bims-metlip 2024-08-18 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2024–08–18
twenty papers selected by
Sofia Costa, Matterworks

MRMQuant: Automated MRM Data Quantitation for Large-Scale Targeted Metabolomics Analysis.
Determination of warfarin in volumetric absorptive microsampling by liquid chromatography-tandem mass spectrometry.
An isotopically-labelled temporal mass spectrometry imaging data analysis workflow to reveal glucose spatial metabolism patterns in bovine lens tissue.
Matrix effects in ultra-high performance supercritical fluid chromatography-mass spectrometry analysis of vitamin E in plasma: The effect of sample preparation and data processing.
Using Variable Data-Independent Acquisition for Capillary Electrophoresis-Based Untargeted Metabolomics.
An 8-(Diazomethyl) Quinoline Derivatized Acyl-CoA in Silico Mass Spectral Library Reveals the Landscape of Acyl-CoA in Aging Mouse Organs.
Rapid UHPLC-MS/MS measurement of pregnanediol 3-glucuronide in spot urine samples for detecting ovulation.
Introducing 'identification probability' for automated and transferable assessment of metabolite identification confidence in metabolomics and related studies.
Direct Determination of Glyphosate and Its Metabolites in Foods of Animal Origin by Liquid Chromatography-Tandem Mass Spectrometry.
Development and validation of an ultra-performance liquid chromatography-tandem mass spectrometry method to quantify the small molecule inhibitors adagrasib, alectinib, brigatinib, capmatinib, crizotinib, lorlatinib, selpercatinib, and sotorasib in human plasma.
Protocol for the simultaneous quantification of oxidative purine lesions in DNA using LC-MS/MS analysis.
A Validated LC-MS/MS Assay for the Quantification of Cholate Isotopes in Human Serum.
Unraveling the complexity of glycosphingolipidome: the key role of mass spectrometry in the structural analysis of glycosphingolipids.
Critical review on in silico methods for structural annotation of chemicals detected with LC/HRMS non-targeted screening.
Validation of two LCHRMS methods for large-scale untargeted metabolomics of serum samples: Strategy to establish method fitness-for-purpose.
Development and validation of a liquid chromatography coupled to a diode array detector (LC-DAD) method for measuring mitotane (DDD) in plasma samples.
MALDI-2-Enabled Oversampling for the Mass Spectrometry Imaging of Metabolites at Single-Cell Resolution.
A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis.
Determining nine fasciolicides and three metabolite residues in milk and infant formula using solid-phase extraction and liquid chromatography-tandem mass spectrometry.
A high-resolution 13C NMR approach for profiling fatty acid unsaturation in lipid extracts and in live C. elegans.

Anal Chem. 2024 Aug 11.

MRMQuant: Automated MRM Data Quantitation for Large-Scale Targeted Metabolomics Analysis.

Ke-Shiuan Lynn, Hsiang-Yu Tang, Chi-Jen Lo, Cheng-Hung Yang, Yi-Ting Tseng, Mei-Ling Cheng.

Multiple reaction monitoring (MRM) is a powerful and popular technique used for metabolite quantification in targeted metabolomics. Accurate and consistent quantitation of metabolites from the MRM data is essential for subsequent analyses. Here, we developed an automated tool, MRMQuant, for targeted metabolomic quantitation using high-throughput liquid chromatography-tandem mass spectrometry MRM data to provide users with an easy-to-use tool for accurate MRM data quantitation with minimal human intervention. This tool has many user-friendly functions and features to inspect and correct the quantitation results as required. MRMQuant possesses the following features to ensure accurate quantitation: (1) dynamic signal smoothing, (2) automatic deconvolution of coeluted peaks, (3) absolute quantitation via standard curves and/or internal standards, (4) visualized inspection and correction, (5) corrections applicable to multiple samples, and (6) batch-effect correction.

DOI: https://doi.org/10.1021/acs.analchem.4c02462
Heliyon. 2024 Jul 30. 10(14): e34500

Determination of warfarin in volumetric absorptive microsampling by liquid chromatography-tandem mass spectrometry.

Yahdiana Harahap, Callista Andinie Mulyadi, Hary Sakti Muliawan, Habibah A Wahab.

   Objective: This study aims to develop and validate bioanalytical method for quantifying warfarin in VAMS samples using liquid chromatography tandem mass spectrometry (LC-MS/MS), directly implementing the method to patients receiving warfarin therapy.
Methods: The UPLC-MS/MS method was developed and optimized, with quercetin as the internal standard. Sample preparation was carried out using protein precipitation with methanol-acetonitrile (1:3 v/v).
Results: Chromatographic separation was achieved using Acquity® UPLC BEH C18 column with 0.1 % formic acid-acetonitrile-methanol (30:69:1 v/v) as mobile phase, in isocratic elution. Multiple Reaction Monitoring (MRM) detection was done using m/z values of 307.10 → 161.06 for warfarin and 301.03 → 150.98 for quercetin as internal standard, using Electrospray Ionization (ESI) negative ion source. The clinical application of the bioanalytical method was carried out on 25 patients receiving warfarin therapy at Universitas Indonesia Hospital and warfarin levels were well within the calibration range from 6.05 to 431.39 ng/mL.
Conclusion: A novel method has been developed to analyze warfarin in VAMS samples. This method has been fully validated according to guideline from FDA 2022 and is linear in the range of 5-500 ng/mL and the value of r ≥ 0.9977, and successfully applied for the analysis of warfarin in VAMS samples of clinical patients.

Keywords:  LC-MS/MS; Therapeutic drug monitoring; Volumetric absorptive microsampling; Warfarin

DOI:  https://doi.org/10.1016/j.heliyon.2024.e34500
Sci Rep. 2024 08 14. 14(1): 18843

An isotopically-labelled temporal mass spectrometry imaging data analysis workflow to reveal glucose spatial metabolism patterns in bovine lens tissue.

Dingchang Shi, Angus C Grey, George Guo.

  Application of stable isotopically labelled (SIL) molecules in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) over a series of time points allows the temporal and spatial dynamics of biochemical reactions to be tracked in a biological system. However, these large kinetic MSI datasets and the inherent variability of biological replicates presents significant challenges to the rapid analysis of the data. In addition, manual annotation of downstream SIL metabolites involves human input to carefully analyse the data based on prior knowledge and personal expertise. To overcome these challenges to the analysis of spatiotemporal MALDI-MSI data and improve the efficiency of SIL metabolite identification, a bioinformatics pipeline has been developed and demonstrated by analysing normal bovine lens glucose metabolism as a model system. The pipeline consists of spatial alignment to mitigate the impact of sample variability and ensure spatial comparability of the temporal data, dimensionality reduction to rapidly map regional metabolic distinctions within the tissue, and metabolite annotation coupled with pathway enrichment modules to summarise and display the metabolic pathways induced by the treatment. This pipeline will be valuable for the spatial metabolomics community to analyse kinetic MALDI-MSI datasets, enabling rapid characterisation of spatio-temporal metabolic patterns from tissues of interest.

Keywords:  Glucose; Kinetic MALDI imaging; Lens; MALDI imaging; Metabolomics; Stable isotope

DOI:  https://doi.org/10.1038/s41598-024-69507-z
Talanta. 2024 Aug 02. pii: S0039-9140(24)01037-3. [Epub ahead of print]280 126658

Matrix effects in ultra-high performance supercritical fluid chromatography-mass spectrometry analysis of vitamin E in plasma: The effect of sample preparation and data processing.

Veronika Pilařová, Kateřina Plachká, Frantisek Svec, Lucie Nováková.

  The approaches to matrix effects determination and reduction in ultra-high performance supercritical fluid chromatography with mass spectrometry detection have been evaluated in this study using different sample preparation methods and investigation of different calibration models. Five sample preparation methods, including protein precipitation, liquid-liquid extraction, supported liquid extraction, and solid phase extraction based on both "bind and elute" and "interferent removal" modes, were optimized with an emphasis on the matrix effects and recovery of 8 forms of vitamin E, including α-, β-, γ-, and δ-tocopherols and tocotrienols, from plasma. The matrix effect evaluation included the use and comparison of external and internal calibration using three models, i.e., least square with no transformation and no weighting (1/x0), with 1/x2 weighting, and with logarithmic transformation. The calibration model with logarithmic transformation provided the lowest %-errors and the best fits. Moreover, the type of the calibration model significantly affected not only the fit of the data but also the matrix effects when evaluating them based on the comparison of calibration curve slopes. Indeed, based on the used calibration model, the matrix effects calculated from calibration slopes ranged from +92% to - 72% for α-tocopherol and from -77% to +19% in the case of δ-tocotrienol. Thus, it was crucial to calculate the matrix effect by Matuszewski's post-extraction approach at six concentration levels. Indeed, a strong concentration dependence was observed for all optimized sample preparation methods, even if the stable isotopically labelled internal standards (SIL-IS) were used for compensation. The significant differences between individual concentration levels and compounds were observed, even when the tested calibration range covered only one order of magnitude. In methods with wider calibration ranges, the inappropriate use of calibration slope comparison instead of the post-extraction addition approach could result in false negative results of matrix effects. In the selected example of vitamin E, solid-phase extraction was the least affected by matrix effects when used in interferent removal mode, but supported liquid extraction resulted in the highest recoveries. We showed that the calibration model, the use of a SIL-IS, and the analyte concentration level played a crucial role in the matrix effects. Moreover, the matrix effects can significantly differ for compounds with similar physicochemical properties and close retention times. Thus, in all bioanalytical applications, where different analytes are typically determined in one analytical run, it is necessary to carefully select the data processing in addition to the method for the sample preparation, SIL-IS, and chromatography.

Keywords:  Calibration curve; Electrospray ionization; Matrix effects; Post-extraction addition; Sample preparation; Single quadrupole mass spectrometry; Ultra-high performance supercritical fluid chromatography

DOI:  https://doi.org/10.1016/j.talanta.2024.126658
J Am Soc Mass Spectrom. 2024 Aug 13.

Using Variable Data-Independent Acquisition for Capillary Electrophoresis-Based Untargeted Metabolomics.

Saki Kiuchi, Yasuhiro Otoguro, Tomoaki Nitta, Mi Hwa Chung, Taiki Nakaya, Yuki Matsuzawa, Katsuya Ohbuchi, Kazunori Sasaki, Hiroyuki Yamamoto, Hiroshi Tsugawa.

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 data set. Postcorrection, the data set 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. 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 significantly altered metabolites in the LPS-administration group, where glycinamide ribonucleotide, not present in any spectral libraries, was newly characterized. Additionally, we retrieved metabolites of false-negative hits during 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.

DOI: https://doi.org/10.1021/jasms.4c00132
Anal Chem. 2024 Aug 16.

An 8-(Diazomethyl) Quinoline Derivatized Acyl-CoA in Silico Mass Spectral Library Reveals the Landscape of Acyl-CoA in Aging Mouse Organs.

Jinhui Yu, Menghao Guo, Ye Liu, Sha Li, Jian Ni, Yu-Qi Feng, Jun Ding.

Acyl-Coenzyme As (acyl-CoAs) are essential intermediates to incorporate carboxylic acids into the bioactive metabolic network across all species, which play important roles in lipid remodeling, fatty acids, and xenobiotic carboxylic metabolism. However, due to the poor liquid chromatographic behavior, the relatively low mass spectrometry (MS) sensitivity, and lack of authentic standards for annotation, the in-depth untargeted profiling of acyl-CoAs is challenging. We developed a chemical derivatization strategy of acyl-CoAs by employing 8-(diazomethyl) quinoline (8-DMQ) as the labeling reagent, which increased the detection sensitivity by 625-fold with good peak shapes. By applying the MS/MS fragmentation rules learned from the MS/MS spectra of 8-DMQ-acyl-CoA authentic standards, an 8-DMQ-acyl-CoA in silico mass spectral library containing 33,344 high-resolution tandem mass spectra of 8,336 acyl-CoA species was created. The in silico library facilitated the high-throughput and automatic annotation of acyl-CoA using multiple metabolomic data processing tools, such as NIST MS Search and MSDIAL. The feasibility of the in silico library in a complex sample was demonstrated by profiling endogenous acyl-CoAs in multiple organs of an aging mouse. 53 acyl-CoA species were annotated, including 12 oxidized fatty acyl-CoAs and 3 novel nonfatty acyl-CoAs. False positive annotations were further screened by developing an eXtreme Gradient Boosting (XGBoost) based retention time prediction model. The organ distribution and the aging dynamics of acyl-CoAs in a mouse model were discussed for the first time, which helped to elucidate the organ-specific function of acyl-CoAs and the role of different acyl-CoA species during aging.

DOI: https://doi.org/10.1021/acs.analchem.4c02113
Biomed Chromatogr. 2024 Aug 16. e5982

Rapid UHPLC-MS/MS measurement of pregnanediol 3-glucuronide in spot urine samples for detecting ovulation.

Laura Leoni, Federica Rosmini, Francesca Ledda, Mirko Parasiliti-Caprino, Fabio Settanni, Antonello Nonnato, Ezio Ghigo, Paolo Moghetti, Giulio Mengozzi, Federico Ponzetto.

  Biochemical confirmation of ovulation typically involves measuring serum progesterone levels during the mid-luteal phase. Alternatively, this information could be obtained by monitoring urinary excretion of conjugated metabolites of ovarian steroids such as pregnanediol 3-glucuronide (PDG) using immunoassay techniques that have methodological limitations. The aim of the present study was to develop a mass spectrometry (MS)-based method for the rapid and accurate measurement of urinary PDG levels in spot urine samples. A "dilute and shoot" ultra-high-performance liquid cromatography tandem mass spectrometry (UHPLC-MS/MS) method was developed for measuring PDG urinary concentration with a 6-min analysis time. The method underwent validation in accordance with ISO 17025 documentation for quantitative methods, proving an efficient separation of PDG from other structurally similar glucuro-conjugated steroid metabolites and ensuring a sufficient sensitivity for detecting the target analyte at concentrations as low as 0.01 μg/mL. The validation protocol yielded satisfactory results in terms of accuracy, repeatability, intermediate precision, and combined uncertainty. Additionally, the stability of both the samples and calibration curves was also conducted. The application to real urine samples confirmed the method's capability to measure PDG levels throughout an entire menstrual cycle and detecting ovulation. The rapidity of the analytical platform would therefore enable high throughput analysis, which is advantageous for large cohort clinical studies.

Keywords:  LC–MS/MS; dilute and shoot; ovulation; pregnanediol glucuronide; urine

DOI:  https://doi.org/10.1002/bmc.5982
bioRxiv. 2024 Jul 31. pii: 2024.07.30.605945. [Epub ahead of print]

Introducing 'identification probability' for automated and transferable assessment of metabolite identification confidence in metabolomics and related studies.

Thomas O Metz, Christine H Chang, Vasuk Gautam, Afia Anjum, Siyang Tian, Fei Wang, Sean M Colby, Jamie R Nunez, Madison R Blumer, Arthur S Edison, Oliver Fiehn, Dean P Jones, Shuzhao Li, Edward T Morgan, Gary J Patti, Dylan H Ross, Madelyn R Shapiro, Antony J Williams, David S Wishart.

Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence - the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in context of the chemical space being considered, are easily automated, or are transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a reference library or chemical space that match to an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multi-property reference libraries constructed from the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.

DOI: https://doi.org/10.1101/2024.07.30.605945
Foods. 2024 Aug 02. pii: 2451. [Epub ahead of print]13(15):

Direct Determination of Glyphosate and Its Metabolites in Foods of Animal Origin by Liquid Chromatography-Tandem Mass Spectrometry.

Marija Denžić Lugomer, Nina Bilandžić, Damir Pavliček, Tiana Novosel.

  Glyphosate is the most used herbicide in agriculture. Its major metabolite is AMPA (aminomethylphosphonic acid), but N-acetyl-AMPA and N-acetylglyphosate are also metabolites of interest. For risk assessment, a general residue definition was proposed as the sum of glyphosate, AMPA, N-acetyl-glyphosate and N-acetyl-AMPA, expressed as glyphosate. A confirmatory method for glyphosate in fat, liver and kidneys, as well as a confirmatory method for AMPA and N-acetyl-glyphosate in all matrices, are still missing. In this paper, we present a method for the quantitative determination of glyphosate residues and its metabolites AMPA, N-acetyl-AMPA and N-acetyl-glyphosate by liquid chromatography-mass spectrometry (LC-MS/MS) in adipose tissue, liver, eggs, milk and honey without derivatization. Different chromatographic columns were tested, with the Hypercarb column providing the best results. The analytes were eluted with mobile phases of acidified water with 1.2% formic acid and 0.5% formic acid in acetonitrile. Sample purification procedures were also optimized by varying the solvent extraction mixtures (water, methanol and mixture ψ (methanol, water) = 1:1, each with the addition of 1% formic acid (v/v)), using different sorbents in solid phase extraction (SPE) (polymeric cationic (PCX) and anionic (PAX)) and using dispersive solid phase extraction (dSPE) (C18 and PSA) by modifying the extraction procedures. Finally, the analytes were extracted from the samples with 1% formic acid in water (v/v). Milk and adipose tissue were purified by the addition of dichloromethane, while liver and egg samples were purified by SPE with a mixed cation exchange sorbent and ultrafiltration with cut-off filters. The proposed analytical procedures were validated according to SANTE/11312/2021 guidelines: linearity, limits of quantification, precision and accuracy were determined for all matrices. The limits of quantification (LOQs) ranged from 0.025 to 0.2 mg kg-1. Precision, expressed as relative standard deviation, was <20%, while accuracy, expressed as analytical recovery, ranged from 70% to 120%. During method validation, the measurement uncertainty was estimated to be <50% for all analytes. Good validation parameters according to the SANTE document were achieved for all analytes. Therefore, the method can be considered reliable and sensitive enough for routine monitoring of polar pesticides. The application of the accredited method in routine analysis will provide data that are useful for the re-evaluation of risk assessment studies in foods of animal origin.

Keywords:  AMPA; LC-MS/MS; N-acetyl-AMPA; N-acetyl-glyphosate; food of animal origin; glyphosate

DOI:  https://doi.org/10.3390/foods13152451
Biomed Chromatogr. 2024 Aug 13. e5986

Development and validation of an ultra-performance liquid chromatography-tandem mass spectrometry method to quantify the small molecule inhibitors adagrasib, alectinib, brigatinib, capmatinib, crizotinib, lorlatinib, selpercatinib, and sotorasib in human plasma.

Esther M Hollander, Nachel M C Zimmerman, Berber Piet, Michel M van den Heuvel, David M Burger, Lindsey H M Te Brake, Rob Ter Heine.

  Small molecule inhibitors (SMIs) are increasingly being used in the treatment of non-small cell lung cancer. To support pharmacokinetic research and clinical treatment monitoring, our aim was to develop and validate an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) assay for quantification of eight SMIs: adagrasib, alectinib, brigatinib, capmatinib, crizotinib, lorlatinib, selpercatinib, and sotorasib. Development of the UPLC-MS/MS assay was done by trying different columns and eluents to optimize peak shape. The assay was validated based on guidelines of the European Medicines Agency. Chromatographic separation was performed with a gradient elution using ammonium formate in water and methanol. Detection was performed using a triple quadrupole tandem mass spectrometer with electrospray ionization. Validation was performed in a range of 10-2500 μg/L for lorlatinib, 25-6250 μg/L for alectinib and crizotinib, 25-10,000 μg/L for capmatinib and selpercatinib, 50-12,500 μg/L for brigatinib, and 100-25,000 μg/L for adagrasib and sotorasib. Imprecision was <8.88% and inaccuracy was <12.5% for all compounds. Seven out of eight compounds were stable for 96 h at room temperature. Sotorasib was stable for 8 h at room temperature. A sensitive and reliable method has been developed to quantify eight SMIs with a single assay, enhancing efficacy and safety of targeted therapies.

Keywords:  mass spectrometry; non‐small cell lung cancer; small molecule inhibitors; targeted therapy

DOI:  https://doi.org/10.1002/bmc.5986
STAR Protoc. 2024 Aug 14. pii: S2666-1667(24)00356-3. [Epub ahead of print]5(3): 103191

Protocol for the simultaneous quantification of oxidative purine lesions in DNA using LC-MS/MS analysis.

Chryssostomos Chatgilialoglu, Marios G Krokidis, Michael A Terzidis.

  Most DNA damages induced through oxidative metabolism are single lesions which can accumulate in tissues. Here, we present a protocol for the simultaneous quantification of oxidative purine lesions (cPu and 8-oxo-Pu) in DNA. We describe steps for enzymatic digestion of DNA and sample pre-purification, followed by quantification through liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. We optimized this protocol in commercially available calf thymus DNA and used genomic and mitochondrial DNA extracted from cell cultures and animal and human tissues.

Keywords:  Chemistry; Mass Spectrometry; Metabolomics

DOI:  https://doi.org/10.1016/j.xpro.2024.103191
J Appl Lab Med. 2024 Aug 16. pii: jfae094. [Epub ahead of print]

A Validated LC-MS/MS Assay for the Quantification of Cholate Isotopes in Human Serum.

Steve M Helmke, Michael P McRae, Uwe Christians, Touraj Shokati, Gregory T Everson.

BACKGROUND: Current methods for evaluating liver health rely on nonspecific blood tests, elastography surrogates for fibrosis, and invasive procedures, none of which directly measure liver function and physiology. Herein we present the analytical validation of a unique, highly sensitive LC-MS/MS assay and dual-sample oral (DuO) cholate challenge test to reliably quantify serial serum concentrations of cholate isotopes administered to patients with liver diseases. The clearance of administered cholate isotopes measured by the assay provides information about liver function and physiology.
METHODS: Analytical method validation of the cholate assay analytes (endogenous unlabeled cholic acid, 24-13C-cholic acid, and 2,2,4,4-D4-cholic acid) in terms of accuracy, precision, analytical sensitivity, analytical specificity, and range of reliable response was completed in human serum samples spiked with quality controls and calibrators in accordance with applicable guidelines. DuO test parameters were validated using samples from 48 subjects representing various liver disease etiologies.
RESULTS: Accuracy (mean biases) for all analytes ranged from 0.1% to 3.7%. Using a nested components-of-variance design (20 days, 2 runs per day, 2 replicates per sample), total imprecision for all analytes ranged from 2.3% to 8.4%. Lower and upper limits of quantitation were established and validated at 0.1 to 10.0 µM. Matrix effects and potential interferents did not affect assay performance. DuO test validation met all prespecified acceptance criteria.
CONCLUSIONS: The method validation studies described herein established the performance characteristics in terms of accuracy, precision, analytical sensitivity, analytical specificity, reportable ranges, and reference intervals of the LC-MS/MS cholate assay and DuO test.

DOI: https://doi.org/10.1093/jalm/jfae094
Anal Bioanal Chem. 2024 Aug 14.

Unraveling the complexity of glycosphingolipidome: the key role of mass spectrometry in the structural analysis of glycosphingolipids.

Karel Hořejší, Michal Holčapek.

  Glycosphingolipids (GSL) are a highly heterogeneous class of lipids representing the majority of the sphingolipid category. GSL are fundamental constituents of cellular membranes that have key roles in various biological processes, such as cellular signaling, recognition, and adhesion. Understanding the structural complexity of GSL is pivotal for unraveling their functional significance in a biological context, specifically their crucial role in the pathophysiology of various diseases. Mass spectrometry (MS) has emerged as a versatile and indispensable tool for the structural elucidation of GSL enabling a deeper understanding of their complex molecular structures and their key roles in cellular dynamics and patholophysiology. Here, we provide a thorough overview of MS techniques tailored for the analysis of GSL, emphasizing their utility in probing GSL intricate structures to advance our understanding of the functional relevance of GSL in health and disease. The application of tandem MS using diverse fragmentation techniques, including novel ion activation methodologies, in studying glycan sequences, linkage positions, and fatty acid composition is extensively discussed. Finally, we address current challenges, such as the detection of low-abundance species and the interpretation of complex spectra, and offer insights into potential solutions and future directions by improving MS instrumentation for enhanced sensitivity and resolution, developing novel ionization techniques, or integrating MS with other analytical approaches for comprehensive GSL characterization.

Keywords:  Derivatization; Fragmentation; Glycosphingolipids; Liquid chromatography; Mass spectrometry; Structural elucidation

DOI:  https://doi.org/10.1007/s00216-024-05475-7
Anal Bioanal Chem. 2024 Aug 14.

Critical review on in silico methods for structural annotation of chemicals detected with LC/HRMS non-targeted screening.

Henrik Hupatz, Ida Rahu, Wei-Chieh Wang, Pilleriin Peets, Emma H Palm, Anneli Kruve.

  Non-targeted screening with liquid chromatography coupled to high-resolution mass spectrometry (LC/HRMS) is increasingly leveraging in silico methods, including machine learning, to obtain candidate structures for structural annotation of LC/HRMS features and their further prioritization. Candidate structures are commonly retrieved based on the tandem mass spectral information either from spectral or structural databases; however, the vast majority of the detected LC/HRMS features remain unannotated, constituting what we refer to as a part of the unknown chemical space. Recently, the exploration of this chemical space has become accessible through generative models. Furthermore, the evaluation of the candidate structures benefits from the complementary empirical analytical information such as retention time, collision cross section values, and ionization type. In this critical review, we provide an overview of the current approaches for retrieving and prioritizing candidate structures. These approaches come with their own set of advantages and limitations, as we showcase in the example of structural annotation of ten known and ten unknown LC/HRMS features. We emphasize that these limitations stem from both experimental and computational considerations. Finally, we highlight three key considerations for the future development of in silico methods.

Keywords:  Generative modeling; Machine learning; Non-targeted analysis; Non-targeted screening; Suspect screening; Untargeted screening

DOI:  https://doi.org/10.1007/s00216-024-05471-x
J Chromatogr A. 2024 Aug 06. pii: S0021-9673(24)00604-6. [Epub ahead of print]1732 465230

Validation of two LCHRMS methods for large-scale untargeted metabolomics of serum samples: Strategy to establish method fitness-for-purpose.

Sietske Grijseels, Terje Vasskog, Pia J Heinsvig, Torbjørn N Myhre, Terkel Hansen, Marie Mardal.

  Untargeted metabolomics by LCHRMS is a powerful tool to enhance our knowledge of pathophysiological processes. Whereas validation of a bioanalytical method is customary in most analytical chemistry fields, it is rarely performed for untargeted metabolomics. This study aimed to establish and validate an analytical platform for a long-term, clinical metabolomics study. Sample preparation was performed with an automated liquid handler and four analytical methods were developed and evaluated. The validation study spanned three batches with twelve runs using individual serum samples and various quality control samples. Data was acquired with untargeted acquisition and only metabolites identified at level 1 were evaluated. Validation parameters were set to evaluate key performance metrics relevant for the intended application: reproducibility, repeatability, stability, and identification selectivity, emphasizing dataset intrinsic variance. Concordance of semi-quantitative results between methods was evaluated to identify potential bias. Spearman rank correlation coefficients (rs) were calculated from individual serum samples. Of the four methods tested, two were selected for validation. A total of 47 and 55 metabolites (RPLC-ESI+- and HILIC-ESI--HRMS, respectively) met specified validation criteria. Quality assurance involved system suitability testing, sample release, run release, and batch release. The median repeatability and within-run reproducibility as coefficient of variation% for metabolites that passed validation on RPLC-ESI+- and HILIC-ESI--HRMS were 4.5 and 4.6, and 1.5 and 3.8, respectively. Metabolites that passed validation on RPLC-ESI+-HRMS had a median D-ratio of 1.91, and 89 % showed good signal intensity after ten-fold dilution. The corresponding numbers for metabolites with the HILIC-ESI--HRMS method was 1.45 and 45 %, respectively. The rs median ({range}) for metabolites that passed validation on RPLC-ESI+- was 0.93 (N = 9 {0.69-0.98}) and on HILIC-ESI--HRMS was 0.93 (N = 22 {0.55-1.00}). The validated methods proved fit-for-purpose and the laboratory thus demonstrated its capability to produce reliable results for a large-scale, untargeted metabolomics study. This validation not only bolsters the reliability of the assays but also significantly enhances the impact and credibility of the hypotheses generated from the studies. Therefore, this validation study serves as a benchmark in the documentation of untargeted metabolomics, potentially guiding future endeavors in the field.

Keywords:  Fit-for-purpose; HILIC; LC-HRMS; Untargeted metabolomics; Validation; Validation reports

DOI:  https://doi.org/10.1016/j.chroma.2024.465230
Clinics (Sao Paulo). 2024 ;pii: S1807-5932(24)00147-9. [Epub ahead of print]79 100470

Development and validation of a liquid chromatography coupled to a diode array detector (LC-DAD) method for measuring mitotane (DDD) in plasma samples.

Anna Sylvia Ferrari Marques, Atecla Nunciata Lopes Alves, Berenice Bilharinho Mendonca, Helena Panteliou Lima-Valassi.

   INTRODUCTION: Mitotane (o,p'-DDD) is the drug of choice for Adrenocortical Carcinomas (ACC) and its measurement in plasma is essential to control drug administration.
OBJECTIVE: To develop and validate a simple, reliable and straightforward method for mitotane determination in plasma samples.
METHOD: Drug-free plasma samples were collected in potassium-ethylenediamine tetraacetate (K-EDTA) tubes and spiked with 1.0, 2.5, 10.0, 25.0 and 50.0 µg/mL of mitotane (DDD). The p,p'-DDD was used as an Internal Standard (IS) and was added at 25.0 µg/mL concentration to all samples, standards and controls. Samples were submitted to protein precipitation with acetonitrile and then centrifuged. 50 uL of the supernatant was injected into an HPLC system coupled to a Diode Array Detector (DAD). DDD and IS were detected at 230 nm in a 12 min isocratic mode with a solvent mixture of 60 % acetonitrile and 40 % formic acid in water with 0.1 % pump mixed, at 0.6 mL/min flow rate, in a reversed-phase (C18) chromatographic column kept at 28°C. The sensitivity, selectivity, precision, presence of carry-over, recovery and matrix-effect, linearity, and method accuracy were evaluated.
RESULTS: The present study's method resulted in a symmetrical peak shape and good baseline resolution for DDD (mitotane) and 4,4'-DDD (internal standard) with retention times of 6.0 min, 6.4 mim, respectively, with resolutions higher than 1.0. Endogenous plasma compounds did not interfere with the evaluated peaks when blank plasma and spiked plasma with standards were compared. Linearity was assessed over the range of 1.00-50.00 µg/mL for mitotane (R2 > 0.9987 and a 97.80 %‒105.50 % of extraction efficiency). Analytical sensitivity was 0.98 µg/mL. Functional sensitivity (LOQ) was 1.00 µg/L, intra-assay and inter-assay coefficient of variations were less than 9.98 %, and carry-over was not observed for this method. Recovery ranged from 98.00 % to 117.00 %, linearity ranged from 95.00 % to 119.00 %, and high accuracy of 89.40 % to 105.90 % with no matrix effects or interference was observed for mitotane measurements. Patients' sample results were compared with previous measurements by the GC-MS method with a high correlation (r = 0.88 and bias = -10.20 %).
CONCLUSION: DDD determination in plasma samples by the developed and validated method is simple, robust, efficient, and sensitive for therapeutic drug monitoring and dose management to achieve a therapeutic index of mitotane in patients with adrenocortical cancer.

Keywords:  Adrenocortical carcinoma; Analytical; Diode array; HPLC; Liquid chromatography; Method validation; Mitotane

DOI:  https://doi.org/10.1016/j.clinsp.2024.100470
J Am Soc Mass Spectrom. 2024 Aug 13.

MALDI-2-Enabled Oversampling for the Mass Spectrometry Imaging of Metabolites at Single-Cell Resolution.

Jayden C McKinnon, Rachelle Balez, Reuben S E Young, Mikayla L Brown, Jeremy S Lum, Liam Robinson, Mikhail E Belov, Lezanne Ooi, Sara Tortorella, Todd W Mitchell, Shane R Ellis.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide valuable insights into the metabolome of complex biological systems such as organ tissues and cells. However, obtaining metabolite data at single-cell spatial resolutions presents a few technological challenges. Generally, spatial resolution is defined by the increment the sample stage moves between laser ablation spots. Stage movements less than the diameter of the focused laser beam (i.e., oversampling) can improve spatial resolution; however, such oversampling conditions result in a reduction in sensitivity. To overcome this, we combine an oversampling approach with laser postionization (MALDI-2), which allows for both higher spatial resolution and improved analyte ionization efficiencies. This approach provides significant enhancements to sensitivity for various metabolite classes (e.g., amino acids, purines, carbohydrates etc.), with mass spectral intensities from 6 to 8 μm pixel sizes (from a laser spot size of ∼13 μm) being commensurate with or higher than those obtained by conventional MALDI at 20 μm pixel sizes for many different metabolites. This technique has been used to map the distribution of metabolites throughout mouse spinal cord tissue to observe how metabolite localizations change throughout specific anatomical regions, such as those distributed to the somatosensory area of the dorsal horn, white matter, gray matter, and ventral horn. Furthermore, this method is utilized for single-cell metabolomics of human iPSC-derived astrocytes at 10 μm pixel sizes whereby many different metabolites, including nucleotides, were detected from individual cells while providing insight into cellular localizations.

DOI: https://doi.org/10.1021/jasms.4c00241
J Mass Spectrom. 2024 Sep;59(9): e5078

A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis.

Dylan H Ross, Erin L Bredeweg, Josie G Eder, Daniel J Orton, Meagan C Burnet, Jennifer E Kyle, Ernesto S Nakayasu, Xueyun Zheng.

  Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to characterize lipids in detail to understand their roles in these complex systems. In particular, lipid double bond (DB) locations are an important component of lipid structure that can only be determined using a few specialized analytical techniques. Ozone-induced dissociation mass spectrometry (OzID-MS) is one such technique that uses ozone to break lipid DBs, producing pairs of characteristic fragments that allow the determination of DB positions. In this work, we apply OzID-MS and LipidOz software to analyze the complex lipids of Saccharomyces cerevisiae yeast strains transformed with different fatty acid desaturases from Histoplasma capsulatum to determine the specific unsaturated lipids produced. The automated data analysis in LipidOz made the determination of DB positions from this large dataset more practical, but manual verification for all targets was still time-consuming. The DL model reduces manual involvement in data analysis, but since it was trained using mammalian lipid extracts, the prediction accuracy on yeast-derived data was reduced. We addressed both shortcomings by retraining the DL model to act as a pre-filter to prioritize targets for automated analysis, providing confident manually verified results but requiring less computational time and manual effort. Our workflow resulted in the determination of detailed DB positions and enzymatic specificity.

Keywords:  deep learning; double bond position; lipidomics; mass spectrometry; ozone‐induced dissociation

DOI:  https://doi.org/10.1002/jms.5078
Food Res Int. 2024 Sep;pii: S0963-9969(24)00823-8. [Epub ahead of print]192 114753

Determining nine fasciolicides and three metabolite residues in milk and infant formula using solid-phase extraction and liquid chromatography-tandem mass spectrometry.

Jianbo Hou, Yingzhu Shi, Renyi Mao, Wen Xie, Peng Wang, Yan Qian, Zelong Zhu, An Chen, Chao Han, Yan Shen.

  A new sensitive method of liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis for nine fasciolicides (closantel, rafoxanide, oxyclozanide, niclosamide, nitroxinil, ioxynil, 4-nitro-3-(trifluoromethyl)phenol, salicylanilide, and triclabendazole) and three metabolite residues (ketotriclabnedazole, triclabendazole sulfone, and triclabendazole sulfoxide) in milk and infant formula was established. The samples were extracted and purified through solid-phase extraction and analyzed using LC-MS/MS. The proposed method demonstrated high accuracy (the average recoveries ranged from 70.5 % to 107.4 %) and high sensitivity (the limits of quantification ranged from 1.0 to 25.0 µg/kg). This method was successfully applied to determine nine fasciolicides and three metabolite residues in 45 milk and infant formula, providing technical support for the safety and quality evaluation of dairy products.

Keywords:  Dairy products; Fasciolicide; LC–MS/MS; Metabolite; Residue analysis

DOI:  https://doi.org/10.1016/j.foodres.2024.114753
J Lipid Res. 2024 Aug 08. pii: S0022-2275(24)00123-8. [Epub ahead of print] 100618

A high-resolution 13C NMR approach for profiling fatty acid unsaturation in lipid extracts and in live C. elegans.

Bruno Hernández Cravero, Gastón Prez, Verónica A Lombardo, Florencia V Guastaferri, Carla B Delprato, Silvia Altabe, Diego de Mendoza, Andres Binolfi.

  Unsaturated fatty acids (UFA) play a crucial role in central cellular processes in animals, including membrane function, development, and disease. Disruptions in UFA homeostasis can contribute to the onset of metabolic, cardiovascular, and neurodegenerative disorders. Consequently, there is a high demand for analytical techniques to study lipid compositions in live cells and multicellular organisms. Conventional analysis of UFA compositions in cells, tissues and organisms involves solvent extraction procedures coupled with analytical techniques such as gas chromatography,mass spectrometry (MS) and/or nuclear magnetic resonance (NMR) spectroscopy. As a non-destructive and non-targeted technique, NMR spectroscopy is uniquely capable of characterizing the chemical profiling of living cells and multicellular organisms. Here we use NMR spectroscopy to analyze C. elegans, enabling the determination of their lipid compositions and fatty acid unsaturation levels both in cell-free lipid extracts and in vivo. The NMR spectra of lipid extracts from wild-type and fat-3 mutant C. elegans strains revealed notable differences due to the absence of Δ-6 fatty acid desaturase activity, including the lack of arachidonic and eicosapentaenoic acyl chains. Uniform 13C-isotope labeling and high-resolution 2D solution-state NMR of live worms confirmed these findings, indicating that the signals originated from fast-tumbling lipid molecules within lipid droplets. Overall, this strategy permits the analysis of lipid storage in intact worms and has enough resolution and sensitivity to identify differences between wild type and mutant animals with impaired fatty acid desaturation. Our results establish methodological benchmarks for future investigations of fatty acid regulation in live C. elegans using NMR.

Keywords:  Arachidonic acid; C. elegans; Lipid droplets; Lipids; Lipids/Chemistry; Physical biochemistry; in-cell NMR; solution state NMR spectroscopy; unsaturated fatty acids

DOI:  https://doi.org/10.1016/j.jlr.2024.100618