bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2019–11–24
twenty-one papers selected by
Sofia Costa, Cold Spring Harbor Laboratory



  1. Biomed Chromatogr. 2019 Nov 22. e4759
      Temocillin is a β-lactamase-resistant penicillin used for the treatment of multiple drug-resistant Gram-negative bacteria. To maximize efficacy and avoid adverse effects, dose regimen had to be quickly adjusted to the clinical situations. This necessitated to develop a rapid, reliable and accurate analytical method. Temocillin and the stable isotopically labeled internal standard ([13 C6 ]-amoxicillin) were extracted from either serum or cerebrospinal fluid by a turbulent flow liquid chromatographic method and eluted onto a octadecyl-silica phase with polar endcapping. Mass spectrometry was conducted using exact mass determination method by an electrospray positive ionization high-resolution mass spectrometry. The LLOQ and ULOQ of the present method were determined to be 0.4 and 200 μg/mL for both serum and CSF samples, respectively. The total analysis time was less than 7 minutes. The recovery range from 87.7 to 120.8 %. Intra- and inter-day precision and trueness were tested at four concentration levels: 0.4, 8, 40 and 160 μg/mL. Values were 6.33 ±1.53%, 8.8 ±1.3%, 8.8 ±0.36% and 2.1 ±0.76%, 5.0 ± 0.54%, 9.9 ±1.0%, 5.8 ±1.6 and 0.1 ±1.1%, for inter-day and intra-day analysis, respectively. Temocillin was found to be stable under all relevant laboratory conditions. The method was cross-validated with a microbiological assay. This method is suitable for accurate measurement of temocillin concentration in small volumes of serum or CSF. Thanks to the on-line extraction procedure, the overall analytical time is compatible with high-throughput analysis for clinical application.
    Keywords:  bioanalysis; high-resolution mass spectroscopy; temocillin; turbulent flow liquid extraction
    DOI:  https://doi.org/10.1002/bmc.4759
  2. J Chromatogr A. 2019 Nov 06. pii: S0021-9673(19)31115-X. [Epub ahead of print] 460686
      Being performance enhancing hormones, endogenous anabolic androgenic steroids (EAAS) are banned from most competitive sports by the World Anti-doping Agency (WADA). In anti-doping control laboratories, routine assays are mainly performed on urine samples of athletes in and out of competitions. Serum constitutes a promising alternative to urine as it is less subjected to manipulation or contamination that may influence the method sensitivity. The simultaneous determination of EAAS including conjugated metabolites using LC-MS is very challenging due to their contradicting chemical behaviors at the ionization interface of the mass spectrometer. This may prejudice their detection or limit the method sensitivity. Herein, we have addressed these challenges and developed a new method for the simultaneous determination of unconjugated, sulphate- and glucuronide-conjugated EAAS (Androsterone, Etiocholanolone, testosterone, epitestosterone, dihydrotestosterone, dehydroepiandrosterone, androstenedione and 17a-hydroxyprogesterone) in human serum using ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS). The use of mass spectrometric detection in full scan mode facilitated the study of the most versatile adducts for detection and quantitation. A solid phase extraction method was developed for the sample preparation prior to analysis. The method limits of quantitation ranged from 0.006 to 7.904 ng/mL and the recoveries ranged from 70.2% to 96.5%. The method calibration was performed in untreated serum representing realistic matrix composition with correlation coeffecients ranged from 0.9859 to 0.9988. Finally, the serum-levels of the investigated steroids were determined in 4 male and 1 female human subjects to provide estimates of baseline levels based on individual values.
    Keywords:  Chromatography; Doping; Endogenous Anabolic androgenic steroids; Mass spectrometry; Solid phase extraction; UHPLC
    DOI:  https://doi.org/10.1016/j.chroma.2019.460686
  3. Curr Protoc Plant Biol. 2019 Dec;4(4): e20100
      Metabolomics has grown into one of the major approaches for systems biology studies, in part driven by developments in mass spectrometry (MS), providing high sensitivity and coverage of the metabolome at high throughput. Untargeted metabolomics allows for the investigation of metabolic phenotypes involving several hundreds to thousands of metabolites. In this approach, all signals in a mass chromatogram are processed in an unbiased way, allowing for a deeper investigation of metabolic phenotypes, but also resulting in significantly more complex data processing and post-processing steps. In this article, we discuss all the intricacies involved in extracting and analyzing metabolites by chromatography coupled to MS, as well as the processing and analysis of such datasets. © 2019 The Authors. Basic Protocol 1: Metabolite extraction for LC-MS Alternate Protocol: Methyl tert-butyl ether (MTBE) extraction for multiple mass spectrometry platforms (GC-polar, LC-polar, LC-lipid) Basic Protocol 2: LC-MS analysis Support Protocol 1: GC-MS derivatization and analysis Support Protocol 2: Lipid analysis Basic Protocol 3: LC-MS data processing Basic Protocol 4: Data analysis Basic Protocol 5: Metabolite annotation Support Protocol 3: Molecular networking using MetNet Support Protocol 4: Co-injection of authentic standards.
    Keywords:  LC-MS; metabolite annotation; metabolomics; molecular networking ; plant metabolomics; untargeted
    DOI:  https://doi.org/10.1002/cppb.20100
  4. J Sep Sci. 2019 Nov 20.
      Lung cancer is the leading type of cancer worldwide in terms of the number of new cases and is responsible for the largest number of deaths due to poor prognosis and difficult early detection. Due to its ability to detect numerous small molecular metabolites simultaneously, metabolomics has been widely used for the assessment of global metabolic changes in a living organism to discover candidate biomarkers for cancer diagnosis, investigate the development of cancer, and provide insights into the underlying pathophysiology. This review will mainly describe recent developments in lung cancer metabolomics in terms of early-stage detection, biomarker discovery and mechanism exploration by using nuclear magnetic resonance, liquid chromatography-mass spectrometry (MS), gas chromatography MS and capillary electrophoresis-MS in the last 10 years. The sample collection and metabolite extraction methods are also summarized. This article is protected by copyright. All rights reserved.
    Keywords:  Metabolomics; capillary electrophoresis- mass spectrometry; gas chromatography-mass spectrometry; liquid chromatography-mass spectrometry; lung cancer
    DOI:  https://doi.org/10.1002/jssc.201900736
  5. Biomed Chromatogr. 2019 Nov 21. e4756
      Currently, liquid chromatography-mass spectrometry (LC-MS) has various applications in different areas such as metabolomics, pharmacokinetics, and pathological studies. Yet, matrix effects resulted from co-existing constituents are a major problem for LC-MS(/MS). Moreover, technical problems and instrumental drifts may lead to ion abundance variance. Thus, an internal standard is required to guarantee the accuracy and precision of the method. Due to their limited number, isotope-coded derivatization (ICD) has been recently introduced to overcome this problem. For ICD, a stable heavy isotope-coded moiety is used for labeling the standard or the control sample and the formed products can act as internal standards. A light form of the reagent is used for labeling the sample. Then, both mixed and analyzed by LC-MS(/MS). This strategy permits the identification of different unknown analytes including potential metabolites and disease biomarkers. All these attributes lead to persistent growth in the applications of ICD LC-MS(/MS) in various biomedical branches. In this article we reviewed the ICD methods published in the last eight years for biomedical applications, as well, we briefly summarized other applications for environmental and food analyses as some of their used ICD reagents were further applied for analyzing biological specimens or have the potential for that.
    Keywords:  LC-MS; biomedical applications; functional groups; isotope-coded derivatization; metabolomics
    DOI:  https://doi.org/10.1002/bmc.4756
  6. Anal Biochem. 2019 Nov 17. pii: S0003-2697(19)31088-7. [Epub ahead of print] 113509
      Allantoin is an excellent biomarker of oxidative stress in humans as the main product of uric acid oxidation by reactive oxygen species. Yet, allantoin determination is still not routinely performed in clinical laboratories. Therefore, we developed a fast, simple, selective, and sensitive UHPLC-MS/MS method for allantoin determination in human serum using an isotopically labeled internal standard. Our analytical protocol provided high sensitivity by mass spectrometry detection and high throughput by HILIC-MS/MS analysis within 4 min, with one-step serum sample preparation approximately within 7 min. Lastly, our protocol was fully validated to demonstrate its reliability in allantoin determination in human serum. The method showed an excellent linear range from 0.05 to 100 μM, with precision ranging from 1.8 to 11.3% (RSD), and with accuracy (relative error %) within ±6.0%. The method was then applied to analyze the concentration of allantoin in serum samples from 71 patients with chronic gout without treatment with xanthine oxidase inhibitors. The median serum allantoin concentration in the cohort was 2.8 μM (n = 71). Overall, our simple analytical protocol has the potential to be easily implemented in clinical routine practice for monitoring allantoin as a key oxidative stress biomarker.
    Keywords:  Allantoin; Gout; Hydrophilic interaction liquid chromatography; Oxidative stress; Tandem mass spectrometry; Validation
    DOI:  https://doi.org/10.1016/j.ab.2019.113509
  7. Biomed Chromatogr. 2019 Nov 20. e4742
      Quantitation of drugs being used for the treatment of chronic lymphocytic leukemia (CLL) in various biological matrices during both pre-clinical and clinical development is very important and often in routine therapeutic drug monitoring. The first developed methods for quantitation was traditionally done on liquid chromatography (LC) in combination with either ultra violet or fluorescence detection. However, the emergence of LC with mass spectrometry in tandem in early 1990s has revolutionized the quantitation as it has provided better sensitivity and selectivity within a shorter run time, hence it became choice of method for the analysis of various drugs. In this review, an overview of reported various bioanalytical methods (HPLC or LC-MS/MS) for the quantification of drugs for the treatment of CLL is given along with applicability of these methods is critically discussed.
    Keywords:  HPLC; LC-MS/MS; bendamustine; bioanalytical methods; chlorambucil; cladribine; cyclophosphamide; fludarabine; ibrutinib; idelalisib; review
    DOI:  https://doi.org/10.1002/bmc.4742
  8. Methods Mol Biol. 2020 ;2083 209-219
      Carotenoids and carotenoids oxidative and enzymatic cleavage products called apocarotenoids are very important bioactive molecules in plants and humans, with different biological functions. Both central and noncentral carotenoid cleavage products have been reported to occur in food and in humans, where they may act as bioactive molecules with functions that were previously attributed to the parent carotenoid. However, relatively few studies are available in the literature on the apocarotenoid occurrence in food and biological fluids which were mainly based on liquid chromatographic separation approaches and even fewer reports are available on the carotenoid and apocarotenoid separation by a direct online supercritical fluid extraction-supercritical fluid chromatography with triple-quadrupole mass spectrometry detection (SFE-SFC-QqQ/MS) methodology. In comparison with offline approaches the online nature of the system drastically reduces the extraction time required in traditional solid/liquid extraction, which may require a few hours. Moreover, it reduces the analysis run time, as well as the risks of sample contamination and the possible occurrence of operator errors, improves run-to-run precision, and enables the setting of batch-type applications. The purpose of this contribution was to provide an updated description of the SFE-SFC-QqQ/MS methodology applied to carotenoid and apocarotenoid analysis in various matrices, although with a particular focus on the apocarotenoid applications.
    Keywords:  Apocarotenoids; Carotenoids; Mass spectrometry; SFE-SFC-QqQ/MS; Supercritical fluid chromatography; Supercritical fluid extraction
    DOI:  https://doi.org/10.1007/978-1-4939-9952-1_16
  9. Curr Alzheimer Res. 2019 Nov 21.
       OBJECTIVE: To characterize the specific metabolomics profiles in the outer membrane vesicles (OMVs) of patients with Alzheimer's disease (AD) and to explore potential metabolic biomarkers and their diagnostic roles.
    METHODS: Nine AD patients and age- and sex-matched healthy controls were enrolled, and feces were collected. OMVs were extracted, purified, and then analyzed using liquid chromatography-tandem mass chromatography (LC-MS/MS) method coupled with a series of multivariate statistical analyses.
    RESULTS: Remarkable differences were found between the OMVs from AD patients and those from healthy controls. A list of differential metabolites and several top-altered metabolic pathways were identified. The levels of aspartate, L-aspartate, imidazole-4-acetate and L-glutamate were confirmed to be highly upregulated in AD-OMVs. Other differential metabolites, such as arachidic acid, prostaglandin G2, and leukotriene B4, were also identified. Furthermore, the differential metabolites possessed higher areas under the ROC curve (AUCs).
    CONCLUSION: Metabolic activity is significantly altered in the OMVs from AD patients. This data might be helpful for identifying novel biomarkers and their diagnostic roles in AD. Furthermore, OMVs metabolomics analysis combined with GWAS could enrich our understanding of the genetic spectrum of AD and lead to early predictions and diagnosis and clinical applications of better AD treatments.
    Keywords:  Alzheimer's disease; Dementia; Genome-wide association studies; LC-MS/MS; Metabolomics; Outer membrane vesicles
    DOI:  https://doi.org/10.2174/1567205016666191121141352
  10. Anal Chem. 2019 Nov 20.
      Direct analyte probed nanoextraction (DAPNe) is a technique that allows extraction of drug and endogenous compounds from a discrete location on a tissue sample using a nano capillary filled with solvent. Samples can be extracted from a spot diameters as low as 6 µm. Studies previously undertaken by our group have shown that the technique can provide good precision (5%) for analysing drug molecules in 150 µm diameter areas of homogenised tissue, provided an internal standard is sprayed on to the tissue prior to analysis. However, without an isotopically labelled standard, the repeatability is poor, even after normalisation to and the spot area or matrix compounds. By application to tissue homogenates spiked with drug compounds, we can demonstrate that it is possible to significantly improve the repeatability of the technique by incorporating a liquid chromatography separation step. Liquid chromatography is a technique for separating compounds prior to mass spectrometry (LC-MS) which enables separation of isomeric compounds that cannot be discriminated using mass spectrometry alone, as well as reducing matrix interferences. Conventionally, LC-MS is carried out on bulk or homogenised samples, which means analysis is essentially an average of the sample and does not take into account discrete areas. This work opens a new opportunity for spatially resolved liquid chromatography mass spectrometry with precision better than 20%.
    DOI:  https://doi.org/10.1021/acs.analchem.9b02821
  11. Curr Protoc Bioinformatics. 2019 Dec;68(1): e86
      MetaboAnalyst (https://www.metaboanalyst.ca) is an easy-to-use web-based tool suite for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since its first release in 2009, MetaboAnalyst has evolved significantly to meet the ever-expanding bioinformatics demands from the rapidly growing metabolomics community. In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst supports a wide array of functions for statistical, functional, as well as data visualization tasks. Some of the most widely used approaches include PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), clustering analysis and visualization, MSEA (metabolite set enrichment analysis), MetPA (metabolic pathway analysis), biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. The current version of MetaboAnalyst (4.0) features a complete overhaul of the user interface and significantly expanded underlying knowledge bases (compound database, pathway libraries, and metabolite sets). Three new modules have been added to support pathway activity prediction directly from mass peaks, biomarker meta-analysis, and network-based multi-omics data integration. To enable more transparent and reproducible analysis of metabolomic data, we have released a companion R package (MetaboAnalystR) to complement the web-based application. This article provides an overview of the main functional modules and the general workflow of MetaboAnalyst 4.0, followed by 12 detailed protocols: © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: Data uploading, processing, and normalization Basic Protocol 2: Identification of significant variables Basic Protocol 3: Multivariate exploratory data analysis Basic Protocol 4: Functional interpretation of metabolomic data Basic Protocol 5: Biomarker analysis based on receiver operating characteristic (ROC) curves Basic Protocol 6: Time-series and two-factor data analysis Basic Protocol 7: Sample size estimation and power analysis Basic Protocol 8: Joint pathway analysis Basic Protocol 9: MS peaks to pathway activities Basic Protocol 10: Biomarker meta-analysis Basic Protocol 11: Knowledge-based network exploration of multi-omics data Basic Protocol 12: MetaboAnalystR introduction.
    Keywords:  MS peaks to pathways; ROC curve; biomarker analysis; chemometrics; joint pathway analysis; meta-analysis; metabolic pathway analysis; metabolite set enrichment analysis; metabolomics; multi-omics integration; network analysis; power analysis; reproducible data analysis; web application
    DOI:  https://doi.org/10.1002/cpbi.86
  12. Curr Protoc Plant Biol. 2019 Dec;4(4): e20101
      Small molecules are not only intermediates of metabolism, but also play important roles in signaling and in controlling cellular metabolism, growth, and development. Although a few systematic studies have been conducted, the true extent of protein-small molecule interactions in biological systems remains unknown. PROtein-metabolite interactions using size separation (PROMIS) is a method for studying protein-small molecule interactions in a non-targeted, proteome- and metabolome-wide manner. This approach uses size-exclusion chromatography followed by proteomics and metabolomics liquid chromatography-mass spectrometry analysis of the collected fractions. Assuming that small molecules bound to proteins would co-fractionate together, we found numerous small molecules co-eluting with proteins, strongly suggesting the formation of stable complexes. Using PROMIS, we identified known small molecule-protein complexes, such as between enzymes and cofactors, and also found novel interactions. © 2019 The Authors. Basic Protocol 1: Preparation of native cell lysate from plant material Support Protocol: Bradford assay to determine protein concentration Basic Protocol 2: Separation of molecular complexes using size-exclusion chromatography Basic Protocol 3: Simultaneous extraction of proteins and metabolites using single-step extraction protocol Basic Protocol 4: Metabolomics analysis Basic Protocol 5: Proteomics analysis.
    Keywords:  complexes; metabolomics; protein-metabolite interactions; proteomics; size-exclusion chromatography
    DOI:  https://doi.org/10.1002/cppb.20101
  13. J Pharm Biomed Anal. 2019 Nov 11. pii: S0731-7085(19)32074-6. [Epub ahead of print] 112980
      In this study, a simple, rapid and sensitive LC-MS/MS analytical method for simultaneous determination of six glucocorticoids including 21-hydroxy deflazacort (21-OH DFZ), prednisolone (PNL), betamethasone (BET), beclomethasone (BEC), triamcinolone acetonide (TCA), budesonide (BUD) in nude mice plasma was developed and validated. Using testosterone as internal standard, the plasma samples were prepared by precipitation with acetonitrile and separated using an ACQUITY UPLC BEH C18 column (100 mm × 2.1 mm, 1.7 μm) with a mobile phase composed of acetonitrile and 0.1 % (v/v) formic acid aqueous solution by gradient elution at a flow rate of 0.3 mL/min. Quantitation was performed on a triple quadruple tandem mass spectrometer by multiple reaction monitoring in positive electrospray ionization mode. Calibration curves were developed over the range of 1-400 ng/mL for TCA, 5-2000 ng/mL for 21-OH DFZ, BET, BEC as well as BUD, and 10-2000 ng/mL for PNL. The accuracy, precision, matrix effect, recovery and stability were validated to be within acceptable criteria. The method was successfully applied to a preclinical pharmacokinetic (PK) study of the six GCs on female nude mice after a single oral dose of 1 mg/kg. The PK profiles of all the six GCs were described by two-compartment model with first-order absorption rate.
    Keywords:  Glucocorticoids; LC–MS/MS; Nude mice; Pharmacokinetic
    DOI:  https://doi.org/10.1016/j.jpba.2019.112980
  14. Anal Biochem. 2019 Nov 18. pii: S0003-2697(19)31077-2. [Epub ahead of print] 113508
       BACKGROUND: The analysis methods for fecal short-chain fatty acids (SCFAs) have evolved considerably. Recently, the role of SCFAs in gastrointestinal physiology and their association with intestinal microbiota and disease were reported. However, the intra-fecal variability and storage stability of SCFAs have not been extensively investigated. The aim of this study was to understand the limitations of the measurement of SCFAs in crude feces and develop a useful pre-examination procedure using the freeze-drying technique.
    METHODS: SCFAs in crude feces, obtained from healthy volunteers, and freeze-dried feces were determined by derivatization with isobutyl chloroformate, followed by liquid-liquid extraction with hexane, and separation and analysis using gas chromatography-mass spectrometry.
    RESULTS: Among the SCFAS, the maximum intra-fecal variability was observed for iso-butyrate (coefficient of variation of 37.7%), but the freeze-drying procedure reduced this variability (coefficient of variation of 7.9%). Similar improvements were also observed for other SCFAs. Furthermore, significant decreases in the SCFA amounts were observed with storage at 4 °C for 24 h.
    CONCLUSIONS: The freeze-drying procedure affords fecal SCFA stability, even with storage at room temperature for 3 d. The freeze-drying procedure allows reliable SCFA measurements without labour-intensive processes. Therefore, the freeze-drying procedure can be applied in basic, clinical, and epidemiological studies.
    Keywords:  Feces; Freeze-drying; Gas chromatography–mass spectrometry; Short-chain fatty acids
    DOI:  https://doi.org/10.1016/j.ab.2019.113508
  15. Metabolites. 2019 Nov 17. pii: E281. [Epub ahead of print]9(11):
      In this study, metastatic melanoma, breast, and prostate cancer cell lines were analyzed using a 1H-NMR-based approach in order to investigate common features and differences of aggressive cancers metabolomes. For that purpose, 1H-NMR spectra of both cellular extracts and culture media were combined with multivariate data analysis, bringing to light no less than 20 discriminant metabolites able to separate the metastatic metabolomes. The supervised approach succeeded in classifying the metastatic cell lines depending on their glucose metabolism, more glycolysis-oriented in the BRAF proto-oncogene mutated cell lines compared to the others. Other adaptive metabolic features also contributed to the classification, such as the increased total choline content (tCho), UDP-GlcNAc detection, and various changes in the glucose-related metabolites tree, giving additional information about the metastatic metabolome status and direction. Finally, common metabolic features detected via 1H-NMR in the studied cancer cell lines are discussed, identifying the glycolytic pathway, Kennedy's pathway, and the glutaminolysis as potential and common targets in metastasis, opening up new avenues to cure cancer.
    Keywords:  NMR; breast cancer; melanoma; metabonomics; metastasis; prostate cancer
    DOI:  https://doi.org/10.3390/metabo9110281
  16. Anal Chem. 2019 Nov 19.
      Advancements in molecular separations coupled with mass spectrometry have enabled metabolome analyses for clinical co-horts. A population of interest for metabolome profiling are patients with rare disease for which abnormal metabolic signatures may yield clues into the genetic basis, as well as mechanistic drivers of the disease and possible treatment options. We under-took the metabolome profiling of a large cohort of patients with mysterious conditions characterized through the Undiagnosed Diseases Network (UDN). Due to the size and enrollment procedures, collection of the metabolomes for UDN patients took place over two years. We describe the study design to adjust for measurements collected over a long time-scale and how this enabled statistical analyses to summarize the metabolome of individual patients. We demonstrate the removal of time-based batch effects, overall statistical characteristics of the UDN population, and two case-studies of interest that demonstrate the utility of metabolome profiling for rare diseases.
    DOI:  https://doi.org/10.1021/acs.analchem.9b03522
  17. Eur J Pharm Sci. 2019 Nov 15. pii: S0928-0987(19)30431-2. [Epub ahead of print] 105158
      N-acetylcysteine amide (NACA) is the amide derivative of N-acetylcysteine (NAC) that is rapidly converted to NAC after systemic administration. It has emerged as a promising thiol antioxidant for multiple indications; however, the pharmacokinetic property is yet unclear due to lack of an accurate quantification method. The present investigation aimed to develop an analytical method for simultaneous quantification of NACA and NAC in plasma. A new reagent (2-(methylsulfonyl)-5-phenyl-1,3,4-oxadiazole, MPOZ) was introduced for thiol stabilization during sample processing and storage. Further, we utilized tris (2-carboxyethyl) phosphine (TCEP) to reduce the oxidized forms of NACA and NAC. After derivatization, NACA-MPOZ and NAC-MPOZ were quantified using liquid chromatography-mass spectrometry (LC-MS). The new method was validated and found to have high specificity, linearity, accuracy, precision, and recovery for the quantification of NACA and NAC in plasma. Furthermore, the formed derivatives of NACA and NAC were stable for 48 h under different conditions. The method was utilized in pharmacokinetic study which showed that the bioavailability of NACA is significantly higher than NAC (67% and 15%, respectively). The pharmacokinetic of NACA obeyed a two-compartment open model. The glutathione (GSH)-replenishing capacity was found to be three to four-fold higher after the administration of NACA compared to that observed after the administration of NAC. In conclusion, the present method is simple, robust and reproducible, and can be utilized in both experimental and clinical studies. NACA might be considered as a prodrug for NAC. Furthermore, this is the first report describing the pharmacokinetics and bioavailability of NACA in mouse.
    Keywords:  2- (methylsulfonyl)-5-phenyl-1,3,4-oxadiazole; Bioavailability; GSH; Liquid chromatography–mass spectrometry; N-acetylcysteine; N-acetylcysteine amide; Pharmacokinetics
    DOI:  https://doi.org/10.1016/j.ejps.2019.105158
  18. Rapid Commun Mass Spectrom. 2019 Nov 22.
       RATIONALE: Mass spectrometry (MS) generally delivers more accurate results than immunoassay (IA) for certain clinically relevant analytes, but IA is still the more prevalent methodology used by clinical laboratories because of barriers to MS adoption, such as lower throughput. Therefore, it is increasingly important to develop new strategies to increase LC-MS/MS throughput so that more accurate results can be delivered to patients and clinicians.
    METHOD: Throughput can be increased by reducing assay calibration time using a single-tube calibrator, a mix of isotopologues of the target analyte at different concentrations in a biological matrix, rather than a set of traditional, multiple-tube calibrators. One injection of a single-tube calibrator can generate a full calibration curve such that each calibration point is from the multiple reaction monitoring (MRM) signal corresponding to a specific isotopologue.
    RESULTS: In this study, a single-tube calibrator (5 levels in 1 vial) and a set of multiple-tube calibrators (7 levels in 7 vials) were used to measure the testosterone concentration in 42 serum samples originally value assigned by the Centers for Disease Control and Prevention (CDC) reference method. The bias between the CDC reference method and the single-tube calibrator measurements and the multiple-tube calibrators measurements was +1.1% and -5.5%, respectively. These results were within the CDC Hormone Standardization (HoSt) program bias acceptance criteria of ±6.4%.
    CONCLUSION: The results show that LC-MS/MS throughput can be increased by using a single-tube calibrator because it reduces assay calibration time while delivering equivalent results to those generated using traditional, multiple-tube calibrators. The single-tube calibrator may also offer cost savings to laboratories through reductions in consumable consumption, technician labor time, and inventory management, as well as to manufacturers because fewer vials would need to be manufactured, tested, stored, and shipped.
    DOI:  https://doi.org/10.1002/rcm.8632
  19. Prostaglandins Leukot Essent Fatty Acids. 2019 Nov 06. pii: S0952-3278(19)30075-4. [Epub ahead of print] 102032
      Prostanoids (PNs) play critical roles in various physiological and pathological processes. Therefore, it is important to understand the alternation of PN expression profiles. However, a simultaneous and efficient quantification system for final PN metabolites in urine has not yet been established. Here, we developed and evaluated a novel method to quantify all final PN metabolites. By purification using a reverse phase solid phase extraction (SPE) column, the matrix effects against the final PGD2, PGE2, and PGF2α metabolites were low, and their accuracies were nearly 100%. The matrix effects against the final PGI2 and TXA2 metabolites were high using reverse phase SPE column purification alone. By applying a tandem SPE method that combined reverse phase and ion exchange SPE columns, the matrix effects decreased so that the accuracy was nearly 100%. To validate the reliability of the method, each final metabolite was quantified from mouse urine to which the PNs (PGD2, PGE2, and PGI2) were intravenously administered. As a result, the amounts of PN metabolites were correlated with those of the PNs administered to the blood in a dose-dependent manner. To validate the method using human samples, the urinary metabolites of Crohn's disease (CD, a PN-related disease) patients and healthy individuals were quantified. All five metabolites were successfully quantified. Only final PGE2 metabolite levels were significantly higher in CD patients than those in healthy individuals, so that the urinary metabolite profiles of CD patients is determined. In conclusion, we developed a novel method to quantify all final PN metabolites simultaneously and efficiently and demonstrated the practicality of the method using human CD patient samples.
    Keywords:  Crohn's disease; Prostanoid; Tandem solid phase extraction method; Urine
    DOI:  https://doi.org/10.1016/j.plefa.2019.102032
  20. Front Mol Biosci. 2019 ;6 120
      Autoimmune diseases (ADs) are rapidly increasing worldwide and accumulating data support a key role of disrupted metabolism in ADs. This study aimed to identify an improved combination of Total Fatty Acids (TFAs) biomarkers as a predictive factor for the presence of autoimmune diseases. A retrospective nested case-control study was conducted in 403 individuals. In the case group, 240 patients diagnosed with rheumatoid arthritis, thyroid disease, multiple sclerosis, vitiligo, psoriasis, inflammatory bowel disease, and other AD were included and compared to 163 healthy individuals. Targeted metabolomic analysis of serum TFAs was performed using GC-MS, and 28 variables were used as input for the predictive models. The primary analysis identified 12 variables that were statistically significantly different between the two groups, and metabolite-metabolite correlation analysis revealed 653 significant correlation coefficients with 90% level of significance (p < 0.05). Three predictive models were developed, namely (a) a logistic regression based on Principal Component Analysis (PCA), (b) a straightforward logistic regression model and (c) an Artificial Neural Network (ANN) model. PCA and straightforward logistic regression analysis, indicated reasonably well adequacy (74.7 and 78.9%, respectively). For the ANN, a model using two hidden layers and 11 variables was developed, resulting in 76.2% total predictive accuracy. The models identified important biomarkers: lauric acid (C12:0), myristic acid (C14:0), stearic acid (C18:0), lignoceric acid (C24:0), palmitic acid (C16:0) and heptadecanoic acid (C17:0) among saturated fatty acids, Cis-10-pentadecanoic acid (C15:1), Cis-11-eicosenoic acid (C20:1n9), and erucic acid (C22:1n9) among monounsaturated fatty acids and the Gamma-linolenic acid (C18:3n6) polyunsaturated fatty acid. The metabolic pathways of the candidate biomarkers are discussed in relation to ADs. The findings indicate that the metabolic profile of serum TFAs is associated with the presence of ADs and can be an adjunct tool for the early diagnosis of ADs.
    Keywords:  autoimmune diseases; biomarkers; inflammation; metabolomics; total fatty acids
    DOI:  https://doi.org/10.3389/fmolb.2019.00120
  21. Mass Spectrom Rev. 2019 Nov 18.
      Liquid biopsy (LB) is defined as a sample of any of body fluids (blood, saliva, tear fluid, urine, sweat, amniotic, cerebrospinal and pleural fluids, cervicovaginal secretion, and wound efflux, amongst others), which can be ex vivo analysed to detect and quantity the target(s) of interest. LB represents diagnostic approach relevant for organ-specific changes and systemic health conditions including both manifested diseases and their prestages such as suboptimal health. Further, experts emphasise that DNA-based analysis alone does not provide sufficient information for optimal diagnostics and effective treatments. Consequently, of great scientific and clinical utility are molecular patterns detected by hybrid technologies such as metabolomic tools and molecular imaging. Future proposed strategies utilise multiomic pillars (generally genome, tanscriptome, proteome, metabolome, epigenome, radiome, and microbiome), system-biological approach, and multivariable algorithms for diagnostic, prognostic, and therapeutic purposes. Current article analyses pros and cons of the mass spectrometry-based technologies, provides eminent examples of a success story "from discovery to clinical application," and demonstrates a "road-map" for the technology-driven paradigm change from reactive to predictive, preventive and personalised medical services as the medicine of the future benefiting the patient and healthcare at large. © 2019 Wiley Periodicals, Inc. Mass Spec Rev.
    Keywords:  Flammer syndrome; biomarker pattern; body fluids; cancer; cardiovascular; glaucoma; individualised patient profile; innovative strategy; liquid biopsy; mass spectrometry; multiomics; phenotyping; predictive preventive personalised medicine; wound healing
    DOI:  https://doi.org/10.1002/mas.21612