bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2020‒08‒02
nine papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

  1. Trends Analyt Chem. 2019 Dec;pii: 115697. [Epub ahead of print]121
      The essence of shotgun lipidomics is to maintain consistency of the chemical environment of lipid samples during mass spectrometry acquisition. This strategy is suitable for large-scale quantitative analysis. This strategy also allows sufficient time to collect data to improve the signal-to-noise ratio. The initial approach of shotgun lipidomics was the electrospray ionization (ESI)-based direct infusion mass spectrometry strategy. With development of mass spectrometry for small molecules, shotgun lipidomics methods have been extended to matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) and ambient mass spectrometry, including MS imaging methods. Furthermore, the object of analysis has extended from organ and body fluid levels to tissue and cell levels with technological developments. In this article, we summarize the status and technical challenges of shotgun lipidomics at different resolution of measurements from the mass spectrometry perspective.
    Keywords:  High resolution mass spectrometry; Lipidomics; Mass spectrometry imaging; Shotgun lipidomics; Single-cell analysis
  2. Methods Mol Biol. 2020 ;2096 179-196
      Metabolic flux analysis represents an essential perspective to understand cellular physiology and offers quantitative information to guide pathway engineering. A valuable approach for experimental elucidation of metabolic flux is dynamic flux analysis, which estimates the relative or absolute flow rates through a series of metabolic intermediates in a given pathway. It is based on kinetic isotope labeling experiments, liquid chromatography-mass spectrometry (LC-MS), and computational analysis that relate kinetic isotope trajectories of metabolites to pathway activity. Herein, we illustrate the mathematic principles underlying the dynamic flux analysis and mainly focus on describing the experimental procedures for data generation. This protocol is exemplified using cyanobacterial metabolism as an example, for which reliable labeling data for central carbon metabolites can be acquired quantitatively. This protocol is applicable to other microbial systems as well and can be readily adapted to address different metabolic processes.
    Keywords:  Cell harvesting; Dynamic flux analysis; Experimental metabolomics; Isotope tracer; LC-MS; Metabolic flux; Quenching
  3. J Anal Methods Chem. 2020 ;2020 8838219
      A simple, rapid, and sensitive liquid chromatography (LC)/mass spectrometry (MS) method was established and validated for simultaneous quantitation of pyrazinamide, isoniazid, rifampicin, and ethambutol in human blood sample. Samples were pretreated by a single-step precipitation with acetonitrile. Chromatographic separation was achieved on XSelecT HSS T3 column by gradient elution with a total run time of 5.0 min. MS detection was performed by a triple quadrupole tandem mass spectrometer in the multiple reaction monitoring mode with a positive electrospray ionization source. Isotope-labeled internal standard, especially rifampicin-D8, was applied to adjust for the loss during sample treatment. The established LC-MS/MS method showed a wide analytical range (pyrazinamide: 1.02∼60.0 μg/mL, isoniazid: 0.152∼10.0 μg/mL, rifampicin: 0.500∼30.0 μg/mL, and ethambutol: 0.0998∼5.99 μg/mL) and a good linearity (r > 0.99 for the four analytes) with acceptable accuracy and precision (90.15%∼104.62% and 94.00%∼104.02% for intra- and interaccuracy, respectively; RSD%: <12.46% and <6.43% for intra- and interprecision, respectively). It also showed excellent recoveries (79.24%∼94.16% for all analytes) and absence of significant matrix effect. This method was successfully applied to the quantification of four first-line antituberculosis (anti-TB) drugs, suggesting its suitability for therapeutic drug monitoring in the clinical practices.
  4. Nat Commun. 2020 Jul 30. 11(1): 3793
      Reproducible research is the bedrock of experimental science. To enable the deployment of large-scale proteomics, we assess the reproducibility of mass spectrometry (MS) over time and across instruments and develop computational methods for improving quantitative accuracy. We perform 1560 data independent acquisition (DIA)-MS runs of eight samples containing known proportions of ovarian and prostate cancer tissue and yeast, or control HEK293T cells. Replicates are run on six mass spectrometers operating continuously with varying maintenance schedules over four months, interspersed with ~5000 other runs. We utilise negative controls and replicates to remove unwanted variation and enhance biological signal, outperforming existing methods. We also design a method for reducing missing values. Integrating these computational modules into a pipeline (ProNorM), we mitigate variation among instruments over time and accurately predict tissue proportions. We demonstrate how to improve the quantitative analysis of large-scale DIA-MS data, providing a pathway toward clinical proteomics.
  5. Cancer Rep (Hoboken). 2019 Dec;2(6): e1229
      BACKGROUND: Current methods to identify, classify, and predict tumor behavior mostly rely on histology, immunohistochemistry, and molecular determinants. However, better predictive markers are required for tumor diagnosis and evaluation. Due, in part, to recent technological advancements, metabolomics and lipid biomarkers have become a promising area in cancer research. Therefore, there is a necessity for novel and complementary techniques to identify and visualize these molecular markers within tumors and surrounding tissue.RECENT FINDINGS: Since its introduction, mass spectrometry imaging (MSI) has proven to be a powerful tool for mapping analytes in biological tissues. By adding the label-free specificity of mass spectrometry to the detailed spatial information of traditional histology, hundreds of lipids can be imaged simultaneously within a tumor. MSI provides highly detailed lipid maps for comparing intra-tumor, tumor margin, and healthy regions to identify biomarkers, patterns of disease, and potential therapeutic targets. In this manuscript, recent advancement in sample preparation and MSI technologies are discussed with special emphasis on cancer lipid research to identify tumor biomarkers.
    CONCLUSION: MSI offers a unique approach for biomolecular characterization of tumor tissues and provides valuable complementary information to histology for lipid biomarker discovery and tumor classification in clinical and research cancer applications.
    Keywords:  biomarkers; carcinogenesis; diagnosis; lipids; mass spectrometery imaging
  6. Anal Bioanal Chem. 2020 Jul 25.
      MALDI mass spectrometry imaging (MALDI-MSI) is a widely used technique to map the spatial distribution of molecules in sectioned tissue. The technique is based on the systematic generation and analysis of ions from small sample volumes, each representing a single pixel of the investigated sample surface. Subsequently, mass spectrometric images for any recorded ion species can be generated by displaying the signal intensity at the coordinate of origin for each of these pixels. Although easily equalized, these recorded signal intensities, however, are not necessarily a good measure for the underlying amount of analyte and care has to be taken in the interpretation of MALDI-MSI data. Physical and chemical properties that define the analyte molecules' adjacencies in the tissue largely influence the local extraction and ionization efficiencies, possibly leading to strong variations in signal intensity response. Here, we inspect the validity of signal intensity distributions recorded from murine cerebellum as a measure for the underlying molar distributions. Based on segmentation derived from MALDI-MSI measurements, laser microdissection (LMD) was used to cut out regions of interest with a homogenous signal intensity. The molar concentration of six exemplary selected membrane lipids from different lipid classes in these tissue regions was determined using quantitative nano-HPLC-ESI-MS. Comparison of molar concentrations and signal intensity revealed strong deviations between underlying concentration and the distribution suggested by MSI data. Determined signal intensity response factors strongly depend on tissue type and lipid species. Graphical abstract.
    Keywords:  Laser microdissection; Laser postionization; Lipids; MALDI; MALDI-2; Mass spectrometry imaging; Nano-HILIC-nano-ESI-MS; Quantification; Signal intensity response
  7. J Chromatogr B Analyt Technol Biomed Life Sci. 2020 Jul 14. pii: S1570-0232(19)31522-3. [Epub ahead of print]1152 122265
      Liquid-chromatography mass spectrometry (LC-MS) is a powerful bioanalytical tool that is gaining widespread use in operational forensic toxicology laboratories. However, changes in ionization efficiency caused by endogenous or exogenous species must be carefully considered. While different modes of ionization can be used, electrospray ionization (ESI) can be especially prone to this phenomenon due to capacity-limited ionization. This decreased ionization efficiency can influence the accuracy and sensitivity of analytical methods. While quantitative matrix effects are evaluated routinely during method development and validation, drug-mediated ion suppression is not always assessed quantitatively, or in sufficient depth. Although stable isotope labeled internal standards (SIL-IS) can mitigate this issue, they are not always commercially available, particularly for new or emerging substances. In this study, the hypnotic drug suvorexant was used as a model compound for the investigation of such interferences. The potential for significant bias in quantitative analysis was demonstrated using this previously validated assay. In this study, quantitative biases due to ionization suppression are discussed, and techniques to overcome this challenge are presented. Decreases in specimen and injection volume were shown to significantly reduce quantitative bias due to drug-mediated suppression. This straight-forward approach can improve the robustness of analytical methodology, which is particularly important when quantitative measurements are relied upon for medicolegal and other purposes.
    Keywords:  Forensic toxicology; Interferences; Ion suppression; LC-MS/MS; LC-Q/TOF-MS; Suvorexant
  8. J Lipid Res. 2020 Jul 22. pii: jlr.D120000726. [Epub ahead of print]
      Bile acids (BAs) have been established as ubiquitous regulatory molecules implicated in a large variety of healthy and pathological processes. However, the scope of BA heterogeneity is often underrepresented in current literature. This is due in part to inadequate detection methods, which fail to distinguish the individual constituents of the BA pool. Thus, the primary aim of this study was to develop a method that would allow the simultaneous analysis of specific C24 BA species, and to apply that method to biological systems of interest. Herein, we describe the generation and validation of an LC-MS/MS assay for quantification of numerous BAs in a variety of cell systems and relevant biofluids and tissue. These studies included the first baseline level assessment for planar BAs, including allocholic acid, in cell lines, biofluids, and tissue in a nonhuman primate (NHP) laboratory animal, Macaca mulatta, in healthy conditions. These results indicate that immortalized cell lines make poor models for the study of bile acid synthesis and metabolism, whereas human primary hepatocytes represent a promising alternative model system. We also characterized the BA pool of M. mulatta in detail. Our results support the use of NHP models for the study of BA metabolism and pathology in lieu of murine models. Moreover, the method developed here can be applied to the study of common and planar C24 BA species in other systems.
    Keywords:  Bile; Bile acids and salts; Bile acids and salts/Biosynthesis; Bile acids and salts/Metabolism; Mass spectrometry; hepatocytes; liver; planar bile acids; plasma; quantitation
  9. SLAS Discov. 2020 Jul 25. 2472555220941843
      During the past decade, mass spectrometry imaging (MSI) has become a robust and versatile methodology to support modern pharmaceutical research and development. The technologies provide data on the biodistribution, metabolism, and delivery of drugs in tissues, while also providing molecular maps of endogenous metabolites, lipids, and proteins. This allows researchers to make both pharmacokinetic and pharmacodynamic measurements at cellular resolution in tissue sections or clinical biopsies. Despite drug imaging within samples now playing a vital role within research and development (R&D) in leading pharmaceutical companies, however, the challenges in turning compounds into medicines continue to evolve as rapidly as the technologies used to discover them. The increasing cost of development of new and emerging therapeutic modalities, along with the associated risks of late-stage program attrition, means there is still an unmet need in our ability to address an increasing array of challenging bioanalytical questions within drug discovery. We require new capabilities and strategies of integrated imaging to provide context for fundamental disease-related biological questions that can also offer insights into specific project challenges. Integrated molecular imaging and advanced image analysis have the opportunity to provide a world-class capability that can be deployed on projects in which we cannot answer the question with our battery of established assays. Therefore, here we will provide an updated concise review of the use of MSI for drug discovery; we will also critically consider what is required to embed MSI into a wider evolving R&D landscape and allow long-lasting impact in the industry.
    Keywords:  DESI; MALDI; MSI; SIMS; imaging; mass spectrometry imaging