alonso.

  The presence of antibiotics in seafood for human consumption may pose a risk for consumers. Furthermore, some marine organisms, such as mussels, can result in appropriate bioindicators of marine contamination. In this work, a multiresidue analytical methodology suitable for the determination of antibiotics and metabolites in mussels is proposed. The target compounds include three sulphonamides and trimethoprim (TMP) and six of their main metabolites. Sample treatment involves extraction and clean-up in a single step using matrix solid-phase dispersion with acetonitrile. Analytical determination was carried out by liquid chromatography-tandem mass spectrometry. Good linearity (R2 > 0.99), accuracy (from 80.8 to 118%), and limits of quantification (lower than 5 ng g-1 (dry matter, dm)) were obtained for all selected compounds. The method was applied to the determination of antibiotics in mussel samples from an exposure assay with contaminated seawater with TMP and sulfamethoxazole (SMX). Both antibiotics were detected in the analysed samples with concentrations up to 77.5 ng g-1 dm. TMP was bioconcentrated to a higher extent than SMX, attributable to its higher hydrophobicity. None of the metabolites were detected. These results demonstrate that Mytilus galloprovincialis is a suitable bioindicator to assess marine pollution.

Keywords:  LC-MS/MS; MSPD; antibiotics; metabolites; mussels; pharmaceuticals

DOI:  https://doi.org/10.3390/molecules29225478
J Sep Sci. 2024 Nov;47(22): e70031

LC-MS-Based Simultaneous Determination of Biomarkers in Dried Urine Spots for the Detection of Cofactor-Dependent Metabolic Disorders in Neonates.

Arya Raveendran, Ashutosh Gupta, Leslie E Lewis, Krishnananda Prabhu, Sudheer Moorkoth.

  Deficiency of cofactors for various enzymes can lead to inborn errors of metabolism. These conditions frequently occur as seizures, which lead to permanent brain damage. Newborn screening for biomarkers associated with these disorders can help in early detection and treatment. Our objective was to establish a liquid chromatography mass spectrometry technique for quantifying biomarkers in dried urine spots to detect specific vitamin-responsive inborn errors metabolism. Biomarkers were extracted from dried urine spots using a methanol:0.1% v/v formic acid solution (75:25) containing an internal standard mixture. Separation was achieved using a Luna PFP column (150 mm × 4.6 mm, 3 µm) under gradient elution conditions. The LC-MS technique was validated as per ICH M10 guidelines. Urine samples from healthy newborns in Udupi district, South India, were analyzed to establish reference values for these biomarkers. The method demonstrated excellent linearity (R2 > 0.99) with low limits of quantification: 0.1 µg/mL for leucine, isoleucine, valine, proline, hydroxyproline, methylmalonic acid, and 3-hydroxyisovaleric acid; 0.01 µg/mL for pipecolic acid and α-aminoadipic semialdehyde; and 0.03 µg/mL for piperideine-6-carboxylate. Interconvertibility between urine and dried urine spot assays was observed from the results of the regression and Bland-Altman analyses. Reference intervals for these biomarkers in the Udupi neonatal population were established using the validated dried urine spot method.

Keywords:  LC–MS; amino acids; cofactor‐dependent metabolic disorder; dried urine spot; newborn screening

DOI:  https://doi.org/10.1002/jssc.70031
Biomed Chromatogr. 2024 Nov 28. e6044

A Review on the Analysis of Chiral Molecules as Disease Biomarkers by LC/MS.

Cemil Aydoğan, Büşra Beltekin Çakan, Ashraf Ali.

  The chiral compounds may be biomarker candidates in human metabolism, which indicates the health status of humans. There are many applications in LC/MS that show that chiral small molecules are promising biomarkers for human diseases. Both clinical and commercial analyses of chiral metabolites are necessary due to the enantiomeric ratios of chiral molecules in biological samples may show both human health status and diseases. This review provides current and advanced LC/MS techniques for the separation and analysis of chiral molecules as disease biomarkers. In particular, sample preparation and chromatographic analysis of potential chiral biomarkers in biological samples are presented. The preparation and applications of several chiral columns used in enantiomeric separation of chiral metabolites/biomarkers by advanced LC/MS techniques are discussed. The improvement of these analyses will enable both the discovery of new chiral biomarkers and the prognosis of human diseases.

Keywords:  HPLC; biomarker; chiral metabolites; chiral separation; enantioselective analysis

DOI:  https://doi.org/10.1002/bmc.6044
Molecules. 2024 Nov 15. pii: 5395. [Epub ahead of print]29(22):

Comparative Metabolomic Analysis of the Nutrient Composition of Different Varieties of Sweet Potato.

Xiaolin Wan, Xiuzhi Wang, Qiang Xiao.

  Sweet potatoes are rich in amino acids, organic acids, and lipids, offering exceptional nutritional value. To accurately select varieties with higher nutritional value, we employed liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze the metabolic profiles of three types of sweet potatoes (white sweet potato flesh, BS; orange sweet potato flesh, CS; and purple sweet potato flesh, ZS). When comparing CS vs. BS, ZS vs. BS, and ZS vs. CS, we found differences in 527 types of amino acids and their derivatives, 556 kinds of organic acids, and 39 types of lipids. After excluding the derivatives, we found 6 amino acids essential for humans across the three sweet potatoes, with 1 amino acid, 11 organic acids, and 2 lipids being detected for the first time. CS had a higher content of essential amino acids, while ZS had a lower content. Succinic acid served as a characteristic metabolite for ZS, helping to distinguish it from the other two varieties. These findings provide a theoretical basis for assessing the nutritional value of sweet potatoes and setting breeding targets while facilitating the selection of optimal varieties for food processing, medicine, and plant breeding.

Keywords:  amino acids; lipids; organic acids; sweet potato; untargeted metabolomics

DOI:  https://doi.org/10.3390/molecules29225395
bioRxiv. 2024 Nov 15. pii: 2024.11.12.623208. [Epub ahead of print]

iModMix : Integrative Module Analysis for Multi-omics Data.

Isis Narváez-Bandera, Ashley Lui, Yonatan Ayalew Mekonnen, Vanessa Rubio, Noah Sulman, Christopher Wilson, Hayley D Ackerman, Oscar E Ospina, Guillermo Gonzalez-Calderon, Elsa Flores, Qian Li, Ann Chen, Brooke Fridley, Paul Stewart.

Summary: The integration of metabolomics with other omics ("multi-omics") offers complementary insights into disease biology. However, this integration remains challenging due to the fragmented landscape of current methodologies, which often require programming experience or bioinformatics expertise. Moreover, existing approaches are limited in their ability to accommodate unidentified metabolites, resulting in the exclusion of a significant portion of data from untargeted metabolomics experiments. Here, we introduce iModMix , a novel approach that uses a graphical lasso to construct network modules for integration and analysis of multi-omics data. iModMix uses a horizontal integration strategy, allowing metabolomics data to be analyzed alongside proteomics or transcriptomics to explore complex molecular associations within biological systems. Importantly, it can incorporate both annotated and unidentified metabolites, addressing a key limitation of existing methodologies. iModMix is available as a user-friendly R Shiny application that requires no programming experience ( https://imodmix.moffitt.org ), and it includes example data from several publicly available multi-omic studies for exploration. An R package is available for advanced users ( https://github.com/biodatalab/iModMix ).
Availability and implementation: Shiny application: https://imodmix.moffitt.org . The R package and source code: https://github.com/biodatalab/iModMix .

DOI: https://doi.org/10.1101/2024.11.12.623208
Metabolites. 2024 Nov 10. pii: 609. [Epub ahead of print]14(11):

Extraction Methods for Brain Biopsy NMR Metabolomics: Balancing Metabolite Stability and Protein Precipitation.

Wenzheng Xiong, Florian Zirpel, M Zameel Cader, Daniel C Anthony, Fay Probert.

  Background/Objectives: Metabolic profiling of tissue samples via liquid-state nuclear magnetic resonance (NMR) requires the extraction of polar metabolites in a suitable deuterated solvent. Such methods often prioritise metabolite recovery over protein removal due to the relatively low sensitivity of NMR metabolomics and the routine use of methods able to supress residual protein signals. However, residual protein may impact metabolite integrity and the metabolite stability after NMR sample preparation is often overlooked. This study aimed to investigate the effect of residual protein contamination in rodent brain extracts and identify a reproducible extraction method that optimises metabolite recovery while ensuring sample stability. Methods: The performance of acetonitrile/water (50-100% MeCN), methanol/water (50-100% MeOH), and methanol/water/chloroform (MeOH/H2O/CHCl3) were assessed for extraction efficiency, reproducibility, residual protein contamination, and metabolite stability up to eight hours post NMR sample preparation. Results: Aspartate and glutamate deuteration were observed in 50% MeCN, 50% MeOH, and 67% MeOH extractions along with the conversion of N-acetyl aspartate to aspartate and acetate in 50% MeCN and 50% MeOH extractions. Both observations correlated with residual protein contamination and, thus, are a result of inadequate protein precipitation, as confirmed by ultrafiltration. MeOH/H2O/CHCl3 extraction preserved the stability of these metabolites while maintaining good extraction efficiency and reproducibility. Conclusions: Thus, we recommend MeOH/H2O/CHCl3 extraction for untargeted brain NMR metabolic profiling due to its effective protein precipitation and reliable performance. Nonetheless, the performance of detecting metabolites prone to oxidation such as ascorbate and glutathione is not improved by this method.

Keywords:  NMR; brain; extraction; metabolites; metabolomics

DOI:  https://doi.org/10.3390/metabo14110609
J Chromatogr B Analyt Technol Biomed Life Sci. 2024 Nov 20. pii: S1570-0232(24)00394-5. [Epub ahead of print]1250 124385

Spatial-resolved metabolome imaging of petals for Forsythia viridissima and Jasminum nudiflorum using online extraction (OLE) coupled to LC-Qtof-MS.

Wenzheng Li, Wei Li, Hangyun He, Maodong Wang, Lijuan Wu, Yang Yang, Pengfei Tu, Wenjing Liu, Yuelin Song.

  MS imaging (MSI) is a powerful technique for investigating the spatial distribution of metabolites in complex biological samples. However, due to the absence of liquid chromatography (LC) separation in routine MSI analysis, matrix effect is obvious and isomers identification remains challenging. To overcome these shortcomings of classical MSI tools (e.g., DESI-MSI and MALDI-MSI) for isomer differentiation and insufficient datapoints for quantification, online extraction-liquid chromatogram-hybrid triple quadrupole-time-of-flight mass spectrometry (OLE-LC-Qtof-MS) platform has been developed for spatial metabolome. As a proof-of-concept, two species flowers namely Forsythia viridissima (FV) and Jasminum nudiflorum (JN) that bloom in early spring were collected, dried, and cut into small pieces (1.0 mm × 1.0 mm). All pieces successively underwent OLE-LC-Qtof-MS measurements. As a result, 46 and 41 metabolites were observed and identified from FV and JN petals, respectively. Particularly, each compound corresponded to a chromatographic peak and isomeric differentiation was achieved amongst a set of chlorogenic acid derivatives. The peak areas of high intensity metabolites were aligned and combined within either species. The datasets were individually converted into heatmaps for all compounds, 87 ones in total, and each grid of any heatmap was assigned to the original location in the petal. Then, the spatial-resolved distribution style of each compound crossing the petal was reflected by the re-organized heatmap bearing the petal shape. As expected, regio-specific occurrence and accumulation were observed for several compounds, particularly among the chlorogenic acid isomers. Above all, OLE-LC-Qtof-MS is an alternative tool for spatial-resolved metabolome attributing to the advantages of isomeric separation and reliable quantification.

Keywords:  Forsythia viridissima; Isomeric differentiation; Jasminum nudiflorum; Online extraction-LC–Qtof-MS; Spatial-resolved metabolome distribution

DOI:  https://doi.org/10.1016/j.jchromb.2024.124385
Redox Biol. 2024 Nov 15. pii: S2213-2317(24)00403-8. [Epub ahead of print]78 103425

Dehydroascorbic acid quantification in human plasma: Simultaneous direct measurement of the ascorbic acid/dehydroascorbic acid couple by UPLC/MS-MS.

P-C Violet, N Munyan, H F Luecke, Y Wang, J Lloyd, K Patra, K Blakeslee, I C Ebenuwa, M Levine.

  Ascorbic acid (AA, vitamin C) and dehydroascorbic acid (DHA) constitute a biological couple. No technique can accurately, independently, and simultaneously quantify both members of the couple in animal and human samples, thereby constraining advances in physiology and pathophysiology. Here we describe a new UPLC/MS/MS method to measure both compounds directly and independently in human plasma. Lower limits of quantification were 16 nM, with linear coefficients >0.99 over a 100-fold concentration range. The method was stable and reproducible with <10 % injection-to-injection variation. Use of isotopic labeled internal standards for both compounds ensured precision and accuracy. Plasma preparation required only 2 steps. In plasma samples from 14 anonymized subjects who met criteria for blood donation, mean concentrations were 6±2 μmol/L (mean ± SD) and 56 ± 14 μmol/L for DHA and AA respectively, with (DHA)/(AA + DHA) ratio of 9.8 %. This method represents a pioneering approach to measuring the AA/DHA couple in human plasma.

Keywords:  Ascorbic acid; Dehydroascorbic acid; Human plasma; Mass spectrometry; Unispray; Vitamin C

DOI:  https://doi.org/10.1016/j.redox.2024.103425
Sci Rep. 2024 11 26. 14(1): 29321

Metabolomics analysis reveals resembling metabolites between humanized γδ TCR mice and human plasma.

Husheem Michael, Gene W Weng, Mikaela M Vallas, Douglas Lovos, Ellen Chen, Paul Sheiffele, Wei Weng.

  Gamma delta (γδ) T cells, which reside in mucosal and epithelial tissues, are integral to immune responses and are involved in various cancers, autoimmune, and infectious diseases. To study human γδ T cells to a translational level, we developed γδ humanized TCR-T1 (HuTCR-T1) mice using our TruHumanization platform. We compared the metabolomic profiles from plasma samples of wild-type (WT), γδ HuTCR-T1 mice, and humans using UHPLC-MS/MS. Untargeted metabolomics and lipidomics were used to screen all detectable metabolites. Principal component analysis revealed that the metabolomic profiles of γδ HuTCR-T1 mice closely resemble those of humans, with a clear segregation of metabolites between γδ HuTCR-T1 and WT mice. Most humanized γδ metabolites were classified as lipids, followed by organic compounds and amino acids. Pathway analysis identified significant alterations in the metabolism of tryptophan, tyrosine, sphingolipids, and glycerophospholipids, shifting these pathways towards a more human-like profile. Immunophenotyping showed that γδ HuTCR-T1 mice maintained normal proportions of both lymphoid and myeloid immune cell populations, closely resembling WT mice, with only a few exceptions. These findings demonstrate that the γδ HuTCR-T1 mouse model exhibits a metabolomic profile that is remarkably similar to that of humans, highlighting its potential as a relevant model for investigating the role of metabolites in disease development and progression. This model also offers an opportunity to discover therapeutic human TCRs.

Keywords:  Bacterial artificial chromosome genomic DNA platform; Humanized mice; Lipidomics; Metabolomics; Plasma; γδ

DOI:  https://doi.org/10.1038/s41598-024-81003-y