bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2021‒03‒14
nine papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

  1. J Am Soc Mass Spectrom. 2021 Mar 08.
      mineXpert is a mass spectrometric data visualization and exploration software supporting only MS1 data that is aimed at proteomics scientists who do rarely require manual MS/MS data visualization and exploration (Rusconi, F. J. Proteome Res. 2019, 18, 2254-2259). In order to adapt it to new use cases in our facility and to widen its user base, mineXpert was entirely rewritten with the main aim of implementing MSn data support. Other feature additions were new data visualization and exploration methods, with an overhaul of the data plotting code to allow more flexible uses of mass data integration results. Further, the whole mass spectral data set can now be explored in a table view where the user may filter the data using a number of criteria that can be logically combined to pinpoint the smallest feature of interest. Ion mobility mass spectrometry is supported with specific data exploration and plotting. With mineXpert2, we provide a software program that will be of use to all mass spectrometrists, without restrictions on the field of endeavor, from pure chemistry to proteomics and metabolomics. As staff members of a mass spectrometry facility, we want to provide all users with a mass spectrometry data visualization and exploration software solution that frees them from the need to use closed-source vendor software. After conversion of the mass data to mzML, mineXpert2 requires no proprietary software whatsoever. The reference implementation is version 7.0.0 or greater. The software, a detailed user manual, and video tutorials are available at
    Keywords:  C++; GPL; LC-MS; MS/MS; MSn; chemistry; ion mobility; isotopic cluster; mass spectrometry; metabolomics; mzML; mzXML; proteomics; software; visualization
  2. Emerg Top Life Sci. 2021 Mar 11. pii: ETLS20200271. [Epub ahead of print]
      Untargeted metabolomics enables the identification of key changes to standard pathways, but also aids in revealing other important and possibly novel metabolites or pathways for further analysis. Much progress has been made in this field over the past decade and yet plant metabolomics seems to still be an emerging approach because of the high complexity of plant metabolites and the number one challenge of untargeted metabolomics, metabolite identification. This final and critical stage remains the focus of current research. The intention of this review is to give a brief current state of LC-MS based untargeted metabolomics approaches for plant specific samples and to review the emerging solutions in mass spectrometer hardware and computational tools that can help predict a compound's molecular structure to improve the identification rate.
    Keywords:  computational biology; mass spectrometry; metabolite identification; metabolomics
  3. J Am Soc Mass Spectrom. 2021 Mar 11.
      In the past decade, hydrophilic interaction liquid chromatography (HILIC) has emerged as an efficient alternative to reversed-phase chromatography (RPC) for the analysis of phospholipid (PL) mixtures based on mass spectrometric detection. Since the separation of PL by HILIC is chiefly based on their headgroup, the mass spectrum of each class can be obtained by spectral averaging under the corresponding HILIC band. Using experimental m/z values resulting from high mass resolution/accuracy instruments, the sum compositions of PL in a specific class can be thus inferred but partial overlapping may occur between signals related to the M + 0 isotopologue of one species and the M + 2/M + 4 isotopologues of species having one/two more C═C bonds in their chemical structures. Here, an automated workflow, named LIPIC (lipid isotopic pattern interference correction), is proposed to account for such interferences. Starting from the experimentally verified assumption that peaks in isotope patterns are Gaussian, LIPIC predicts, as a function of m/z ratio, signal intensities due to M + 2 and M + 4 isotopologues of species with one or two more C = C bonds than the target one and calculates the corrected intensity for the M + 0 isotopologue of the latter. Thanks to an iterative procedure, the suggested algorithm compensates also for slight shifts occurring between experimental and theoretical m/z ratios related to isotopologue peaks. Examples of applications to simulated and experimental mass spectra of two PL classes, i.e., phosphatidylcholines (PC) and cardiolipins (CL), emphasize the increased extent of correction at the increase of molecular masses of involved species.
    Keywords:  electrospray ionization mass spectrometry; hydrophilic interaction liquid chromatography; isotopologue interference; phospholipids
  4. Anal Chem. 2021 Mar 10.
      Dissolved metabolites serve as nutrition, energy, and chemical signals for microbial systems. However, the full scope and magnitude of these processes in marine systems are unknown, largely due to insufficient methods, including poor extraction of small, polar compounds using common solid-phase extraction resins. Here, we utilized pre-extraction derivatization and ultrahigh performance liquid chromatography electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) to detect and quantify targeted dissolved metabolites in seawater and saline culture media. Metabolites were derivatized with benzoyl chloride by their primary and secondary amine and alcohol functionalities and quantified using stable isotope-labeled internal standards (SIL-ISs) produced from 13C6-labeled benzoyl chloride. We optimized derivatization, extraction, and sample preparation for field and culture samples and evaluated matrix-derived biases. We have optimized this quantitative method for 73 common metabolites, of which 50 cannot be quantified without derivatization due to low extraction efficiencies. Of the 73 metabolites, 66 were identified in either culture media or seawater and 45 of those were quantified. This derivatization method is sensitive (detection limits = pM to nM), rapid (∼5 min per sample), and high throughput.
  5. J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Feb 16. pii: S1570-0232(21)00068-4. [Epub ahead of print]1168 122588
      Ascorbic acid (AA) and uric acid (UA) are known as two of the major antioxidants in biological fluids. We report a novel liquid chromatography-mass spectrometry with time-of-flight (LC-MS-TOF) method for the simultaneous quantification of ascorbic and uric acids using MPA, antioxidant solution and acetonitrile as a protein precipitating agent. Both compounds were separated from interferences using a reverse phase C18 column with water and acetonitrile gradient elution (both with formic acid) and identified and quantified by MS in the negative ESI mode. Isotope labeled internal standards were also added to ensure the accuracy of the measures. The method was validated for exhaled breath condensate (EBC), nasal lavage (NL) and plasma samples by assessing selectivity, linearity, accuracy and precision, recovery and matrix effect and stability. Sample volumes below 250 µL were used and linear ranges were determined between 1 - 25 and 1 - 40 µg/mL for ascorbic and uric acid, respectively, for plasma samples, and between 0.05 - 5 (AA) and 0.05 - 7.5 (UA) µg/mL for EBC and NL samples. The new method was successfully applied to real samples from subjects that provided each of the studied matrices. Results showed higher amounts determined in plasma samples, with similar profiles for AA and UA in EBC and NL but at much lower concentrations.
    Keywords:  Ascorbic acid; Biological matrices; Exhaled breath condensate (EBC); LC-MS-TOF; Nasal lavage; Plasma; Quantification; Uric acid; Validation
  6. J Agric Food Chem. 2021 Mar 08.
      Echium oil has great nutritional value as a result of its high content of α-linolenic acid (ALA, 18:3ω-3) and stearidonic acid (SDA, 18:4ω-3). However, the comprehensive lipid profiling and exact structural characterization of bioactive polyunsaturated lipids in echium oil have not yet been obtained. In this study, we developed a novel pseudotargeted lipidomics strategy for comprehensive profiling and lipid structural elucidation of polyunsaturated lipid-rich echium oil. Our approach integrated untargeted lipidomics analysis with a targeted lipidomics strategy based on Paternò-Büchi (PB)-tandem mass spectrometry (MS/MS) using 2-acetylpyridine (2-AP) as the reaction reagent, allowing for high-coverage lipid profiling and simultaneous determination of C═C locations in triacylglycerols (TGs), diacylglycerols (DGs), free fatty acids (FFAs), and sterol esters (SEs) in echium oil. A total of 209 lipid species were profiled, among which 162 unsaturated lipids were identified with C═C location assignment and 42 groups of ω-3 and ω-6 C═C location isomers were discovered. In addition, relative isomer ratios of certain groups of lipid C═C location isomers were revealed. This pseudotargeted lipidomics strategy described in this study is expected to provide new insight into structural characterization of distinctive bioactive lipids in food.
    Keywords:  C═C locations; Paternò−Büchi reaction; comprehensive lipidomics analysis; echium oil; pseudotargeted lipidomics; stearidonic acid; α-linolenic
  7. J Proteome Res. 2021 Mar 12.
      Complex biological samples, in particular, in proteomics and metabolomics research, are often analyzed using mass spectrometry paired with liquid chromatography or gas chromatography. The chromatography stage adds a third dimension (retention time) to the usual 2D mass spectrometry output (mass/charge, detected ion counts). Experimental results are often discovered by complex computational analysis, but it is not always possible to know if the data has been correctly interpreted. To perform quality-control checks, it can often be helpful to verify the results by manually examining the raw data, and it is typically easier to understand the data in a graphical, rather than numerical, form. 3D graphics hardware is present in most modern computers but is rarely utilized by bioinformatics software, even when the data to be viewed are naturally 3D. lcmsWorld is new software that uses graphics hardware to quickly and smoothly examine and compare LC-MS data. A preprocessing step allows the software to subsequently access any area of the data instantly at multiple levels of detail. The data can then be freely navigated while the software automatically selects, loads, and displays the most appropriate detail. lcmsWorld is open source. Releases, source code, and example data files are available via
    Keywords:  3D; LC-MS; lcmsWorld; mass spectrometry; metabolomics; proteomics; software; visualization
  8. J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Feb 21. pii: S1570-0232(21)00071-4. [Epub ahead of print]1168 122591
      A simple, rapid, and sensitive LC-MS/MS method for determining concentrations of the anticancer alkaloid vincristine in micro volumes of mouse plasma was developed and validated in positive ion mode. Separation of vincristine and the internal standard [2H3]-vincristine was achieved on an Accucore aQ column with a gradient mobile phase delivered at a flow rate of 0.4 mL/min and a run time of 2.2 min. Calibration curves were linear (r2 > 0.99, n = 8) up to 250 ng/mL, with a lower limit of quantitation of 2.5 ng/mL. The matrix effect and extraction recovery for vincristine were ranging 108-110% and 88.4-107%, respectively. The intra-day and inter-day precision of quality controls tested at 3 different concentrations were always less than 15%, and accuracy ranged from 91.7 to 107%. The method was successfully applied to evaluate the pharmacokinetic profile of vincristine in wild-type and CYP3A-deficient mice in support of a project to provide mechanistic insight into drug-drug interactions and to identify sources of inter-individual pharmacokinetic variability associated with vincristine-induced peripheral neuropathy.
    Keywords:  Mouse plasma; Pharmacokinetics; UHPLC-MS/MS; Vincristine
  9. Sci Rep. 2021 Mar 11. 11(1): 5657
      As a powerful phenotyping technology, metabolomics provides new opportunities in biomarker discovery through metabolome-wide association studies (MWAS) and the identification of metabolites having a regulatory effect in various biological processes. While mass spectrometry-based (MS) metabolomics assays are endowed with high throughput and sensitivity, MWAS are doomed to long-term data acquisition generating an overtime-analytical signal drift that can hinder the uncovering of real biologically relevant changes. We developed "dbnorm", a package in the R environment, which allows for an easy comparison of the model performance of advanced statistical tools commonly used in metabolomics to remove batch effects from large metabolomics datasets. "dbnorm" integrates advanced statistical tools to inspect the dataset structure not only at the macroscopic (sample batches) scale, but also at the microscopic (metabolic features) level. To compare the model performance on data correction, "dbnorm" assigns a score that help users identify the best fitting model for each dataset. In this study, we applied "dbnorm" to two large-scale metabolomics datasets as a proof of concept. We demonstrate that "dbnorm" allows for the accurate selection of the most appropriate statistical tool to efficiently remove the overtime signal drift and to focus on the relevant biological components of complex datasets.