bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2023‒09‒10
eight papers selected by
Sofia Costa, Matterworks

  1. Electrophoresis. 2023 Sep 05.
      Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.
    Keywords:  data processing; experimental design; mass spectrometry; single-cell heterogeneity; single-cell metabolomics
  2. J Chromatogr B Analyt Technol Biomed Life Sci. 2023 Sep 04. pii: S1570-0232(23)00280-5. [Epub ahead of print]1229 123870
      BACKGROUND: Kynurenine and respective metabolites exhibit bioactivity as well as tryptophan, an essential amino acid, and the neurotransmitter serotonin. Dysregulations in the kynurenine pathway are involved in neurodegenerative/neuropsychiatric disorders and diabetes mellitus type 2 but also in cancer. Therefore, measurements of kynurenine-related metabolites will improve the general understanding for kynurenine pathway relevance in disease pathogenesis.METHODS: Tryptophan, serotonin, picolinic acid, quinolinic acid, 3-OH-kynurenine, kynurenine, 3-OH-anthranilic acid, kynurenic acid, anthranilic acid as well as nicotinic acid and the redox cofactor NAD+ were analyzed in heterogeneous matrices by ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). After validation, the described method was applied for measurements of native metabolite concentrations in murine tissues and cellular systems including pathway-shift monitoring after treatment with the tryptophan-2,3-dioxygenase-inhibitor 680C91. In addition, the method was evaluated for its ability for integration into multi-omics approaches using a single sample metabolite extraction procedure.
    RESULTS: A simple and sensitive UPLC-MS/MS method for simultaneous quantification of up to 10 kynurenine-related metabolites in four biological matrices was developed. Within a run time of 6.5 min, chromatographic separation of kynurenine-related metabolites, including the isomers nicotinic acid and picolinic acid, was achieved without derivatization. Validation parameters, including interday precision (<14.8%), mean accuracy (102.4% ± 12.9%) and linear detection ranges of more than three orders of magnitude, indicate method reliability. Depending the investigated sample matrix, the majority of metabolites were successfully detected and quantified in native murine and cell culture derived sample materials. Furthermore, the method allowed to monitor the impact of a tryptophan-2,3-dioxygenase-inhibitor on kynurenine pathway in a cellular system and is suitable for multi-assay analyses using aliquots from the same cell extract.
    CONCLUSION: The described UPLC-MS/MS method provides a simple tool for the simultaneous quantification of kynurenine pathway metabolites. Due to its suitability for many physiological matrices, the method provides wide application for disease-related experimental settings.
    Keywords:  Kynurenine; Kynurenine pathway; Serotonin; Tryptophan; UPLC-MS/MS
  3. Proteomics. 2023 Sep 05. e2300032
      Metabolomics, the systematic measurement of small molecules (<1000 Da) in a given biological sample, is a fast-growing field with many different applications. In contrast to transcriptomics and proteomics, sharing of data is not as widespread in metabolomics, though more scientists are sharing their data nowadays. However, to improve data analysis tools and develop new data analytical approaches and to improve metabolite annotation and identification, sharing of reference data is crucial. Here, different possibilities to share (metabolomics) data are reviewed and some recent approaches and applications regarding the (re-)use and (re-)analysis are highlighted.
    Keywords:  bioinformatics; data; databases; metabolomics; processing and analysis; technology
  4. Anal Chem. 2023 Sep 04.
      The development of ion mobility-mass spectrometry (IM-MS) has revolutionized the analysis of small molecules, such as metabolomics, lipidomics, and exposome studies. The curation of comprehensive reference collision cross-section (CCS) databases plays a pivotal role in the successful application of IM-MS for small-molecule analysis. In this study, we presented AllCCS2, an enhanced version of AllCCS, designed for the universal prediction of the ion mobility CCS values of small molecules. AllCCS2 incorporated newly available experimental CCS data, including 10,384 records and 7713 unified values, as training data. By leveraging a neural network trained on diverse molecular representations encompassing mass spectrometry features, molecular descriptors, and graph features extracted using a graph convolutional network, AllCCS2 achieved exceptional prediction accuracy. AllCCS2 achieved median relative error (MedRE) values of 0.31, 0.72, and 1.64% in the training, validation, and testing sets, respectively, surpassing existing CCS prediction tools in terms of accuracy and coverage. Furthermore, AllCCS2 exhibited excellent compatibility with different instrument platforms (DTIMS, TWIMS, and TIMS). The prediction uncertainties in AllCCS2 from the training data and the prediction model were comprehensively investigated by using representative structure similarity and model prediction variation. Notably, small molecules with high structural similarities to the training set and lower model prediction variation exhibited improved accuracy and lower relative errors. In summary, AllCCS2 serves as a valuable resource to support applications of IM-MS technologies. The AllCCS2 database and tools are freely accessible at
  5. J Sep Sci. 2023 Sep 08. e2300090
      It has been proved that purine metabolites are implicated in various biological syndromes and disorders. Therefore, the realization of panoramic detection of purine metabolites will be of great significance to the pathogenesis of purine metabolic disorders. In the present study, an ultra-high performance liquid chromatography with tandem mass spectrometry method was developed for the comprehensive quantification of purine metabolites in rat plasma. The 17 purine metabolites were separated and quantified in the short running time of 15 min. The proposed method was strictly validated by applying SeraSub solution as a matrix and proved to be linear (R2 ≥ 0.9944), accurate (the recoveries of all analytes ranged from 85.3% to 103.0%, with relative standard deviation values ≤ 9.3%), and precise (the intra- and inter-day precisions were less than 10.8% and 12.4%, respectively). The method was then successfully applied to the qualification of the endogenous purine metabolites in acute gouty arthritis rats, as well as colchicine and anthocyanin-intervened rats. Results showed that uric acid, xanthine, hypoxanthine, and xanthine were considered the key factors of acute gouty arthritis. The established method and measurement of purines in rat plasma might help the investigation of the action mechanisms between purine disorders and related diseases.
    Keywords:  Lycium ruthenicum Murr; acute gouty arthritis; comprehensive quantification; purine metabolites
  6. Foods. 2023 Aug 23. pii: 3177. [Epub ahead of print]12(17):
      With the current advancement in mass spectrometry (MS)-based lipidomics, the knowledge of lipidomes and their diverse roles has greatly increased, enabling a deeper understanding of the action of bioactive lipid molecules in plant- and animal-based foods. This review provides in-depth information on the practical use of MS techniques in lipidomics, including lipid extraction, adduct formation, MS analysis, data processing, statistical analysis, and bioinformatics. Moreover, this contribution demonstrates the effectiveness of MS-based lipidomics for identifying and quantifying diverse lipid species, especially triacylglycerols and phospholipids, in foods. Further, it summarizes the wide applications of MS-based lipidomics in food science, such as for assessing food processing methods, detecting food adulteration, and measuring lipid oxidation in foods. Thus, MS-based lipidomics may be a useful method for identifying the action of individual lipid species in foods.
    Keywords:  HPLC-MS/MS; food adulteration; food processing; informatics; lipid extraction
  7. Magn Reson Chem. 2023 Sep 04.
      One-dimensional (1D) proton-nuclear magnetic resonance (1 H-NMR) spectroscopy is an established technique for the deconvolution of complex biological sample types via the identification/quantification of small molecules. It is highly reproducible and could be easily automated for small to large-scale bioanalytical, epidemiological, and in general metabolomics studies. However, chemical shift variability is a serious issue that must still be solved in order to fully automate metabolite identification. Herein, we demonstrate a strategy to increase the confidence in assignments and effectively predict the chemical shifts of various NMR signals based upon the simplest form of statistical models (i.e., linear regression). To build these models, we were guided by chemical homology in serum/plasma metabolites classes (i.e., amino acids and carboxylic acids) and similarity between chemical groups such as methyl protons. Our models, built on 940 serum samples and validated in an independent cohort of 1,052 plasma-EDTA spectra, were able to successfully predict the 1 H NMR chemical shifts of 15 metabolites within ~1.5 linewidths (Δv1/2 ) error range on average. This pilot study demonstrates the potential of developing an algorithm for the accurate assignment of 1 H NMR chemical shifts based solely on chemically defined constraints.
    Keywords:  1H NMR; automation; biofluid; blood; metabolites identification; metabolomics
  8. ACS Omega. 2023 Aug 29. 8(34): 31256-31264
      In this study, we developed and validated a novel method that allows for the extraction and quantitation of nicotine from a variety of commercially available oral tobacco products including loose and pouched traditional moist smokeless tobacco products, and oral tobacco-derived nicotine (OTDN) lozenges, gums, and pouches. The method employed an extraction technique consisting of salting-out assisted liquid-liquid extraction using sodium hydroxide and acetonitrile in conjunction with ultra-high pressure liquid chromatography coupled to mass spectrometry. Accurate quantitation was obtained using nicotine methyl-d3 isotopically labeled internal standard. Chromatographic separation of nicotine and nicotine methyl-d3 internal standard was achieved using a Waters Acquity C18 column (50 mm × 2.1 mm i.d., 2.5 μm) with 10 mM ammonium acetate buffer (pH = 10) and acetonitrile as mobile phase A and B, respectively. Using a gradient elution and a flow rate of 0.4 mL/min for 5 min runtime, nicotine eluted at 1.74 min. The method was validated according to ICH guidelines for all the sample types with an accuracy for nicotine within 89-109%. Repeatability and intermediate precision were both estimated to be ≤7% relative standard deviation (% RSD). This method is applicable for a wide range of traditional moist smokeless and OTDN tobacco products.