bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2021‒09‒12
fifteen papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

  1. Mass Spectrom Rev. 2021 Sep 05. e21729
      Lipids, serving as the structural components of cellular membranes, energy storage, and signaling molecules, play the essential and multiple roles in biological functions of mammals. Mass spectrometry (MS) is widely accepted as the first choice for lipid analysis, offering good performance in sensitivity, accuracy, and structural characterization. However, the untargeted qualitative profiling and absolute quantitation of lipids are still challenged by great structural diversity and high structural similarity. In recent decade, chemical derivatization mainly targeting carboxyl group and carbon-carbon double bond of lipids have been developed for lipidomic analysis with diverse advantages: (i) offering more characteristic structural information; (ii) improving the analytical performance, including chromatographic separation and MS sensitivity; (iii) providing one-to-one chemical isotope labeling internal standards based on the isotope derivatization regent in quantitative analysis. Moreover, the chemical derivatization strategy has shown great potential in combination with ion mobility mass spectrometry and ambient mass spectrometry. Herein, we summarized the current states and advances in chemical derivatization-assisted MS techniques for lipidomic analysis, and their strengths and challenges are also given. In summary, the chemical derivatization-based lipidomic approach has become a promising and reliable technique for the analysis of lipidome in complex biological samples.
    Keywords:  chemical derivatization; chemical isotope labeling; ion mobility mass spectrometry; lipidomics; mass spectrometry
  2. BMC Bioinformatics. 2021 Sep 07. 22(1): 423
      BACKGROUND: Assessing the reproducibility of measurements is an important first step for improving the reliability of downstream analyses of high-throughput metabolomics experiments. We define a metabolite to be reproducible when it demonstrates consistency across replicate experiments. Similarly, metabolites which are not consistent across replicates can be labeled as irreproducible. In this work, we introduce and evaluate the use (Ma)ximum (R)ank (R)eproducibility (MaRR) to examine reproducibility in mass spectrometry-based metabolomics experiments. We examine reproducibility across technical or biological samples in three different mass spectrometry metabolomics (MS-Metabolomics) data sets.RESULTS: We apply MaRR, a nonparametric approach that detects the change from reproducible to irreproducible signals using a maximal rank statistic. The advantage of using MaRR over model-based methods that it does not make parametric assumptions on the underlying distributions or dependence structures of reproducible metabolites. Using three MS Metabolomics data sets generated in the multi-center Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPD) study, we applied the MaRR procedure after data processing to explore reproducibility across technical or biological samples. Under realistic settings of MS-Metabolomics data, the MaRR procedure effectively controls the False Discovery Rate (FDR) when there was a gradual reduction in correlation between replicate pairs for less highly ranked signals. Simulation studies also show that the MaRR procedure tends to have high power for detecting reproducible metabolites in most situations except for smaller values of proportion of reproducible metabolites. Bias (i.e., the difference between the estimated and the true value of reproducible signal proportions) values for simulations are also close to zero. The results reported from the real data show a higher level of reproducibility for technical replicates compared to biological replicates across all the three different datasets. In summary, we demonstrate that the MaRR procedure application can be adapted to various experimental designs, and that the nonparametric approach performs consistently well.
    CONCLUSIONS: This research was motivated by reproducibility, which has proven to be a major obstacle in the use of genomic findings to advance clinical practice. In this paper, we developed a data-driven approach to assess the reproducibility of MS-Metabolomics data sets. The methods described in this paper are implemented in the open-source R package marr, which is freely available from Bioconductor at .
    Keywords:  Mass spectrometry; Metabolomics; Reproducibility
  3. Bioinformatics. 2021 Sep 08. pii: btab644. [Epub ahead of print]
      SUMMARY: We present the LipidQuant 1.0 tool for automated data processing workflows in lipidomic quantitation based on lipid class separation coupled with high-resolution mass spectrometry. Lipid class separation workflows, such as hydrophilic interaction liquid chromatography or supercritical fluid chromatography, should be preferred in lipidomic quantitation due to the coionization of lipid class internal standards with analytes from the same class. The individual steps in the LipidQuant workflow are explained, including lipid identification, quantitation, isotopic correction, and reporting results. We show the application of LipidQuant data processing to a small cohort of human serum samples.AVAILABILITY AND IMPLEMENTATION: The LipidQuant 1.0 is freely available at Zenodo and
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
  4. J Agric Food Chem. 2021 Sep 07.
      Bile acids are being increasingly investigated in humans and laboratory animals as markers for various diseases in addition to their important functions, such as promoting the emulsification in fat digestion and preventing gallstone formation. In humans and animals, primary bile acids are formed from cholesterol in the liver, converted in the intestine into various secondary bile acids by the intestinal microbiota and reabsorbed in the terminal ileum, and partially returned to the liver. A universal high-throughput workflow, including a simple workup, was applied as a tool for bile acid analysis in animal studies. The complex bile acid profiles in various tissues, organs, and body fluids from different animals were mapped using a newly developed comprehensive liquid chromatography-tandem mass spectrometry method. The method can also be used in screening food to obtain information about the nutritional content of bile acids. This could be relevant to investigations on various animal diseases and on the bioavailability of bile acids that pass through the gastric tract.
    Keywords:  UHPLC-ESI-LC-MS/MS; animal tissue; bile acid distribution; bile acids; targeted metabolite profiling
  5. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi. 2021 Aug 20. 39(8): 612-616
      Objective: To establish a LC-MS/MS method for determination of paraquat and diquat in plasma and urine samples. Methods: Plasma is precipitated by acetonitrile then diluent with phosphate buffer (pH=7) , urine is diluent with phosphate buffer (pH=7) , then diluent samples extracted with Oasis WCX solid-phase extraction column. Samples were analyzed using LC-MS/MS in multiple reaction monitoring (MRM) mode. The analytical column was XBridge®BEH-HILIC (100 mm×2.1 mm×2.5 μm) and the mobile phase were 100 mmol ammonium formate add 0.5% formic acid and acetonitrile. Paraquat was quantified by internal standard method and diquat by external standard method. Results: The calibration curves of paraquat and diquat were linear in the concentration range of 10.0~120.0 μg/L, the correlation coefficient (r) were 0.9985~0.9994. The limit of detection of paraquat in plasma and urine were 1.98 μg/L and 1.00 μg/L, respectively, the recovery rate were 100.2%~107.3%, the RSD were 1.6%~3.3%. The limit of detection of diquat in plasma and urine were 1.80 μg/L and 2.77 μg/L, respectively, the recovery rate were 85.3%~93.1%, the RSD were 1.8%~5.5%. Conclusion: This method is sensitive and accurate, and can simultaneously determine paraquat and diquat in plasma and urine.
    Keywords:  Diquat; LC-MS/MS; Paraquat; Plasma; Urine
  6. Anal Bioanal Chem. 2021 Sep 08.
      A new gas chromatography-tandem mass spectrometry method for the determination of mono- and dihydroxylated polycyclic aromatic hydrocarbon metabolites (OH-PAHs and diol-PAHs) in urine was developed and validated. Various sample preparation procedures were compared, namely liquid-liquid extraction (LLE), dispersive solid-phase extraction (dSPE), and SPE, alone or combined. A novel two-stage derivatization approach using 2 silylation reagents was developed, and an experimental procedure design was used to optimize the programmed temperature vaporization-solvent vent injection (PTV-SV) GC parameters. The method focused on 11 target compounds resulting from four- to five-ring suspected carcinogenic PAHs. SPE was identified as an acceptable and more convenient extraction method for all tested metabolites, with extraction rates ranging from 63 to 86% and relative standard deviations lower than 20%. The two-stage derivatization approach successfully allowed first the derivatization of OH-PAHs by MTBSTFA (N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide) and then diol-PAHs by BSTFA (N,O-bis(trimethylsilyl)trifluoroacetamide) in a single run. The limits of quantification were in the range of 0.01-0.02 μg l-1 for OH-PAHs and 0.02-0.2 μg l-1 for diol-PAHs. The intra- and interday precisions were lower than 10%. The method was applied to determine PAH metabolites in urine collected at the beginning and at the end of the working week from 6 workers involved in aluminum production. The mean diol-PAH levels at the end of the week were 10 to 20 times higher (0.86-2.34 μg g-1 creatinine) than those of OH-PAHs (0.03-0.30 μg g-1). These results confirmed the usefulness of this new analytical technique for detecting and characterizing metabolic patterns of PAHs in urine and assessing carcinogenic occupational exposures.
    Keywords:  Derivatization; Extraction techniques; Mono- and dihydroxylated metabolites; Polycyclic aromatic hydrocarbons; Tandem mass spectrometry; Urine
  7. Anal Chem. 2021 Sep 07.
      In comparison to proteomics, the application of two-dimensional liquid chromatography (2D LC) in the field of metabolomics is still premature. One reason might be the elevated chemical complexity and the associated challenge of selecting proper separation conditions in each dimension. As orthogonality of dimensions is a major issue, the present study aimed for the identification of successful stationary phase combinations. To determine the degree of orthogonality, first, six different metrics, namely, Pearson's correlation coefficient (1 - |R|), the nearest-neighbor distances (H̅NND), the "asterisk equations" (AO), and surface coverage by bins (SCG), convex hulls (SCCH), and α-convex hulls (SCαH), were critically assessed by 15 artificial 2D data sets, and a systematic parameter optimization of α-convex hulls was conducted. SGG, SCαH with α = 0.1, and H̅NND generated valid results with sensitivity toward space utilization and data distribution and, therefore, were applied to pairs of experimental retention time sets obtained for >350 metabolites, selected to represent the chemical space of human urine. Normalized retention data were obtained for 23 chromatographic setups, comprising reversed-phase (RP), hydrophilic interaction liquid chromatography (HILIC), and mixed-mode separation systems with an ion exchange (IEX) contribution. As expected, no single LC setting provided separation of all considered analytes, but while conventional RP×HILIC combinations appeared rather complementary than orthogonal, the incorporation of IEX properties into the RP dimension substantially increased the 2D potential. Eventually, one of the most promising column combinations was implemented for an offline 2D LC time-of-flight mass spectrometry analysis of a lyophilized urine sample. Targeted screening resulted in a total of 164 detected metabolites and confirmed the outstanding coverage of the 2D retention space.
  8. Anal Chim Acta. 2021 Sep 15. pii: S0003-2670(21)00635-8. [Epub ahead of print]1178 338809
      We present a new analytical approach for the analysis of triacylglycerol fatty acyls distribution by normal phase liquid chromatography (NPLC) coupled with APPI+-HRMS. The NPLC method used allows the separation of more than 30 classes of lipids. The energy of the APPI+ source enables the formation of low-intensity ions B fragments ([RC = O+74]+ <3%), characteristic of lipids with a glycerol esterified by one or more fatty acyls. We found the relative intensities of ions B were close to the fatty acyl distribution. To establish the proof of concept, we decided to focus on the triacylglycerols (TGs) class, the major component of plant oils. By either NPLC or FIA, the TGs class appeared as a single peak. In our experimental conditions, ions B are always present in the mass spectra of TGs and each ion B is specific to a fatty acyl group. The Orbitrap mass spectrometer featured high enough resolution and accuracy to identify ions B and distinguish them from other TG fragment ions. A further adjustment of the fatty acyls relative quantities calculation from ions B intensities was computed using weighting coefficients of ions B response. The methodology was developed and validated using plant oils characterized by a GC-FID reference method. NPLC-APPI+-HRMS method offers the advantage of analyzing the fatty acyl composition of complex lipid extracts without the need for sample preparation.
    Keywords:  Atmospheric pressure photoionization; Fatty acids composition; Lipids; Normal phase chromatography; Orbitrap mass spectrometry; Triacylglycerols
  9. Molecules. 2021 Aug 28. pii: 5231. [Epub ahead of print]26(17):
      Metabolomics and lipidomics have demonstrated increasing importance in underlying biochemical mechanisms involved in the pathogenesis of diseases to identify novel drug targets and/or biomarkers for establishing therapeutic approaches for human health. Particularly, bioactive metabolites and lipids have biological activity and have been implicated in various biological processes in physiological conditions. Thus, comprehensive metabolites, and lipids profiling are required to obtain further advances in understanding pathophysiological changes that occur in cells and tissues. Chirality is one of the most important phenomena in living organisms and has attracted long-term interest in medical and natural science. Enantioselective separation plays a pivotal role in understanding the distribution and physiological function of a diversity of chiral bioactive molecules. In this context, it has been the goal of method development for targeted and untargeted metabolomics and lipidomic assays. Herein we will highlight the benefits and challenges involved in these stereoselective analyses for clinical samples.
    Keywords:  CE-MS; LC-MS; chiral amino acids; chiral biomarkers; lipidomics; metabolomics; stereoisomers
  10. Anal Chim Acta. 2021 Sep 15. pii: S0003-2670(21)00377-9. [Epub ahead of print]1178 338551
      Single-cell analysis can allow for an in-depth understanding of diseases, diagnostics, and aid the development of therapeutics. However, single-cell analysis is challenging, as samples are both extremely limited in size and complex. But the concept is gaining promise, much due to novel sample preparation approaches and the ever-improving field of mass spectrometry. The mass spectrometer's output is often linked to the preceding compound separation step, typically being liquid chromatography (LC). In this review, we focus on LC's role in single-cell omics. Particle-packed nano LC columns (typically 50-100 μm inner diameter) have traditionally been the tool of choice for limited samples, and are also used for single cells. Several commercial products and systems are emerging with single cells in mind, featuring particle-packed columns or miniaturized pillar array systems. In addition, columns with inner diameters as narrow as 2 μm are being explored to maximize sensitivity. Hence, LC column down-scaling is a key focus in single-cell analysis. But narrow columns are associated with considerable technical challenges, while single cell analysis may be expected to become a "routine" service, requiring higher degrees of robustness and throughput. These challenges and expectations will increase the need and attention for the development (and even the reinvention) of alternative nano LC column formats. Therefore, monolith columns and even open tubular columns may finally find their "killer-application" in single cell analysis.
    Keywords:  Liquid chromatography; Mass spectrometry; Metabolomics; Proteomics; Single cell
  11. J Lab Physicians. 2021 Jun;13(2): 123-128
      Objectives  Therapeutic drug monitoring (TDM) of isavuconazole, which is a novel broad-spectrum antimycoticum against invasive fungal infections, ensures an effective exposure of the drug and minimizes the risk of toxicity. This study is aimed at evaluating the analytical performance of a dual-column liquid chromatography-tandem mass-spectrometry (LC-MS/MS) method for isavuconazole quantification. Materials and Methods  The method was performed on a Voyager TSQ Quantum triple quadrupole instrument equipped with an Ultimate 3000 chromatography system (Thermo Fisher Scientific, San Jose, California, United States). Analytical and preanalytical requirements of the isavuconazole LC-MS/MS method were evaluated. Sample stability measurements were performed at room temperature (RT) and in serum tubes with separator gel. Results  The isavuconazole LC-MS/MS method was linear over the concentration range of 0.2 to 12.8 mg/L. The coefficient of determination ( r 2 ) always exceeded 0.999. Within- and between-run precision ranged between 1.4 to 2.9% and 1.5 to 3.0%, the recovery between 93.9 and 102.7%. At RT, serum samples were stable for 3 days. Isavuconazole serum concentrations were significantly lower after incubation (18 hours) in serum tubes with separator gel at RT. Conclusion  The dual-column isavuconazole LC-MS/MS is a reliable tool for the TDM of isavuconazole. Serum samples are stable for at least 3 days and should be collected in tubes without separator gel.
    Keywords:  antifungal agents; isavuconazole; liquid chromatography-tandem mass-spectrometry; therapeutic drug monitoring; triazole
  12. Anal Chim Acta. 2021 Sep 08. pii: S0003-2670(21)00472-4. [Epub ahead of print]1177 338646
      It is now well-established that dysregulation of the tricarboxylic acid (TCA) cycle enzymes succinate dehydrogenase, fumarate hydratase, and isocitrate dehydrogenase leads to the abnormal cellular accumulation of succinate, fumarate, and 2-hydroxyglutarate, respectively, which contribute to the formation and malignant progression of numerous types of cancers. Thus, these metabolites, called oncometabolites, could potentially be useful as tumour-specific biomarkers and as therapeutic targets. For this reason, the development of analytical methodologies for the accurate identification and determination of their levels in biological matrices is an important task in the field of cancer research. Currently, hyphenated gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) techniques are the most powerful analytical tools in what concerns high sensitivity and selectivity to achieve such difficult task. In this review, we first provide a brief description of the biological formation of oncometabolites and their oncogenic properties, and then we present an overview and critical assessment of the GC-MS and LC-MS based analytical approaches that are reported in the literature for the determination of oncometabolites in biological samples, such as biofluids, cells, and tissues. Advantages and drawbacks of these approaches will be comparatively discussed. We believe that the present review represents the first attempt to summarize the applications of these hyphenated techniques in the context of oncometabolite analysis, which may be useful to new and existing researchers in this field.
    Keywords:  Biological samples; Gas chromatography-mass spectrometry; Liquid chromatography-mass spectrometry; Oncometabolites; Tumour biomarkers
  13. J AOAC Int. 2021 Sep 08. pii: qsab101. [Epub ahead of print]
      BACKGROUND: In Guangdong Province of China, the climate here is very wet, so there are many different fungus living in the aquatic feeds, which produce mycotoxins. These compounds contaminate agriculture products world-wide and represent a great threat to human health. It is necessary to determine their contamination level in aquatic feeds.OBJECTIVE: A high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) method was developed for the quantitative analysis of aflatoxin B1, aflatoxin M1, T-2 toxin, HT-2 toxin, deoxynivalenol, ochratoxin, and zearalenone in the fish and shrimp feed.
    METHODS: Samples were extracted with acetonitrile-water (V: V = 3:1), and degreased with acetonitrile-saturated hexane. Such obtained extract was cleaned up with a multitoxin column. The target compounds were separated on a C18 chromatographic column and analyzed simultaneously by electrospray ionization mass spectrometry in both positive or negative ion mode. Detected compounds were quantified by using the matrix-matched external standard method.
    RESULTS: Under the optimized conditions, good linearities for the analytes in corresponding concentration range were obtained with correlation coefficients (r2) higher than 0.9948. LOD ranged from 1.83 to 12.63 μg/kg, and LOQ ranged from 5.49 to 37.89 μg/kg. Average recoveries for the target mycotoxins at three spiked levels ranged from 80.5% to 116.5% with RSD ranging from 2.4% to 10.4%. 23 real aquafeed samples were determined by this method, and 7 kinds of toxins were all detected.
    CONCLUSIONS: Obtained results showed that developed method could be successfully applied for the simultaneous determination of mycotoxins in aquatic feeds.
  14. Anal Chem. 2021 Sep 07.
      Mass spectrometry (MS) is widely used in science and industry. It allows accurate, specific, sensitive, and reproducible detection and quantification of a huge range of analytes. Across MS applications, quantification by MS has grown most dramatically, with >50 million experiments/year in the USA alone. However, quantification performance varies between instruments, compounds, different samples, and within- and across runs, necessitating normalization with analyte-similar internal standards (IS) and use of IS-corrected multipoint external calibration curves for each analyte, a complicated and resource-intensive approach, which is particularly ill-suited for multi-analyte measurements. We have developed an internal calibration method that utilizes the natural isotope distribution of an IS for a given analyte to provide internal multipoint calibration. Multiple isotope distribution calibrators for different targets in the same sample facilitate multiplex quantification, while the emerging random-access automated MS platforms should also greatly benefit from this approach. Finally, isotope distribution calibration allows mathematical correction for suboptimal experimental conditions. This might also enable quantification of hitherto difficult, or impossible to quantify, targets, if the distribution is adjusted in silico to mimic the analyte. The approach works well for high resolution, accurate mass MS for analytes with at least a modest-sized isotopic envelope. As shown herein, the approach can also be applied to lower molecular weight analytes, but the reduction in calibration points does reduce quantification performance.
  15. PLoS Comput Biol. 2021 Sep 07. 17(9): e1009105
      Over-representation analysis (ORA) is one of the commonest pathway analysis approaches used for the functional interpretation of metabolomics datasets. Despite the widespread use of ORA in metabolomics, the community lacks guidelines detailing its best-practice use. Many factors have a pronounced impact on the results, but to date their effects have received little systematic attention. Using five publicly available datasets, we demonstrated that changes in parameters such as the background set, differential metabolite selection methods, and pathway database used can result in profoundly different ORA results. The use of a non-assay-specific background set, for example, resulted in large numbers of false-positive pathways. Pathway database choice, evaluated using three of the most popular metabolic pathway databases (KEGG, Reactome, and BioCyc), led to vastly different results in both the number and function of significantly enriched pathways. Factors that are specific to metabolomics data, such as the reliability of compound identification and the chemical bias of different analytical platforms also impacted ORA results. Simulated metabolite misidentification rates as low as 4% resulted in both gain of false-positive pathways and loss of truly significant pathways across all datasets. Our results have several practical implications for ORA users, as well as those using alternative pathway analysis methods. We offer a set of recommendations for the use of ORA in metabolomics, alongside a set of minimal reporting guidelines, as a first step towards the standardisation of pathway analysis in metabolomics.