bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2020‒08‒30
eleven papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

  1. Metabolites. 2020 Aug 25. pii: E342. [Epub ahead of print]10(9):
    Züllig T, Zandl-Lang M, Trötzmüller M, Hartler J, Plecko B, Köfeler HC.
      In the highly dynamic field of metabolomics, we have developed a method for the analysis of hydrophilic metabolites in various biological samples. Therefore, we used hydrophilic interaction chromatography (HILIC) for separation, combined with a high-resolution mass spectrometer (MS) with the aim of separating and analyzing a wide range of compounds. We used 41 reference standards with different chemical properties to develop an optimal chromatographic separation. MS analysis was performed with a set of pooled biological samples human cerebrospinal fluid (CSF), and human plasma. The raw data was processed in a first step with Compound Discoverer 3.1 (CD), a software tool for untargeted metabolomics with the aim to create a list of unknown compounds. In a second step, we combined the results obtained with our internally analyzed reference standard list to process the data along with the Lipid Data Analyzer 2.6 (LDA), a software tool for a targeted approach. In order to demonstrate the advantages of this combined target-list based and untargeted approach, we not only compared the relative standard deviation (%RSD) of the technical replicas of pooled plasma samples (n = 5) and pooled CSF samples (n = 3) with the results from CD, but also with XCMS Online, a well-known software tool for untargeted metabolomics studies. As a result of this study we could demonstrate with our HILIC-MS method that all standards could be either separated by chromatography, including isobaric leucine and isoleucine or with MS by different mass. We also showed that this combined approach benefits from improved precision compared to well-known metabolomics software tools such as CD and XCMS online. Within the pooled plasma samples processed by LDA 68% of the detected compounds had a %RSD of less than 25%, compared to CD and XCMS online (57% and 55%). The improvements of precision in the pooled CSF samples were even more pronounced, 83% had a %RSD of less than 25% compared to CD and XCMS online (28% and 8% compounds detected). Particularly for low concentration samples, this method showed a more precise peak area integration with its 3D algorithm and with the benefits of the LDAs graphical user interface for fast and easy manual curation of peak integration. The here-described method has the advantage that manual curation for larger batch measurements remains minimal due to the target list containing the information obtained by an untargeted approach.
    Keywords:  CSF; LC-MS; LDA; XCMS; metabolomics; plasma
  2. Nat Commun. 2020 Aug 28. 11(1): 4334
    Zhou Z, Luo M, Chen X, Yin Y, Xiong X, Wang R, Zhu ZJ.
      The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobility - mass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here, we curate an ion mobility CCS atlas, namely AllCCS, and develop an integrated strategy for metabolite annotation using known or unknown chemical structures. The AllCCS atlas covers vast chemical structures with >5000 experimental CCS records and ~12 million calculated CCS values for >1.6 million small molecules. We demonstrate the high accuracy and wide applicability of AllCCS with medium relative errors of 0.5-2% for a broad spectrum of small molecules. AllCCS combined with in silico MS/MS spectra facilitates multi-dimensional match and substantially improves the accuracy and coverage of both known and unknown metabolite annotation from biological samples. Together, AllCCS is a versatile resource that enables confident metabolite annotation, revealing comprehensive chemical and metabolic insights towards biological processes.
  3. J Biomol Tech. 2020 Aug;31(Suppl): S21
    Dhungana S, Molloy B, Plumb R, Li J.
      There is increasing need for throughput as the metabolomics studies are getting larger. Throughput can be achieved on the analytical side by using rapid methods or speeding up the data analysis and metabolite identification steps. Series of rapid UPLC-MS/MS methods have been developed on a single platform with identical analysis workflow for high throughput measurement of derivatized amino acids, acylcarnitines, bile acids, free fatty acids, tryptophan metabolites in human serum to support metabolomics research. The separation of isomers (amino acids and bile acids) are achieved in analytical runtimes of <4mins making these methods powerful and are well suited for a Core laboratory. Here we discuss these methods and demonstrate their usability for the analysis of metabolites in patient derived serum samples during targeted multi-omics analysis. Sample preparation involved protein precipitation with methanol (1:4 serum:methanol) for the extraction of acylcarnitines, bile acids, and free fatty acids. For amino acid analysis, serum samples were prepared using the Waters™ AccQTag Kit following the Kit protocol. Tryptophan metabolites sample preparation was achieved using Oasis HLB PRiME µElution Plate. UPLC separation was performed on an ACQUITY UPLC I-Class System (fixed loop), equipped with a CORTECS T3 2.7 µm (2.1 x 30 mm) analytical column. A 2 µ Lextract was injected at a flow rate of 1.3 mL/min. Mobile phase A was 0.01% formic acid (aq) and Mobile phase B was 50% isopropanol in acetonitrile containing 0.01% formic acid. The LC gradient and column equilibration times were optimized for each class of metabolites. The analytical column temperature was maintained at 60°C. Multiple Reaction Monitoring (MRM) analyses were performed using a Xevo TQ-S micro mass spectrometer. All experiments were performed in electrospray ionization mode. Data processing was done using in TargetLynx and Skyline.
  4. J Biomol Tech. 2020 Aug;31(Suppl): S20-S21
    Dhungana S, Munjoma N, Isaac G, Gethings L, Plumb R.
      Bladder cancer is the 10th most common cancer and occurs when abnormal tissue growth develops within the bladder lining. Recent bladder cancer studies suggest that a strict distribution pattern of lipid species and enzymes determine cell fate through regulatory mechanisms. Targeted lipid analysis of plasma samples from bladder cancer patients and healthy subjects was conducted using the LipidQuan platform. LipidQuan package was downloaded from the Waters Targeted Omics Method Library (TOML), which provided all the chromatographic settings and MRM transitions required for lipid analysis. Targeted LC-MS data were acquired in positive and negative ion ESI modes. Over 400 lipids were quantified. Quantification was achieved using calibration curves of plasma spiked with known concentrations of SIL standards prior to extraction. By using surrogate standards prepared and analyzed under identical conditions to those of endogenous lipids, the quantification of endogenous lipids within the same class was achieved. The use of a commercially available, premixed SIL solution per lipid class, rather than a SIL standard for each measured lipid, significantly reduces the overall cost of the study. Deuterated standards were used to assess linear response, with typical R2 values ranging from 0.97 - 0.99 for the various lipid classes in both modes of ionization. Ceramides, LPCs, PCs, and SM are differentially expressed in bladder cancer samples when compared to samples from healthy controls. Pathway analysis revealed a number of components related to inflammation, oxidative stress, and immunity as being significant. A rapid, quantitative lipidomics method (LipidQuan) was deployed for the analysis of plasma in a bladder cancer comparative study. This eliminated method development time and allowed implementation of the methods within minutes. This is of great benefit to a core laboratory. LPCs, Cer, and SM were found to be important markers of bladder cancer.
  5. J Am Soc Mass Spectrom. 2020 Aug 28.
    Thompson C, Witt M, Forcisi S, Moritz F, Kessler N, Laukien FH, Schmitt-Kopplin P.
      A major bottleneck in metabolomics is the annotation of molecular formula as a first step to tentative structure assignment of known and unknown metabolites. The direct observation of isotopic fine structure (IFS) provides the ability to confidently assign an unknown's molecular formula out of a complex mass spectrum. However, the majority of mass spectrometers deployed for metabolomic studies do not have sufficient resolving power and high-fidelity isotope ratios in the mass range of interest to determine molecular formulae from IFS data. To increase the number of unknowns for which IFS can be determined, a segmented 'box car' approach using a selection quadrupole as a broadband mass filter is used. In this longer, enhanced dynamic range discovery experiment, selected ions in a specific mass range are accumulated before detection by the analyzer cell. The mass filter window is then moved across the entire mass range resulting in a composite mass spectrum covering the m/z range of interest for phenomics research. The effectiveness of the FIA-CASI-FTMS workflow utilizing IFS for molecular formula assignment is realized with the implementation of the dynamically harmonized cell, which distinguishes the approach from other segmented workflows due to the analytical properties of the cell. The discovery approach was applied to a human plasma sample to confidently assign unknown molecular formula as part of the quest to illuminate its metabolic 'dark matter' via high-fidelity IFS ratio determinations. The FIA-CASI-FTMS workflow showed a 2.6-fold increase in both matching with HMDB based and increase in IFS pattern.
  6. Nat Methods. 2020 Aug 24.
    Nothias LF, Petras D, Schmid R, Dührkop K, Rainer J, Sarvepalli A, Protsyuk I, Ernst M, Tsugawa H, Fleischauer M, Aicheler F, Aksenov AA, Alka O, Allard PM, Barsch A, Cachet X, Caraballo-Rodriguez AM, Da Silva RR, Dang T, Garg N, Gauglitz JM, Gurevich A, Isaac G, Jarmusch AK, Kameník Z, Kang KB, Kessler N, Koester I, Korf A, Le Gouellec A, Ludwig M, Martin H C, McCall LI, McSayles J, Meyer SW, Mohimani H, Morsy M, Moyne O, Neumann S, Neuweger H, Nguyen NH, Nothias-Esposito M, Paolini J, Phelan VV, Pluskal T, Quinn RA, Rogers S, Shrestha B, Tripathi A, van der Hooft JJJ, Vargas F, Weldon KC, Witting M, Yang H, Zhang Z, Zubeil F, Kohlbacher O, Böcker S, Alexandrov T, Bandeira N, Wang M, Dorrestein PC.
      Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.
  7. J Am Soc Mass Spectrom. 2020 Aug 25.
    Downes DP, Zhong W, Zhang J, Chen B, Satapati S, Metzger D, Godinez G, Lao J, Sheth PR, McLaren DG, Talukdar S, Previs SF.
      Spatial characterization of triglyceride metabolism is an area of significant interest which can be enabled by mass spectrometry imaging via recent advances in neutral lipid laser desorption analytical approaches (LDI-MS). Here, we extend recent advancements in gold assisted neutral lipid imaging and demonstrate the potential to map lipid flux in rodents. We address here critical issues surrounding the analytical configuration and interpretation of the data for a group of select triglycerides. Specifically, we examined how the signal intensity and spatial resolution would impact the apparent isotope ratio in a given analyte (which is an important consideration when performing MS based kinetics studies of this kind) with attention given to molecular ions and not fragments. We evaluated the analytics by contrasting lipid flux in a well characterized mouse models, including fed vs fed states and different dietary perturbations. In total, the experimental paradigm described here should enable studies of hepatic lipogenesis; presumably, this logic can be enhanced via the inclusion of ion mobility and/or fragmentation. Although this study was carried out in a robust model of liver lipogenesis, we expect that the model system could be expanded to a variety of tissues where zonated (or heterogeneous) lipid synthesis may occur, including solid tumor metabolism.
  8. J Biomol Tech. 2020 Aug;31(Suppl): S24
    McLaughlin T, Chien A.
      Advances in fields such as metabolomics and biotherapeutics have generated a growing need for open access mass spectrometry methods supporting a wide range of analytes beyond traditional synthetic small molecules, from amino acids to antibodies. High resolution time of flight and orbitrap mass spectrometers are instruments of choice for intact protein analysis; they also support many qualitative and quantitative small molecule workflows and have the mass stability and operational reliability needed in an open access lab setting. Our challenge is to configure one LC/HRMS system to support a broad spectrum of applications without manual intervention. Providing multiple complementary chromatography options is key to maximizing flexibility. We set up an Open Access LC/HRMS system composed of a Waters Acquity UPLC with 4 column manager and Thermo Exactive Classic, mass calibrated once a week. A suite of methods using 4 columns and 4 solvents allows switching among intact protein and small molecule methods on the fly: Waters BioResolve RP Mab Polyphenyl, Agilent Poroshell C18, Agilent Zorbax SB-C8, and SeQuant ZIC-HILIC columns, run using 0.1% formic acid in water, 0.1% formic acid in acetonitrile, methanol, and 5mM ammonium acetate plus 0.1% formic acid in water. Software solutions empower users to acquire and analyze their own data. A vendor-neutral Open Access instrument control platform, Remote Analyzer from SpectralWorks, allows users to queue samples by choosing from a menu of established methods. Users have several options for data processing: vendor-neutral software from MesReNova and Protein Metrics, and instrument-specific software on computers at the core. Our poster demonstrates the diversity of applications supported by this platform, including method parameters with example chromatograms and spectra for each of the four columns. Maximizing flexibility in this manner maximizes the utility of existing instrumentation for a broader user base.
  9. Rapid Commun Mass Spectrom. 2020 Aug 24. e8928
    Delvaux A, Rathahao-Paris E, Alves S.
      RATIONALE: Isomer metabolites are involved in metabolic pathways, and their characterization is essential but remains challenging even using high performance analytical platform. The addition of ion mobility prior to mass analysis can help to separate isomers. Here, the ability of a recently developed trapped ion mobility spectrometry (TIMS) system to separate metabolite isomers was examined.METHODS: Three pairs of estrogen isomers were studied as a model of isomeric metabolites under both negative and positive electrospray ionization (ESI) modes using a commercial TIMS-TOF MS instrument. The standard metabolites were also spiked in human urine to evaluate the efficiency of TIMS to separate isomers in complex mixtures.
    RESULTS: The estradiol glucuronide isomers (E2 β-3G and E2 β-17G) could be distinguished as deprotonated species, while the estradiol epimers (E2 β and E2 α) and the methoxyestradiol isomers (2-MeO-E2 β and 4-MeO-E2 β) were separated as lithiated adducts in positive ionization mode. When performing analyses in the urine matrix, no alteration in the ion mobility resolving power was observed and the measured CCS values varied less than 1.0 %.
    CONCLUSIONS: The TIMS-TOF instrument enabled the separation of the metabolite isomers with very small differences in CCS values (ΔCCS% = 2 %). It is shown to be an effective tool for the rapid characterization of isomers in complex matrices.
  10. J Chromatogr B Analyt Technol Biomed Life Sci. 2020 Aug 01. pii: S1570-0232(20)30577-8. [Epub ahead of print]1155 122299
    Buziau AM, Scheijen JLJM, Stehouwer CDA, Simons N, Brouwers MCGJ, Schalkwijk CG.
      BACKGROUND: The study of the involvement of fructose in the pathogenesis of cardiometabolic disease requires accurate and precise measurements of serum and urinary fructose. The aim of the present study was to develop and validate such a method by Ultra Performance Liquid Chromatography-tandem Mass Spectrometry (UPLC-MS/MS).METHODS: Fructose was quantified using hydrophilic interaction UPLC-MS/MS with a labelled internal standard. Serum fructose levels were determined in healthy individuals (n = 3) after a 15-gram oral fructose load. Twenty-four hours urinary fructose levels were determined in individuals consuming low (median: 1.4 g/day, interquartile range [IQR]: 0.9-2.0; n = 10), normal (31 g/day, 23-49; n = 15) and high (70 g/day, 55-84; n = 16) amounts of fructose.
    RESULTS: The calibration curves showed perfect linearity in water, artificial, serum, and urine matrices (r2 > 0.99). Intra- and inter-day assay variation of serum and urinary fructose ranged from 0.3 to 5.1% with an accuracy of ~98%. Fasting serum fructose levels (5.7 ± 0.6 µmol/L) increased 60 min after a 15-gram oral fructose load (to 150.3 ± 41.7 µmol/L) and returned to normal after 180 min (8.4 ± 0.6 µmol/L). Twenty-four hours urinary fructose levels were significantly lower in low fructose consumers when compared to normal and high fructose consumers (median: 36.1 µmol/24 h, IQR: 26.4-64.2; 142.3 µmol/24 h, 98.8-203.0; and 238.9 µmol/24 h, 127.1-366.1; p = 0.004 and p < 0.001, respectively).
    CONCLUSION: Fructose concentrations can be measured accurately and precisely with this newly-developed UPLC-MS/MS method. Its robustness makes it suitable for assessing the value of fructose in clinical studies.
    Keywords:  Fructose; Method validation; Serum; Sugars; Ultra-performance liquid chromatography tandem mass-spectrometry (UPLC-MS/MS); Urine