bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2023–09–24
thirteen papers selected by
Sofia Costa, Matterworks
  1. A feasible protocol to profile bile acids in dried blood spots from rats using a UHPLC-MS/MS method combining a surrogate matrix.
  2. Validation of an LC-MS/MS assay for rapid and simultaneous quantification of 21 kinase inhibitors in human plasma and serum for therapeutic drug monitoring.
  3. Identification of metabolites from complex mixtures by 3D correlation of 1H NMR, MS and LC data using the SCORE-metabolite-ID approach.
  4. MIST-CF: Chemical Formula Inference from Tandem Mass Spectra.
  5. A rapid and sensitive method for determination of methylene-diphosphonate in rat bone using liquid chromatography-mass spectrometry.
  6. Flash entropy search to query all mass spectral libraries in real time.
  7. Fluoride derivatization-enabled sensitive and simultaneous detection of biomarkers for nitrogen mustard in human plasma and urine via gas chromatography tandem mass spectrometry.
  8. MSFC: a new feature construction method for accurate diagnosis of mass spectrometry data.
  9. Is the automated Elecsys tacrolimus assay on the Roche cobas e 602 analyzer an acceptable replacement for a liquid chromatography-tandem mass spectrometry-based assay?
  10. Comparing MS imaging of lipids by WALDI and MALDI: two technologies for evaluating a common ground truth in MS imaging.
  11. Exact p-value calculation for XCorr scoring of high-resolution MS/MS data.
  12. Liquid chromatographic retention time prediction models to secure and improve the feature annotation process in high-resolution mass spectrometry.
  13. Two-dimensional isomer differentiation using liquid chromatography-tandem mass spectrometry with in-source, droplet-based derivatization.
  1. Analyst. 2023 Sep 18.
    A feasible protocol to profile bile acids in dried blood spots from rats using a UHPLC-MS/MS method combining a surrogate matrix.
    Ziying Ma, Ning Sheng, Jinlan Zhang.
      Dried blood spot (DBS) sampling is a promising method for microliter blood sample collection with the advantages of convenient transportation, storage and clinical operations. However, it is challenging to develop an analytical protocol to determine endogenous metabolites, such as bile acids (BAs) in DBSs, due to the low-blood-volume character of DBSs and the complex features of filter paper. Herein, we developed a method of fast ultra-high performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) to profile and quantify BAs in DBSs. The pretreatment methods were optimized and a two-step solvent addition method, where a small amount of water was firstly added to moisten the DBS and then methanol was added, showed high extraction efficiency for multiple BAs in DBSs. The UHPLC-MS/MS conditions were optimized and 35BAs in different types could be profiled with good resolution and quantified with acceptable precision and accuracy. Preparation of a DBS surrogate matrix without endogenous BAs has been well developed using rat erythrocytes in BSA solution and showed good performance on both the signal suppression/enhancement percentage and parallelism assessment evaluation of three different stable-isotope-labeled (SIL) BAs. The established protocol was successfully applied to profile BAs in DBSs of intrahepatic cholestasis model and healthy control rats with good repeatability. To our knowledge, it is the first time that 35 BAs in DBSs could be well profiled and an appropriate DBS surrogate matrix has been developed. This protocol presents future-oriented applications of DBSs for relevant preclinical studies to profile BAs and probe biomarkers.
    DOI:  https://doi.org/10.1039/d3an00900a
  2. J Chromatogr B Analyt Technol Biomed Life Sci. 2023 Sep 09. pii: S1570-0232(23)00282-9. [Epub ahead of print]1229 123872
    Validation of an LC-MS/MS assay for rapid and simultaneous quantification of 21 kinase inhibitors in human plasma and serum for therapeutic drug monitoring.
    Zaid N Al Shirity, Niels Westra, Kai van Hateren, Thijs H Oude Munnink, Jos G W Kosterink, Paola Mian, Marjolijn N Lub-de Hooge, Daan J Touw, Bahez Gareb.
      Kinase inhibitors have revolutionized cancer treatment in the past 25 years and currently form the cornerstone of many treatments. Due to the increasing evidence for therapeutic drug monitoring (TDM) of kinase inhibitors, the need is growing for new assays to rapidly evaluate kinase inhibitor plasma concentrations. In this study, we developed an LC-MS/MS assay for the rapid and simultaneous quantification of 21 kinase inhibitors. First, a literature search was conducted to ensure that the linear ranges of the analytes were in line with the reported therapeutic windows and/or TDM reference values. Subsequently, the assay was validated according to FDA and EMA guidelines for linearity, selectivity, carry-over, accuracy, precision, dilution integrity, matrix effect, recovery, and stability. The assay was fast, with a short run-time of 2 min per sample. Sample pre-treatment consisted of protein precipitation with methanol enriched with stable isotope-labeled internal standards (SIL-IS), and the mixture was vortexed and centrifuged before sample injection. Separation was achieved using a C18 column (3 μm,50 × 2.1 mm) with a gradient of two mobile phases (ammonium formate buffer pH 3.5 and acetonitrile). Analyte detection was conducted in positive ionization mode using selected reaction monitoring. The assay was accurate and precise in plasma as well as in serum. Extraction recovery ranged between 95.0% and 106.0%, and the matrix effect was 95.7%-105.2%. The stability of the analytes varied at room temperature and in refrigerated conditions. However, all drugs were found to be stable for 7 days in the autosampler. The clinical applicability of the analytical method (486 analyzed samples between 1 July 2022-1 July 2023) as well as external quality control testing results were evaluated. Taken together, the results demonstrate that the analytical method was validated and applicable for routine analyses in clinical practice.
    Keywords:  Bioanalysis; Kinase Inhibitors; LC-MS/MS; Therapeutic Drug Monitoring; Tyrosine Kinase Inhibitors; Validation
    DOI:  https://doi.org/10.1016/j.jchromb.2023.123872
  3. Sci Rep. 2023 Sep 22. 13(1): 15834
    Identification of metabolites from complex mixtures by 3D correlation of 1H NMR, MS and LC data using the SCORE-metabolite-ID approach.
    Stephanie Watermann, Marie-Christin Bode, Thomas Hackl.
      Not only in metabolomics studies, but also in natural product chemistry, reliable identification of metabolites usually requires laborious steps of isolation and purification and remains a bottleneck in many studies. Direct metabolite identification from a complex mixture without individual isolation is therefore a preferred approach, but due to the large number of metabolites present in natural products, this approach is often hampered by signal overlap in the respective 1H NMR spectra. This paper presents a method for the three-dimensional mathematical correlation of NMR with MS data over the third dimension of the time course of a chromatographic fractionation. The MATLAB application SCORE-metabolite-ID (Semi-automatic COrrelation analysis for REliable metabolite IDentification) provides semi-automatic detection of correlated NMR and MS data, allowing NMR signals to be related to associated mass-to-charge ratios from ESI mass spectra. This approach enables fast and reliable dereplication of known metabolites and facilitates the dynamic analysis for the identification of unknown compounds in any complex mixture. The strategy was validated using an artificial mixture and further tested on a polar extract of a pine nut sample. Straightforward identification of 40 metabolites could be shown, including the identification of β-D-glucopyranosyl-1-N-indole-3-acetyl-N-L-aspartic acid (1) and Nα-(2-hydroxy-2-carboxymethylsuccinyl)-L-arginine (2), the latter being identified in a food sample for the first time.
    DOI:  https://doi.org/10.1038/s41598-023-43056-3
  4. J Chem Inf Model. 2023 Sep 19.
    MIST-CF: Chemical Formula Inference from Tandem Mass Spectra.
    Samuel Goldman, Jiayi Xin, Joules Provenzano, Connor W Coley.
      Chemical formula annotation for tandem mass spectrometry (MS/MS) data is the first step toward structurally elucidating unknown metabolites. While great strides have been made toward solving this problem, the current state-of-the-art method depends on time-intensive, proprietary, and expert-parametrized fragmentation tree construction and scoring. In this work, we extend our previous spectrum Transformer methodology into an energy-based modeling framework, MIST-CF: Metabolite Inference with Spectrum Transformers for Chemical Formula prediction, for learning to rank chemical formula and adduct assignments given an unannotated MS/MS spectrum. Importantly, MIST-CF learns in a data-dependent fashion using a Formula Transformer neural network architecture and circumvents the need for fragmentation tree construction. We train and evaluate our model on a large open-access database, showing an absolute improvement of 10% top 1 accuracy over other neural network architectures. We further validate our approach on the CASMI2022 challenge data set, achieving nearly equivalent performance to the winning entry within the positive mode category without any manual curation or postprocessing of our results. These results demonstrate an exciting strategy to more powerfully leverage MS2 fragment peaks for predicting MS1 precursor chemical formulas with data-driven learning.
    DOI:  https://doi.org/10.1021/acs.jcim.3c01082
  5. J Pharm Biomed Anal. 2023 Sep 16. pii: S0731-7085(23)00496-X. [Epub ahead of print]236 115727
    A rapid and sensitive method for determination of methylene-diphosphonate in rat bone using liquid chromatography-mass spectrometry.
    Linqi Zhang, Yonglong Zeng, Yan Zeng, Dan Hu, Hengmao Liu, Rui Peng, Xiaofang Liang, Jianyu Liu.
      A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for the determination of methylene-diphosphonate (MDP) in rat bone. This method employed derivatization of MDP and allowed rapid and sensitive quantification of MDP in rat shin bone. The analyte was extracted from the bone tissues with phosphoric acid and derivatized to MDP tetramethyl phosphonate using trimethylsilyl diazomethane (TMS-DAM). MDP tetramethyl phosphonate was then quantified by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), with high selectivity, accuracy, and precision. The total run time was 6.5 min. The lower limit of quantification was 2.00 ng/mL. The intra- and inter-assay precision (in RSD) calculated from quality control samples was less than 15%, and the accuracy was between 98.1% and 100.2%. The analytical process for the determination of MDP in rat bone is fully described, which is a pivotal step for further biomedical research on MDP.
    Keywords:  Derivatization; LC-MS/MS; Methylene-diphosphonate; Pharmacokinetics; Tetramethyl Phosphonate
    DOI:  https://doi.org/10.1016/j.jpba.2023.115727
  6. Nat Methods. 2023 Sep 21.
    Flash entropy search to query all mass spectral libraries in real time.
    Yuanyue Li, Oliver Fiehn.
      Public repositories of metabolomics mass spectra encompass more than 1 billion entries. With open search, dot product or entropy similarity, comparisons of a single tandem mass spectrometry spectrum take more than 8 h. Flash entropy search speeds up calculations more than 10,000 times to query 1 billion spectra in less than 2 s, without loss in accuracy. It benefits from using multiple threads and GPU calculations. This algorithm can fully exploit large spectral libraries with little memory overhead for any mass spectrometry laboratory.
    DOI:  https://doi.org/10.1038/s41592-023-02012-9
  7. RSC Adv. 2023 Sep 08. 13(39): 27535-27548
    Fluoride derivatization-enabled sensitive and simultaneous detection of biomarkers for nitrogen mustard in human plasma and urine via gas chromatography tandem mass spectrometry.
    Fang-Chao Yang, Yang Yang, Long Yan, Feng-Yun Wang, Lei Wu, Ming-Zhu Xia, Xiao-Sen Li.
      Methyl-diethanolamine (CAS: 105-59-9), ethyl-diethanolamine (CAS: 139-87-7), and triethanolamine (CAS: 102-71-6) were identified as the degradation products and bio-markers of nitrogen mustard exposure. Sensitive and convenient detection methods for amino alcohol are of great importance to identify nitrogen mustard exposure in forensic analysis. Herein, analytical methods including gas chromatography-tandem mass spectrometry combined with heptafluorobutyryl derivatization and solid phase extraction were established for retrospective detection of the biomarkers in human plasma and urine samples. The efficiency of the method was improved by optimizing the conditions for sample preparation and the GC-MS/MS method. The optimization included the derivatization temperature, reaction time, reagent dosage and solid phase extraction cartridges, eluent and pH of the loading sample. The results indicated that the SCX cartridge resulted in better enrichment and purification effects, and the best recovery could be obtained with pH = 3-4 for the loading samples and an eluent of 2 mL 10% NH4OH/MeOH. The GC-MS/MS parameters were also optimized for better specificity and sensitivity. The established method was fully validated for each analyte both in plasma and urine matrixes. The linear range of analytes in plasma was 1.0-1000 ng mL-1 with a correlation parameter (R2) of ≥0.994, intra-day/inter-day accuracy of 93.7-117%, and relative standard deviation (RSD) of ≤6.5%. Meanwhile the results in urine were 1.0-1000 ng mL-1 with R2 of ≥0.996, intra-day/inter-day accuracy of 94.3-122%, and RSD of ≤6.6%. The detection limit of the analytes was 1.0 ng mL-1. The method was applied for the detection and identification of trace amino alcohols present in urine samples dispatched by the Organization for the Prohibition of Chemical Weapons (OPCW) and the results were confirmed to be correct.
    DOI:  https://doi.org/10.1039/d3ra04697d
  8. Sci Rep. 2023 Sep 21. 13(1): 15694
    MSFC: a new feature construction method for accurate diagnosis of mass spectrometry data.
    Xin Feng, Zheyuan Dong, Yingrui Li, Qian Cheng, Yongxian Xin, Qiaolin Lu, Ruihao Xin.
      Mass spectrometry technology can realize dynamic detection of many complex matrix samples in a simple, rapid, compassionate, precise, and high-throughput manner and has become an indispensable tool in accurate diagnosis. The mass spectrometry data analysis is mainly to analyze all metabolites in the organism quantitatively and to find the relative relationship between metabolites and physiological and pathological changes. A feature construction of mass spectrometry data (MSFS) method is proposed to construct the features of the original mass spectrometry data, so as to reduce the noise in the mass spectrometry data, reduce the redundancy of the original data and improve the information content of the data. Chi-square test is used to select the optimal non-redundant feature subset from high-dimensional features. And the optimal feature subset is visually analyzed and corresponds to the original mass spectrum interval. Training in 10 kinds of supervised learning models, and evaluating the classification effect of the models through various evaluation indexes. Taking two public mass spectrometry datasets as examples, the feasibility of the method proposed in this paper is verified. In the coronary heart disease dataset, during the identification process of mixed batch samples, the classification accuracy on the test set reached 1.000; During the recognition process, the classification accuracy on the test set advanced to 0.979. On the colorectal liver metastases data set, the classification accuracy on the test set reached 1.000. This paper attempts to use a new raw mass spectrometry data preprocessing method to realize the alignment operation of the raw mass spectrometry data, which significantly improves the classification accuracy and provides another new idea for mass spectrometry data analysis. Compared with MetaboAnalyst software and existing experimental results, the method proposed in this paper has obtained better classification results.
    DOI:  https://doi.org/10.1038/s41598-023-42395-5
  9. Am J Clin Pathol. 2023 Sep 19. pii: aqad114. [Epub ahead of print]
    Is the automated Elecsys tacrolimus assay on the Roche cobas e 602 analyzer an acceptable replacement for a liquid chromatography-tandem mass spectrometry-based assay?
    Anastasia Gant Kanegusuku, Kiang-Teck J Yeo.
       OBJECTIVES: This study evaluated the suitability and accuracy of the automated Roche Elecsys tacrolimus electrochemiluminescence immunoassay (ECLIA) by comparing it with a current laboratory-developed test by liquid chromatography-tandem mass spectrometry (LC-MS/MS).
    METHODS: The tacrolimus ECLIA was evaluated for precision, linearity, interference, and postextraction stability. Accuracy was compared with LC-MS/MS.
    RESULTS: The tacrolimus ECLIA assay is precise, exhibits a measuring range of 0.75 to 30 ng/mL, and is tolerant of significant interferences (plasma indices: hemolysis <2306, icterus <55, lipemia <1427, and biotin <1200 ng/mL). Comparison with LC-MS/MS revealed a 26% proportional bias in patient samples evaluated for tacrolimus concentration (y = 1.26x + 0.08; r2 = 0.97; Sy/x = 0.94; n = 43) and an absolute mean (SD) bias of 2.2 (1.7) ng/mL. Postextraction studies confirmed that samples were stable for up to 30 minutes under routine laboratory conditions.
    CONCLUSIONS: The 2 major challenges for implementation of the tacrolimus ECLIA assay are the postextraction sample stability and the significant proportional bias observed compared with the LC-MS/MS reference method. The 30-minute window for analysis of extracted samples is a practical challenge to the routine workflow of the core laboratory. In addition, disagreement between the immunoassay and LC-MS/MS methods can lead to discordant clinical interpretations and ultimately affect patient care.
    Keywords:  LC-MS/MS; automation; immunoassay; immunosuppressant; tacrolimus; transplant monitoring
    DOI:  https://doi.org/10.1093/ajcp/aqad114
  10. Analyst. 2023 Sep 21.
    Comparing MS imaging of lipids by WALDI and MALDI: two technologies for evaluating a common ground truth in MS imaging.
    Léa Ledoux, Yanis Zirem, Florence Renaud, Ludovic Duponchel, Michel Salzet, Nina Ogrinc, Isabelle Fournier.
      In this study, we conducted a direct comparison of water-assisted laser desorption ionization (WALDI) and matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging, with MALDI serving as the benchmark for label-free molecular tissue analysis in biomedical research. Specifically, we investigated the lipidomic profiles of several biological samples and calculated the similarity of detected peaks and Pearson's correlation of spectral profile intensities between the two techniques. We show that, overall, MALDI MS and WALDI MS present very close lipidomic analyses and that the highest similarity is obtained for the norharmane MALDI matrix. Indeed, for norharmane in negative ion mode, the lipidomic spectra revealed 100% similarity of detected peaks and over 0.90 intensity correlation between both technologies for five samples. The MALDI-MSI positive ion lipid spectra displayed more than 83% similarity of detected peaks compared to those of WALDI-MSI. However, we observed a lower percentage (77%) of detected peaks when comparing WALDI-MSI with MALDI-MSI due to the rich WALDI-MSI lipid spectra. Despite this difference, the global lipidomic spectra showed high consistency between the two technologies, indicating that they are governed by similar processes. Thanks to this similarity, we can increase datasets by including data from both modalities to either co-train classification models or obtain cross-interrogation.
    DOI:  https://doi.org/10.1039/d3an01096a
  11. Proteomics. 2023 Sep 19. e2300145
    Exact p-value calculation for XCorr scoring of high-resolution MS/MS data.
    Kishankumar Bhimani, Arina Peresadina, Dmitrii Vozniuk, Attila Kertész-Farkas.
      Exact p-value (XPV)-based methods for dot product-like score functions-such as the XCorr score implemented in Tide, SEQUEST, Comet or shared peak count-based scoring in MSGF+ and ASPV-provide a fairly good calibration for peptide-spectrum-match (PSM) scoring in database searching-based MS/MS spectrum data identification. Unfortunately, standard XPV methods, in practice, cannot handle high-resolution fragmentation data produced by state-of-the-art mass spectrometers because having smaller bins increases the number of fragment matches that are assigned to incorrect bins and scored improperly. In this article, we present an extension of the XPV method, called the high-resolution exact p-value (HR-XPV) method, which can be used to calibrate PSM scores of high-resolution MS/MS spectra obtained with dot product-like scoring such as the XCorr. The HR-XPV carries remainder masses throughout the fragmentation, allowing them to greatly increase the number of fragments that are properly assigned to the correct bin and, thus, taking advantage of high-resolution data. Using four mass spectrometry data sets, our experimental results demonstrate that HR-XPV produces well-calibrated scores, which in turn results in more trusted spectrum annotations at any false discovery rate level.
    Keywords:  PSM scoring; exact p-value; high resolution; score calibration; tandem mass spectrometry
    DOI:  https://doi.org/10.1002/pmic.202300145
  12. Talanta. 2023 Sep 17. pii: S0039-9140(23)00965-7. [Epub ahead of print]267 125214
    Liquid chromatographic retention time prediction models to secure and improve the feature annotation process in high-resolution mass spectrometry.
    Julien Parinet, Yassine Makni, Thierno Diallo, Thierry Guérin.
      The development of quantitative structure-retention relationship (QSRR) models has, until recently, required an adequate selection of molecular descriptors necessarily obtained based on a known chemical structure. However, these complex descriptors are not always available nor calculable when the high-resolution mass spectrometry (HRMS) annotation process is underway. Depending on the level of annotation, many structures or even various molecular formulas could be candidates. To secure and improve the annotation process and to save time, a QSRR model (using only 0D molecular descriptors) to predict retention times in reverse-phase liquid chromatography (RPLC) based on the molecular formula was developed, and a general QSRR annotation-based methodology was also proposed.
    Keywords:  Annotation; LC-HRMS; Methodology; Pesticides; QSRR
    DOI:  https://doi.org/10.1016/j.talanta.2023.125214
  13. Analyst. 2023 Sep 22.
    Two-dimensional isomer differentiation using liquid chromatography-tandem mass spectrometry with in-source, droplet-based derivatization.
    Derik R Heiss, Enoch Amoah, Abraham K Badu-Tawiah.
      Saccharides are increasingly used as biomarkers and for therapeutic purposes. Their characterization is challenging due to their low ionization efficiencies and inherent structural heterogeneity. Here, we illustrate how the coupling of online droplet-based reaction, in a form of contained electrospray (ES) ion source, with liquid chromatography (LC) tandem mass spectrometry (MS/MS) allows the comprehensive characterization of sucrose isomers. We used the reaction between phenylboronic acid and cis-diols for on-the-fly derivatization of saccharides eluting from the LC column followed by in situ MS/MS analysis, which afforded diagnostic fragment ions that enabled differentiation of species indistinguishable by chromatography or mass spectrometry alone. For example, chromatograms differing only by 2% in retention times were flagged to be different based on incompatible MS/MS fragmentation patterns. This orthogonal LC-contained-ES-MS/MS method was applied to confirm the presence of turanose, palatinose, maltulose, and maltose, which are structural isomers of sucrose, in three different honey samples. The reported workflow does not require modification to existing mass spectrometers, and the contained-ES platform itself acts both as the ion source and the reactor, all promising widespread application.
    DOI:  https://doi.org/10.1039/d3an01276j
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