bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2020‒12‒13
twenty-five papers selected by
Sofia Costa
Cold Spring Harbor Laboratory


  1. J Chromatogr Sci. 2020 Dec 12. pii: bmaa104. [Epub ahead of print]
    Stella A, Dey S.
      Amplifex Diene reagent was employed to derivatize estradiol (E2) to enhance the analyte signal at low picogram concentrations. This derivatization enabled measurement of E2 (and other estrogens) in ESI+ mode, earlier retention times for analytes than other methods, avoidance of MS harmful ammonium fluoride in mobile phases, and an LLOQ below 1 pg/mL. The sample preparation workflow involved liquid-liquid extraction followed by Amplifex Diene derivatization for 10 min at ambient temperature. Samples were chromatographed using a standard C18 column and analyzed using a SCIEX 6500+ mass spectrometer. The assay calibrators were prepared in-house, traceable to certified reference materials, and ranged from 1.29 to 624 pg/mL. A method comparison to samples from the CDC HoSt program yielded a correlation coefficient of 0.9858 and bias of -1.37%. The LLOQ using certified reference material was 0.66 pg/mL. The intra-run precision was <9.00% for low- and high-level samples, whereas the inter-run precision was 15.2 and 5.43% for low- and high-level samples, respectively. No interference from other clinically relevant steroids was found. Amplifex Diene derivatized E2 and estrone (E1) was found to be stable for over 6 months, both refrigerated and frozen.
    DOI:  https://doi.org/10.1093/chromsci/bmaa104
  2. J Chromatogr A. 2020 Dec 02. pii: S0021-9673(20)31049-9. [Epub ahead of print]1635 461775
    Galla Z, Rajda C, Rácz G, Grecsó N, Baráth Á, Vécsei L, Bereczki C, Monostori P.
      Concurrent measurement of tyrosine, tryptophan and their metabolites, and other co-factors could help to diagnose and better understand a wide range of metabolic and neurological disorders. The two metabolic pathways are closely related to each other through co-factors, regulator molecules and enzymes. By using high performance liquid chromatography coupled to electrospray ionization triple quadrupole mass spectrometry, we present a robust, selective and comprehensive method to determine 30 molecules within 20 min using a Waters Atlantis dC18. The method was validated according to the guideline of European Medicines Agency on bioanalytical method validation. Analytical performance met all the EMA requirements and the assay covered the relevant clinical concentrations. Linear correlation coefficients were all >0.998. Intra-day and inter-day accuracy were between 80-119% and 81-117%, precision 1-19% respectively. The method was applied to measure TYR, TRP and their metabolites, and other neurologically important molecules in human serum and CSF samples. The assay can facilitate the diagnosis and is suitable for determination of reference values in clinical laboratories.
    Keywords:  CSF; Kynurenine; LC-MS/MS; Neurotransmitter; Pterin; Serum
    DOI:  https://doi.org/10.1016/j.chroma.2020.461775
  3. Leg Med (Tokyo). 2020 Nov 28. pii: S1344-6223(20)30156-5. [Epub ahead of print]48 101822
    Jinlei L, Wurita A, Xuejun W, Hongkun Y, Jie G, Liqin C.
      OBJECTIVE: A high-throughput and sensitive method using supramolecular solvent (SUPRASs) for detecting 9 benzodiazepines and zolpidem in human urine and blood by gas chromatography-tandem mass spectrometry (GC-MS/MS) was newly established and applied to authentic human urine and blood samples in this study.METHODS: Urine and blood samples were subjected to liquid-liquid extractions with supramolecular solvent mixture which consists of tetrahydrofuran and 1-hexanol. The solvent layer was evaporated to dryness by stream of nitrogen. The residue was reconstituted with methanol, and subjected to analysis by GC-MS/MS in multiple reaction monitoring (MRM) mode; internal standard method was employed for quantifying of each targeted compound.
    RESULTS: The regression equation has a good linear relationship with correlation coefficients for all tested compounds were not lower than 0.9991. The lower limits of the quantification ranged from 0.20 to 5 ng/mL for tested compounds in urine; Meanwhile, the lower limits of the quantification in this method ranged from 1 to 50 ng/mL for tested compounds in blood. These results showed that excellent reproducibility and satisfactory extraction recovery rates could be obtained for the established analytical method for 10 drugs in both blood and urine samples.
    CONCLUSION: The established method in this study was high-throughput, simple and sufficiently sensitive for determining of benzodiazepinesand zolpidem in human urine and blood. Therefore, this newly established method could be of use for qualitative and quantitative determination of such drugs in urine and blood samples either for clinical poisoning monitoring or for forensic identification.
    Keywords:  Benzodiazepines; Blood; Gas chromatography tandem mass spectrometry; Supramolecular solvent; Urine; Zolpidem
    DOI:  https://doi.org/10.1016/j.legalmed.2020.101822
  4. J Chromatogr A. 2020 Nov 26. pii: S0021-9673(20)31032-3. [Epub ahead of print]1635 461758
    Mamani-Huanca M, de la Fuente AG, Otero A, Gradillas A, Godzien J, Barbas C, López-Gonzálvez Á.
      Capillary electrophoresis coupled to mass spectrometry is a power tool in untargeted metabolomics studies to analyze charged and polar compounds. However, identification is a challenge due to the variability of migration times and the lack of MS/MS spectra in CE-TOF-MS, the type of instruments most frequently employed. We present here a CE-MS search platform incorporated in CEU Mass Mediator to annotate metabolites with a confidence level L2. For its the development we analyzed 226 compounds using two fragmentor voltages: 100 and 200 V. The information obtained, such as relative migration times (RMT) and in-source fragments, were incorporated into the platform. In addition, we validated the CE-MS search functionality using different types of biological samples such as plasma samples (human, rat, and rabbit), mouse macrophages, and human urine. The RMT tolerance percentage for the search of metabolites has been determined, establishing 5% for all compounds, except for the compounds migrating in the electro-osmotic flow, for which the tolerance should be of 10%. It has also been demonstrated the robustness of the in-source fragmentation, which makes possible the annotation of compounds by means of their fragmentation pattern. As an example, 3-methylhistidine and 1-methilhistidine, whose RMT are very close, have been annotated. Studies of the fragmentation mechanisms of acyl-L-carnitines have shown that in-source fragmentation follows the general fragmentation rules and is a suitable alternative to MS/MS.
    Keywords:  CE-MS Search; CEU Mass Mediator; in-source fragmentation; metabolite identification; plasma
    DOI:  https://doi.org/10.1016/j.chroma.2020.461758
  5. J Pharm Biomed Anal. 2020 Nov 21. pii: S0731-7085(20)31665-4. [Epub ahead of print] 113779
    Ares-Fuentes AM, Lorenzo RA, Fernández P, Carro AM.
      The illicit market for new psychoactive substances (NPS) is continuously growing. Designer benzodiazepines (DBZD) and Z-hypnotics are increasingly being used for self-medication or recreational purposes. The limited regulation and little biological information available about NPS have raised the need for analytical methods capable of extracting and quantifying them in human biological fluids. In this work, a procedure based on microextraction by packed sorbent (MEPS) in combination with ultra-high performance liquid chromatography and tandem mass spectrometry (UHPLC-MS/MS) has been developed to determine the designer benzodiazepines (clonazolam, deschloroetizolam, nifoxipam, flubromazolam and meclonazepam), and the Z-hypnotics (zolpidem, zaleplon and zopiclone) in plasma. A 3342//16 asymmetric screening design was used to study extraction variables such as the type and volume of eluent, pH, number of extraction cycles, volume of washing solvent and type of sorbent. The ensuing analytical method was validated in terms of linearity by standard addition calibration curves at eight different analyte concentration levels from 0.5-500 ng mL-1. R2 values, limits of detection (LOD) and limits of quantification (LOQ) fell in the ranges 0.9900-0.9988, 0.5-5 ng mL-1 and 1-10 ng mL-1. Intra and interday precision expressed as relative standard deviations, were < 10.6 % and process efficiency ranged from 63 to 117 % for the quality control samples. The proposed method detected zolpidem and various other benzodiazepines in plasma samples from overdoses cases.
    Keywords:  Designer benzodiazepine; Microextraction by packed sorbent; Plasma; Ultra-high performance liquid chromatography-tandem mass spectrometry; Z- hypnotic
    DOI:  https://doi.org/10.1016/j.jpba.2020.113779
  6. Talanta. 2021 Feb 01. pii: S0039-9140(20)31163-2. [Epub ahead of print]223(Pt 2): 121872
    Gray N, Lawler NG, Yang R, Morillon AC, Gay MCL, Bong SH, Holmes E, Nicholson JK, Whiley L.
      Metabolic phenotyping using mass spectrometry (MS) is being applied to ever increasing sample numbers in clinical and epidemiology studies. High-throughput and robust methods are being developed for the accurate measurement of metabolites associated with disease. Traditionally, quantitative assays have utilized triple quadrupole (QQQ) MS based methods; however, the use of such focused methods removes the ability to perform discovery-based metabolic phenotyping. An integrated workflow for the hybrid simultaneous quantification of 34 biogenic amines in combination with full scan high-resolution accurate mass (HRAM) exploratory metabolic phenotyping is presented. Primary and secondary amines are derivatized with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate prior to revered-phase liquid chromatographic separation and mass spectrometric detection. Using the HRAM-MS data, retrospective phenotypic data mining could be performed, demonstrating the versatility of HRAM-MS instrumentation in a clinical and molecular epidemiological environment. Quantitative performance was assessed using two MS detector platforms: Waters TQ-XS (QQQ; n = 3) and Bruker Impact II QToF (HRAMS-MS; n = 2) and three human biofluids (plasma, serum and urine). Finally, each platform was assessed using a certified external reference sample (NIST SRM 1950 plasma). Intra- and inter-day accuracy and precision were comparable between the QQQ and QToF instruments (<15%), with excellent linearity (R2 > 0.99) over the quantification range of 1-400 μmol L-1. Quantitative values were comparable across all instruments for human plasma, serum and urine samples, and calculated concentrations were verified against certified reference values for NIST SRM 1950 plasma as an external reference. As a real-life biological exemplar, the method was applied to plasma samples obtained from SARS-CoV-2 positive patients versus healthy controls. Both the QQQ and QToF approaches were equivalent in being able to correctly classify SARS-CoV-2 positivity. Critically, the use of HRAM full scan data was also assessed for retrospective exploratory mining of data to extract additional biogenic amines of biomarker interest beyond the 34 quantified targets.
    Keywords:  Amino acids; Biogenic amines; COVID-19; Cross validation; High-resolution accurate mass; Metabolic profiling; Quantitative mass spectrometry; SARS-CoV-2; Triple quadrupole; UHPLC
    DOI:  https://doi.org/10.1016/j.talanta.2020.121872
  7. Anal Chim Acta. 2021 Jan 15. pii: S0003-2670(20)31080-1. [Epub ahead of print]1142 28-37
    van der Laan T, Elfrink H, Azadi-Chegeni F, Dubbelman AC, Harms AC, Jacobs DM, Braumann U, Velders AH, van Duynhoven J, Hankemeier T.
      The unambiguous identification of unknown compounds is of utmost importance in the field of metabolomics. However, current identification workflows often suffer from error-sensitive methodologies, which may lead to incorrect structure annotations of small molecules. Therefore, we have developed a comprehensive identification workflow including two highly complementary techniques, i.e. liquid chromatography (LC) combined with mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), and used it to identify five taste-related retention time and m/z features in soy sauce. An off-line directed two-dimensional separation was performed in order to purify the features prior to the identification. Fractions collected during the first dimension separation (reversed phase low pH) were evaluated for the presence of remaining impurities next to the features of interest. Based on the separation between the feature and impurities, the most orthogonal second dimension chromatography (hydrophilic interaction chromatography or reversed phase high pH) was selected for further purification. Unknown compounds down to tens of micromolar concentrations were tentatively annotated by MS and structurally confirmed by MS and NMR. The mass (0.4-4.2 μg) and purity of the isolated compounds were sufficient for the acquisition of one and two-dimensional NMR spectra. The use of a directed two-dimensional chromatography allowed for a fractionation that was tailored to each feature and remaining impurities. This makes the fractionation more widely applicable to different sample matrices than one-dimensional or fixed two-dimensional chromatography. Five proline-based 2,5-diketopiperazines were successfully identified in soy sauce. These cyclic dipeptides might contribute to taste by giving a bitter flavour or indirectly enhancing umami flavour.
    Keywords:  Food; Identification; Mass spectrometry; Metabolomics; Nuclear magnetic resonance spectroscopy; Two-dimensional chromatography
    DOI:  https://doi.org/10.1016/j.aca.2020.10.054
  8. Xenobiotica. 2020 Dec 07. 1-33
    Molloy BJ, King A, Mullin L, Gethings LA, Riley R, Plumb RS, Wilson ID.
      The metabolism and pharmacokinetics of gefitinib (Iressa®, N-(3-chloro-4-fluorophenyl)-7-methoxy-6-(3-morpholino-propoxy)quinazolin-4-amine), a selective thymidylate kinase inhibitor for the epidermal growth factor receptor (EGFR) was studied after IV and PO administration to male C57BL6 mice at 10 and 50 mg/kg respectively. The pharmacokinetics and metabolism of gefitinib were investigated using a range of rapid UHPLC-MS and UHPLC-IM-HRMS methods, using both reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC), to rapidly determine the drugs pharmacokinetics and metabolic fate. Rapid oral absorption resulted in peak plasma concentrations at 1 h of ca. 7 μg/ml, that declined with a half-life of 3.8h (2.6h for the IV route), and providing an estimated oral bioavailablity of 53%. Gefitinib itself was the major circulating drug-related compound in plasma extracts, with a total of 11 metabolites identified. The urinary profiles determined using both HILIC and RP-UPLC-IM-MS detected gefitinib and 10 metabolites or 15 metabolites respectively including the detection of a number of novel glucuronide and sulfate conjugates. Despite rapid, sub 5 min, LC profiling methods being employed metabolite coverage was shown to be high and compared well with that of previous studies.
    Keywords:  Gefitinib; ion mobility; metabolite profiling; novel conjugates; pharmacokinetics
    DOI:  https://doi.org/10.1080/00498254.2020.1859643
  9. J Pharm Biomed Anal. 2020 Nov 20. pii: S0731-7085(20)31659-9. [Epub ahead of print] 113773
    Chen H, Xie H, Huang S, Xiao T, Wang Z, Ni X, Deng S, Lu H, Hu J, Li L, Wen Y, Shang D.
      Targeted metabolomics analysis based on triple quadrupole (QQQ) MS coupled with multiple reaction monitoring mode (MRM) is the gold standard for metabolite quantification and it is widely applied in metabolomics. However, standard compounds for each metabolite and the corresponding analogs are necessary for quantitative measurements. To identify the differentially present metabolites in various groups, determining the relative concentration of metabolites would be more efficient than accurate quantification. In this study, a relatively quantitative targeted method was established for metabonomics research, on the basis of hydrophilic interaction liquid chromatography (HILIC)/QQQ MS operated in MRM mode. The quality control-base random forest signal correction algorithm (QC-RFSC algorithm) was applied for quality control instead of the internal standard method. High quality relative quantification was achieved without internal standards, and integrated peak areas were successfully used for statistical and pathway analyses. Amino acids and neurotransmitters (dopamine, kynurenic acid, urocanic acid, tryptophan, kynurenine, tyrosine, valine, threonine, serine, alanine, glycine, glutamine, citrulline, GABA, glutamate, aspartate, arginine, ornithine and histidine) in serum samples were simultaneously determined with the newly developed method. To demonstrate the applicability of this method in large-scale analyses, we analyzed the above metabolites in serum from patients with major depression. The serum levels of glutamate, aspartate, threonine, glycine and alanine were significantly higher, and those of citrulline, kynurenic acid and urocanic acid were significantly lower, in patients with major depression than in controls. This is the first report of the difference in urocanic acid, a compound reported to improve glutamate biosynthesis and release in the central nervous system, between healthy controls and patients with major depression.
    Keywords:  Amino acids; HILIC-MS/MS; Major depression; Neurotransmitters; QC-RFSC algorithm; Relatively quantitative targeted method
    DOI:  https://doi.org/10.1016/j.jpba.2020.113773
  10. J Pharm Biomed Anal. 2020 Nov 20. pii: S0731-7085(20)31649-6. [Epub ahead of print] 113763
    Chen A, Zhang Y, Sun D, Xu Y, Guo Y, Wang X.
      Arachidonic acid (AA) is closely associated with breast cancer. In addition to the two metabolic pathways regulated by cyclooxygenase and lipoxygenase, AA has a third metabolic pathway through which cytochrome P450 (CYP) enzymes produce hydroxyeicosatetraenoic acids (HETEs) and epoxyeicosatrienoic acids (EETs). The targeted CYP-mediated pathway of AA can not only kill cancer cells but also inhibit the interstitial microenvironment around a tumor. Therefore, it makes sense to identify potential biomarkers from the AA metabolome for the diagnosis and treatment of breast cancer. This study established a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the analysis of AA and its main metabolites, EETs and HETEs, in MMTV-PyMT mice, a spontaneous breast cancer mouse model. The results showed that there were significant differences in the concentrations of AA, 12-HETE, 19-HETE and 8,9-EET in plasma and tumor tissues between normal and MMTV-PyMT mice. Therefore, the eicosanoids mentioned above may be used as new biomarkers for breast cancer diagnosis. This study provides a new perspective for the recognition and diagnosis of breast cancer.
    Keywords:  Arachidonic acid (AA); Biomarker; Breast cancer; Cytochrome P450; LC–MS/MS
    DOI:  https://doi.org/10.1016/j.jpba.2020.113763
  11. J Chromatogr A. 2020 Nov 19. pii: S0021-9673(20)31012-8. [Epub ahead of print]1635 461738
    Wang C, Liu J, Chen Y, Zhang L, Li L, Xu R, Xing G, Yuan M.
      An online solid-phase extraction (SPE)-coupled liquid chromatography-mass spectrometry (LC-MS) method was established for the determination of 10 nitrated polycyclic aromatic hydrocarbons (nitro-PAHs) in water. Water samples were mixed with methanol to generate 40% methanol solutions (v/v), and filtered by 0.45 μm membrane. The filtration with polytetrafluoroethylene(PTFE) membrane got higher recovery rates than nylon membrane, especially for 4-ring and 5-ring nitro-PAHs. 2.5 mL solution was directly injected into online SPE flow path to allow for online purification and enrichment of target analytes in the SPE column. The nitro-PAHs eluted from the SPE column were automatically transferred to the analytical flow path by a well-designed valve-switching system. With the optimization of LC and MS condition, ten nitro-PAH isomers was separated and detected from each other by LC-MS/MS with negative atmospheric pressure chemical ionization (APCI). It was firstly found that nitro-PAHs could produce strong [M-H]- precursor ions in the primary MS besides [M+e]- and [M+15]-. In the secondary MS, the precursor ions mainly lose NO neutral molecule (30 Daltons) to produce daughter ions. The online SPE and LC-MS analysis process was completed in 15.5 min. The linear correlation coefficients of 10 nitro-PAH standard curves were higher than 0.99. The detection limits of nitro-PAHs were about 1.2~22.2 ng/L (S/N=3). The intra-day and inter-day reproducibility (RSD, n=6) were 1.6%~8.4% and 5.3%~16.9%, respectively. The recoveries of 10, 40 and 200 ng/L in tap water were 71.7%~106.4%, 79.7%~100.9% and 73.0%~105.5%, with the corresponding RSD of 2.4%~10.5%, 2.1%~8.6% and 2.7%~6.2%, respectively.
    Keywords:  Atmospheric pressure chemical ionization; Isomer separation; Liquid chromatography-mass spectrometry; Nitrated polycyclic aromatic hydrocarbons; Online solid-phase extraction; Water
    DOI:  https://doi.org/10.1016/j.chroma.2020.461738
  12. Metabolomics. 2020 Dec 09. 16(12): 126
    Huang L, Currais A, Shokhirev MN.
      INTRODUCTION: Cellular metabolites are generated by a complex network of biochemical reactions. This makes interpreting changes in metabolites exceptionally challenging.OBJECTIVES: To develop a computational tool that integrates multiomics data at the level of reactions.
    METHODS: Changes in metabolic reactions are modeled with input from transcriptomics/proteomics measurements of enzymes and metabolomic measurements of metabolites.
    RESULTS: We developed SUMMER, which identified more relevant signals, key metabolic reactions, and relevant underlying biological pathways in a real-world case study.
    CONCLUSION: SUMMER performs integrative analysis for data interpretation and exploration. SUMMER is freely accessible at http://summer.salk.edu and the code is available at https://bitbucket.org/salkigc/summer .
    Keywords:  Bioinformatics software; Integrative analysis; Interactive user interface; Metabolomics; Multiomics; Web server
    DOI:  https://doi.org/10.1007/s11306-020-01750-7
  13. J Appl Lab Med. 2020 Dec 06. pii: jfaa166. [Epub ahead of print]
    Kushnir MM, Song B, Yang E, Frank EL.
      BACKGROUND: Pyridoxal 5'-phosphate (PLP) is the primary circulatory form of vitamin B6, an essential cofactor for numerous biochemical enzymatic reactions. Conventional PLP analysis using high-performance liquid chromatography (HPLC) with fluorescence requires derivatization and long injection-to-injection time. Development of high-throughput LC-MS/MS assays is desirable.METHODS: Stable isotope labeled internal standard was added to aliquots of samples, proteins were precipitated using trichloroacetic acid, and supernatants were analyzed by multiple reaction monitoring using LC-MS/MS in positive ion mode. Analysis time for PLP was 3.0 min using single column HPLC separation and 2.4 min using alternating column regeneration (ACR). Clinical evaluation of the method included review of results (n = 102 386) from routine performance of the assay.
    RESULTS: The assay was linear to 500 nmol/L; limit of quantification was 5 nmol/L. Imprecision (CV) of the assay was <5%. Equivalent performance was observed for single HPLC column and ACR. In 62% of routinely analyzed patient samples, PLP concentrations were within the reference interval; higher PLP concentrations were observed in samples from males than from females. Vitamin B6 deficiency was lowest in children and highest in elderly adults. Lower PLP concentrations were observed in samples collected during winter/spring than during summer/fall. We observed lower concentrations in plasma collected in lithium heparin tubes, suggesting PLP degradation caused by the anticoagulant.
    CONCLUSIONS: This LC-MS/MS method allows PLP determination using simple sample preparation and short analysis time. We observed association of PLP concentrations with age, sex, and season of sample collection. Our data indicate that lithium heparin anticoagulant tubes reduce measured PLP concentration.
    Keywords:  liquid chromatography; mass spectrometry; nutritional assessment; pyridoxal 5′-phosphate; vitamin B6
    DOI:  https://doi.org/10.1093/jalm/jfaa166
  14. Methods Mol Biol. 2021 ;2130 157-168
    Aviram R, Wang C, Han X, Asher G.
      Lipidomics approaches provide quantitative characterization of hundreds of lipid species from biological samples. Recent studies highlight the value of these methods in studying circadian biology, and their potential goes far beyond studying lipid metabolism per se. For example, lipidomics analyses of subcellular compartments can be used to determine daily rhythmicity of different organelles and their intracellular dynamics. In this chapter we describe in detail the procedure for around the clock shotgun lipidomics, from sample preparation to bioinformatics analyses. Sample preparation includes biochemical fractionation of nuclei and mitochondria from mouse liver harvested throughout the day. Lipid content is determined and quantified, in unbiased manner and with wide coverage, using multidimensional mass spectrometry shotgun lipidomics (MDMS-SL). Circadian parameters are then determined with nonparametric statistical tests. Overall, the approach described herein is applicable for various animal models, tissues, and organelles, and is expected to yield new insight on various aspects of circadian biology and lipid metabolism.
    Keywords:  Circadian; Lipid metabolism; Liver; Mass spectrometry; Mitochondria; Mouse; Nuclei; Shotgun lipidomics
    DOI:  https://doi.org/10.1007/978-1-0716-0381-9_12
  15. Forensic Sci Int. 2020 Nov 14. pii: S0379-0738(20)30457-6. [Epub ahead of print]318 110595
    Garneau B, Desharnais B, Laquerre J, Côté C, Taillon MP, Martin PY, Daigneault G, Mireault P, Lajeunesse A.
      Several New Psychoactive Substances (NPS) enter the illicit drug market each year. This constant evolution of compounds to screen is challenging to law enforcement and drug chemists, and even more so to forensic toxicologists, who need to detect such compounds which might be at low concentrations in complex biological matrices. While some technological solutions are better suited than others to address such a challenge (e.g., high resolution mass spectrometry), laboratories with limited instrumental and financial resources are faced with a complex task: systematically screening for a rapidly evolving NPS panel using an accredited method run on standard equipment (e.g., liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS)). This work presents a solution to this challenge: a complete workflow from the detection of a regional NPS threat to its implementation in a method accredited under the ISO 17025:2017 norm. Initial LC-MS/MS method included 55 NPS and metabolites (31 Novel Synthetic Opioids (NSO), 22 NSO metabolites and 2 designer benzodiazepines). Following their identification as relevant territorial threats, flualprazolam, then isotonitazene, were added to the contingent. By relying on development aiming for maximal integration to the current analysis workflow, systematic NPS screening using this method was easily implemented. Between March 2019 and March 2020, the 5 079 forensic cases analyzed in the province of Québec (Canada) revealed a NPS positivity rate of 3.4%. While 94% involved designer benzodiazepines, 5% involved NSO. This process, combining high efficiency, simple detection technology, ISO accreditation and rapid response to new threats resulted in a four-fold increase in NPS detection.
    Keywords:  Designer benzodiazepines; LC–MS/MS screening; New psychoactive substance; Novel synthetic opioids
    DOI:  https://doi.org/10.1016/j.forsciint.2020.110595
  16. Int J Mol Sci. 2020 Dec 04. pii: E9252. [Epub ahead of print]21(23):
    Piechocka J, Wieczorek M, Głowacki R.
      Gas chromatography-mass spectrometry technique (GC-MS) is mainly recognized as a tool of first choice when volatile compounds are determined. Here, we provide the credible evidence that its application in analysis can be extended to non-volatile sulfur-containing compounds, to which methionine (Met), homocysteine (Hcy), homocysteine thiolactone (HTL), and cysteine (Cys) belong. To prove this point, the first method, based on GC-MS, for the identification and quantification of Met-related compounds in human saliva, has been elaborated. The assay involves simultaneous disulfides reduction with tris(2-carboxyethyl)phosphine (TCEP) and acetonitrile (MeCN) deproteinization, followed by preconcentration by drying under vacuum and treatment of the residue with a derivatizing mixture containing anhydrous pyridine, N-trimethylsilyl-N-methyl trifluoroacetamide (MSTFA), and trimethylchlorosilane (TMCS). The validity of the method was demonstrated based upon US FDA recommendations. The assay linearity was observed over the range of 0.5-20 µmol L-1 for Met, Hcy, Cys, and 1-20 µmol L-1 for HTL in saliva. The limit of quantification (LOQ) equals 0.1 µmol L-1 for Met, Hcy, Cys, while its value for HTL was 0.05 µmol L-1. The method was successfully applied to saliva samples donated by apparently healthy volunteers (n = 10).
    Keywords:  N-trimethylsilyl-N-methyl trifluoroacetamide; amino acid; aminothiol; cysteine; gas chromatography–mass spectrometry; homocysteine; homocysteine thiolactone; human saliva; methionine; sulfur amino acid
    DOI:  https://doi.org/10.3390/ijms21239252
  17. BMC Bioinformatics. 2020 Dec 07. 21(1): 561
    Canzler S, Hackermüller J.
      BACKGROUND: Gaining biological insights into molecular responses to treatments or diseases from omics data can be accomplished by gene set or pathway enrichment methods. A plethora of different tools and algorithms have been developed so far. Among those, the gene set enrichment analysis (GSEA) proved to control both type I and II errors well. In recent years the call for a combined analysis of multiple omics layers became prominent, giving rise to a few multi-omics enrichment tools. Each of these has its own drawbacks and restrictions regarding its universal application.RESULTS: Here, we present the multiGSEA package aiding to calculate a combined GSEA-based pathway enrichment on multiple omics layers. The package queries 8 different pathway databases and relies on the robust GSEA algorithm for a single-omics enrichment analysis. In a final step, those scores will be combined to create a robust composite multi-omics pathway enrichment measure. multiGSEA supports 11 different organisms and includes a comprehensive mapping of transcripts, proteins, and metabolite IDs.
    CONCLUSIONS: With multiGSEA we introduce a highly versatile tool for multi-omics pathway integration that minimizes previous restrictions in terms of omics layer selection, pathway database availability, organism selection and the mapping of omics feature identifiers. multiGSEA is publicly available under the GPL-3 license at https://github.com/yigbt/multiGSEA and at bioconductor: https://bioconductor.org/packages/multiGSEA .
    Keywords:  Bioconductor; GSEA; Multi-omics; Pathway enrichment; R; Software
    DOI:  https://doi.org/10.1186/s12859-020-03910-x
  18. Talanta. 2021 Feb 01. pii: S0039-9140(20)31031-6. [Epub ahead of print]223(Pt 2): 121740
    Gomez-Gomez A, Sabbaghi M, Haro N, Albanell J, Menéndez S, González M, Gil-Gómez G, Rovira A, Pozo OJ.
      Formalin-fixed paraffin-embedded (FFPE) tissues play an irreplaceable role in cancer research. Although extensive research has been conducted for the detection of DNA, RNA and proteins in FFPE samples, literature dealing with the FFPE determination of small molecules is scarce. In this study, we aimed to explore the potential of targeted metabolomics in FFPE specimens. For that purpose, we developed a LC-MS/MS method for the quantification of acidic metabolites in FFPE samples. The method involves trimming tissue slices from FFPE blocks, deparaffinization, lysis of the tissue, o-benzyl hydroxylamine derivatization and LC-MS/MS detection. Deparaffinization and lysis steps were optimized to maximize the analytes extraction and to minimize the effect of the ubiquitous presence of some metabolites in the paraffin. Two validation approaches were applied: (i) using blank paraffin as matrix and (ii) using actual human FFPE tissue samples by standard additions. The method quantified 40 metabolites with appropriate accuracy (commonly 80-120%) and precision (CV 2-19%) in both validation approaches. LLOQs ranging 0.88-2001 pg mg-1 with low-moderate matrix effects (commonly 85-115%) were obtained. FFPE samples from 15 patients with colorectal cancer were analyzed and metabolites concentrations in tumor vs matched normal FFPE tissues were compared. Results show that tumor tissues have a well-established fingerprint including an increase in ketogenesis, a decrease in lipogenesis and an imbalance in the tricarboxylic acid cycle.
    Keywords:  Cancer; Carboxylic acids; Formalin-fixed paraffin-embedded; Liquid chromatography-tandem mass spectrometry; Mass spectrometry; Targeted metabolomics
    DOI:  https://doi.org/10.1016/j.talanta.2020.121740
  19. Cancers (Basel). 2020 Dec 04. pii: E3642. [Epub ahead of print]12(12):
    Liu X, Liu G, Chen L, Liu F, Zhang X, Liu D, Liu X, Cheng X, Liu L.
      Diagnosis of ovarian cancer is difficult due to the lack of clinical symptoms and effective screening algorithms. In this study, we aim to develop models for ovarian cancer diagnosis by detecting metabolites in urine and plasma samples. Ultra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive ion mode was used for metabolome quantification in 235 urine samples and 331 plasma samples. Then, Urine and plasma metabolomic profiles were analyzed by univariate and multivariate statistics. Four groups of samples: normal control, benign, borderline and malignant ovarian tumors were enrolled in this study. A total of 1330 features and 1302 features were detected from urine and plasma samples respectively. Based on two urine putative metabolites, five plasma putative metabolites and five urine putative metabolites, three models for distinguishing normal-ovarian tumors, benign-malignant (borderline + malignant) and borderline-malignant ovarian tumors were developed respectively. The AUC (Area Under Curve) values were 0.987, 0876 and 0.943 in discovery set and 0.984, 0.896 and 0.836 in validation set for three models. Specially, the diagnostic model based on 5 plasma putative metabolites had better early-stage diagnosis performance than CA125 alone. The AUC values of the model were 0.847 and 0.988 in discovery and validation set respectively. Our results showed that normal and ovarian tumors have unique metabolic signature in urine and plasma samples, which shed light on the ovarian cancer diagnosis and classification.
    Keywords:  diagnosis; early diagnosis; metabolomics; ovarian tumors; plasma; urine
    DOI:  https://doi.org/10.3390/cancers12123642
  20. Anal Chem. 2020 Dec 08.
    Smith KM, Wilson ID, Rainville PD.
      We describe a method for the analysis of organic acids, including those of the tricarboxylic acid cycle (TCA cycle), by mixed-mode reversed-phase chromatography, on a CSH Phenyl-Hexyl column, to accomplish mixed-mode anion-exchange separations, which results in increased retention for acids without the need for ion-pairing reagents or other mobile phase additives. The developed method exhibited good retention time reproducibility for over 650 injections or more than 5 days of continuous operation. Additionally, it showed excellent resolution of the critical pairs, isocitric acid and citric acid as well as malic acid and fumaric acid, among others. The use of hybrid organic-inorganic surface technology incorporated into the hardware of the column not only improved the mass spectral quality and subsequent database match scoring but also increased the recovery of the analytes, showing particular benefit for low concentrations of phosphorylated species. The method was applied to the comparative metabolomic analysis of urine samples from healthy controls and breast cancer positive subjects. Unsupervised PCA analysis showed distinct grouping of samples from healthy and diseased subjects, with excellent reproducibility of respective injection clusters. Finally, abundance plots of selected analytes from the tricarboxylic acid cycle revealed differences between healthy control and disease groups.
    DOI:  https://doi.org/10.1021/acs.analchem.0c03863
  21. Diagnostics (Basel). 2020 Dec 05. pii: E1052. [Epub ahead of print]10(12):
    Lokhov PG, Trifonova OP, Maslov DL, Balashova EE.
      In metabolomics, mass spectrometry is used to detect a large number of low-molecular substances in a single analysis. Such a capacity could have direct application in disease diagnostics. However, it is challenging because of the analysis complexity, and the search for a way to simplify it while maintaining the diagnostic capability is an urgent task. It has been proposed to use the metabolomic signature without complex data processing (mass peak detection, alignment, normalization, and identification of substances, as well as any complex statistical analysis) to make the analysis more simple and rapid.METHODS: A label-free approach was implemented in the metabolomic signature, which makes the measurement of the actual or conditional concentrations unnecessary, uses only mass peak relations, and minimizes mass spectra processing. The approach was tested on the diagnosis of impaired glucose tolerance (IGT).
    RESULTS: The label-free metabolic signature demonstrated a diagnostic accuracy for IGT equal to 88% (specificity 85%, sensitivity 90%, and area under receiver operating characteristic curve (AUC) of 0.91), which is considered to be a good quality for diagnostics.
    CONCLUSIONS: It is possible to compile label-free signatures for diseases that allow for diagnosing the disease in situ, i.e., right at the mass spectrometer without complex data processing. This achievement makes all mass spectrometers potentially versatile diagnostic devices and accelerates the introduction of metabolomics into medicine.
    Keywords:  blood plasma; diagnostic signature; impaired glucose tolerance; label-free; mass spectrometry
    DOI:  https://doi.org/10.3390/diagnostics10121052
  22. J Chem Inf Model. 2020 Dec 07.
    Nuñez JR, Mcgrady M, Yesiltepe Y, Renslow RS, Metz TO.
      Thousands of chemical properties can be calculated for small molecules, which can be used to place the molecules within the context of a broader "chemical space." These definitions vary based on compounds of interest and the goals for the given chemical space definition. Here, we introduce a customizable Python module, chespa, built to easily assess different chemical space definitions through clustering of compounds in these spaces and visualizing trends of these clusters. To demonstrate this, chespa currently streamlines prediction of various molecular descriptors (predicted chemical properties, molecular substructures, AI-based chemical space, and chemical class ontology) in order to test six different chemical space definitions. Furthermore, we investigated how these varying definitions trend with mass spectrometry (MS)-based observability, that is, the ability of a molecule to be observed with MS (e.g., as a function of the molecule ionizability), using an example data set from the U.S. EPA's nontargeted analysis collaborative trial, where blinded samples had been analyzed previously, providing 1398 data points. Improved understanding of observability would offer many advantages in small-molecule identification, such as (i) a priori selection of experimental conditions based on suspected sample composition, (ii) the ability to reduce the number of candidate structures during compound identification by removing those less likely to ionize, and, in turn, (iii) a reduced false discovery rate and increased confidence in identifications. Factors controlling observability are not fully understood, making prediction of this property nontrivial and a prime candidate for chemical space analysis. Chespa is available at github.com/pnnl/chespa.
    DOI:  https://doi.org/10.1021/acs.jcim.0c00899
  23. Talanta. 2021 Feb 01. pii: S0039-9140(20)30999-1. [Epub ahead of print]223(Pt 1): 121708
    Chang WC, Wang PH, Chang CW, Chen YC, Liao PC.
      Over recent years, metabolomics has been featured as the state-of-the-art technology that successfully opens the paths to understanding biological mechanisms and facilitating biomarker discovery. However, the inherent dynamic and sensitive nature of the metabolome have been challenging the accuracy of capturing the timepoints of interest while using biofluids such as urine and blood. Hair has thus emerged as a valuable analytical specimen for the long-term and retrospective determinations. Unfortunately, notwithstanding the apparent interest on global hair metabolomics, very few studies have engaged in the optimisation of the extraction strategy. In this study, we systemically investigated the extraction procedures for hair metabolome using a single factor experimental design. Three pH values (acidic, neutral, and basic) in aqueous solution, six extraction solvents (methanol, acetonitrile, acetone, phosphate-buffered saline, deionised water, and dichloromethane), different compositions of selected solvent mixtures and their sequential extraction, and a series of extraction times (15, 45, 60, 120, 240, and 480 min) were evaluated. The ideal condition for hair extraction is ultrasonic-assisted extraction with methanol:phosphate-buffered saline 50:50 (v/v) under +55 °C for 240 min. This strategy may secure the true composition of the metabolome, maximise the signal abundance, and guarantee a high coverage of wide-range metabolites in a straightforward approach. The optimised extraction strategy was then coupled with structure annotation tools for hair metabolome profiling. After a single RPLC-HRMS run, hair metabolite identification was achieved as the annotations of 171 probable structures and 853 tentative structures as well as the assignments of 414 unequivocal molecular formulae. In conclusion, we established an efficient extraction strategy for untargeted hair metabolomics, which the method is deliverable to any analytical laboratories and the sample can be directly profiled by means of a conventional RPLC-HRMS gradient.
    Keywords:  Complementary matrices; High-resolution mass spectrometry; Metabolome; Non-targeted; Optimisation; Untargeted
    DOI:  https://doi.org/10.1016/j.talanta.2020.121708
  24. Metabolites. 2020 Dec 08. pii: E501. [Epub ahead of print]10(12):
    Williams HC, Piron MA, Nation GK, Walsh AE, Young LEA, Sun RC, Johnson LA.
      Stable isotope-resolved metabolomics (SIRM) is a powerful tool for understanding disease. Advances in SIRM techniques have improved isotopic delivery and expanded the workflow from exclusively in vitro applications to in vivo methodologies to study systemic metabolism. Here, we report a simple, minimally-invasive and cost-effective method of tracer delivery to study SIRM in vivo in laboratory mice. Following a brief fasting period, we orally administered a solution of [U-13C] glucose through a blunt gavage needle without anesthesia, at a physiological dose commonly used for glucose tolerance tests (2 g/kg bodyweight). We defined isotopic enrichment in plasma and tissue at 15, 30, 120, and 240 min post-gavage. 13C-labeled glucose peaked in plasma around 15 min post-gavage, followed by period of metabolic decay and clearance until 4 h. We demonstrate robust enrichment of a variety of central carbon metabolites in the plasma, brain and liver of C57/BL6 mice, including amino acids, neurotransmitters, and glycolytic and tricarboxylic acid (TCA) cycle intermediates. We then applied this method to study in vivo metabolism in two distinct mouse models of diseases known to involve dysregulation of glucose metabolism: Alzheimer's disease and type II diabetes. By delivering [U-13C] glucose via oral gavage to the 5XFAD Alzheimer's disease model and the Lepob/ob type II diabetes model, we were able to resolve significant differences in multiple central carbon pathways in both model systems, thus providing evidence of the utility of this method to study diseases with metabolic components. Together, these data clearly demonstrate the efficacy and efficiency of an oral gavage delivery method, and present a clear time course for 13C enrichment in plasma, liver and brain of mice following oral gavage of [U-13C] glucose-data we hope will aid other researchers in their own 13C-glucose metabolomics study design.
    Keywords:  13C-glucose; Alzheimer’s disease; SIRM; brain metabolism; diabetes; gavage; metabolomics; stable isotope
    DOI:  https://doi.org/10.3390/metabo10120501
  25. Saudi J Biol Sci. 2020 Dec;27(12): 3727-3734
    Qamar W, Alqahtani S, Ahamad SR, Ali N, Altamimi MA.
      Recent advances in metabolomics provide tools to investigate human metabolome in order to establish new parameters to study different approaches towards diagnostics, diseases and their treatment. The present study focused on the untargeted identification of metabolites in serum of patients with coronary artery disease who were under treatment at the time of sample collection. AUCs (Area Under the Curves) from different peaks were considered for the analysis and comparison purposes. The metabolome was studied using GC-MS (Gas Chromatography Mass Spectrometry) and the metabolites were identified with NIST (The National Institute of Standards and Technology) and Wiley library matches. A total of 17 metabolites were identified and focused on to compare with the metabolome of healthy individuals. T test analysis found significant differences in alanine, malonic acid, ribitol, D-glucose, mannose (P < 0.001), acetohydroxamic acid, N-carboxyglycine, and aminobutyrate (P < 0.05). Principal Component Analysis of serum metabolites data found three components out of 17 metabolites; RC1 (Acetohydroxamic acid, alanine, D-glucose, malonic acid, mannose, N-carboxy glycine and ribitol), RC2 (Heptadecanoic acid, hexadecanoic acid, octadecanoic acid and Trans-9-octadecanoic acid), RC3 (Aminobutyrate, D-sorbit, gamma lactone, valine, benzene propanoic acid and lactic acid). No correlation was found among the components.
    Keywords:  AUCs; GC–MS; Metabolomics; Principal component analysis; Serum metabolome
    DOI:  https://doi.org/10.1016/j.sjbs.2020.08.019