bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2022‒07‒31
38 papers selected by
Sofia Costa
Matterworks


  1. Metabolites. 2022 Jul 25. pii: 684. [Epub ahead of print]12(8):
      MAVEN, an open-source software program for analysis of LC-MS metabolomics data, was originally released in 2010. As mass spectrometry has advanced in the intervening years, MAVEN has been periodically updated to reflect this advancement. This manuscript describes a major update to the program, MAVEN2, which supports LC-MS/MS analysis of metabolomics and lipidomics samples. We have developed algorithms to support MS/MS spectral matching and efficient search of large-scale fragmentation libraries. We explore the ability of our approach to separate authentic from spurious metabolite identifications using a set of standards spiked into water and yeast backgrounds. To support our improved lipid identification workflow, we introduce a novel in-silico lipidomics library covering major lipid classes and compare searches using our novel library to searches with existing in-silico lipidomics libraries. MAVEN2 source code and cross-platform application installers are freely available for download from GitHub under a GNU permissive license [ver 3], as are the in silico lipidomics libraries and corresponding code repository.
    Keywords:  GUI; fragmentation; identification; lipidomics; metabolomics; open-source; software; visualization
    DOI:  https://doi.org/10.3390/metabo12080684
  2. Metabolites. 2022 Jun 29. pii: 605. [Epub ahead of print]12(7):
      Metabolite annotation has been a challenging issue especially in untargeted metabolomics studies by liquid chromatography coupled with mass spectrometry (LC-MS). This is in part due to the limitations of publicly available spectral libraries, which consist of tandem mass spectrometry (MS/MS) data acquired from just a fraction of known metabolites. Machine learning provides the opportunity to predict molecular fingerprints based on MS/MS data. The predicted molecular fingerprints can then be used to help rank putative metabolite IDs obtained by using either the precursor mass or the formula of the unknown metabolite. This method is particularly useful to help annotate metabolites whose corresponding MS/MS spectra are missing or cannot be matched with those in accessible spectral libraries. We investigated a convolutional neural network (CNN) for molecular fingerprint prediction based on data acquired by MS/MS. We used more than 680,000 MS/MS spectra obtained from the MoNA repository and NIST 20, representing about 36,000 compounds for training and testing our CNN model. The trained CNN model is implemented as a python package, MetFID. The package is available on GitHub for users to enter their MS/MS spectra and corresponding putative metabolite IDs to obtain ranked lists of metabolites. Better performance is achieved by MetFID in ranking putative metabolite IDs using the CASMI 2016 benchmark dataset compared to two other machine learning-based tools (CSI:FingerID and ChemDistiller).
    Keywords:  deep learning; metabolite identification; metabolomics; molecular fingerprint
    DOI:  https://doi.org/10.3390/metabo12070605
  3. Metabolites. 2022 Jun 23. pii: 584. [Epub ahead of print]12(7):
      Mass spectrometry is a widely used technology to identify and quantify biomolecules such as lipids, metabolites and proteins necessary for biomedical research. In this study, we catalogued freely available software tools, libraries, databases, repositories and resources that support lipidomics data analysis and determined the scope of currently used analytical technologies. Because of the tremendous importance of data interoperability, we assessed the support of standardized data formats in mass spectrometric (MS)-based lipidomics workflows. We included tools in our comparison that support targeted as well as untargeted analysis using direct infusion/shotgun (DI-MS), liquid chromatography-mass spectrometry, ion mobility or MS imaging approaches on MS1 and potentially higher MS levels. As a result, we determined that the Human Proteome Organization-Proteomics Standards Initiative standard data formats, mzML and mzTab-M, are already supported by a substantial number of recent software tools. We further discuss how mzTab-M can serve as a bridge between data acquisition and lipid bioinformatics tools for interpretation, capturing their output and transmitting rich annotated data for downstream processing. However, we identified several challenges of currently available tools and standards. Potential areas for improvement were: adaptation of common nomenclature and standardized reporting to enable high throughput lipidomics and improve its data handling. Finally, we suggest specific areas where tools and repositories need to improve to become FAIRer.
    Keywords:  FAIR; bioinformatics; data format; database; lipidomics; mass spectrometry; standardization
    DOI:  https://doi.org/10.3390/metabo12070584
  4. Metabolites. 2022 Jul 19. pii: 665. [Epub ahead of print]12(7):
      Identification of xenobiotics and their phase I/II metabolites in poisoned patients remains challenging. Systematic approaches using bioinformatic tools are needed to detect all compounds as exhaustively as possible. Here, we aimed to assess an analytical workflow using liquid chromatography coupled to high-resolution mass spectrometry with data processing based on a molecular network to identify tramadol metabolites in urine and plasma in poisoned patients. The generated molecular network from liquid chromatography coupled to high-resolution tandem mass spectrometry data acquired in both positive and negative ion modes allowed for the identification of 25 tramadol metabolites in urine and plasma, including four methylated metabolites that have not been previously reported in humans or in vitro models. While positive ion mode is reliable for generating a network of tramadol metabolites displaying a dimethylamino radical in their structure, negative ion mode was useful to cluster phase II metabolites. In conclusion, the combined use of molecular networks in positive and negative ion modes is a suitable and robust tool to identify a broad range of metabolites in poisoned patients, as shown in a fatal tramadol-poisoned patient.
    Keywords:  clinical toxicology; high-resolution tandem mass spectrometry; molecular network; tramadol; untargeted metabolomics
    DOI:  https://doi.org/10.3390/metabo12070665
  5. Nat Commun. 2022 Jul 28. 13(1): 4365
      Reproducibility, traceability, and transparency have been long-standing issues for metabolomics data analysis. Multiple tools have been developed, but limitations still exist. Here, we present the tidyMass project ( https://www.tidymass.org/ ), a comprehensive R-based computational framework that can achieve the traceable, shareable, and reproducible workflow needs of data processing and analysis for LC-MS-based untargeted metabolomics. TidyMass is an ecosystem of R packages that share an underlying design philosophy, grammar, and data structure, which provides a comprehensive, reproducible, and object-oriented computational framework. The modular architecture makes tidyMass a highly flexible and extensible tool, which other users can improve and integrate with other tools to customize their own pipeline.
    DOI:  https://doi.org/10.1038/s41467-022-32155-w
  6. IEEE Trans Biomed Eng. 2022 Jul 27. PP
      OBJECTIVE: Mass spectrometry has become the method of choice for single cell analysis due to its high sensitivity of detection and capability in analyzing a large number of metabolites simultaneously. For a long time, an automated and miniaturized system capable of extracting cellular contents from single cells at the pico-liter level for pico-ESI analysis has been lacking.METHODS: This paper presents a first-of-its-kind automated and miniaturized pico-liter extraction system for single-cell MS. The key modules, including imaging, bus controller, and fluidic driving are customized to achieve satisfactory performance at affordable costs, resulting in a miniaturized system movable on a trolley and connectable with the MS. To enable automation, a single cell trapping device, new image-based one-pixel accuracy positioning methods for cells and micropipette, and a surface-tension-based 1-pL accuracy volume control scheme are developed.
    RESULTS: The system is able to control the solvent loading at 1.97±0.05 nL, solvent dispensing at 14-15 pL, and solvent evaporation at 689±48 pL. MS experiments demonstrate a throughput of 20 cells/h.
    CONCLUSION: The system has achieved better performance in consistency (∼21%), sensitivity (∼28%), and success rate (up to 40%) than manual operation.
    SIGNIFICANCE: This automated and miniaturized system lays a solid basis for applying pico-ESI MS analysis in the automated and high-throughput single cell MS analysis, such as single-cell metabolomics and lipidomics.
    DOI:  https://doi.org/10.1109/TBME.2022.3194255
  7. J Chromatogr A. 2022 Aug 16. pii: S0021-9673(22)00498-8. [Epub ahead of print]1677 463305
      In the chiral separation of amino acids, liquid chromatography has been mainly used because of the physicochemical properties of the analytes. To date, only few reports of the use of supercritical fluid chromatography (SFC) for the analysis of chiral amino acids exist, and there is much room for improvement in terms of the number of measurable amino acids, peak shape, and analysis time. In this study, we developed a novel method for the chiral analysis of native amino acids using a system combining SFC and tandem mass spectrometry. Specifically, the separation of amino acid enantiomers was investigated using a CROWNPAK CR-I(+) column with a chiral stationary phase of optically active crown ether. Methanol/water mobile phase with trifluoroacetic acid as a modifier based on supercritical carbon dioxide (CO2) was used. At a low modifier concentration of 30% for the separation of hydrophilic compounds, 18 proteinogenic amino acid enantiomers except glycine and proline were successfully separated with resolution (Rs) = 1.96-33.62 within 6.5 min. In attempt to shorten the analysis time, the flow rate was increased; using a CO2/modifier ratio of 60/40 at a flow rate of 3 mL/min, ultrafast chromatography of 17 amino acid enantiomers, except histidine, was achieved with retention time ≤ 1 min and resolution ≥ 1.5. The developed ultrafast chiral separation method was verified by analyzing a commercially available black vinegar, which detected eight kinds of d-amino acids. The present method has thus confirmed to be successful and practical in terms of both analyte coverage and throughput.
    Keywords:  Amino acid; Chiral separation; Mass spectrometry; Supercritical fluid chromatography; Ultrafast chromatography
    DOI:  https://doi.org/10.1016/j.chroma.2022.463305
  8. Pharmaceuticals (Basel). 2022 Jul 21. pii: 901. [Epub ahead of print]15(7):
      Data-independent acquisition (DIA) based strategies have been explored in recent years for improving quantitative analysis of metabolites. However, the data analysis is challenging for DIA methods as the resulting spectra are highly multiplexed. Thus, the DIA mode requires advanced software analysis to facilitate the data deconvolution process. We proposed a pipeline for quantitative profiling of pharmaceutical drugs and serum metabolites in DIA mode after comparing the results obtained from full-scan, Data-dependent acquisition (DDA) and DIA modes. using open-access software. Pharmaceutical drugs (10) were pooled in healthy human serum and analysed by LC-ESI-QTOF-MS. MS1 full-scan and Data-dependent (MS2) results were used for identification using MS-DIAL software while deconvolution of MS1/MS2 spectra in DIA mode was achieved by using Skyline software. The results of acquisition methods for quantitative analysis validated the remarkable analytical performance of the constructed workflow, proving it to be a sensitive and reproducible pipeline for biological complex fluids.
    Keywords:  MS-DIAL; Perseus; Skyline; data-dependent acquisition; data-independent acquisition; metabolomics
    DOI:  https://doi.org/10.3390/ph15070901
  9. J Mass Spectrom Adv Clin Lab. 2022 Aug;25 36-43
      Introduction: The quantitative measurement of circulating gut bacteria-derived metabolites has increased in recent years due to their associations with health and disease. While much of the previous attention has been placed on metabolites considered as deleterious to health, a shift to the investigation of short-chain fatty acids (SCFAs) as potential health promotors has been observed.Objectives: To develop a simple, high-throughput and quantitative assay to measure gut-derived SCFAs in clinically relevant biofluids using gas chromatography-mass spectrometry (GC-MS).
    Methods: A short (7.5 min) GC-MS assay was optimized for measurement of seven straight- and branched-chain SCFAs and their deuterated isotopes using a wax-based column for analysis without prior derivatization. The assay was validated using routine criteria to assess precision, accuracy, matrix effects, recovery, and extraction reproducibility. Assay applicability was tested in cohorts of healthy individuals and kidney disease patients.
    Results: The assay was demonstrated to be precise, accurate and reproducible with acceptable levels of matrix effect and analyte recovery. Lower limits of detection and quantitation were in the low ng/mL range. An investigation into different blood collection tube chemistries demonstrated that lithium heparin plasma and serum clotting activator tubes are recommended for use in future cross-study comparisons. Kidney disease patient analyses demonstrated variable differences across SCFAs when comparing hemodialysis to earlier stages of chronic kidney disease, demonstrating the suitability of the assay for translation to clinical analyses.
    Conclusion: The assay has been validated and identified as reliable for use in larger-scale studies for the analysis of SCFAs in human plasma and serum.
    Keywords:  Biomarker; Gas chromatography-mass spectrometry; Kidney disease; Short-chain fatty acids; Validation
    DOI:  https://doi.org/10.1016/j.jmsacl.2022.07.002
  10. Int J Mol Sci. 2022 Jul 21. pii: 8021. [Epub ahead of print]23(14):
      In this work, we developed and validated a robust and sensitive method of liquid chromatography with high-resolution mass spectrometry in parallel reaction monitoring (PRM) mode for ST-246 (tecovirimat) quantification in human blood plasma. The method was compared with the multiple reaction monitoring (MRM) technique and showed better selectivity and similar sensitivity in a wider concentration range (10-5000 ng/mL). Within this range, intra- and interday variability of precision and accuracy were within acceptable ranges in accordance with the European Medicines Agency guidelines, and recovery was 87.9-100.6%. Samples were stable at 4 °C within 48 h and at -20 °C up to 3 months. The recovery and matrix effects in the proposed HRMS method were about 5% higher than those reported for the MRM method, but the PRM method showed better accuracy with comparable precision. It was found that the ST-246 concentration shown by the PRM method is approximately 24% higher than the output of the MRM one. Nonetheless, the high selectivity with similar sensitivity, as compared with traditional MRM methods, makes the proposed approach attractive for research and clinical use.
    Keywords:  LC-HRMS; PRM; blood plasma; high-resolution mass spectrometry; tecovirimat
    DOI:  https://doi.org/10.3390/ijms23148021
  11. Metabolites. 2022 Jun 25. pii: 593. [Epub ahead of print]12(7):
      Tracer metabolomics is a powerful technology for the biomedical community to study and understand disease-inflicted metabolic mechanisms. However, the interpretation of tracer metabolomics results is highly technical, as the metabolites' abundances, tracer incorporation and positions on the metabolic map all must be jointly interpreted. The field is currently lacking a structured approach to help less experienced researchers start the interpretation of tracer metabolomics datasets. We propose an approach using an intuitive visualization concept aided by a novel open-source tool, and provide guidelines on how researchers can apply the approach and the visualization tool to their own datasets. Using a showcase experiment, we demonstrate that the visualization approach leads to an intuitive interpretation that can ease researchers into understanding their tracer metabolomics data.
    Keywords:  biochemical pathways; data visualization; tracer metabolomics
    DOI:  https://doi.org/10.3390/metabo12070593
  12. J Mass Spectrom. 2022 Aug;57(8): e4875
      In mass spectrometry imaging (MSI) applications of infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI), an exogenous ice layer is the gold standard for an energy-absorbing matrix. However, the formation of the ice matrix requires additional time and instrument hardware, so glycerol was investigated herein as an alternative to the ice matrix to potentially improve spatial resolution and ionization, while decreasing experiment time. Glycerol solutions of varying concentrations were sprayed over top of rat liver tissue sections for analysis by IR-MALDESI and compared to the typical ice matrix condition. Additionally, we tested if combining the ice matrix and glycerol matrix would further improve analyses. Matrix conditions were evaluated by comparing ion abundance of six lipid species, the laser ablation spot diameter, and number of METASPACE annotations. The ion abundances were also normalized to the volume of tissue ablated to correct for lower abundance values due to less ablated tissue. It was observed that utilizing a 50% glycerol matrix without ice provides improved spatial resolution with lipid abundances and annotations comparable to the ice matrix standard, while decreasing the time required to complete an IR-MALDESI tissue imaging experiment.
    Keywords:  IR-MALDESI; energy-absorbing matrix; glycerol; mass spectrometry imaging
    DOI:  https://doi.org/10.1002/jms.4875
  13. Methods Mol Biol. 2022 ;2539 235-260
      Metabolite profiling provides insights into the metabolic signatures, which themselves are considered as phonotypes closely related to the agronomic and phenotypic traits such as yield, nutritional values, stress resistance, and nutrient use efficiency. GC-MS is a sensitive and high-throughput analytical platform and has been proved to be a vital tool for the analysis of primary metabolism to provide an overview of cellular and organismal metabolic status. The potential of GC-MS metabolite profiling as a tool for detecting metabolic changes in plants grown in a high-throughput plant phenotyping platform was explored. In this chapter, we describe an integrated workflow of semi-targeted GC-high-resolution (HR)-time-of-flight (TOF)-MS metabolomics with both the analytical and computational steps, focusing mainly on the sample preparation, GC-HR-TOF-MS analysis part, and data analysis for plant phenotyping efforts.
    Keywords:  GC-HR-TOF-MS; Metabolomics; Phenomics; Plant phenotyping
    DOI:  https://doi.org/10.1007/978-1-0716-2537-8_19
  14. J Chromatogr A. 2022 Aug 16. pii: S0021-9673(22)00513-1. [Epub ahead of print]1677 463320
      A comparison of positive and negative ionization modes in LC-ESI-MS/MS was carried out for the analysis of derivatized amino acids in 15 different beer samples. 22 free amino acids were derivatized using Diethyl ethoxymethylenemalonate (DEEMM) and their content was determined. When using the DEEMM as derivatization reagent the negative ionization mode provided analytical performance equal to or in some cases even superior to the positive ionization mode. For 6 amino acids (Thr, β-Ala, α-Ala, Met, Val and Orn) the negative mode led to lower LoQ values, while the positive mode offered lower LoQ values for 5 amino acids (Arg, Asp, Glu, GABA, and Pro). The remaining 11 amino acids showed similar LoQ values in both modes. Because of this, negative ionization mode allowed to detect and quantify amino acids such as: β-Alanine, threonine, and ornithine whose concentrations were low in most of the analysed samples. The relative standard deviation (RSD) for the results in both modes were similar. The method's linearity was determined to be in the range of 1 to 130 ppb with r2 > 0.99. Recoveries ranged from 93 to 112%. Negative mode was less affected by matrix effects the main effect was signal enhancement. In contrast, the positive ionization mode suffered from signal enhancement as well as signal suppression.
    Keywords:  Beer; Derivatization; Electrospray; Free amino acids; LC-MS
    DOI:  https://doi.org/10.1016/j.chroma.2022.463320
  15. Redox Biol. 2022 Jul 13. pii: S2213-2317(22)00173-2. [Epub ahead of print]55 102401
      BACKGROUND: Hydrogen sulfide (H2S), a gaseous signaling molecule that impacts multiple physiological processes including aging, is produced via select mammalian enzymes and enteric sulfur-reducing bacteria. H2S research is limited by the lack of an accurate internal standard-containing assay for its quantitation in biological matrices.METHODS: After synthesizing [34S]H2S and developing sample preparation protocols that avoid sulfide contamination with the addition of thiol-containing standards or reducing reagents, we developed a stable isotope-dilution high performance liquid chromatography tandem-mass spectrometry (LC-MS/MS) method for the simultaneous quantification of Total H2S and other abundant thiols (cysteine, homocysteine, glutathione, glutamylcysteine, cysteinylglycine) in biological matrices, conducted a 20-day analytical validation/normal range study, and then both analyzed circulating Total H2S and thiols in plasma from 400 subjects, and within 20 volunteers before and after antibiotic-induced suppression of gut microbiota.
    RESULTS: Using the new assay, all analytes showed minimal interference, no carryover, and excellent intra- and inter-day reproducibility (≤7.6%, and ≤12.7%, respectively), linearity (r2 > 0.997), recovery (90.9%-110%) and stability (90.0%-100.5%). Only circulating Total H2S levels showed significant age-associated reductions in both males and females (p < 0.001), and a marked reduction following gut microbiota suppression (mean 33.8 ± 17.7%, p < 0.001), with large variations in gut microbiota contribution among subjects (range 6.0-66.7% reduction with antibiotics).
    CONCLUSIONS: A stable-isotope-dilution LC-MS/MS method is presented for the simultaneous quantification of Total H2S and multiple thiols in biological matrices. We then use this assay panel to show a striking age-related decline and gut microbiota contribution to circulating Total H2S levels in humans.
    Keywords:  Aging; Cysteine; Cysteinylglycine; Glutathione; Gut microbiota; Homocysteine; Hydrogen sulfide; Liquid chromatography tandem mass spectrometry; Microbiome; Plasma thiol; γ-glutamylcysteine
    DOI:  https://doi.org/10.1016/j.redox.2022.102401
  16. Metabolites. 2022 Jul 23. pii: 678. [Epub ahead of print]12(8):
      Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021-the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.
    Keywords:  NMR spectroscopy; advances; imaging; metabolomics; review
    DOI:  https://doi.org/10.3390/metabo12080678
  17. Biomed Chromatogr. 2022 Jul 27. e5467
      Navtemadlin is an orally bioavailable small molecule that blocks the protein-protein interaction between MDM2 and the tumor suppressor protein p53, leading to p53-mediated cell cycle arrest and apoptosis. It is being evaluated in clinical trials for a variety of malignancies, both as a single agent and in combination regimens. A sensitive, robust LC-MS/MS method was developed to quantitate navtemadlin in plasma, and this method was also validated using brain tissue homogenate. Sample preparation involved protein precipitation of plasma or brain tissue homogenate using acetonitrile. Navtemadlin, navtemadlin glucuronide, and the internal standard, D6 -navtemadlin, were separated from microsomal incubation extracts using gradient elution and a Zorbax XDB C18 column. Analytes were detected using a SCIEX 5500 triple quadrupole mass spectrometer in positive electrospray ionization mode. The assay range of 1-1,000 ng/mL was shown to be accurate (96.1-102.0% and 95.7-104%) and precise (CV ≤ 10.6% and ≤ 6.6%) in plasma and brain tissue homogenate, respectively. An 8,000 ng/mL navtemadlin sample diluted 1:10 (v/v) with plasma was also accurately quantitated. Navtemadlin has been stable in frozen plasma at -70°C for at least 20 months. This validated LC-MS/MS method was applied to determine navtemadlin concentrations in plasma and brain tissue samples from two separate patients receiving 120 mg/day navtemadlin on protocol ABTC1604.
    Keywords:  Assay; Navtemadlin; Tandem mass spectrometry; Validation
    DOI:  https://doi.org/10.1002/bmc.5467
  18. Clin Chim Acta. 2022 Jul 20. pii: S0009-8981(22)01238-4. [Epub ahead of print]534 115-127
      A sensitive and rapid liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for the simultaneous determination of tryptophan (Trp) and ten metabolites of kynurenine pathway, including kynurenine (Kyn), 3-hydroxy-kynurenine (3-HK), kynurenic acid (KA), xanthurenic acid (XA), 3-Hydroxy-anthranilic acid (3-HANA), quinolinic acid (QA), nicotinic acid mononucleotide (NaMN), picolinic acid (Pic), nicotinamide (NAM) and nicotinic acid (NA) in both plasma and urine. This LC-MS/MS method was used to predict the occurrence of acute kidney injury (AKI) in a cohort of patients with cardiac surgery under cardiopulmonary bypass (CPB). Urinary concentrations of Pic, as well as Pic to Trp and Pic to 3-HANA ratios were highly predictive of an AKI episode the week after CPB, indicating that Pic could be a predictive biomarker of AKI. Thus, monitoring the kynurenine pathway activity with this LC-MS/MS method is a clinically relevant tool to identify new biomarkers of kidney injury.
    Keywords:  Acute kidney injury; Kynurenic acid; Kynurenine pathway; Mass spectrometry; Picolinic acid; Quinolinic acid; Tryptophan
    DOI:  https://doi.org/10.1016/j.cca.2022.07.009
  19. J Chem Inf Model. 2022 Jul 29.
      Tandem mass spectrometry (MS/MS) is a primary tool for the identification of small molecules and metabolites where resultant spectra are most commonly identified by matching them with spectra in MS/MS reference libraries. The high degree of variability in MS/MS spectrum acquisition techniques and parameters creates a significant challenge for building standardized reference libraries. Here we present a method to improve the usefulness of existing MS/MS libraries by augmenting available experimental spectra data sets with statistically interpolated spectra at unreported collision energies. We find that highly accurate spectral approximations can be interpolated from as few as three experimental spectra and that the interpolated spectra will be consistent with true spectra gathered from the same instrument as the experimental spectra. Supplementing existing spectral databases with interpolated spectra yields consistent improvements to identification accuracy on a range of instruments and precursor types. Applying this method yields significant improvements (∼10% more spectra correctly identified) on large data sets (2000-10 000 spectra), indicating this is a quick yet adept tool for improving spectral matching in situations where available reference libraries are not yet sufficient. We also find improvements of matching spectra across instrument types (between an Agilent Q-TOF and an Orbitrap Elite), at high collision energies (50-90 eV), and with smaller data sets available through MassBank.
    DOI:  https://doi.org/10.1021/acs.jcim.2c00620
  20. Anal Bioanal Chem. 2022 Jul 26.
      Diabetic nephropathy (DN) is the leading cause of end-stage renal disease. Limitations in current diagnosis and screening methods have sparked a search for more specific and conclusive biomarkers. Hyperglycemic conditions generate a plethora of harmful molecules in circulation and within tissues. Oxidative stress generates reactive α-dicarbonyls and β-unsaturated hydroxyhexenals, which react with proteins to form advanced glycation end products. Mass spectrometry imaging (MSI) enables the detection and spatial localization of molecules in biological tissue sections. Here, for the first time, the localization and semiquantitative analysis of "reactive aldehydes" (RAs) 4-hydroxyhexenal (4-HHE), 4-hydroxynonenal (4-HNE), and 4-oxo-2-nonenal (4-ONE) in the kidney tissues of a diabetic mouse model is presented. Ionization efficiency was enhanced through on-tissue chemical derivatization (OTCD) using Girard's reagent T (GT), forming positively charged hydrazone derivatives. MSI analysis was performed using matrix-assisted laser desorption ionization (MALDI) coupled with Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR). RA levels were elevated in diabetic kidney tissues compared to lean controls and localized throughout the kidney sections at a spatial resolution of 100 µm. This was confirmed by liquid extraction surface analysis-MSI (LESA-MSI) and liquid chromatography-mass spectrometry (LC-MS). This method identified β-unsaturated aldehydes as "potential" biomarkers of DN and demonstrated the capability of OTCD-MSI for detection and localization of poorly ionizable molecules by adapting existing chemical derivatization methods. Untargeted exploratory distribution analysis of some precursor lipids was also assessed using MALDI-FT-ICR-MSI.
    Keywords:  Diabetic nephropathy; Mass spectrometry imaging; Matrix-assisted laser desorption ionization; On-tissue chemical derivatization; Reactive aldehydes
    DOI:  https://doi.org/10.1007/s00216-022-04229-7
  21. Plant Cell Environ. 2022 Jul 28.
      Plant metabolomics has been used widely in plant physiology, in particular to analyse metabolic responses to environmental parameters. Derivatization (via trimethylsilylation and methoximation) followed by GC-MS metabolic profiling is a major technique to quantify low molecular weight, common metabolites of primary carbon, sulphur and nitrogen metabolism. There are now excellent opportunities for new generation analyses, using high resolution, exact mass GC-MS spectrometers that are progressively becoming relatively cheap. However, exact mass GC-MS analyses for routine metabolic profiling are not common, since there is no dedicated available database. Also, exact mass GC-MS is usually dedicated to structural resolution of targeted secondary metabolites. Here, we present a curated database for exact mass metabolic profiling (made of 336 analytes, 1,064 characteristic exact mass fragments) focused on molecules of primary metabolism. We show advantages of exact mass analyses, in particular to resolve isotopic patterns, localise S-containing metabolites, and avoid identification errors when analytes have common nominal mass peaks in their spectrum. We provide a practical example using leaves of different Arabidopsis ecotypes and show how exact mass GC-MS analysis can be applied to plant samples and identify metabolic profiles. This article is protected by copyright. All rights reserved.
    Keywords:  database; high resolution; isotope; mass spectrometry; metabolomics
    DOI:  https://doi.org/10.1111/pce.14407
  22. Photochem Photobiol Sci. 2022 Jul 29.
      BACKGROUND: UVB absorption by 7-dehydrocholesterol (7DHC) in the skin triggers the production of vitamin D and its metabolites, which maintain calcium homeostasis. Detection and measurement of 7DHC in skin using modern liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques have been lacking, yet there is need for such a technique to provide more information on 7DHC concentration and its UVB responses in human skin.OBJECTIVES: To develop and validate a reliable method to measure 7DHC concentration in skin.
    METHODS: Human skin punch biopsies of 5 mm diameter obtained through the Manchester Skin Health Biobank were utilised. 7DHC was extracted with ethyl acetate:methanol 1:1 (v/v) and derivatised using 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD), to allow for improved ionisation of 7DHC through Electrospray Ionisation Mass Spectrometry (ESI-MS). Solid supported liquid extraction (SLE) was also employed to allow the removal of larger lipids from 7DHC and minimise potential matrix effects.
    RESULTS: The LC-MS/MS assay satisfied International Council for Harmonisation research standards for method validation. Calibration curve was linear with a typical r2 of 0.997, coefficient of variation was 11.1% and 4.32% for inter-assay and intra-assay imprecision, respectively. Lower limit of quantification was 1.6 µg/g and upper limit of quantification was 100 µg/g, SLE recovery of 7DHC was on average 91.4%.
    CONCLUSIONS: We have developed a robust, precise and accurate assay for the detection and quantification of 7DHC in small samples of human skin (0.2 cm2 surface area). This novel method of extraction and quantification will be valuable to future vitamin D photobiology research.
    Keywords:  7-Dehydrocholesterol; High-performance liquid chromatography (HPLC); Photobiology; Skin; Tandem mass spectrometry (MS/MS); Vitamin D
    DOI:  https://doi.org/10.1007/s43630-022-00274-4
  23. Se Pu. 2022 Aug;40(8): 746-752
      Rice is a major dietary staple in many communities owing to its high nutritional value and characteristic aroma. Oryzanol, a mixture of ferulic acid esters of triterpene alcohols and phytosterols, is a major group of phytochemicals found in rice. 24-Methylenecycloartanyl ferulate (24MCA-FA), cycloartenyl ferulate (CA-FA), and campestanyl ferulate (Camp-FA) have been identified as the primary components of oryzanol. At present, for the quantification of oryzanol in rice and rice products, UV spectroscopy or high performance liquid chromatography (HPLC) is widely employed. However, these methods cannot differentiate individual oryzanols, resulting in higher measured values. To extract oryzanol, methods including liquid-liquid extraction, acidulation extraction, and direct solvent extraction have been typically employed, as they do not require specific extraction instrumentation. However, there has been no systematic study on the direct solvent extraction and purification conditions of oryzanol in rice. In this study, a rapid and accurate analytical method based on HPLC-MS/MS and mixed-mode anion exchange (MAX) solid-phase extraction was established to determine the content of three oryzanols (24MCA-FA, CA-FA, and Camp-FA) in rice. The MS parameters, such as the collision energy of three ion pairs of each oryzanol, were optimized. Further, the chromatographic separation conditions and response intensities of the oryzanols in different mobile phases were compared. The effects of different pretreatment conditions on the extraction efficiency of the three oryzanols in rice samples and different purification conditions on their recovery were investigated. Combined with the external standard method, the three oryzanols in rice were successfully quantified. The results showed that the baseline separation and highest response for the three oryzanols were achieved using the Agilent Eclipse XDB-C8 chromatographic column (150 mm×2.1 mm, 3.5 μm) when methanol∶ acetonitrile in a 1∶1 ratio (v/v) and an aqueous solution of 5 mmol/L ammonium acetate were used as the mobile phases for gradient elution. The extraction rate of the three oryzanols was highest when using 2.5 g of the sample, adding 20 mL of methanol, soaking for 12 h, ultrasonicating at a temperature of 40 ℃ for 20 min, and centrifuging the extracted solutions at 4500 r/min for 10 min. The samples were purified by MAX, and the sample matrix effect was found to be lesser than 1.6%-10.8%. Under the optimum conditions, the calibration curves of the three oryzanols showed good linearity (correlation coefficients r2≥0.9983) within their respective linear ranges. The limits of detection were in the range of 0.5-1.0 μg/L, and limits of quantification were in the range of 2.0-3.5 μg/L. Accuracy and precision experiments were performed on rice samples spiked at three levels (2, 5, and 10 times the background concentration), with three replicates. The average recoveries of the three oryzanols ranged from 86.1% to 110.6%, and the relative standard deviations (RSDs) were between 0.9% and 3.2%. The method showed good performance when applied to the analysis of real samples. In conclusion, the developed method can determine the content of the three oryzanols in rice quickly and accurately, and can be used for the subsequent measurement of oryzanol compounds in rice.
    Keywords:  high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS); mixed-mode solid-phase extraction; oryzanol; rice
    DOI:  https://doi.org/10.3724/SP.J.1123.2021.12016
  24. Biomed Chromatogr. 2022 Jul 29. e54772
      A fast, uncomplicated, sensitive, and fully validated high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method has been developed for estimating L-amino acids in the plasma of schizophrenic patients. The gradient-elution chromatographic method was implemented with the Luna® PFP column (50 × 2.0 mm, 5-μm), and a mobile phase of 0.1% formic acid in water and methanol was used. The intraday and interday variability of the L-amino acids were less than 13.11%, and their accuracy ranged from 85.14 - 116.75% at the quality control levels and the lower limit of quantification (LLOQ) ranged from 2.5 - 15 nM. The extraction efficiency (apparent recovery) of amino acids from healthy plasma was employed by spiking the plasma with standard amino acids at the quality control levels. Their percentage recoveries ranged from 80.4% to 119.94%. Our method has a short run time and fast sample preparation compared with existing methods, which are suffered from long preparative steps and/or time-consuming analysis, restricted reagents, and suboptimal performance characteristics presently available technologies. Therefore, the proposed HPLC-MS/MS method was effectively applied for monitoring the L-amino acids in the plasma of schizophrenic patients and healthy volunteers.
    Keywords:  Amino acids; Liquid chromatography-tandem mass spectrometry; Metabolic disorders; Schizophrenia
    DOI:  https://doi.org/10.1002/bmc.5472
  25. Metabolites. 2022 Jul 21. pii: 671. [Epub ahead of print]12(7):
      The analysis of high-throughput metabolomics mass spectrometry data across multiple biological sample types (biospecimens) poses challenges due to missing data. During differential abundance analysis, dropping samples with missing values can lead to severe loss of data as well as biased results in group comparisons and effect size estimates. However, the imputation of missing data (the process of replacing missing data with estimated values such as a mean) may compromise the inherent intra-subject correlation of a metabolite across multiple biospecimens from the same subject, which in turn may compromise the efficacy of the statistical analysis of differential metabolites in biomarker discovery. We investigated imputation strategies when considering multiple biospecimens from the same subject. We compared a novel, but simple, approach that consists of combining the two biospecimen data matrices (rows and columns of subjects and metabolites) and imputes the two biospecimen data matrices together to an approach that imputes each biospecimen data matrix separately. We then compared the bias in the estimation of the intra-subject multi-specimen correlation and its effects on the validity of statistical significance tests between two approaches. The combined approach to multi-biospecimen studies has not been evaluated previously even though it is intuitive and easy to implement. We examine these two approaches for five imputation methods: random forest, k nearest neighbor, expectation-maximization with bootstrap, quantile regression, and half the minimum observed value. Combining the biospecimen data matrices for imputation did not greatly increase efficacy in conserving the correlation structure or improving accuracy in the statistical conclusions for most of the methods examined. Random forest tended to outperform the other methods in all performance metrics, except specificity.
    Keywords:  imputation; mass spectrometry; metabolomics; missing data; multi-biospecimen; multivariate analysis
    DOI:  https://doi.org/10.3390/metabo12070671
  26. Metabolites. 2022 Jun 23. pii: 583. [Epub ahead of print]12(7):
      Bile acids are a key mediator of the molecular microbiome-host interaction, and various mass spectrometry-based assays have been developed in the recent decade to quantify a wide range of bile acids. We compare existing methodologies to harmonize them. Methodology for absolute quantification of bile acids from six laboratories in Europe were compared for the quantification of the primary bile acids cholic acid (CA) and chenodeoxycholic acid (CDCA) and conjugated products glycocholic acid (GCA) and taurocholic acid (TCA). For the bacterially modified secondary bile acids, the quantification of deoxycholic acid (DCA) and lithocholic acid (LCA) was compared. For the murine bile acids, we used the primary muricholic acids (α-MCA and, β-MCA) and the intestinally produced secondary bile acid muricholic (ω-MCA). The standards were spiked into methanol:water (1:1) mix as well as in human and murine serum at either low concentration range (150-3000 nM) or high concentration range (1500-40,000 nM). The precision was better for higher concentrations. Measurements for the hydrophobic unconjugated bile acids LCA and ω-MCA were the most challenging. The quality assessments were generally very similar, and the comprehensive analyses demonstrated that data from chosen locations can be used for comparisons between studies.
    Keywords:  LC-MS/MS; absolute quantification; bile acids; human serum; murine serum; ring trial
    DOI:  https://doi.org/10.3390/metabo12070583
  27. Methods Enzymol. 2022 ;pii: S0076-6879(21)00452-3. [Epub ahead of print]670 285-309
      Apocarotenoids (APOs) are a class of carotenoid oxidation products with high structural and functional diversity. Apart from serving as precursors of phytohormones, fungal pheromones and vitamin A, several APOs act as signaling molecules involved in stress response and growth as regulators in plants. To comprehensively profile plant APOs, we established an improved ultra-high performance liquid chromatography-hybrid quadrupole-Orbitrap mass spectrometer (UHPLC-Q-Orbitrap MS) analytical platform. The improved APO analytical platform consists of an optimized sequential APO sample preparation and multiple UHPLC-MS detection methods and was successfully used to identify and quantify multiple subclasses of APOs from tomato fruits. By integrating ultrasound-assisted extraction, solid phase extraction, and chemical derivatization, the improved sequential APOs sample preparation facilitates the simultaneous preparation of different subclasses of APOs from plant materials. In addition, multiple UHPLC-MS detection methods enables high throughput analysis of APOs. Application of this analytical strategy can make important contributions to understanding the function of these compounds and significantly facilitate the elucidation of plant APO metabolism.
    Keywords:  Apocarotenoids; Diapocarotenals; Glycosylated apocarotenoids; Tomato; Ultra-high performance liquid chromatography-mass spectrometry
    DOI:  https://doi.org/10.1016/bs.mie.2021.10.012
  28. Se Pu. 2022 Aug;40(8): 704-711
      This study aimed to establish a method for the rapid determination of trace estrogens in honey samples by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) using imine-linked porous covalent organic framework material (IL-COF-1) as the adsorbent for solid-phase extraction (SPE). Estradiol (E1), diethylstilbestrol (DES), estriol (E3), β-estradiol (E2), and ethinylestradiol (EE2) were used as the target analytes. A single factor optimization method was performed to optimize the extraction effect by adding estrogens to honey samples. The optimal conditions were as follows. A total of 30 mg IL-COF-1 was filled in the SPE column. The sample pH was adjusted to 7. The sample was loaded at a flow rate of 3 mL/min and eluted with 5 mL of a 1% (v/v) NH3·H2O-methanol solution. The flow rate of the eluent was 0.4 mL/min. NaCl was not added in the extraction process. HPLC coupled to electrospray ionization and triple quadrupole mass spectrometry was introduced to quantify the estrogens in the extracts. The estrogens were separated on a Thermo Fisher Scientific C18 analytical column (100 mm×2.1 mm, 5 μm). Acetonitrile and 5 mmol/L ammonium acetate solution were used as the mobile phases for gradient elution. The column temperature was set at 40 ℃, and the autosampler temperature was maintained at 10 ℃. The rapid qualitative and quantitative analysis of the five estrogens in the honey samples was operated under multiple reaction monitoring mode in a negative electrospray ion source mode. IL-COF-1 prepared in six batches was used as a filler for the SPE column. The relative standard deviations (RSDs) of the recoveries of the estrogens among different batches were 5.2%-9.1%. The reusability of IL-COF-1 material was assessed. After six SPE cycles on the same solid-phase extraction column, the RSDs of the estrogen recoveries were 2.5%-6.1%, indicating that IL-COF-1 has good reusability. The recoveries of estrogens obtained on an IL-COF-1 solid-phase extraction column within 6 days (tested once a day) were 95.1%-107.4%, and the RSDs were 6.2%-8.9%. These results confirmed that the SPE filler had good stability. The method validation results showed that the linear detection ranges were 1-500 ng/g for E3, E2, and EE2, and 0.1-100 ng/g for E1 and DES withe the correlation coefficients of 0.9934-0.9972. The limits of detection (LODs, S/N=3) were 0.01-0.30 ng/g, and the limits of quantification (LOQs, S/N=10) were 0.05-0.95 ng/g. Five estrogens were added (50 ng/g) for the repeated experiments. The RSDs of the intra-day precision were 3.2%-6.6%. The RSDs of the inter-day precision were 4.2%-7.9%. This method was applied to determine the estrogen levels in four honey samples, and no estrogen was found. The recoveries of the five estrogens in sample spiked at three levels including low, middle, and high levels were investigated, and satisfactory recoveries (80.1%-115.2%) were obtained. The SPE-HPLC-MS/MS method based on IL-COF-1 is rapid, accurate, and sensitive, making it suitable for analyzing and detecting estrogen in honey. Further exploration of the use of IL-COF-1 for the extraction processes is in progress.
    Keywords:  covalent organic framework; estrogen; honey; liquid chromatography (LC); solid-phase extraction (SPE); sorbent; tandem mass spectrometry (MS/MS)
    DOI:  https://doi.org/10.3724/SP.J.1123.2022.03017
  29. Toxins (Basel). 2022 Jun 24. pii: 432. [Epub ahead of print]14(7):
      Ochratoxin A (OTA) is one of the major mycotoxins causing severe effects on the health of humans and animals. Ochratoxin alpha (OTα) is a metabolite of OTA, which is produced through microbial or enzymatic hydrolysis, and one of the preferred routes of OTA detoxification. The methods described here are applicable for the extraction and quantification of OTA and OTα in several pig and poultry matrices such as feed, feces/excreta, urine, plasma, dried blood spots, and tissue samples such as liver, kidney, muscle, skin, and fat. The samples are homogenized and extracted. Extraction is either based on a stepwise extraction using ethyl acetate/sodium hydrogencarbonate/ethyl acetate or an acetonitrile/water mixture. Quantitative analysis is based on reversed-phase liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Method validation was successfully performed and the linearity, limit of quantification, accuracy, precision as well as the stability of the samples, were evaluated. The analyte recovery of the spiked samples was between 80 and 120% (80-150% for spiked concentrations ≤ 1 ng/g or ng/mL) and the relative standard deviation was ≤ 15%. Therefore, we provide a toolbox for the extraction and quantification of OTA and OTα in all relevant pig and poultry matrices.
    Keywords:  chicken matrices; liquid chromatography; method validation; mycotoxin; swine matrices; tandem mass spectrometry
    DOI:  https://doi.org/10.3390/toxins14070432
  30. J Chromatogr A. 2022 Jul 16. pii: S0021-9673(22)00541-6. [Epub ahead of print]1678 463348
      Analytical derivatization is a technique that alters the structure of an analyte and produces a product more suitable for analysis. While this process can be time-consuming and add reagents to the procedure, it can also facilitate the isolation of the analyte(s), enhance analytes' stability, improve separation and sensitivity, and reduce matrix interferences. Since derivatization is a functional group analysis, it improves selectivity by separating reactive from neutral compounds during sample preparation. This technique introduces detector-orientated tags into analytes that lack suitable physicochemical properties for detection at low concentrations. Notably, many regulatory bodies, especially those in the environmental field, require these characteristics in analytical methods. This review focuses on note-worthy analytical derivatization methods employed in environmental analyses with functional groups, phenol, carboxylic acid, aldehyde, ketone, and thiol in aqueous, soil, and atmospheric sample matrices. Both advantages and disadvantages of analytical derivatization techniques are discussed. In addition, we discuss the future directions of analytical derivatization methods in environmental analysis and the potential challenges.
    Keywords:  Analytical derivatization; Environmental analysis; Sample preparation; Solid-phase analytical derivatization
    DOI:  https://doi.org/10.1016/j.chroma.2022.463348
  31. Metabolites. 2022 Jun 23. pii: 585. [Epub ahead of print]12(7):
      Flux balance analysis (FBA) is a key method for the constraint-based analysis of metabolic networks. A technical problem may occur in FBA when known (e.g., measured) fluxes of certain reactions are integrated into an FBA scenario rendering the underlying linear program (LP) infeasible, for example, due to inconsistencies between some of the measured fluxes causing a violation of the steady-state or other constraints. Here, we present and compare two methods, one based on an LP and one on a quadratic program (QP), to find minimal corrections for the given flux values so that the FBA problem becomes feasible. We provide a general guide on how to treat infeasible FBA systems in practice and discuss relevant examples of potentially infeasible scenarios in core and genome-scale metabolic models. Finally, we also highlight and clarify the relationships to classical metabolic flux analysis, where solely algebraic approaches are used to compute unknown metabolic rates from measured fluxes and to balance infeasible flux scenarios.
    Keywords:  Escherichia coli; constraint-based modeling; mass balances; metabolic flux analysis; quadratic programming; weighted least-squares
    DOI:  https://doi.org/10.3390/metabo12070585
  32. Methods Enzymol. 2022 ;pii: S0076-6879(22)00112-4. [Epub ahead of print]670 423-457
      Accurate and sensitive methods to quantify carotenoids in blood plasma/serum are the basis for assessing carotenoid intake and associating physiological effects. This chapter introduces carotenoid chemistry, an overview of carotenoid food sources, and current knowledge of carotenoid absorption and metabolism, along with factors that affect these processes. We also detail a commonly used method to extract plasma/serum carotenoids using liquid-liquid extraction and analysis by high performance liquid chromatography coupled with diode array detection (HPLC-DAD). A spreadsheet to aid in this quantitative analysis can be found at www.github.com/CooperstoneLab/carotenoid-analysis.
    Keywords:  Blood; Carotenoids; HPLC; Liquid-liquid extraction; Plasma; Quantitative analysis; Serum
    DOI:  https://doi.org/10.1016/bs.mie.2022.03.021
  33. Molecules. 2022 Jul 16. pii: 4540. [Epub ahead of print]27(14):
      A CZE-MS method was developed for the determination of several phenolic compounds (phenolic acids, flavonoids). Since the analysis of these components necessitates the application of basic conditions for CZE separation and negative ionization mode for MS detection, the simplest choice was to use 0.5 M NH4OH and IPA:water (1:1 v/v%) as the background electrolyte and sheath liquid, respectively. The LOD values ranged between 0.004-1.9 mg/L showing that there are relatively large differences in the ionization (and chemical) features of these compounds. The precision data were better than 0.75 RSD% for migration times and were between 5-8 RSD% for peak areas. In order to test the applicability of the developed method, a honey sample was analyzed.
    Keywords:  capillary zone electrophoresis; honey; mass spectrometry; phenolic compounds
    DOI:  https://doi.org/10.3390/molecules27144540
  34. Molecules. 2022 Jul 10. pii: 4417. [Epub ahead of print]27(14):
      The 8-iso-prostaglandin F2α (8-iso-PGF2α) biomarker is used as the gold standard for tracing lipid oxidative stress in vivo. The analysis of urinary 8-iso-PGF2α is challenging when dealing with trace amounts of 8-iso-PGF2α and the complexity of urine matrixes. A packed-fiber solid-phase extraction (PFSPE)-coupled with HPLC-MS/MS-method, based on polystyrene (PS)-electrospun nanofibers, was developed for the specific determination of 8-iso-PGF2α in urine and compared with other newly developed LC-MS/MS methods. The method, which simultaneously processed 12 samples within 5 min on a self-made semi-automatic array solid-phase extraction processor, was the first to introduce PS-electrospun nanofibers as an adsorbent for the extraction of 8-iso-PGF2α and was successfully applied to real urine samples. After optimizing the PFSPE conditions, good linearity in the range of 0.05-5 ng/mL with R2 &gt; 0.9996 and a satisfactory limit of detection of 0.015 ng/mL were obtained, with good intraday and interday precision (RSD &lt; 10%) and recoveries of 95.3-103.8%. This feasible method is expected to be used for the batch quantitative analysis of urinary 8-iso-PGF2α.
    Keywords:  8-iso-prostaglandin F2α (8-iso-PGF2α); HPLC-MS/MS; electrospun nanofibers; oxidative stress; solid phase extraction; urine
    DOI:  https://doi.org/10.3390/molecules27144417
  35. Metabolites. 2022 Jul 11. pii: 633. [Epub ahead of print]12(7):
      A simple, sensitive, and reliable quantification and identification method was developed and validated for simultaneous analysis of 58 bile acids (BAs) in human and rodent (mouse and rat) fecal samples. The method involves an extraction step with a 5% ammonium-ethanol aqueous solution; the BAs were quantified by high-resolution mass spectrometry (ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry, UPLC-Q-TOF). The recoveries were 80.05-120.83%, with coefficient variations (CVs) of 0.01-9.82% for three biological species. The limits of detection (LODs) were in the range of 0.01-0.24 μg/kg, and the limits of quantification (LOQs) ranged from 0.03 to 0.81 μg/kg. In addition, the analytical method was used to identify and quantify BAs in end-stage renal disease (ESRD) patients, C57BL/6 mice, and Sprague-Dawley (SD) rats. The fecal BA profile and analysis of BA indices in these samples provide valuable information for further BA metabolic disorder research.
    Keywords:  BA indices; UPLC–Q-TOF; bile acids; isomerization; sulfation; wet feces
    DOI:  https://doi.org/10.3390/metabo12070633
  36. Anal Biochem. 2022 Jul 20. pii: S0003-2697(22)00286-X. [Epub ahead of print] 114826
      NMR metabolomics has inherent capabilities for studying biofluids, such as reproducibility, minimal sample preparation, non-destructiveness, and molecular structure elucidation; however, reliable quantitation of metabolites is still a challenge because of the complex matrix of the samples. The serum is one of the most common samples in clinical studies but possibly the most difficult for NMR analysis because of the high content of proteins, which hampers the detection and quantification of metabolites. Different processes for protein removal, such as ultrafiltration and precipitation, have been proposed, but require sample manipulation, increase time and cost, and possibly lead to loss of information in the metabolic profile. Alternative methods that rely on filtering protein signals by NMR pulse sequencing are commonly used, but standardisation of acquisition parameters and spectra calibration is far from being reached. The present technical note is a critical assessment of the sparsely suggested calibrants, pulse sequences and acquisition parameters toward an optimised combination of the three for accurate and reproducible quantification of metabolites in intact serum.
    DOI:  https://doi.org/10.1016/j.ab.2022.114826
  37. Metabolites. 2022 Jul 26. pii: 694. [Epub ahead of print]12(8):
      Compound identification is a critical step in untargeted metabolomics. Its most important procedure is to calculate the similarity between experimental mass spectra and either predicted mass spectra or mass spectra in a mass spectral library. Unlike the continuous similarity measures, there is no study to assess the performance of binary similarity measures in compound identification, even though the well-known Jaccard similarity measure has been widely used without proper evaluation. The objective of this study is thus to evaluate the performance of binary similarity measures for compound identification in untargeted metabolomics. Fifteen binary similarity measures, including the well-known Jaccard, Dice, Sokal-Sneath, Cosine, and Simpson measures, were selected to assess their performance in compound identification. using both electron ionization (EI) and electrospray ionization (ESI) mass spectra. Our theoretical evaluations show that the accuracy of the compound identification was exactly the same between the Jaccard, Dice, 3W-Jaccard, Sokal-Sneath, and Kulczynski measures, between the Cosine and Hellinger measures, and between the McConnaughey and Driver-Kroeber measures, which were practically confirmed using mass spectra libraries. From the mass spectrum-based evaluation, we observed that the best performing similarity measures were the McConnaughey and Driver-Kroeber measures for EI mass spectra and the Cosine and Hellinger measures for ESI mass spectra. The most robust similarity measure was the Fager-McGowan measure, the second-best performing similarity measure in both EI and ESI mass spectra.
    Keywords:  EI; ESI; binary similarity measure; compound identification; mass spectrometry; untargeted metabolomics
    DOI:  https://doi.org/10.3390/metabo12080694
  38. Ann Rev Mar Sci. 2022 Jul 25.
      Lipids are structurally diverse biomolecules that serve multiple roles in cells. As such, they are used as biomarkers in the modern ocean and as paleoproxies to explore the geological past. Here, I review lipid geochemistry, biosynthesis, and compartmentalization; the varied uses of lipids as biomarkers; and the evolution of analytical techniques used to measure and characterize lipids. Advancements in high-resolution accurate-mass mass spectrometry have revolutionized the lipidomic and metabolomic fields, both of which are quickly being integrated into marine meta-omic studies. Lipidomics allows us to analyze tens of thousands of features, providing an open analytical window and the ability to quantify unknown compounds that can be structurally elucidated later. However, lipidome annotation is not a trivial matter and represents one of the biggest challenges for oceanographers, owing in part to the lack of marine lipids in current in silico databases and data repositories. A case study reveals the gaps in our knowledge and open opportunities to answer fundamental questions about molecular-level control of chemical reactions and global-scale patterns in the lipidscape. Expected final online publication date for the Annual Review of Marine Science, Volume 15 is January 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
    DOI:  https://doi.org/10.1146/annurev-marine-040422-094104