bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2021‒05‒16
eight papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

  1. Talanta. 2021 Aug 15. pii: S0039-9140(21)00288-5. [Epub ahead of print]231 122367
      The lipidomic research is currently devoting considerable effort to the harmonization that should enable the generation of comparable and accurate quantitative lipidomic data across different laboratories and regardless of the mass spectrometry-based platform used. In the present study, we systematically investigate the effects of the experimental setup on quantitative lipidomics data obtained by two lipid class separation approaches, hydrophilic interaction liquid chromatography (HILIC) and ultrahigh-performance supercritical fluid chromatography (UHPSFC), coupled to two different quadrupole - time of flight (QTOF) mass spectrometers from the same vendor. This approach is applied for measurements of 268 human plasma samples of healthy volunteers and renal cell carcinoma patients resulting in four data sets. We investigate and visualize differences among these data sets by multivariate data analysis methods, such as principal component analysis (PCA), orthogonal partial least square discriminant analysis (OPLS-DA), box plots, and logarithmic correlations of molar concentrations of individual lipid species. The results indicate that even measurements in the same laboratory for the same samples using different analytical platforms may yield slight variations in the molar concentrations determined. The normalization to a reference sample with defined lipid concentrations can further diminish these small differences, resulting in highly homogenous molar concentrations of individual lipid species. This strategy indicates a potential approach towards the reporting of comparable quantitative results independent from the quantitative approach and mass spectrometer used, which is important for a wider acceptance of lipidomics data in various biomarker inter-laboratory studies and ring trials.
    Keywords:  Hydrophilic interaction liquid chromatography; Lipidomics; Mass spectrometry; Normalization; Plasma; Quantitation; Supercritical fluid chromatography
  2. Talanta. 2021 Aug 15. pii: S0039-9140(21)00257-5. [Epub ahead of print]231 122336
      Investigation into monosaccharides is critical for studies of oligosaccharides structure and function in biological processes. However, monosaccharides quantification is still challenge due to their isomeric structure and high hydrophilic properties. Besides, it was difficult to obtain isotopic internal standards (IS) of each monosaccharide in complex matrixes. Herein, we developed a novel strategy for the qualification and quantification of monosaccharides in urine using two structure analogs 1-(4-methylphenyl)-3-methyl-5-pyrazolone (MPMP) and1-phenyl-3-methyl-5-pyrazolone (PMP) as non-isotopically paired labeling (NIPL) reagents by liquid chromatograph-tandem mass spectrometry (LC-MS/MS). The derivatized monosaccharides by NIPL method not only had sufficient retention time differences on reversed-phase column, but also exhibited predominant product ion pairs (m/z 189 & m/z 175) in the multiple reaction monitoring (MRM) mode. In this method, PMP labeled standards were adopted as one-to-one internal standards (ISs). 12 urinary monosaccharides were successfully determined and the linear ranges expanded five orders of magnitude with limit of quantification (LOQ) varied from 0.09 ng mL-1 to 0.36 ng mL-1 as well as the accuracy higher than 98.15% and the relative standard derivation (RSD) lower than 7.92%. With assistance of multivariate analysis, the targeted monosaccharide biomarkers were firstly obtained for the diagnosis of bladder cancer. By the inexpensive NIPL reagents-MPMP/PMP, the developed strategy possessed the specific advantages of low cost, simple operation, high sensitivity and high accuracy for the qualification and quantitation of monosaccharides. As expected, this method will provide an alternative application potential for targeted metabolomics analysis.
    Keywords:  Chemical derivatization; Qualification and quantification; Tandem mass spectrometry; Targeted monosaccharide biomarkers
  3. Anal Methods. 2021 May 14.
      Gas chromatography-mass spectrometry (GC-MS) provides a complementary analytical platform for capturing volatiles, non-polar and (derivatized) polar metabolites and exposures from a diverse array of matrixes. High resolution (HR) GC-MS as a data generation platform can capture data on analytes that are usually not detectable/quantifiable in liquid chromatography mass-spectrometry-based solutions. With the rise of high-resolution accurate mass (HRAM) GC-MS systems such as GC-Orbitrap-MS in the last decade after the time-of-flight (ToF) renaissance, numerous applications have been found in the fields of metabolomics and exposomics. In a short span of time, a multitude of studies have used GC-Orbitrap-MS to generate exciting new high throughput data spanning from diverse basic to applied research areas. The GC-Orbitrap-MS has found application in both targeted and untargeted efforts for capturing metabolomes and exposomes across diverse studies. In this review, I capture and summarize all the reported studies to date, and provide a snapshot of the milieu of commercial and open-source software solutions, spectral libraries, and informatics solutions available to a GC-Orbitrap-MS system instrument user or a data analyst dealing with these datasets. Lastly, but importantly, I provide an account on data sharing and meta-data capturing solutions that are available to make HRAM GC-MS based metabolomics and exposomics studies findable, accessible, interoperable, and reproducible (FAIR). These FAIR practices would allow data generators and users of GC-HRMS instruments to help the community of GC-MS researchers to collaborate and co-develop exciting tools and algorithms in the future.
  4. J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Mar 24. pii: S1570-0232(21)00152-5. [Epub ahead of print]1173 122672
      The demand for analysis of carotenoids (CAR) and fat-soluble vitamins (FSV) is continuously expanding, but currently used sample preparation methods either require complicated extraction procedure or large sample volume, let alone the reliability of the results. This study aimed to develop a fast, high-efficient, and high-throughput method based on supported liquid extraction (SLE) for the simultaneous extraction of FSV and CAR from human serum before using high-performance liquid chromatography-diode array detector (HPLC-DAD) analysis. The optimization of SLE parameters was achieved through response surface methodology (RSM) based on the Box-Behnken design (BBD) and included serum-water-extraction solvent ratio and eluent volume. Under optimal conditions, the proposed method gives acceptable limits of detection (LOD) (0.005-0.3 μg/mL), good recovery (89.6-110.9%) as well as relative standard deviation (RSD) of less than 10.1% by consuming lower serum sample (100 μL) and less sample preparation time (2 min per sample). Compared with liquid-phase extraction (LLE), the SLE delivers rapid extraction with higher recovery, better reproducibility, and lower matrix effect for CAR and FSV analysis. The method has been successfully applied to quantify CAR and FSV levels in serum of healthy individuals and age-related macular degeneration (AMD) patients, demonstrating the feasibility of the proposed method for epidemiology and routine applications.
    Keywords:  Biological analysis; Carotenoids; Fat-soluble vitamins; High-throughput; Response surface methodology; Supported liquid extraction
  5. Chemosphere. 2021 Jul;pii: S0045-6535(21)00460-4. [Epub ahead of print]274 129991
      Exposure to endogenous and exogenous factors can result in the formation of a wide variety of DNA adducts, and these may lead to gene mutations, thereby contributing to the development of cancer. DNA adductomics, a novel tool for exposomics, aims to detect the totality of DNA adducts. Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is the state-of-the-art method for DNA adductomic analysis, although its high cost has limited widespread use. In this study, we compared the analytical performance between HRMS and the more popular/accessible triple-quadrupole MS (QqQ-MS). We initially developed and optimized a hybrid quadrupole-linear ion trap-orbitrap MS (Q-LIT-OT-MS) method, considering the detection of both purine and pyrimidine adducts. LC-Q-LIT-OT-MS and LC-QqQ-MS methods were compared by non-targeted screening of formaldehyde-induced DNA adducts. Using the results from Q-LIT-OT-MS as the gold standard, QqQ-MS successfully detected 12 out of 18 formaldehyde-induced DNA adducts/inter-strand crosslinks (ICLs). QqQ-MS however also produced nine false-positive results owing to the inherent instrumental mass resolution limits. To discriminate the false-positive results from the accurate ones, we firstly introduced a statistical analysis, partial least squares-discriminant analysis, which efficiently excluded the false signals. Six DNA adducts/ICLs were not detected by QqQ-MS, due to insufficient sensitivity. This could be overcome by employing a selected reaction monitoring scan mode with multiple injections. Overall, this study demonstrated that high resolution may not be a strict requirement for MS-based DNA adductomics. LC-QqQ-MS with statistical analysis, could also provide a comparable performance as HRMS for pre-screening purposes.
    Keywords:  DNA adductome; DNA adducts/Inter-strand crosslinks; Formaldehyde; PLS-DA; Q-LIT-OT-MS; QqQ-MS
  6. Wei Sheng Yan Jiu. 2021 Mar;50(2): 301-307
      OBJECTIVE: To establish a method for the determination of vitamin A(retinol) and four active forms of vitamin E(α-tocopherol, β-tocopherol, γ-tocopherol and δ-tocopherol) in human serum by ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometry(UPLC-MS/MS).METHODS: The sample was deproteinized by methanol, then extracted by n-hexane, dryness under nitrogen and followed by a reconstitution with methanol. The analysis was performed on a C_(30) column(3 mm×150 mm, 2. 6 μm), and isometric elution using 0. 1% formic acid in methanol and 5 mmol/L ammonium formate in 0. 1% formic acid as the mobile phase. The samples were determined by mass spectrometry in the positive ion mode with the multiple reaction monitoring mode, quantified by the internal standard method.
    RESULTS: Vitamin A and four active forms of vitamin E were separated within 42 minutes, and β-tocopherol and γ-tocopherol can be distinguished. The linear was good for retinol in the range of 0. 0050-2. 5 μg/mL, 0. 036-20 μg/mL for α-tocopherol, 0. 042-8. 0 μg/mL for β-tocopherol and 0. 020-10 μg/mL for the other tocopherols. The limits of detection for retinol and tocopherols were in the range of 5. 76-31. 6 ng/mL. Recoveries of retinol and tocopherols at different levels were in range of 84. 4%-118. 6%, with the relative standard deviations were 1. 22%-8. 50%(n=6).
    CONCLUSION: This method is fast, accurate and sensitive and the preprocessing is simple, which can be used for determination of vitamin A and four active forms of vitamin E in human serum effectively.
    Keywords:  retinol; serum; tocopherol; ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometry(UPLC-MS/MS); vitamin A; vitamin E
  7. Chem Rev. 2021 May 12.
      A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.
  8. Metabolomics. 2021 May 11. 17(5): 49
      BACKGROUND: Precision medicine, space exploration, drug discovery to characterization of dark chemical space of habitats and organisms, metabolomics takes a centre stage in providing answers to diverse biological, biomedical, and environmental questions. With technological advances in mass-spectrometry and spectroscopy platforms that aid in generation of information rich datasets that are complex big-data, data analytics tend to co-evolve to match the pace of analytical instrumentation. Software tools, resources, databases, and solutions help in harnessing the concealed information in the generated data for eventual translational success.AIM OF THE REVIEW: In this review, ~ 85 metabolomics software resources, packages, tools, databases, and other utilities that appeared in 2020 are introduced to the research community.
    KEY SCIENTIFIC CONCEPTS OF REVIEW: In Table 1 the computational dependencies and downloadable links of the tools are provided, and the resources are categorized based on their utility. The review aims to keep the community of metabolomics researchers updated with all the resources developed in 2020 at a collated avenue, in line with efforts form 2015 onwards to help them find these at one place for further referencing and use.
    Keywords:  Annotation; Database; In silico; Metabolite; Metabolomics; Program; Recourse; Software; Tool