bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2022‒10‒30
forty-two papers selected by
Sofia Costa

  1. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Oct 19. pii: S1570-0232(22)00418-4. [Epub ahead of print]1212 123513
      For large-scale and long-term metabolomics studies that involve a large batch or multiple batches of analyses, batch effects cause nonbiological systematic biases that may lead to false positive or false negative findings. Quantitative monitoring and correction of batch effects is critical to the development of reproducible and robust metabolomics platforms either for untargeted or targeted analyses. To achieve sufficient retention and separation of a broad range of metabolites with diverse chemical structures and physicochemical properties, LC-MS/MS based targeted metabolomics often involves 3 complemented chromatographic separation methods, including reversed-phase liquid chromatography (RP-LC), hydrophilic interaction liquid chromatography (HILIC), and ion-pair liquid chromatography (IP-LC). The purpose of this study is to quantitatively evaluate intra-batch variations or injection order effects of the RP-LC, HILIC, and IP-LC methods for targeted metabolomics analyses, and develop strategies to minimize intra-batch variations and correct injection order effects for problematic metabolites. Both RP-LC and HILIC methods exhibit robust intra-batch reproducibility in 0.2 µM standard mix QC, with ∼96 % of the measured metabolites showing acceptable intra-batch variations (<20 %); whereas, the intra-batch reproducibility for some metabolites in cell matrix QC may be compromised due to stability issue, suboptimal chromatographic retention, and/or matrix effects causing ionization suppression and/or retention instability. The IP-LC method exhibits significant injection order effects, which could be effectively corrected by the developed exponential models of signal drift trends as a function of injection order for individual targeted metabolites.
    Keywords:  Batch effect; Hydrophilic interaction liquid chromatography (HILIC); Injection order effect; Ion-pair liquid chromatography; LC-MS/MS based targeted metabolomics; Reversed-phase liquid chromatography
  2. Sheng Wu Gong Cheng Xue Bao. 2022 Oct 25. 38(10): 3940-3955
      Stable isotope 13C labeling is an important tool to analyze cellular metabolic flux. The 13C distribution in intracellular metabolites can be detected via mass spectrometry and used as a constraint in intracellular metabolic flux calculations. Then, metabolic flux analysis algorithms can be employed to obtain the flux distribution in the corresponding metabolic reaction network. However, in addition to carbon, other elements such as oxygen in the nature also have natural stable isotopes (e.g., 17O, 18O). This makes the isotopic information of elements other than the 13C marker interspersed in the isotopic distribution measured by the mass spectrometry, especially that of the molecules containing many other elements, which leads to large errors. Therefore, it is essential to correct the mass spectrometry data before performing metabolic flux calculations. In this paper, we proposed a method for construction of correction matrix based on Python language for correcting the measurement errors due to natural isotope distribution. The method employed a basic power method for constructing the correction matrix with simple structure and easy coding implementation, which can be directly applied to data pre-processing in 13C metabolic flux analysis. The correction method was then applied to the intracellular metabolic flux analysis of 13C-labeled Aspergillus niger. The results showed that the proposed method was accurate and effective, which can serve as a reliable data correction method for accurate microbial intracellular metabolic flux analysis.
    Keywords:  Python; mass spectrometry; metabolic flux analysis; natural isotope correction matrix
  3. Diagnostics (Basel). 2022 Sep 20. pii: 2273. [Epub ahead of print]12(10):
      BACKGROUND: Methylmalonic acid (MMA) is an essential indicator of vitamin B12 (VB12) deficiency and inherited metabolic disorders (IMDs). The increasing number of requests for MMA testing call for higher requirements for convenient MMA testing methods. This study aims to develop a convenient quantification method for serum MMA.METHODS: The method was established based on the stable isotope-dilution liquid chromatography-tandem mass spectroscopy (ID-LC-MS/MS) technique. The LC-MS/MS parameters and sample preparation were optimized. Specificity, sensitivity, robustness, accuracy, and clinical applicability were validated according to CLSI C62-A guidelines. MMA levels in VB12-sufficient subjects and VB12-deficient subjects were measured.
    RESULTS: MMA and its intrinsic isomer, i.e., succinic acid (SA), were completely separated. The average slope, intercept, and correlation relationship (R) with 95% confidence intervals, during the two months, were 0.992 (0.926-1.059), -0.004 (-0.012-0.004), and 0.997 (0.995-0.999), respectively. The limit of detection and quantification were &lt;0.058 μmol/L and 0.085 μmol/L, respectively. Intra-run, inter-run, and total imprecisions were 1.42-2.69%, 3.09-5.27%, and 3.22-5.47%, respectively. The mean spiked recoveries at the three levels were 101.51%, 92.40%, and 105.95%, respectively. The IS-corrected matrix effects were small. The VB12-deficient subjects showed higher MMA levels than VB12-sufficient subjects.
    CONCLUSIONS: A convenient LC-MS/MS method for serum MMA measurement was developed and validated, which could be suitable for large-scale MMA testing and evaluating MMA levels in VB12-deficient patients.
    Keywords:  liquid chromatography–tandem mass spectrometry; method improvements; methylmalonic acid; vitamin B12 deficiency
  4. J Vis Exp. 2022 Sep 20.
      Untargeted metabolomics techniques are being widely used in recent years. However, the rapidly increasing throughput and number of samples create an enormous amount of spectra, setting challenges for quality control of the mass spectrometry spectra. To reduce the false positives, false discovery rate (FDR) quality control is necessary. Recently, we developed a software for FDR control of untargeted metabolome identification that is based on a Target-Decoy strategy named XY-Meta. Here, we demonstrated a complete analysis pipeline that integrates XY-Meta and metaX together. This protocol shows how to use XY-meta to generate a decoy database from an existing reference database and perform FDR control using the Target-Decoy strategy for large-scale metabolome identification on an open-access dataset. The differential analysis and metabolites annotation were performed after running metaX for metabolites peaks detection and quantitation. In order to help more researchers, we also developed a user-friendly cloud-based analysis platform for these analyses, without the need for bioinformatics skills or any computer languages.
  5. Metabolites. 2022 Oct 21. pii: 1005. [Epub ahead of print]12(10):
      Untargeted metabolomics approaches deal with complex data hindering structural information for the comprehensive analysis of unknown metabolite features. We investigated the metabolite discovery capacity and the possible extension of the annotation coverage of the Feature-Based Molecular Networking (FBMN) approach by adding two novel nutritionally-relevant (contextual) mass spectral libraries to the existing public ones, as compared to widely-used open-source annotation protocols. Two contextual mass spectral libraries in positive and negative ionization mode of ~300 reference molecules relevant for plant-based nutrikinetic studies were created and made publicly available through the GNPS platform. The postprandial urinary metabolome analysis within the intervention of Vaccinium supplements was selected as a case study. Following the FBMN approach in combination with the added contextual mass spectral libraries, 67 berry-related and human endogenous metabolites were annotated, achieving a structural annotation coverage comparable to or higher than existing non-commercial annotation workflows. To further exploit the quantitative data obtained within the FBMN environment, the postprandial behavior of the annotated metabolites was analyzed with Pearson product-moment correlation. This simple chemometric tool linked several molecular families with phase II and phase I metabolism. The proposed approach is a powerful strategy to employ in longitudinal studies since it reduces the unknown chemical space by boosting the annotation power to characterize biochemically relevant metabolites in human biofluids.
    Keywords:  bioinformatics; chemometrics; computational metabolomics; human urine; liquid chromatography; untargeted mass spectrometry
  6. Methods Enzymol. 2022 ;pii: S0076-6879(22)00303-2. [Epub ahead of print]676 279-303
      Untargeted liquid chromatography/mass spectrometry (LC-MS) can contribute a comprehensive and unbiased picture of the metabolic space of plants. These data can be used to quantify natural metabolite variation for genome wide association studies, to compare global metabolic responses from environmental or genetic perturbations, and to identify previously undescribed metabolites in Nature. A major limitation with untargeted metabolomics is the classification and identification of the thousands of metabolite features that can be detected in a single analytical run. Isotopic labeling improves the informational value of these datasets by categorizing metabolites as being derived from specific upstream precursors and/or to known metabolic pathways. When a 13C-labeled precursor is fed to either a plant or tissue, the downstream metabolites produced from it have a higher m/z value than the molecules in the pre-existing pool, generating an m/z peak pair that can be specifically identified within the MS data. This paper outlines methods and principles to consider when supplementing untargeted MS data with isotopic labeling, including how to choose the appropriate isotopic label, grow and feed plant tissues to maximize label uptake and incorporation into derivatives, optimize LC-MS methods, and interpret the resulting labeling data. Although the focus here is on annotation of amino acid-derived metabolites using LC-MS, we anticipate that the methods are generally adaptable to other precursors, plant species, and chromatographic approaches.
    Keywords:  Amino acids; Isotopic labeling; LC-MS; Specialized metabolites; Untargeted metabolomics
  7. Brief Bioinform. 2022 Oct 21. pii: bbac455. [Epub ahead of print]
      Large-scale metabolomics is a powerful technique that has attracted widespread attention in biomedical studies focused on identifying biomarkers and interpreting the mechanisms of complex diseases. Despite a rapid increase in the number of large-scale metabolomic studies, the analysis of metabolomic data remains a key challenge. Specifically, diverse unwanted variations and batch effects in processing many samples have a substantial impact on identifying true biological markers, and it is a daunting challenge to annotate a plethora of peaks as metabolites in untargeted mass spectrometry-based metabolomics. Therefore, the development of an out-of-the-box tool is urgently needed to realize data integration and to accurately annotate metabolites with enhanced functions. In this study, the LargeMetabo package based on R code was developed for processing and analyzing large-scale metabolomic data. This package is unique because it is capable of (1) integrating multiple analytical experiments to effectively boost the power of statistical analysis; (2) selecting the appropriate biomarker identification method by intelligent assessment for large-scale metabolic data and (3) providing metabolite annotation and enrichment analysis based on an enhanced metabolite database. The LargeMetabo package can facilitate flexibility and reproducibility in large-scale metabolomics. The package is freely available from
    Keywords:  data integration; data processing; large-scale metabolomics; marker identification; metabolite annotation
  8. Front Bioinform. 2022 ;2 842964
      In natural products research, chemodiverse extracts coming from multiple organisms are explored for novel bioactive molecules, sometimes over extended periods. Samples are usually analyzed by liquid chromatography coupled with fragmentation mass spectrometry to acquire informative mass spectral ensembles. Such data is then exploited to establish relationships among analytes or samples (e.g., via molecular networking) and annotate metabolites. However, the comparison of samples profiled in different batches is challenging with current metabolomics methods since the experimental variation-changes in chromatographical or mass spectrometric conditions - hinders the direct comparison of the profiled samples. Here we introduce MEMO-MS2 BasEd SaMple VectOrization-a method allowing to cluster large amounts of chemodiverse samples based on their LC-MS/MS profiles in a retention time agnostic manner. This method is particularly suited for heterogeneous and chemodiverse sample sets. MEMO demonstrated similar clustering performance as state-of-the-art metrics considering fragmentation spectra. More importantly, such performance was achieved without the requirement of a prior feature alignment step and in a significantly shorter computational time. MEMO thus allows the comparison of vast ensembles of samples, even when analyzed over long periods of time, and on different chromatographic or mass spectrometry platforms. This new addition to the computational metabolomics toolbox should drastically expand the scope of large-scale comparative analysis.
    Keywords:  computational metabolomics; drug discovery; mass spectrometry; natural products; vectorization
  9. Sheng Wu Gong Cheng Xue Bao. 2022 Oct 25. 38(10): 3674-3681
      Metabolomics, which mainly studies the metabolite components of organisms, tissues, cells and their dynamic changes, is an emerging omics technology following genomics and proteomics. Metabolites are the final products of cellular regulation, and the concentration of metabolites is considered to be the ultimate response of a biological system to genetic or environmental changes. Secondary metabolites with chemical diversity are widely present in living organisms, thus accurate quantification of secondary metabolites through appropriate analytical platforms is an important task of metabolomics. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is the most commonly used method for the detection of metabolites, providing a basis for the wide application of plant secondary metabolites. This review summarizes the advances of using LC-MS/MS techniques for the detection of phytohormone, folic acid, flavonoids and other secondary metabolites.
    Keywords:  liquid chromatography-tandem mass spectrometry (LC-MS/MS); plant metabolomics; plant secondary metabolites
  10. Handb Exp Pharmacol. 2022 Oct 30.
      Nuclear Magnetic Resonance (NMR) spectroscopy is one of the two major analytical platforms in the field of metabolomics, the other being mass spectrometry (MS). NMR is less sensitive than MS and hence it detects a relatively small number of metabolites. However, NMR exhibits numerous unique characteristics including its high reproducibility and non-destructive nature, its ability to identify unknown metabolites definitively, and its capabilities to obtain absolute concentrations of all detected metabolites, sometimes even without an internal standard. These characteristics outweigh the relatively low sensitivity and resolution of NMR in metabolomics applications. Since biological mixtures are highly complex, increased demand for new methods to improve detection, better identify unknown metabolites, and provide more accurate quantitation continues unabated. Technological and methodological advances to date have helped to improve the resolution and sensitivity and detection of a larger number of metabolite signals. Efforts focused on measuring unknown metabolite signals have resulted in the identification and quantitation of an expanded pool of metabolites including labile metabolites such as cellular redox coenzymes, energy coenzymes, and antioxidants. This chapter describes quantitative NMR methods in metabolomics with an emphasis on recent methodological developments, while highlighting the benefits and challenges of NMR-based metabolomics.
    Keywords:  Fast NMR methods; Isotope tagging; Metabolomics; Nuclear magnetic resonance (NMR); Quantitation
  11. Metabolites. 2022 Oct 19. pii: 992. [Epub ahead of print]12(10):
      Metabolite identification in non-targeted NMR-based metabolomics remains a challenge. While many peaks of frequently occurring metabolites are assigned, there is a high number of unknowns in high-resolution NMR spectra, hampering biological conclusions for biomarker analysis. Here, we use a cluster analysis approach to guide peak assignment via statistical correlations, which gives important information on possible structural and/or biological correlations from the NMR spectrum. Unknown peaks that cluster in close proximity to known peaks form hypotheses for their metabolite identities, thus, facilitating metabolite annotation. Subsequently, metabolite identification based on a database search, 2D NMR analysis and standard spiking is performed, whereas without a hypothesis, a full structural elucidation approach would be required. The approach allows a higher identification yield in NMR spectra, especially once pathway-related subclusters are identified.
    Keywords:  NMR spectroscopy; metabolite identification; metabolomics; urine
  12. Metabolites. 2022 Oct 12. pii: 963. [Epub ahead of print]12(10):
      Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular "omics" technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.
    Keywords:  NMR spectroscopy; metabolomics; standardisation; variation; workflow
  13. Metabolites. 2022 Sep 30. pii: 931. [Epub ahead of print]12(10):
      Biotransformation reactions that xenobiotics undergo during their metabolism are crucial for their proper excretion from the body, but can also be a source of toxicity, especially in the case of reactive metabolite formation. Unstable, reactive metabolites are capable of covalent binding to proteins, and have often been linked to liver damage and other undesired side effects. A common technique to assess the formation of reactive metabolites employs trapping them in vitro with glutathione and characterizing the resulting adducts by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Some endogenous compounds, however, can interfere with xenobiotic metabolites of interest, making the analysis more difficult. This study demonstrates the usefulness of isotope-labeled compounds to detect and elucidate the structures of both stable metabolites and trapped adducts of three estrogen analogs using an untargeted LC-MS/MS workflow. The metabolism of estradiol, estrone and ethinyl estradiol was investigated. Unlabeled and deuterated versions of these three compounds were incubated with human or rat liver microsomes in the presence of two different trapping agents, namely glutathione and N-acetylcysteine. The detection of closely eluting deuterated peaks allowed us to confirm the formation of several known metabolites, as well as many previously uncharacterized ones. The structure of each adduct was elucidated by the detailed analysis of high-resolution MS/MS spectra for elucidating fragmentation pathways with accurate mass measurements. The use of isotopic labeling was crucial in helping confirm many metabolites and adduct structures, as well as removing endogenous interferences.
    Keywords:  LC-MS/MS; estradiol; estrone; ethinyl estradiol; metabolism; reactive metabolites; stable isotope labelling; structural elucidation
  14. Metab Eng Commun. 2022 Dec;15 e00209
      Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.
    Keywords:  Constraint-based modelling; Dynamic metabolomics; Kinetic modelling; Machine learning; Quantitative metabolomics; Spatial metabolomics
  15. Anal Bioanal Chem. 2022 Oct 29.
      The present research is focused on the optimization of an automatized sample preparation and fast gas chromatography-mass spectrometry (GC-MS) method for the analysis of fatty acid methyl esters (FAMEs) in blood samples and dietary supplements, with the primary objective being a significant reduction of the analysis time and, hence, an enhanced sample throughput. The mass spectrometer was operated in the scan/selected ion monitoring (SIM) acquisition method, thus enabling the obtainment of qualitative and (highly sensitive) quantitative data. The separation of FAMEs was obtained in about 11 min by using a micro-bore column of dimensions 15 m × 0.10 mm ID × 0.10 µm df with a polyethylene glycol stationary phase. The novelty of the research involves reducing analysis time by using the novel fast GC-MS method with increased identification reliability and sensitivity in a single chromatographic run. With regard to the figures of merit, linearity, accuracy, and limits of detection (LoD) and quantification (LoQ) were determined. Specifically, regression coefficients were between 0.9901 and 0.9996; the LoDs ranged from 0.05 to 1.02 µg g-1 for the blood analysis method, and from 0.05 to 0.26 mg g-1 in the case of the dietary supplement approach. With respect to LoQs, the values were in the ranges of 0.15-3.39 µg g-1 and 0.15-0.86 mg g-1 for blood and dietary supplements analysis methods, respectively. Accuracy was evaluated by analyzing certified reference materials (human plasma, fish oil).
    Keywords:  Dried blood spot; Fast GC–MS; Fatty acid methyl esters; Lipidomics; Scan/SIM acquisition; Selected ion monitoring
  16. Anal Chim Acta. 2022 Nov 15. pii: S0003-2670(22)01061-3. [Epub ahead of print]1233 340490
      Glucuronidation is a common phase II metabolic process for drugs and xenobiotics which increases their solubility for excretion. Acyl glucuronides (glucuronides of carboxylic acids) present concerns as they have been implicated in gastrointestinal toxicity and hepatic failure. Despite the substantial success in the bulk analysis of these species, previous attempts using traditional mass spectrometry imaging (MSI) techniques have completely or partially failed and therefore little is known about their localization in tissues. Herein, we use nanospray desorption electrospray ionization mass spectrometry imaging (nano-DESI MSI), an ambient liquid extraction-based ionization technique, as a viable alternative to other MSI techniques to examine the localization of diclofenac, a widely used nonsteroidal anti-inflammatory drug, and its metabolites in mouse kidney and liver tissues. MSI data acquired over a broad m/z range showed low signals of the drug and its metabolites resulting from the low ionization efficiency and substantial signal suppression on the tissue. Significant improvements in the signal-to-noise were obtained using selected ion monitoring (SIM) with m/z windows centered around the low-abundance ions of interest. Using nano-DESI MSI in SIM mode, we observed that diclofenac acyl glucuronide and hydroxydiclofenac are localized to the inner medulla and cortex of the kidney, respectively, which is consistent with the previously reported localization of enzymes that process diclofenac into its respective metabolites. In contrast, a uniform distribution of diclofenac and its metabolites was observed in the liver tissue. Concentration ratios of diclofenac and hydroxydiclofenac calculated from nano-DESI MSI data are generally in agreement to those obtained using liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Collectively, our results demonstrate that nano-DESI MSI can be successfully used to image diclofenac and its primary metabolites and derive relative quantitative data from different tissue regions. Our approach will enable a better understanding of metabolic processes associated with diclofenac and other drugs that are difficult to analyze using commercially available MSI platforms.
    Keywords:  Diclofenac; Mass spectrometry imaging; Metabolite localization; Mouse kidney and liver tissue; Nanospray desorption electrospray ionization (nano-DESI)
  17. Front Mol Biosci. 2022 ;9 1026184
      The broad coverage of untargeted metabolomics poses fundamental challenges for the harmonization of measurements along time, even if they originate from the very same instrument. Internal isotopic standards can hardly cover the chemical complexity of study samples. Therefore, they are insufficient for normalizing data a posteriori as done for targeted metabolomics. Instead, it is crucial to verify instrument's performance a priori, that is, before samples are injected. Here, we propose a system suitability testing platform for time-of-flight mass spectrometers independent of liquid chromatography. It includes a chemically defined quality control mixture, a fast acquisition method, software for extracting ca. 3,000 numerical features from profile data, and a simple web service for monitoring. We ran a pilot for 21 months and present illustrative results for anomaly detection or learning causal relationships between the spectral features and machine settings. Beyond mere detection of anomalies, our results highlight several future applications such as 1) recommending instrument retuning strategies to achieve desired values of quality indicators, 2) driving preventive maintenance, and 3) using the obtained, detailed spectral features for posterior data harmonization.
    Keywords:  analytical chemistry; mass spectrometry; metabolomics; quality assurance; quality control
  18. J Clin Lab Anal. 2022 Oct 25. e24738
      BACKGROUND: Plasma renin activity (PRA) is one of the recommended screening indicators for primary aldosteronism (PA) diagnosis and had become increasingly important in hypertension identification, medication guidance, and endocrine disorder confirmation.METHODS: To provide an overview of the PRA measurement progress and clinical value, this review summarizes the main contributing factors related to PRA measurement and necessary precautions during the entire analysis process. We also outline the characteristics of PRA in different endocrine diseases and their clinical utility.
    RESULTS: Significant inconsistency was observed in PRA measurement methods, including immunoassay and isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC/MS/MS), which could be attributed to preanalytical, analytical, and postanalytical variations. Meanwhile, consensus about environmental and procedural factors during the entire analytical process, including storage temperature, incubation condition, blank subtraction, and standardized operational procedures across different self-developed assay laboratories, could be important to minimize analytical variations. Furthermore, commutable uniform calibrators should be prepared to improve consistency, ultimately achieving accurate and reliable measurement of PRA.
    CONCLUSION: This review summarizes the clinical utilization of PRA as a biomarker in multiple diseases, elaborating on routine detection methods and the key factors in the analytical process. We also provide feasible strategies for improving standardization and facilitating PRA assessment for larger-scale clinical applications.
    Keywords:  isotope dilution liquid chromatography-tandem mass spectrometry; mineralocorticoid receptor; plasma renin activity; primary aldosteronism; standardization
  19. Exp Eye Res. 2022 Oct 20. pii: S0014-4835(22)00364-5. [Epub ahead of print] 109283
      Sex steroids play a role in regulation of tear film function and may exert their action locally at the ocular surface. However, measurement of sex steroids in tears is difficult due to small-volume tear samples and very low concentrations of the hormones. This short communication highlights what has been achieved to date in the analysis of tear sex steroids using ultra-performance LC-MS (UPLC-MS) as previously published, and reports further and more recent investigations toward optimising mass spectrometry method sensitivity and accuracy. The published UPLC-MS method successfully measured progesterone, androsterone glucuronide and 5α-androstane-3α,17β-diol in pooled basal tears of postmenopausal women, and fourteen sex steroid standards in methanol. Limitations included sub-optimal limits of detection (LOD) and lower limits of quantification (LLOQ) for some analytes (particularly oestrogens), exclusion of sample matrix effects and no use of internal standards. This update reports on further experiments carried out to improve sensitivity and accuracy. Sample matrix effects, internal standard spiking, and derivatisation with dansyl chloride and oximes were investigated. Dansylation significantly improved the LOD and LLOQ of oestrogens and their metabolites, by a factor of 10 for oestradiol and a factor of 5 for oestrone, but sensitivity of this updated method is not sufficient however for analysis of these oestrogens in human tears. Using gas chromatography-mass spectrometry (GC-MS) as an alternative technique to LC-MS, improved sensitivity for derivatised oestradiol is reported. This work demonstrates the need to develop higher sensitivity methods and points researchers towards specific MS ionisation techniques for future analysis of sex steroids in tears, in order to progress current understanding of the role of sex steroids in tear function and dry eye.
    Keywords:  GC-MS; LC-MS; Serum; Sex steroids; Tear film
  20. Bioinformatics. 2022 Oct 29. pii: btac706. [Epub ahead of print]
      SUMMARY: ADViSELipidomics is a novel Shiny app for preprocessing, analyzing, and visualizing lipidomics data. It handles the outputs from LipidSearch and LIQUID for lipid identification and quantification and the data from the Metabolomics Workbench. ADViSELipidomics extracts information by parsing lipid species (using LIPID MAPS classification) and, together with information available on the samples, performs several exploratory and statistical analyses. When the experiment includes internal lipid standards, ADViSELipidomics can normalize the data matrix, providing normalized concentration values per lipids and samples. Moreover, it identifies differentially abundant lipids in simple and complex experimental designs, dealing with batch effect correction. Finally, ADViSELipidomics has a user-friendly Graphical User Interface (GUI) and supports an extensive series of interactive graphics.AVAILABILITY AND IMPLEMENTATION: ADViSELipidomics is freely available at
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
  21. Metabolites. 2022 Oct 05. pii: 945. [Epub ahead of print]12(10):
      Omics approaches in plant analysis find many different applications, from classification to new bioactive compounds discovery. Metabolomics seems to be one of the most informative ways of describing plants' phenotypes, since commonly used methods such as liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance spectroscopy (NMR) could provide a huge amount of information about samples. However, due to high efficiency, many disadvantages arise with the complexity of the experimental design. In the present work, we demonstrate an untargeted metabolomics pipeline with the example of a Humulus lupulus classification task. LC-MS profiling of brewing cultivars samples was carried out as a starting point. Hierarchical cluster analysis (HCA)-based classification in combination with nested feature selection was provided for sample discrimination and marker compounds discovery. Obtained metabolome-based classification showed an expected difference compared to genetic-based classification data. Nine compounds were found to have the biggest classification power during nested feature selection. Using database search and molecular network construction, five of them were identified as known hops bitter compounds.
    Keywords:  Humulus lupulus; machine learning; metabolomics; untargeted profiling
  22. J Chromatogr A. 2022 Oct 18. pii: S0021-9673(22)00758-0. [Epub ahead of print]1684 463567
      In this study, we developed and validated a simple, fast and sensitive LC-MS/MS method for the measurement of tetrodotoxin (TTX) in human plasma. Three HILIC-type solid phase extraction (SPE) carriers (PSA, silica, Siphila i HILIX) with different stationary phase functional groups were compared. The Siphila i HILIX SPE plate containing multi-carboxyl groups was finally selected due to obviously better extraction recovery of TTX (about 80% of recovery from plasma samples) than the other two and no significant matrix effects were observed, which was speculated to have mixed-mode synergistic effects of hydrophilic interaction and ion exchange. 100μL plasma sample was precipitated rapidly with acetonitrile containing 1% trichloroacetic acid, and filtrates were loaded onto Siphila i HILIX 96 well SPE plate. After washed with 95% acetonitrile, TTX was eluted with 200μL of 50% acetonitrile containing 1% trichloroacetic acid. 2μL of elution solution was directly injected into LC-MS/MS and the total run time on a BEH amide column was 4.5 min. The method avoids the evaporation and ultrafiltration processes which is simple and timesaving (<30 min). TTX and internal standard (arginine-15N4) were monitored in positive mode using m/z 320.3→162.2 (quantification transition for TTX), 320.3→284.1 (confirmation transition for TTX) and 179.2→63.0 (transition for IS), respectively. The method was linear in the range of 0.1-20 ng/mL for TTX with the low limit of quantification (S/N > 10) of 0.1 ng/mL; the intra- and inter-assay accuracies were in the range of 98.5%-99.8% (relative standard deviations, RSDs ≤ 5.92%) and 98.8-99.5% (RSDs ≤ 6.23%), respectively. Biases of spiking analysis were ranged from -7.00% to 7.43% for healthy human plasma samples (RSDs ≤ 8.83%) and from -5.00% to 3.93% for hemolytic, high triglyceride, high cholesterol and high bilirubin plasma samples (RSDs ≤ 6.40%), which proved the good anti-interference property of the method. The results showed that the method is sensitive, accurate, specific, reliable, and can be used to monitor the concentration of TTX in plasma to meet the needs of clinical research and poisoning screening.
    Keywords:  Human plasma; Hydrophilic-interaction/ion-exchange; LC-MS/MS; Mixed-mode solid phase extraction; Tetrodotoxin
  23. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Oct 13. pii: S1570-0232(22)00397-X. [Epub ahead of print]1212 123493
      Periprosthetic joint infection is a challenging infection involving the joint prosthesis and adjacent tissue, such as synovial fluid, synovial tissue, and bone tissue. The current treatment consists of multiple surgical revisions and long-term antibiotic therapy. Treatment failure can cause poor functional outcome and reduced quality of life. Further research on the extent of antibiotic penetration into the infected tissues is of great importance. Our work aimed to develop and validate a novel ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the determination of the commonly administered antibiotics vancomycin and clindamycin in plasma and synovial fluid. An extraction procedure consisting of zinc sulfate precipitation and dilution with eluent was used for both analytes. Chromatographic separation was performed on a Waters Acquity UPLC HSS T3 C18 column (1.8 µm, 2.1 × 100 mm), and quantification was carried out by a Waters Xevo TQ-S micro mass spectrometer. Stable isotope-labeled vancomycin-d10 served as internal standard. The method validation was performed based on the guidelines of the EMA and FDA. The calibration curves were linear over the range of 0.5-50 mg/L, with a coefficient of determination above 0.990. The validation results for precision and accuracy, specificity, matrix effects and stability were all within the acceptance range. An accurate and rapid method for the simultaneous quantification of vancomycin and clindamycin in human plasma and synovial fluid on the UPLC-MS/MS was developed, optimized and validated. The analysis has a run time of 5.2 min and 50 µL sample volume is needed. This developed method was successfully applied in eight patients with PJI and is suitable to determine the exposure of antibiotics in plasma and synovial fluid in patients during current PK/PD studies.
    Keywords:  Clindamycin; Liquid-chromatography; Mass spectrometry; Periprosthetic joint infection; Synovial fluid; Vancomycin
  24. Anal Chem. 2022 Oct 28.
      Inositol and inositol phosphates (IPx) are central metabolites. Their accurate quantitative analysis in complex biological samples is challenging due to lengthy sample preparation procedures, sample losses by strong adsorption to surfaces, and unpredictable matrix effects. Currently, U13C-inositol and U13C-IPx are not available from commercial sources. In this study, we developed a method that is capable of generating U13C-inositol and U13C-IPx. An inositol-independent cell line L929S was cultured in inositol-free medium supplemented with U13C-glucose. Inositol contamination in FBS was observed as the critical parameter for labeling efficiency (LE). A balance between cell growth and LE was achieved by adopting a two-step labeling strategy. In the first step, a LE of 90% could be obtained by normal cell growth in the long-term. Cells were then cultured in a second step in ultra-labeling medium for improved LE for a short duration before harvesting. The generated U13Canalogs were of high isotopic purity (>99%). Utilized as internal standards spiked before sample preparation in biological applications, U13Canalogs can effectively compensate sample loss during sample preparation as well as the matrix effect during electrospray ionization. An exemplary pharmacological study was conducted with phospholipase C inhibitor and activator to document the great utility of the prepared stable isotope-labeled internal standards in elucidating the PLC-dependent IP code. U13CIPx are used as internal standards to generate quantitative profiles of IPx in HeLa cell samples after treatment with PLC inhibitor and activator. This established method generating U13Canalogs is cost-effective, robust, and reproducible, which can facilitate quantitative studies of inositol and IPx in biological scenarios.
  25. Toxins (Basel). 2022 Sep 20. pii: 651. [Epub ahead of print]14(10):
      Mycotoxin contamination of foodstuffs is a health concern worldwide and monitoring human exposure to mycotoxins is a key concern. Most mycotoxins and their metabolites are excreted in urine, but a reliable detection method is required, considering the low levels present in this biological sample. The aim of this work is to validate a sensitive methodology capable of simultaneously determining ten targeted mycotoxins as well as detecting untargeted ones by using Liquid Chromatography coupled to Quadrupole Time of Flight Mass Spectrometry (LC-Q-TOF-MS). The targeted mycotoxins were: enniatin A, B, A1, and B1, beauvericine, aflatoxin B1, B2, G1 and G2, and ochratoxin A. Several extraction procedures such as liquid-liquid extraction, dilute and shoot, and QuEChERS were assessed. Finally, a modified simple QuEChERS extraction method was selected. Creatinine adjustment and matrix-matched calibration curves are required. The limit of detection and limit of quantification values ranged from 0.1 to 1.5 and from 0.3 to 5 ng/mL, respectively. Recoveries achieved were higher than 65% for all mycotoxins. Later, the method was applied to 100 samples of women's urine to confirm the applicability and determine their internal exposure. The untargeted mycotoxins most found were trichothecenes, zearalenones, and ochratoxins.
    Keywords:  biomonitoring; mycotoxins; simple extraction; untargeted; women urine
  26. Toxics. 2022 Oct 18. pii: 619. [Epub ahead of print]10(10):
      Synthetic cannabinoids, a class of psychoactive compounds, are controlled as new psychoactive substances (NPSs) identified by the early warning system (EWS) of the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). At present, several new synthetic cannabinoids have appeared in the illegal drug market, including 4-methylnaphthalen-1-yl-(1-pentylindol-3-yl) methanone (JWH-122), methyl (1-(5-fluoropentyl)-1H-indazole-3-carbonyl)-L-valinate (5F-AMB), and methyl 2-(1-(4-fluorobenzyl)-1Hindazole-3-carboxamido)-3-methylbutanoate (AMB-FUBINACA). A convenient, rapid, and highly sensitive analytical method was developed to determine three synthetic cannabinoids in rat plasma and urine. The liquid chromatography tandem mass spectrometry (LC-MS/MS) method was optimized and validated to analyze the three synthetic cannabinoids in rat plasma and urine. The method identified intra-assay precision (1.3-9.0% and 2.8-6.7%), inter-assay precision (3.0-8.6% and 3.9-8.8%), limits of detection (0.003-0.004 ng/mL and 0.00125-0.002 ng/mL) and quantification (0.012-0.016 ng/mL and 0.003-0.005 ng/mL), recovery (95.4-106.8% and 92.0-106.8%) for rat plasma and urine, and the matrix effect (93.4-118.0%) for rat urine, and the correlation coefficients were above 0.99 in the linear range. The established LC-MS/MS method was successfully used to simultaneously detect the JWH-122 and 5F-AMB in rat plasma and JWH-122, 5F-AMB, and AMB-FUBINACA in rat urine. The present study provides methodological support for internal exposure assessment of three synthetic cannabinoids and promotes the quantitative analysis and technical supervision of synthetic cannabinoids.
    Keywords:  4-methylnaphthalen-1-yl-(1-pentylindol-3-yl) methanone; LC-MS/MS; methyl (1-(5-fluoropentyl)-1H-indazole-3-carbonyl)-L-valinate; methyl 2-(1-(4-fluorobenzyl)-1H-indazole-3-carboxamido)-3-methylbutanoate; synthetic cannabinoids
  27. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Oct 14. pii: S1570-0232(22)00408-1. [Epub ahead of print]1212 123503
      Vitamin B6 and its metabolites play a crucial role in the development and interaction of brain metabolism. Following diagnostic improvements additional inherited disorders in vitamin B6 metabolism have been identified, most of them leading to a severe epileptic disorder accompanied by progressive neurological deficits including intellectual disability and microcephaly. Since early treatment can improve the outcome, fast and reliable detection of metabolic biomarkers is important. Therefore, the analysis of vitamin B6 metabolites has become increasingly important, but is, however, still challenging and limited to a few specialized laboratories. Until today, vitamin B6 metabolites are measured by liquid chromatography tandem mass spectrometry (LC-MS/MS) using trichloroacetic acid for protein precipitation. In this work, we present the development and validation of a new, accurate and reliable method for analysis and quantification of the vitamin B6 vitamers pyridoxal 5́-phosphate (PLP), pyridoxal (PL), pyridoxine (PN), pyridoxamine (PM) and pyridoxic acid (PA) in human CSF samples using acetonitrile for protein precipitation. The method is based on ultra-performance liquid chromatography-tandem mass spectrometry using electrospray ionization (UPLC-ESI-MS/MS). The calibration was performed in surrogate matrix Ringer solution and metabolites were quantified by their corresponding isotopically labelled internal standards. A protein precipitation by acetonitrile was applied greatly improving chromatographic separation of the metabolites in a 4.7 min chromatographic run. The method was validated following the European Medical Agency (EMA) and Food and Drug Administration (FDA) guidelines for bioanalytical method validation. The metabolites were quantified from 5 to 200 nmol/L with a seven-point calibration curve and minimum coefficient of regression of 0.99. The validation was performed with quality control samples at four concentration levels with surrogate matrix ringer solution and pooled CSF material. Within- and inter-day accuracy and precision in Ringer solution were within 85.4 % (PLP) and 114.5 % (PM) and from 2.6 % (PA) to 16.5 % (PLP). Within- and inter-day accuracy and precision in pooled CSF material were within 90.5 % (PN) and 120.1 % (PL) and from 1.7 % (PA) to 19.0 % (PM). The method was tested by measuring of 158 CSF samples to determine reference ranges. The B6 vitamers PLP and PL were determined in all CSF samples above 5 nmol/L while PN, PM and PA showed concentrations below or near LOQ. Probable supplementation of PLP was detected in eight CSF samples, which revealed high concentrations of PM, PN, PL, or PA, whereas PLP was in the reference range or slightly elevated. The method is suitable for the application within a routine diagnostic laboratory.
    Keywords:  Cerebrospinal fluid CSF; Pyridoxal 5́-phosphate; Pyridoxine-dependent epilepsy; UPLC-ESI-MS/MS; Vitamin B(6)
  28. ACS Meas Sci Au. 2022 Oct 19. 2(5): 466-474
      Mass spectrometry imaging (MSI) enables label-free mapping of hundreds of molecules in biological samples with high sensitivity and unprecedented specificity. Conventional MSI experiments are relatively slow, limiting their utility for applications requiring rapid data acquisition, such as intraoperative tissue analysis or 3D imaging. Recent advances in MSI technology focus on improving the spatial resolution and molecular coverage, further increasing the acquisition time. Herein, a deep learning approach for dynamic sampling (DLADS) was employed to reduce the number of required measurements, thereby improving the throughput of MSI experiments in comparison with conventional methods. DLADS trains a deep learning model to dynamically predict molecularly informative tissue locations for active mass spectra sampling and reconstructs high-fidelity molecular images using only the sparsely sampled information. Experimental hardware and software integration of DLADS with nanospray desorption electrospray ionization (nano-DESI) MSI is reported for the first time, which demonstrates a 2.3-fold improvement in throughput for a linewise acquisition mode. Meanwhile, simulations indicate that a 5-10-fold throughput improvement may be achieved using the pointwise acquisition mode.
  29. Metabolites. 2022 Oct 21. pii: 1002. [Epub ahead of print]12(10):
      Metabolomics has advanced from innovation and functional genomics tools and is currently a basis in the big data-led precision medicine era. Metabolomics is promising in the pharmaceutical field and clinical research. However, due to the complexity and high throughput data generated from such experiments, data mining and analysis are significant challenges for researchers in the field. Therefore, several efforts were made to develop a complete workflow that helps researchers analyze data. This paper introduces a review of the state-of-the-art computer-aided tools and databases in metabolomics established in recent years. The paper provides computational tools and resources based on functionality and accessibility and provides hyperlinks to web pages to download or use. This review aims to present the latest computer-aided tools, databases, and resources to the metabolomics community in one place.
    Keywords:  computer; databases; metabolite; metabolomics; omics; pathway analysis; tools
  30. Zhonghua Yu Fang Yi Xue Za Zhi. 2022 Oct 06. 56(10): 1520-1526
      Due to its ultra-high sensitivity, specificity and throughput, liquid chromatography tandem mass spectrometry (LC-MS/MS) has become an important analytical tool in clinical laboratories in quantifying various small molecules, such as vitamins, bile acids, steroids and other internal metabolites relevant to maternal diseases. As an effective means of screening and diagnosing diseases in preventive medicine, LC-MS/MS has been widely used in maternal and child health, contributing to the reduction of the incidence of maternal and child diseases and premature morbidity and mortality. At present, LC-MS/MS is an emerging and powerful platform in laboratory testing in China, facing both challenges and opportunities. In this article, the representative applications in the field of maternal and child health are summarized and discussed, along with the major hurdles of LC-MS/MS in clinical recognition and implementation.
  31. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Oct 14. pii: S1570-0232(22)00388-9. [Epub ahead of print]1212 123484
      A rapid, high-performance, and accurate on-line TurboFlow ultra high performance liquid chromatography-quadrupole/Orbitrap high resolution mass spectrometry method was developed for the analysis of 46 per- and polyfluoroalkyl substances (PFAS), including 17 perfluoroalkylcarboxylic acids, 15 perfluoroalkylsulfonates, 3 fluorinated telomer sulfonates, 2 perfluoroalkyl unsaturated carboxylates, 2 perfluorooctanesulfonamidoacetic acid, 3 perfluorooctanesulfonamides, hexafluoropropylene oxide-dimer acid, ammonium 4,8-dioxa-3H-perfluorononanoate, 6:2 chlorinated polyfluorinated ether sulfonate (Cl-PFESA), and 8:2 Cl-PFESA, in human serum. The TurboFlow column, mobile phase, sample injection volume, loading flow rate, and elution time were optimized. The linearities of matrix calibration curves, method limits of quantification, accuracy and precision were investigated for method validation. Serum samples (50 μL) were precipitated with acetonitrile and directly injected into the system. The method showed good linearity (R2 > 0.99), satisfactory recoveries (matrix-spiked recoveries range: 68.9%-115.7%), good precision (relative standard deviation ranges: 1.2%-12.1%) and a low method limit of quantification (0.1-1 ng mL-1). The developed method is rapid, accurate and convenient for large-scale biomonitoring of PFAS in humans. Fifty real serum samples from China were analyzed and the results showed that br-perfluorooctanesulfonate (PFOS) accounted for approximately 30% of the ∑PFOS in serum, which suggested there was high exposure to 6:2 Cl-PFESA.
    Keywords:  Human serum; On-line TurboFlow SPE; PFAS isomers; Per- and polyfluoroalkyl substances (PFAS)
  32. Methods Enzymol. 2022 ;pii: S0076-6879(22)00302-0. [Epub ahead of print]676 239-278
      The plant hormone auxin plays important roles throughout the entire life span of a plant and facilitates its adaptation to a changing environment. Multiple metabolic pathways intersect to control the levels and flux through indole-3-acetic acid (IAA), the primary auxin in most plant species. Measurement of changes in these pathways represents an important objective to understanding core aspects of auxin signal regulation. Such studies have become approachable through the technologies encompassed by targeted metabolomics. By monitoring incorporation of stable isotopes from labeled precursors into proposed intermediates, it is possible to trace pathway utilization and characterize new biosynthetic routes to auxin. Chemical inhibitors that target specific steps or entire pathways related to auxin synthesis aid these techniques. Here we describe methods for obtaining stable isotope labeled pathway intermediates necessary for pathway analysis and quantification of compounds. We describe how to use isotope dilution with methods employing either gas chromatography or high performance liquid chromatography mass spectrometry techniques for sensitive analysis of IAA. Complete biosynthetic pathway analysis in seedlings using multiple stable isotope-labeled precursors and chemical inhibitors coupled with highly sensitive liquid chromatography-mass spectrometry methods are described that allow rapid measurement of isotopic flux into biochemical pools. These methods should prove to be useful to researchers studying aspects of the auxin metabolic network in vivo in a variety of plant tissues and during various environmental conditions.
    Keywords:  Auxin biosynthesis; Isotope dilution analysis; Mass spectrometry; Metabolic inhibitors; Pathway analysis; Stable isotope labeling
  33. Biomed Pharmacother. 2022 Oct 21. pii: S0753-3322(22)01288-4. [Epub ahead of print]156 113899
      Cannabinoid derivates have been largely used for different medical purpose. In the literature, several methods capable of separating THC and its principles metabolites are described, although Δ8- and Δ9-THC separation has not been completely achieved. THC metabolism has not been fully understood and metabolites plasma distribution in healthy and pathological patients remains to further deepen. The aim of this study was the validation of UHPLC-MS/MS method for the quantification of 10 cannabinoids in human plasma, as important tool for improving clinical efficacy of cannabis administration. Obtained results were in accordance with recommendations of ICH Harmonised Guideline for bioanalytical method validation, showing a good linearity, optimal accuracy as well as satisfactory results in terms of intra-day and inter-day precision and matrix effect. Furthermore, blood sampling study was performed to investigate the better collection method. Optimal separation of Δ-9-tetrahydrocannabinol (Δ9-THC), Δ8-tetrahydrocannabinol (Δ8-THC) was obtained. The present method showed optimal linearity and satisfactory results in terms of specificity and selectivity. Recovery was between 92.0% and 96.5% for all analytes. The matrix-effect showed good performance; no carry over was observed. Cannabinoid metabolites present in higher plasma concentrations were: 11-Hydroxy-Δ9-tetrahydrocannabinol, 11-Nor-9carboxy-Δ9-tetrahydrocannabinol and THC-COOH-glucuronide. Method performance makes it suitable for routine purposes and a potential tool for therapeutic ranges definition. The present work will be used to test several samples in a long-term clinical study, paving the way for further future works.
    Keywords:  Cannabinoids; Liquid chromatography; Medical cannabis; Tandem mass spectrometry; Δ8-THC; Δ9-THC
  34. Anal Chim Acta. 2022 Nov 15. pii: S0003-2670(22)01078-9. [Epub ahead of print]1233 340507
      A novel approach to the determination of sulfonamides in milk based on the Lab-In-Syringe technique is presented. The method involves automated salting-out liquid-liquid extraction of the analytes, allowing simultaneous sample deproteination without requiring centrifugation or manual sample handling. The procedural parameters, including salt type, solvent-to-sample ratio, and salt solution volume, were studied. The extracts obtained were diluted in situ and transferred to online coupled liquid chromatography for analyte separation carried out in parallel to the subsequent extraction. In this way, a sample throughput of approximately 6 h-1 was achieved. The detection limits ranged from 25 to 32 μg L-1 using a 500 μL milk sample and spectrophotometric detection. The applicability of the developed method to sample analysis was proven by recovery values ranging from 73.2% to 94.1% (86.3% on average) for milk samples of different fat content spiked at 3 μg mL-1 level. Straightforward automation of one of the most laborious preparation steps in food analysis, i.e., deproteination, was demonstrated.
    Keywords:  Automated centrifugation-less sample deproteinization; Lab-in-syringe; Online coupled sample preparation to liquid chromatography; Protein precipitation; Salting out homogeneous liquid-liquid extraction; Sulfonamides in milk
  35. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Oct 10. pii: S1570-0232(22)00389-0. [Epub ahead of print]1211 123485
      Abnormal salivary amino acid (AA) levels may indicate dysfunction of the body. Being noninvasive, sampling easily and cost-effective of saliva, a rapid, precise and simple analysis method has become very important for quantitative salivary AA profiles. After one-step to precipitate protein, the resultant extraction was derived with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) within 10 min. Quantitation of AA profile was achieved within 6 min in a single run by ultra-high performance liquid chromatography coupled with a single quadrupole mass spectrometry (UHPLC-QDA detector). The method was validated with acceptable accuracy ranging from 80.33 % to 122.31 %, appropriate linearity with the coefficient (R2) more than 0.991, good intra- and inter-day precision, repeatability and stability (RSD < 15 %). The recoveries at three different spiked concentrations ranged over 79.18 %-125.36 % while the matrix effect was from -19.86 % to 11.95 %. This simple, rapid and robust method was successfully applied to quantify human salivary 30 amino acids, in which the levels of taurine, γ-aminobutyric acid, methionine and tryptophan in healthy people were close to the LOQs. Besides, the levels of histidine and cystine were not able to be measured due to their relatively high LOQs, which were considered as the limitations of this developed method.
    Keywords:  Amino acids; Derivatization; Saliva; UHPLC-QDA detector
  36. Anal Chem. 2022 Oct 25.
      A major obstacle for reusing and integrating existing data is finding the data that is most relevant in a given context. The primary metadata resource is the scientific literature describing the experiments that produced the data. To stimulate the development of natural language processing methods for extracting this information from articles, we have manually annotated 100 recent open access publications in Analytical Chemistry as semantic graphs. We focused on articles mentioning mass spectrometry in their experimental sections, as we are particularly interested in the topic, which is also within the domain of several ontologies and controlled vocabularies. The resulting gold standard dataset is publicly available and directly applicable to validating automated methods for retrieving this metadata from the literature. In the process, we also made a number of observations on the structure and description of experiments and open access publication in this journal.
  37. Rapid Commun Mass Spectrom. 2022 Oct 24. e9422
      RATIONALE: Small amounts of biofluid samples are frequently found at crime scenes, however existing gold standard methods such as LC-MS frequently require destructive extraction of the sample before a time-consuming analysis which puts strain on forensic analysis providers and can preclude further sample analysis. This study presents the application of Sheath Flow Probe Electrospray Ionization - Mass Spectrometry (sfPESI-MS) to the direct analysis of drug metabolites in dried blood spots as a high throughput, minimally destructive alternative.METHODS: A rapid direct analysis method using a sfPESI ionisation source coupled to an Orbitrap Exactive mass spectrometer was applied to detect cocaine metabolites (benzoylecgonine, BZE, cocaethylene, CE, and ecgonine methyl ester, EME) from dried blood spots. An optimisation study exploring the use of different chemical modifiers (formic acid and sodium acetate) in the sfPESI probe extraction solvent was conducted to enhance the sensitivity and reproducibility of the sfPESI-MS method.
    RESULTS: Optimization of the extraction solvent significantly enhanced the sensitivity and reproducibility of the sfPESI-MS method. A quantitative response over a 5-point calibration range 0.5 to 10 μg/mL was obtained for benzoylecgonine (R2 = 0.9979) and cocaethylene (R2 = 0.9948). Limits-of-detection (LoD) of 1.31, 0.29 and 0.15 μg/mL were achieved for EME, BZE and CE respectively from 48-hour aged dried blood spots with % RSD across the calibration range ranging between 19-28 % for [BZE+H]+ , 13-21 % for [CE+H]+ and 12-29 % for [EME+H]+ .
    CONCLUSIONS: A rapid (< 20 seconds) quantitative method for the direct analysis of cocaine metabolites from dried blood spots which requires no prior sample preparation was developed. While the LoD achieved for BZE (LoD: 0.29 μg/mL) was above the UK threshold limit of exposure for drug driving (0.05 μg/mL), the method may be suitable for use in identifying overdose in forensic analysis.
  38. Anal Chem. 2022 Oct 27.
      High-throughput analysis in fields such as industrial biotechnology, combinatorial chemistry, and life sciences is becoming increasingly important. Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique providing exhaustive molecular information on complex samples. Flow NMR in particular is a cost- and time-efficient method for large screenings. In this study, we have developed a novel 3.0 mm inner diameter polychlorotrifluoroethylene (PCTFE) flow cell for a segmented-flow analysis (SFA) - NMR automated platform. The platform uses FC-72 fluorinated oil and fluoropolymer components to achieve a fully fluorinated flow path. Samples were repeatably transferred from 96-deepwell plates to the flow cell by displacing a fixed volume of oil, with a transfer time of 42 s. 1H spectra were acquired fully automated with 500 and 600 MHz NMR spectrometers. The spectral performance of the novel PCTFE cell was equal to that of commercial glass cells. Peak area repeatability was excellent with a relative standard deviation of 0.1-0.5% for standard samples, and carryover was below 0.2% without intermediate washing. The sample temperature was conditioned by using a thermostated transfer line in order to reduce the equilibration time in the probe and increase the throughput. Finally, analysis of urine samples demonstrated the applicability of this platform for screening complex matrices.
  39. Clin Chem Lab Med. 2022 Oct 26.
      Mass spectrometry (MS) has been a gold standard in the clinical laboratory for decades. Although historically refined to limited areas of study such as neonatal screening and steroid analysis, technological advancements in the field have resulted in MS becoming more powerful, versatile, and user-friendly than ever before. As such, the potential for the technique in clinical chemistry has exploded. The past two decades have seen advancements in biomarker detection for disease diagnostics, new methods for protein measurement, improved methodologies for reliable therapeutic drug monitoring, and novel technologies for automation and high throughput. Throughout this time, Clinical Chemistry and Laboratory Medicine has embraced the rapidly developing field of mass spectrometry, endeavoring to highlight the latest techniques and applications that have the potential to revolutionize clinical testing. This mini review will highlight a selection of these critical contributions to the field.
    Keywords:  GC-MS; LC-MS; mass spectrometry
  40. J Proteome Res. 2022 Oct 26.
      In recent years, the concept of cell heterogeneity in biology has gained increasing attention, concomitant with a push toward technologies capable of resolving such biological complexity at the molecular level. For single-cell proteomics using Mass Spectrometry (scMS) and low-input proteomics experiments, the sensitivity of an orbitrap mass analyzer can sometimes be limiting. Therefore, low-input proteomics and scMS could benefit from linear ion traps, which provide faster scanning speeds and higher sensitivity than an orbitrap mass analyzer, however at the cost of resolution. We optimized an acquisition method that combines the orbitrap and linear ion trap, as implemented on a tribrid instrument, while taking advantage of the high-field asymmetric waveform ion mobility spectrometry (FAIMS) pro interface, with a prime focus on low-input applications. First, we compared the performance of orbitrap- versus linear ion trap mass analyzers. Subsequently, we optimized critical method parameters for low-input measurement by data-independent acquisition on the linear ion trap mass analyzer. We conclude that linear ion traps mass analyzers combined with FAIMS and Whisper flow chromatography are well-tailored for low-input proteomics experiments, and can simultaneously increase the throughput and sensitivity of large-scale proteomics experiments where limited material is available, such as clinical samples and cellular subpopulations.
    Keywords:  FAIMS-MS; data acquisition; low-input applications; mass spectrometry; peptide identification optimization; ultrasensitive proteomics
  41. Metabolites. 2022 Oct 19. pii: 993. [Epub ahead of print]12(10):
      Plant samples are potential sources of physiologically active secondary metabolites and their classification is an extremely important task in traditional medicine and other fields of research. In the production of herbal drugs, different plant parts of the same or related species can serve as adulterants for primary plant material. The use of highly informative and relatively easily accessible tools, such as liquid chromatography and low-resolution mass spectrometry, helps to solve these tasks by means of fingerprint analysis. In this study, to reveal specific plant part features for 20 species from one family (Apiaceae), and to preserve the maximum information content, two approaches are suggested. In both cases, minimal raw data pretreatment, including rescaling of time and m/z axes and cutting off some uninformative regions, was applied. For the support vector machine (SVM) method, tensor unfolding was required, while neural networks (NNs) were able to work directly with squared heatmaps as input data. Moreover, five data augmentation variants are proposed, to overcome the typical problem of a lack of data. As a result, a comparable F1-score close to 0.75 was achieved by SVM and two employed NN architectures. Eight marker compounds belonging to chlorophylls, lipids, and coumarin apio-glucosides were tentatively identified as characteristic of their corresponding sample groups: roots, stems, leaves, and fruits. The proposed approaches are simple, information-saving and can be applied to a broad type of tasks in metabolomics.
    Keywords:  Apiaceae; augmentation; neural networks; raw LC-MS data; support vector machine
  42. Anal Methods. 2022 Oct 27.
      2-Phenoxyethanol (PhE) is used as a broad-spectrum preservative in several consumer products like cosmetics and cleaning agents. To enable the analysis and assessment of human exposure to PhE, a fast and sensitive LC-MS/MS method for the quantification of two PhE metabolites, namely phenoxyacetic acid (PhAA) and 4-hydroxyphenoxyacetic acid (4-OH-PhAA) in human urine and blood was developed and validated. The method is based on liquid chromatography combined with tandem mass spectrometry (LC-MS/MS). Sample preparation was different for both matrices: either a simple "dilute&shoot"-approach for urine samples or a liquid-liquid-extraction (LLE) for blood samples was used. The limit of quantification (LOQ) is 10 μg L-1 and 6 μg L-1 for PhAA and 20 μg L-1 and 10 μg L-1 for 4-OH-PhAA in urine and blood, respectively. The method was applied to urine samples of 153 persons without occupational exposure to PhE and to blood samples of 7 additional volunteers. In blood, PhAA was detected in 57% of all samples (range: <LOQ - 0.017 mg L-1), while 4-OH-PhAA was not detectable. In contrast to that, PhAA was found in 99% and 4-OH-PhAA in 95% of all urine samples. The median concentrations in urine were 0.99 mg L-1 (range: <LOQ - 53.83 mg L-1) for PhAA and 0.11 mg L-1 (<LOQ - 4.98 mg L-1) for 4-OH-PhAA, respectively. Analyses after acid hydrolysis showed that both urinary metabolites are excreted unconjugated.