bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2022–10–02
23 papers selected by
Sofia Costa, Matterworks



  1. Anal Chim Acta. 2022 Oct 09. pii: S0003-2670(22)00923-0. [Epub ahead of print]1229 340352
      Covalent or non-covalent heterogeneous multimerization of molecules associated with extracts from biological samples analyzed via LC-MS are quite difficult to recognize/annotate and therefore the prevalence of multimerization remains largely unknown. In this study, we utilized 13C labeled and unlabeled Pichia pastoris extracts to recognize heterogeneous multimers. More specifically, between 0.8% and 1.5% of the biologically-derived features detected in our experiments were confirmed to be heteromers, about half of which we could successfully annotate with monomeric partners. Interestingly, we found specific chemical classes such as nucleotides to disproportionately contribute to heteroadducts. Furthermore, we compiled these compounds into the first MS/MS library that included data from heteromultimers to provide a starting point for other labs to improve the annotation of such ions in other metabolomics data sets. Then, the detected heteromers were also searched in publicly accessible LC-MS datasets available in Metabolights, Metabolomics WB and GNPS/MassIVE to demonstrate that these newly annotated ions are also relevant to other public datasets. Furthermore, in additional datasets (Triticum aestivum, Fusarium graminearum, and Trichoderma reesei) our developed workflow also detected 0.5%-4.9% of metabolite features to originate from heterodimers, demonstrating heteroadducts to be present in metabolomics studies at a low percentage.
    Keywords:  Adduct; Annotation; Identification; Liquid chromatography; Mass spectrometry; Metabolomics
    DOI:  https://doi.org/10.1016/j.aca.2022.340352
  2. Front Mol Biosci. 2022 ;9 952149
      Untargeted metabolomics aims at measuring the entire set of metabolites in a wide range of biological samples. However, due to the high chemical diversity of metabolites that range from small to large and more complex molecules (i.e., amino acids/carbohydrates vs. phospholipids/gangliosides), the identification and characterization of the metabolome remain a major bottleneck. The first step of this process consists of searching the experimental monoisotopic mass against databases, thus resulting in a highly redundant/complex list of candidates. Despite the progress in this area, researchers are still forced to manually explore the resulting table in order to prioritize the most likely identifications for further biological interpretation or confirmation with standards. Here, we present TurboPutative (https://proteomics.cnic.es/TurboPutative/), a flexible and user-friendly web-based platform composed of four modules (Tagger, REname, RowMerger, and TPMetrics) that streamlines data handling, classification, and interpretability of untargeted LC-MS-based metabolomics data. Tagger classifies the different compounds and provides preliminary insights into the biological system studied. REname improves putative annotation handling and visualization, allowing the recognition of isomers and equivalent compounds and redundant data removal. RowMerger reduces the dataset size, facilitating the manual comparison among annotations. Finally, TPMetrics combines different datasets with feature intensity and relevant information for the researcher and calculates a score based on adduct probability and feature correlations, facilitating further identification, assessment, and interpretation of the results. The TurboPutative web application allows researchers in the metabolomics field that are dealing with massive datasets containing multiple putative annotations to reduce the number of these entries by 80%-90%, thus facilitating the extrapolation of biological knowledge and improving metabolite prioritization for subsequent pathway analysis. TurboPutative comprises a rapid, automated, and customizable workflow that can also be included in programmed bioinformatics pipelines through its RESTful API services. Users can explore the performance of each module through demo datasets supplied on the website. The platform will help the metabolomics community to speed up the arduous task of manual data curation that is required in the first steps of metabolite identification, improving the generation of biological knowledge.
    Keywords:  LC-MS; lipids; metabolite ID prioritize; putative annotations; simplification
    DOI:  https://doi.org/10.3389/fmolb.2022.952149
  3. Anal Chem. 2022 Sep 30.
      The ability to identify abnormalities in the body's saccharide profile is a promising means for early disease detection but requires analytical tools capable of detecting saccharides at low concentrations and/or for volume-limited samples. The preferred analysis approach for these compounds, liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS), often lacks sensitivity due to poor ionization efficiency. In this work, we employ a modified electrospray interface-termed contained-electrospray (contained-ESI) to couple accelerated droplet chemistry to conventional LC-MS for the online and automated separation, derivatization, and detection of saccharides. The chromatographic component enables complex sample and mixtures analysis with low sample volume requirements, while the enhanced reaction kinetics afforded by electrosprayed microdroplets facilitates rapid, on-the-fly derivatization to boost sensitivity. Derivatization occurs during ion formation as analytes elute from the column, eliminating the need for superfluous post-column derivatization hardware or complicated benchtop protocols. A grounded coupler was incorporated to shield the LC from the high-voltage ion source, and method conditions were optimized to accommodate the low flow rates preferred for microdroplet reactions. The new LC-contained-ESI-MS/MS platform was demonstrated for the analysis of several mono-, di-, and oligosaccharides using in-source droplet-based phenylboronic acid derivatization. Femtomole limits of detection were achieved for a 1 μL injection, representing sensitivity enhancement of 1-2 orders of magnitude over conventional LC-ESI-MS/MS without derivatization. In addition, isobaric saccharides that are difficult to differentiate by MS alone were easily distinguished. Method precision, accuracy, and linearity were established, and the ability to detect oligosaccharides at trace levels in human urine and plasma was demonstrated.
    DOI:  https://doi.org/10.1021/acs.analchem.2c03736
  4. Anal Bioanal Chem. 2022 Sep 28.
      Organic acid (OA) analysis is a specific test for inherited metabolic disorders (IMDs); however, the previous detection methods are laborious and costly. This study aims to develop a rapid method for the simultaneous quantification of serum and urine OA profiles. The method was established based on the liquid chromatography-tandem mass spectrometry (LC-MS/MS) technique. The specificity, sensitivity, robustness, and accuracy of the established method were validated. Fifteen healthy subjects and nine IMD patients were measured for clinical validation. OAs with their intrinsic isomers were completely separated. The LC-MS/MS analysis time was 5.5 min. Calibration curves were linear within the ranges of 27.00 μg/g for all OAs. The average correlation relationship (R) varied from 0.9891 to 0.9998. The limit of detection and limit of quantification varied from 0.003 to 0.07 μg/g and 0.006 to 0.08 μg/g, respectively. No obvious carryover was observed. The intra-assay, inter-assay, and total imprecisions were 1.22-4.14%, 0.90-5.20%, and 1.67-5.90%, respectively. The mean spiked recovery at the three levels varied from 94.31 to 106.68%. The matrix effects can be compensated for by internal standard correction. Nine IMD patients were identified. A robust LC-MS/MS method for the rapid determination of serum and urine OA profiles without derivatization or liquid-liquid extraction was developed and validated. The analysis of five common OAs can be completed in short minutes. This innovative LC-MS/MS method for OA profiles may present its potential in future rapid screening and diagnosis of IMDs.
    Keywords:  Inherited metabolic disorders; Liquid chromatography-tandem mass spectrometry; Newborn screening; Organic acid profiles
    DOI:  https://doi.org/10.1007/s00216-022-04316-9
  5. Se Pu. 2022 Sep;40(9): 788-796
      Plants produce a wide variety of secondary metabolites in the process of evolution. Secondary metabolites have highly diverse structures due to the modification of the basic skeletons of metabolites. They are required for interaction with the environment and are produced in response to abiotic/biotic stress. Characterization of secondary metabolic pathways is significant to plant molecular breeding and natural product biosynthesis. The liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS) is one of the major techniques for untargeted metabolomics study. The LC-HRMS/MS method could detect tens of thousands of metabolic features and provide abundant structural information. It has been widely used in the discovery and characterization of the secondary metabolome. However, due to the largely diverse structure and limited records in the mass spectral library, the annotation of the secondary metabolome is very difficult. To address the analytical challenges associated with the vast structural diversity and the large numbers of secondary metabolites, particularly those previously unknown structural metabolites, a novel method for the efficient characterization of pathway-associated metabolites was developed. Modification reactions and MS/MS spectral information were collected using the metabolic pathways database and mass spectral library. Screening and annotation of metabolites involved in phenylpropanoid metabolism in maize leaves were used as an example. First, a database of modified groups was established via pathway-associated modifications from open access metabolic pathway database and literature. Here, pathway databases included the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Plant Metabolic Pathways (PlantCyc). A total of 61 modification types were enrolled, including 10 generic and 51 pathway-specific modifications. Modified metabolomes were filtered from untargeted LC-HRMS/MS metabolomics data. Next, MS/MS spectra of the pathway-associated compounds (probe molecules) were collected in the Global Natural Products Social Molecular Networking (GNPS) MS/MS spectral library. The MS/MS of compounds assigned to chemical classes of phenylpropanoids were kept. An MS/MS spectral database of the probe molecules was constructed. It included 2677 spectra of 1542 phenylpropanoid compounds in the positive mode and 814 spectra of 661 phenylpropanoid compounds in the negative mode. Then, an MS/MS molecular network was generated by modified metabolome and probe molecules. The clusters comprising both probe molecules and modified metabolites were kept. To explore more previously unknown structural metabolites, the clusters with one more pathway-specific modified metabolite were retained even though they didn't contain any probe molecule. A total of 392 and 417 phenylpropanoid pathway-related metabolic metabolites were obtained in positive and negative ion modes, respectively. The pathway-associated metabolites were annotated based on the propagation of the molecular network. For the metabolites within the co-cluster, annotations were performed using the probe molecules as the initial seed. The modification group's substructure information was used for network propagation annotation. For the clusters containing only pathway-specific modified metabolites, the annotation is similar to the above process if identified nodes were present within the cluster. Otherwise, de novo annotation was manually executed based on substructure information. Finally, 129 unique metabolites were annotated after integration and removal of redundancy. Ten annotated metabolites were validated using commercially available or synthesized reference compounds. The other annotation results were validated using predicted chemical classes, in silico MS/MS, and predicted retention time. They are mainly involved in the downstream branch of phenylpropanoid pathways, including the flavonoid pathway (8 flavonoids, 19 flavonoid O-glycosides, 32 flavonoid C-glycosides), the hydroxycinnamic acid pathway (31 hydroxycinnamic acids and derivatives), and the lignan pathway (22 neo-lignans/lignan/lignan glycosides). All the annotated structures were searched against the PubChem and SciFinder databases. Among them, 26 metabolites were previously unreported in both the databases. In this study, the pathway-associated metabolites could be quickly discovered and annotated by the integration of probe molecules and modified metabolome. It provides a method for the in-depth study of the phenylpropanoid pathway.
    Keywords:  annotation; liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS); modified metabolome; probe molecule; secondary metabolites
    DOI:  https://doi.org/10.3724/SP.J.1123.2022.03025
  6. J Pharm Biomed Anal. 2022 Sep 15. pii: S0731-7085(22)00481-2. [Epub ahead of print]221 115060
      Short-chain carboxylic acids (SCCAs) produced by gut microbial fermentation may reflect gastrointestinal health. Their concentrations in serum and urine are indicative of specific metabolic pathway activity; therefore, accurate quantitation of SCCAs in different biofluids is desirable. However, it is often challenging to quantitate SCCAs since matrix effects, induced by the presence of a vast variety of other compounds other than SCCAs in complex biofluids, can suppress or enhance signals. Materials used for sample preparation may introduce further analytical challenges. This study reports for the first time a LC-MS/MS-based method to quantitate ten SCCAs (lactate, acetate, 2-hydroxybutyrate, propionate, isobutyrate, butyrate, 2-methylbutyrate, isovalerate, valerate and hexanoate) and evaluates the matrix effects in five human biofluids: serum, urine, stool, and contents from the duodenum and intestinal stoma bags. The optimized method, using 3-Nitrophenylhydrazone as a derivatization agent and a Charge Surface Hybrid reverse phase column, showed clear separation for all SCCAs at a concentration range of 0.1-100 µM, in a 10.5 min run without carry-over effects. The validation of the method showed a good linearity (R2 > 0.99), repeatability (CV ≤ 15%) assessed by intra- and inter-day monitoring. The lowest limit of detection (LLOD) was 25 nM and lowest limit of quantitation (LLOQ) was 50 nM for nine SCCA except acetate at 0.5 and 1 µM, respectively. Quantitative accuracy in all biofluids for most compounds was < ±15%. In summary, this methodology has the advantages over other techniques for its simple and fast sample preparation and a high level of selectivity, repeatability and robustness for SCCA quantification. It also reduced interferences from the matrix or sample containers, making it ideal for use in high-throughput analyses of biofluid samples from large-scale studies.
    Keywords:  3-NPH; CSH; Colostomy bag; Derivatization; Ostomy pouch; Short chain fatty acids
    DOI:  https://doi.org/10.1016/j.jpba.2022.115060
  7. Front Mol Biosci. 2022 ;9 972190
      The aim of this review is to show the risks of artifact formation in metabolomics analyses. Metabolomics has developed in a major tool in system biology approaches to unravel the metabolic networks that are the basis of life. Presently TLC, LC-MS, GC-MS, MS-MS and nuclear magnetic resonance are applied to analyze the metabolome of all kind of biomaterials. These analytical methods require robust preanalytical protocols to extract the small molecules from the biomatrix. The quality of the metabolomics analyses depends on protocols for collecting and processing of the biomaterial, including the methods for drying, grinding and extraction. Also the final preparation of the samples for instrumental analysis is crucial for highly reproducible analyses. The risks of artifact formation in these steps are reviewed from the point of view of the commonly used solvents. Examples of various artifacts formed through chemical reactions between solvents or contaminations with functional groups in the analytes are discussed. These reactions involve, for example, the formation of esters, trans-esterifications, hemiacetal and acetal formation, N-oxidations, and the formation of carbinolamines. It concerns chemical reactions with hydroxyl-, aldehyde-, keto-, carboxyl-, ester-, and amine functional groups. In the analytical steps, artifacts in LC may come from the stationary phase or reactions of the eluent with analytes. Differences between the solvent of the injected sample and the LC-mobile phase may cause distortions of the retention of analytes. In all analytical methods, poorly soluble compounds will be in all samples at saturation level, thus hiding a potential marker function. Finally a full identification of compounds remains a major hurdle in metabolomics, it requires a full set of spectral data, including methods for confirming the absolute stereochemistry. The putative identifications found in supplemental data of many studies, unfortunately, often become "truly" identified compounds in papers citing these results. Proper validation of the protocols for preanalytical and analytical procedures is essential for reproducible analyses in metabolomics.
    Keywords:  artifacts; decomposition; extraction; metabolomics; solvents
    DOI:  https://doi.org/10.3389/fmolb.2022.972190
  8. Bioinformatics. 2022 Sep 27. pii: btac647. [Epub ahead of print]
       SUMMARY: Untargeted metabolomics data analysis is highly labor intensive and can be severely frustrated by both experimental noise and redundant features. Homologous polymer series are a particular case of features that can either represent large numbers of noise features, or alternatively represent features of interest with large peak redundancy. Here we present homologueDiscoverer, an R package which allows for the targeted and untargeted detection of homologue series as well as their evaluation and management using interactive plots and simple local database functionalities.
    AVAILABILITY: homologueDiscoverer is freely available at github https://github.com/kevinmildau/homologueDiscoverer.
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    DOI:  https://doi.org/10.1093/bioinformatics/btac647
  9. J Proteome Res. 2022 Sep 30.
      Advances in metabolomics analysis and data treatment increase the knowledge of complex biological systems. One of the most used methodologies is gas chromatography-mass spectrometry (GC-MS) due to its robustness, high separation efficiency, and reliable peak identification through curated databases. However, methodologies are not standardized, and the derivatization steps in GC-MS can introduce experimental errors and take considerable time, exposing the samples to degradation. Here, we propose the injection-port derivatization (IPD) methodology to increase the throughput in plasma metabolomics analysis by GC-MS. The IPD method was evaluated and optimized for different families of metabolites (organic acids, amino acids, fatty acids, sugars, sugar phosphates, etc.) in terms of residence time, injection-port temperature, and sample/derivatization reagent ratio. Finally, the method's usefulness was validated in a study consisting of a cohort of obese patients with or without nonalcoholic steatohepatitis. Our results show a fast, reproducible, precise, and reliable method for the analysis of biological samples by GC-MS. Raw data are publicly available at MetaboLights with Study Identifier MTBLS5151.
    Keywords:  gas chromatography; injection-port derivatization; mass spectrometry; metabolomics; nonalcoholic steatohepatitis
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00119
  10. Front Microbiol. 2022 ;13 958785
      Metabolomics is a mainstream strategy for investigating microbial metabolism. One emerging application of metabolomics is the systematic quantification of metabolic boundary fluxes - the rates at which metabolites flow into and out of cultured cells. Metabolic boundary fluxes can capture complex metabolic phenotypes in a rapid assay, allow computational models to be built that predict the behavior of cultured organisms, and are an emerging strategy for clinical diagnostics. One advantage of quantifying metabolic boundary fluxes rather than intracellular metabolite levels is that it requires minimal sample processing. Whereas traditional intracellular analyses require a multi-step process involving extraction, centrifugation, and solvent exchange, boundary fluxes can be measured by simply analyzing the soluble components of the culture medium. To further simplify boundary flux analyses, we developed a custom 96-well sampling system-the Microbial Containment Device (MCD)-that allows water-soluble metabolites to diffuse from a microbial culture well into a bacteria-free analytical well via a semi-permeable membrane. The MCD was designed to be compatible with the autosamplers present in commercial liquid chromatography-mass spectrometry systems, allowing metabolic fluxes to be analyzed with minimal sample handling. Herein, we describe the design, evaluation, and performance testing of the MCD relative to traditional culture methods. We illustrate the utility of this platform, by quantifying the unique boundary fluxes of four bacterial species and demonstrate antibiotic-induced perturbations in their metabolic activity. We propose the use of the MCD for enabling single-step metabolomics sample preparation for microbial identification, antimicrobial susceptibility testing, and other metabolic boundary flux applications where traditional sample preparation methods are impractical.
    Keywords:  antibiotic susceptibility testing (AST); bacteria identification; fabrication; liquid chromatography-mass spectrometry; metabolic boundary fluxes; metabolic preference assay; metabolomics
    DOI:  https://doi.org/10.3389/fmicb.2022.958785
  11. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Sep 20. pii: S1570-0232(22)00377-4. [Epub ahead of print]1210 123473
      Fatty acids (FAs) are associated with many physiological functions of tissues, and their alteration has been linked with tissue-specific or systemic diseases. The current situation warrants us to have a sensitive and specific method for analysis of total FAs simultaneously from the biological fluid so that the risk prediction, diagnosis or prognosis of the disease can be made effectively. Because of greater sensitivity and resolution, a method of gas chromatography-ion trap mass spectrometry (GC-IT/MS) has been optimized and validated to quantify simultaneously 19 total FAs levels in plasma and compared with GC-triple quadrupole mass spectrometry. FAs have been transesterified by methanolic acetyl chloride to fatty acid methyl esters (FAMEs). A 65 min GC method separated all 19 FAMEs. The calibration curve had good linearity up to 313-922 μM with a correlation coefficient between 0.9882 and 0.9998. The LODs and LOQs of FAMEs were in the range of 0.63 to 9.55 and 2.12 to 31.8 μM, respectively. The method has recovery up to 144 %, stability at 4 °C for 48 h and one freeze-thaw cycle, and good intra-day and inter-day precision. The optimized method has been used to quantify plasma total FAs in type 2 diabetes mellitus patients with and without acute coronary syndrome. Though a significant difference has been found between IT/MS and triple quadrupole mass spectrometry, the GC-IT/MS can help to quantify total FAs in the clinical setting.
    Keywords:  Fatty acids; Gas chromatography–ion trap mass spectrometry; Method validation; Transesterification
    DOI:  https://doi.org/10.1016/j.jchromb.2022.123473
  12. J Am Soc Mass Spectrom. 2022 Sep 29.
      Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is a hybrid, ambient ionization source that combines the advantages of electrospray ionization and matrix-assisted laser desorption/ionization, making it a versatile tool for both high-throughput screening (HTS) and mass spectrometry imaging (MSI) studies. To expand the capabilities of the IR-MALDESI source, an entirely new architecture was designed to overcome the key limitations of the previous source. This next-generation (NextGen) IR-MALDESI source features a vertically mounted IR-laser, a planar translation stage with computerized sample height control, an aluminum enclosure, and a novel mass spectrometer interface plate. The NextGen IR-MALDESI source has improved user-friendliness, improved overall versatility, and can be coupled to numerous Orbitrap mass spectrometers to accommodate more research laboratories. In this work, we highlight the benefits of the NextGen IR-MALDESI source as an improved platform for MSI and direct analysis. We also optimize the NextGen MALDESI source component geometries to increase target ion abundances over a wide m/z range. Finally, documentation is provided for each NextGen IR-MALDESI part so that it can be replicated and incorporated into any lab space.
    Keywords:  Design of Experiments; High-Throughput Screening; IR-MALDESI; Mass Spectrometry Imaging; Orbitrap Mass Spectrometer
    DOI:  https://doi.org/10.1021/jasms.2c00178
  13. Talanta. 2022 Sep 20. pii: S0039-9140(22)00728-7. [Epub ahead of print]253 123932
      To facilitate application in ophthalmological and systemic diseases, there is a need to standardize preanalytical and analytical steps for metabo-lipidomics in human tears. We assessed different methods for each step of the workflow, from sampling to omics profiles acquisition, to provide the largest metabo-lipidomic coverage with the most robust analytical criteria in human tears. We compared reproducibility according to different extraction methods, two sampling techniques, three volumes (2 μL, 5 μL, 10 μL) and eye laterality using ultra-high-performance liquid chromatography coupled with tandem high-resolution mass spectrometry for metabolomic and lipidomic application. The effect of age on the tear metabo-lipidome was also investigated in healthy subjects. The extraction method using methanol/water provided the best results for Schirmer strip metabolomics, while Folch extraction was superior for lipidomics, whatever the sampling method used. When comparing both sampling methods, microcapillary glass tube was superior to Schirmer strip for metabolomics but comparable for lipidomics. The 5 μL volume provided a satisfying metabo-lipidomic coverage. There was no significant difference in tear metabo-lipidome between both eyes in healthy subjects. While most metabolites and lipids where not influenced by age, the phenylalanine-tyrosine-tryptophan pathway, aminoacyl t-RNA biosynthesis, and alanine-aspartate-glutamate metabolism were the 3 principal pathways associated with the 15 most variable metabolites according to age. The current findings will contribute to improve metabo-lipidomic workflow in human tears for the identification of new biomarkers. Preanalytical and analytical standardization is mandatory in order to perform better between-study comparisons and increase the chances of transferring laboratory findings into clinical practice.
    Keywords:  Lipidomic; Liquid chromatography; Mass spectrometry; Metabolomic; Tears
    DOI:  https://doi.org/10.1016/j.talanta.2022.123932
  14. Se Pu. 2022 Sep;40(9): 797-809
      Various types of oxidative dyes used in hair dye products possess poor stability and have varying frequency of use. Interference problems also frequently arise in actual sample measurements. Therefore, it is necessary to establish a simple, rapid, accurate, and specific method for the determination of common dyes in hair dye products for their effective regulation. In this study, dyes were grouped according to their frequency of use. Using a C18 column that minimizes the silanol effect and influence of metals, the quantitative high performance liquid chromatography (HPLC) method for 32 dyes listed in Safety and Technical Standards for Cosmetics (2015 edition) was optimized, and a high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) confirmatory method for the dyes was established. The samples were extracted using a mixed solution of ethanol-water (1∶1, v/v) with 10 g/L sodium bisulfite solution as an antioxidant, vortexed and mixed, and then extracted by ultrasonication in an ice bath for 10 min. Methanol, acetonitrile, and phosphate buffer were used as the mobile phases in the HPLC analysis. Additionally, two different elution conditions (chromatographic gradient) were used for the separation of 32 oxidative dyes, which were detected at a wavelength of 280 nm. The HPLC separations were compared using columns of particle sizes 5 μm and 2.7 μm; 5 μm C18 columns with better anti-interference and antiblocking ability were selected. Satisfactory separation was achieved for all three commercial C18 columns with a particle size of 5 μm, and the method had good general usability. In condition 1, 17 commonly used dyes and three less commonly used dyes were assigned to group Ⅰ and separated by HPLC; in condition 2, eight banned dyes and four other less commonly used dyes were assigned to group Ⅱ and separated by HPLC. The HPLC-MS/MS method used 5 mmol/L ammonium acetate aqueous solution-acetonitrile and 5 mmol/L acetic acid aqueous solution-acetonitrile as mobile phases in the positive and negative ion modes, respectively. Multiple reaction monitoring (MRM) was performed for qualitative and quantitative analyses in the electrospray ionization mode. Under the examined conditions, six pairs of isomers were well resolved. For the HPLC and HPLC-MS/MS methods, the relative standard deviations (RSDs) of the intra-day precision and 48 h stability tests were less than 10%. The recoveries were between 82.6% and 114.9% (RSD<10%). In the HPLC method, 32 dyes showed good linearity in an approximate range of 10-500 mg/L (r2>0.99), and the limits of detection (LODs) were 9.7-40.1 μg/g. The linear range of hydroquinone in the HPLC-MS/MS method was 2.0-79.7 mg/L, and the LOD was 8.0 μg/g; the linear ranges of the other components were approximately 0.1-4 mg/L, and the LODs were 0.01-0.4 μg/g. The actual samples were simultaneously measured by HPLC, HPLC-MS/MS, and the standard method. Finally, 16 of the 32 dyes were detected, and the detected contents ranged from 58 to 25160 μg/g. The RSDs of the results obtained from the three detection methods were between 1.9% and 10.1%. All detected components were within the limits of group Ⅰ of this method. In comparison with methods reported in the literature and the standard method, this method covers all components for the routine regulatory inspection of oxidative dyes in cosmetics. The method can separate the commonly used dyes under the same HPLC conditions and avoid interference from 15 other commonly used dyes during the analysis of actual samples. A suitable HPLC-MS/MS confirmatory method was also established for the identification of currently unknown substances in the statutory inspection of cosmetics. The method is simple, rapid, accurate, and specific with general usability and good operability.
    Keywords:  hair dye products; high performance liquid chromatography (HPLC); high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS); oxidative dyes
    DOI:  https://doi.org/10.3724/SP.J.1123.2022.03003
  15. Anal Methods. 2022 Sep 27.
      Accurate quantitative information of the analytes in mass spectrometry imaging (MSI) is fundamental for determining the accurate spatial distribution, which can provide additional insight into the living processes, disease progression or the pharmacokinetic-pharmacodynamic mechanisms. However, performing a quantitative analysis in MSI is still challenging. This review focuses on the quantitation-related factors and recent advances in the strategies of quantitative MSI (q-MSI) of small molecules. The main quantitation-related factors are discussed according to the new investigations in recent years, including the regionally varied extraction efficiencies and ionization efficiencies, signal-concentration regression functions, and the repeatability of surface sampling/ionization methods. Newly developed quantitation strategies in MSI based on aforementioned factors are introduced, including new techniques in standard curve calibration with normalization to an internal standard, kinetic calibration, and chemometric methods. Different strategies for validating q-MSI methods are discussed. Finally, the future perspectives to q-MSI are proposed.
    DOI:  https://doi.org/10.1039/d2ay01257j
  16. Analyst. 2022 Sep 28.
      Amino acids are closely related to human health, and their rapid determination is important for the rapid diagnosis, timely treatment, and assessment of serious diseases. In this work, we propose a novel paper-based sample-processing device combined with isotope-dilution MS for the fast analysis of 11 amino acids from blood samples. By using an isoelectric focusing electrokinetic separation method, without the aid of carrier ampholytes and the addition of inhibitors, this approach uses only the characteristic of the isoelectric point of the target amino acids to achieve separation and purification from other coexisting components in the medium; it can meet the requirements for mass spectrometry detection. Driven by a DC voltage, a stable and sharp pH gradient (pH 3-10.5 over 5 mm) can be established in a glass-fiber paper-based fluidic channel with a MS-friendly electrolyte. Amphoteric species can be well separated from the complex blood matrix and concentrated into a narrow band in the channel within 2 min, which is 20 times faster than a commercial kit method. The method can be applied to both liquid and dry spot samples, and the cleaned sample band can be simply dissolved for direct IDMS detection in ESI MRM mode. This method is a promising strategy for the rapid MS-based detection of amino acids from serum without pre-separation via liquid chromatography.
    DOI:  https://doi.org/10.1039/d2an01261h
  17. Anal Chem. 2022 Sep 29.
      Based on the Venturi self-pumping effect, real-time sniffing with mass spectrometry (R-sniffing MS) is developed as a tool for direct and real-time mass spectrometric analysis of both gaseous and solid samples. It is capable of dual-mode operation in either gaseous or solid phase, with the corresponding techniques termed as Rg-sniffing MS and Rs-sniffing MS, respectively. In its gaseous mode, Rg-sniffing MS is capable of analyzing a gaseous mixture with response time (0.8-2.1 s rise time and 7.3-9.6 s fall time), spatial resolution (<80 μm), three-dimensional diffusion imaging, and aroma distribution imaging of red pepper. In its solid mode, an appropriate solvent droplet desorbs the sample from a solid surface, followed by the aspiration of the mixture using the Venturi self-pumping effect into the mass spectrometer, wherein it is ionized by a standard ion source. Compared with the desorption electrospray ionization (DESI) technique, Rs-sniffing MS demonstrated considerably improved limit of detection (LOD) values for arginine (0.07 μg/cm2 Rs-sniffing vs 1.47 μg/cm2 DESI), thymopentin (0.10 μg/cm2 vs 2.67 μg/cm2), and bacitracin (0.16 μg/cm2 vs 2.28 μg/cm2). Rs-sniffing is applicable for the detection of C60(OCH3)6Cl-, an intermediate in the methoxylation reaction involving C60Cl6 (solid) and methanol (liquid). The convenient and highly sensitive R-sniffing MS has a characteristic separation of desorption from the ionization process, in which the matrix atmosphere of desorption can be interfaced by a pipe channel and self-pumped by the Venturi effect with consequent integration using a standard ion source. The R-sniffing MS operates in a voltage-, heat-, and vibration-free environment, wherein the analyte is ionized by a standard ion source. Consequently, a wide range of samples can be analyzed simultaneously by the R-sniffing MS technique, regardless of their physical state.
    DOI:  https://doi.org/10.1021/acs.analchem.2c01759
  18. Anal Bioanal Chem. 2022 Oct 01.
      Tile-based Fisher ratio (F-ratio) analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS) data is a powerful, supervised discovery methodology for pinpointing sample class-distinguishing analytes between two or more sample classes. Herein, we extend this analytical methodology to focus upon specific chemical groups in kerosene-based aerospace fuel using solid-phase extraction (SPE). Treating samples with SPE removes specific compounds depending on the SPE stationary phase (i.e., silica), creating an altered "pass" sample, identical to the original "neat" sample except for the extracted compounds. Application of F-ratio analysis to the neat samples against the pass samples provides global discovery with a numerically sorted hit list of all analytes affected by the SPE procedure. Sections of GC × GC-TOFMS data from the top analyte hits are reconstructed to form a "stitch" chromatogram to visualize the sample class-distinguishing compounds, revealing excellent agreement with the extract chromatogram. Additionally, utilizing the four-grid tiling scheme developed for tile-based F-ratio analysis, we demonstrate a tile-based pairwise analysis method, referred to as 1v1 analysis, to discover analytes that differ in concentration between two fuel chromatograms. Application of 1v1 analysis is highly efficient since replicates do not necessarily need to be run on the GC × GC-TOFMS instrument, which is beneficial for sample-limited applications. The 1v1 analyses discovered most of the same features as F-ratio analysis, ranging from 69 to 81% of the features discovered by F-ratio analysis while requiring one-sixth the data. Lastly, the overall methodology is applied to three candidate rocket fuels to better understand the compound class-distinguishing differences. The separate hit lists produced for high-concentration bulk hydrocarbon differences and low-concentration level polar compound differences provided valuable insight into these candidate rocket fuels.
    Keywords:  Comprehensive two-dimensional gas chromatography; Kerosene-based rocket fuel; Solid-phase extraction; Supervised fuel comparison; Time-of-flight mass spectrometry
    DOI:  https://doi.org/10.1007/s00216-022-04348-1
  19. Front Mol Neurosci. 2022 ;15 883466
      13C metabolic flux analysis (13C-MFA) has emerged as a forceful tool for quantifying in vivo metabolic pathway activity of different biological systems. This technology plays an important role in understanding intracellular metabolism and revealing patho-physiology mechanism. Recently, it has evolved into a method family with great diversity in experiments, analytics, and mathematics. In this review, we classify and characterize the various branch of 13C-MFA from a unified perspective of mathematical modeling. By linking different parts in the model to each step of its workflow, the specific technologies of 13C-MFA are put into discussion, including the isotope labeling model (ILM), isotope pattern measuring technique, optimization algorithm and statistical method. Its application in physiological research in neural cell has also been reviewed.
    Keywords:  13C fluxomics; isotope labeling model; isotope tracing; metabolic flux analysis; neural cell
    DOI:  https://doi.org/10.3389/fnmol.2022.883466
  20. J Proteome Res. 2022 Sep 29.
      It has long been known that biological species can be identified from mass spectrometry data alone. Ten years ago, we described a method and software tool, compareMS2, for calculating a distance between sets of tandem mass spectra, as routinely collected in proteomics. This method has seen use in species identification and mixture characterization in food and feed products, as well as other applications. Here, we present the first major update of this software, including a new metric, a graphical user interface and additional functionality. The data have been deposited to ProteomeXchange with dataset identifier PXD034932.
    Keywords:  compareMS2; distance metric; molecular phylogenetics; quality control; tandem mass spectrometry
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00457
  21. Rapid Commun Mass Spectrom. 2022 Sep 28. e9406
       RATIONALE: Exhaled breath contains many substances that are closely related to human metabolism. Analysis of its composition is important for human health, but it is difficult. Since the volatile molecules in breath samples are exhaled instantaneously, easily diffused and modified, and at low level of presence, difficult to identify and quantify.
    METHODS: A modified direct analysis in real time (DART) ion source was used for high resolution mass spectrometry measurement of human metabolites in exhaled breath through online monitoring and offline analysis, in both positive and negative ion modes. The improved system enabled the breath volatiles as well as condensates to be directly sampled, rapidly transmitted and efficiently ionized in a confined region, and then detected by Orbitrap mass analyzer.
    RESULTS: The molecular features with online and offline analysis of exhaled breath were demonstrated with obvious differences. A total of ~65 metabolites in positive ion mode and ~55 metabolites in negative ion mode were identified based on accurate m/z values. Exhalome profile and the composition proportion of different classes of compounds were obtained. The relative contents of metabolites from breath varied during different time periods throughout a day.
    CONCLUSIONS: A more complete picture of the human breath metabolome was provided combining the results obtained from both online and offline analysis. The developed method is capable of analyzing breath samples with different status rapidly and directly, and it is featured by simple operation, and metabolite identification, requiring little or no sample preparation.
    DOI:  https://doi.org/10.1002/rcm.9406
  22. Anal Chim Acta. 2022 Oct 09. pii: S0003-2670(22)00932-1. [Epub ahead of print]1229 340361
      The number of open access databases containing experimental and predicted collision cross section (CCS) values is rising and leads to their increased use for compound identification. However, the reproducibility of reference values with different instrumental designs and the comparison between predicted and experimental CCS values is still under evaluation. This study compared experimental CCS values of 56 small molecules (Contaminants of Emerging Concern) acquired by both drift tube (DT) and travelling wave (TW) ion mobility mass spectrometry (IM-MS). The TWIM-MS included two instrumental designs (Synapt G2 and VION). The experimental TWCCSN2 values obtained by the TWIM-MS systems showed absolute percent errors (APEs) < 2% in comparison to experimental DTIMS data, indicating a good correlation between the datasets. Furthermore, TWCCSN2 values of [M - H]- ions presented the lowest APEs. An influence of the compound class on APEs was observed. The applicability of prediction models based on artificial neural networks (ANN) and multivariate adaptive regression splines (MARS), both built using TWIM-MS data, was investigated for the first time for the prediction of DTCCSN2 values. For [M+H]+ and [M - H]- ions, the 95th percentile confidence intervals of observed APEs were comparable to values reported for both models indicating a good applicability for DTIMS predictions. For the prediction of DTCCSN2 values of [M+Na]+ ions, the MARS based model provided the best results with 73.9% of the ions showing APEs below the threshold reported for [M+Na]+. Finally, recommendations for database transfer and applications of prediction models for future DTIMS studies are made.
    Keywords:  CCS comparison; CCS database; Compounds of emerging concern; Drift tube ion mobility separation; Quality assurance guidelines; Travelling wave ion mobility separation
    DOI:  https://doi.org/10.1016/j.aca.2022.340361
  23. Environ Sci Technol. 2022 Sep 26.
      
    Keywords:  enrichment analysis; environmental metabolomics; metabolic pathway; metabolomics; metabonomics; over-representation analysis; pathway analysis
    DOI:  https://doi.org/10.1021/acs.est.2c05588