bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2020‒01‒26
ten papers selected by
Sofia Costa
Cold Spring Harbor Laboratory


  1. J Lipid Res. 2020 Jan 21. pii: jlr.D119000591. [Epub ahead of print]
    Yuan TF, Le J, Wang ST, Li Y.
      Analysis of the global steroid metabolism in human can shed light on the etiologies of steroid-related diseases. However, existing methods require large amounts of serum, and lack accuracy evaluation. Here, we developed an LC-MS/MS method for simultaneous quantification of 12 steroid hormones, including testosterone, pregnenolone, progesterone, androstenedione, corticosterone, 11-deoxycortisol, cortisol, 17-hydroxypregnenolone, 17-hydroxyprogesterone, dehydroepiandrosterone, estriol, and estradiol. Steroids and the spiked internal standards in 100 μL serum were extracted by protein precipitation and liquid-liquid extraction. The organic phase was dried by evaporation and isonicotinoyl chloride was added for  steroid derivatization, followed by evaporation under nitrogen and redissolving in 50% methanol. Chromatographic separation was performed on a reverse-phase PFP column, and analytes were detected on a triple quadrupole mass spectrometer with ESI. The lower limits of quantification ranged from 0.005 ng/mL for estradiol to 1 ng/mL for cortisol. Apparent recoveries of steroids at high-, medium- and low- concentrations in quality-control samples were between 86.4% and 115.0%. There were limited biases (-10.7%-10.5%) between the measured values and the authentic values, indicating that the method has excellent reliability. An analysis of the steroid metabolome in pregnant women highlighted the applicability of the method in clinical serum samples. We conclude that the LC-MS/MS method reported here enables steroid metabolome analysis with high accuracy and reduced serum consumption, indicating that it may be useful tool for both clinical and scientific laboratory research.
    Keywords:  Cholesterol; Derivatization; Hormones/Steroid; Mass spectrometry; Pregnancy; Steroid hormones; global metabolite analysis; steroid-related disease
    DOI:  https://doi.org/10.1194/jlr.D119000591
  2. J Proteome Res. 2020 Jan 24.
    Misra BB, Olivier M.
      Gas chromatography-mass spectrometry (GC-MS) platforms are typically run in electron ionization (EI) mode for mass spectral matching and metabolite annotation. With the advent of high resolution mass spectrometry (HRMS), soft ionization techniques such as chemical ionization (CI) may provide additional coverage for compound identification. We evaluated NIST SRM 1950 pooled plasma reference sample using a HRGC-MS instrument [GC-Orbitrap-MS with electron ionization (EI), positive chemical ionization (PCI), and negative CI (NCI) capabilities) for metabolite annotation and quantification to assess the suitability of the platform for routine discovery metabolomics. Using both open source and vendor workflows, we validated the spectral matches with an in-house spectral library (Wake Forest CPM GC-MS spectral and retention time libraries) of EI-MS and CI-MS/MS spectra obtained from chemical standards. We confidently [metabolomics standards initiative (MSI) confidence level 2] identified 263, 93, and 65 metabolites using EI, PCI, and NCI modes, respectively, of which 270 metabolites (64%) were validated using our Wake Forest CPM GC-MS spectral libraries. When compared to published LC-MS-based efforts using the same NIST SRM 1950 plasma sample, there was only 17% overlap between the two platforms. In addition, the metabolomics analysis of community approved standard human plasma demonstrated the ability of EI- and CI-MS modes of analysis using a HRGC-MS platform to enable reproducible and interoperable spectral matching.
    DOI:  https://doi.org/10.1021/acs.jproteome.9b00774
  3. Sci Rep. 2020 Jan 24. 10(1): 1170
    Gil M, Reynes C, Cazals G, Enjalbal C, Sabatier R, Saucier C.
      A rapid Ultra Performance Liquid Chromatography coupled with Quadrupole/Time Of Flight Mass Spectrometry (UPLC-QTOF-MS) method was designed to quickly acquire high-resolution mass spectra metabolomics fingerprints for rosé wines. An original statistical analysis involving ion ratios, discriminant analysis, and genetic algorithm (GA) was then applied to study the discrimination of rosé wines according to their origins. After noise reduction and ion peak alignments on the mass spectra, about 14 000 different signals were detected. The use of an in-house mass spectrometry database allowed us to assign 72 molecules. Then, a genetic algorithm was applied on two series of samples (learning and validation sets), each composed of 30 commercial wines from three different wine producing regions of France. Excellent results were obtained with only four diagnostic peaks and two ion ratios. This new approach could be applied to other aspects of wine production but also to other metabolomics studies.
    DOI:  https://doi.org/10.1038/s41598-020-58193-2
  4. Anal Bioanal Chem. 2020 Jan 22.
    Mlynek F, Himmelsbach M, Buchberger W, Klampfl CW.
      Investigations into the interaction of xenobiotics with plants (and in particular edible plants) have gained substantial interest, as water scarcity due to climate-change-related droughts requires the more frequent use of reclaimed wastewaters for irrigation in agriculture. Non-steroidal anti-inflammatory drugs are common contaminants found in wastewater treatment plant effluents. For this reason, the interaction of nine edible plants with diclofenac (DCF), a widely used representative of this group of drugs, was investigated. For this purpose, plants were hydroponically grown in a medium containing DCF. For the detection of unknown DCF-related metabolites formed in the plant upon uptake of the parent drug' a new workflow based on the use of HPLC coupled to drift-tube ion-mobility quadrupole time-of-flight/mass spectrometry (DTIM QTOF-MS) was developed. Thereby' for chromatographic peaks eluting from the HPLC, drift times were recorded, and analytes were subsequently fragmented in the DTIM QTOF-MS to provide significant fragments. All information available (retention times, drift times, fragment spectra, accurate mass) was finally combined' allowing the suggestion of molecular formulas for 30 DCF-related metabolites formed in the plant, whereby 23 of them were not yet known from the literature.
    Keywords:  Diclofenac; Drift-tube ion-mobility mass spectrometry; Environmental analysis; Pharmaceuticals; Plant metabolism
    DOI:  https://doi.org/10.1007/s00216-020-02429-7
  5. Metabolites. 2020 Jan 22. pii: E43. [Epub ahead of print]10(2):
    Ten-Doménech I, Ramos-Garcia V, Piñeiro-Ramos JD, Gormaz M, Parra-Llorca A, Vento M, Kuligowski J, Quintás G.
      Human milk (HM) is considered the gold standard for infant nutrition. HM contains macro- and micronutrients, as well as a range of bioactive compounds (hormones, growth factors, cell debris, etc.). The analysis of the complex and dynamic composition of HM has been a permanent challenge for researchers. The use of novel, cutting-edge techniques involving different metabolomics platforms has permitted to expand knowledge on the variable composition of HM. This review aims to present the state-of-the-art in untargeted metabolomic studies of HM, with emphasis on sampling, extraction and analysis steps. Workflows available from the literature have been critically revised and compared, including a comprehensive assessment of the achievable metabolome coverage. Based on the scientific evidence available, recommendations for future untargeted HM metabolomics studies are included.
    Keywords:  capillary electrophoresis – mass spectrometry (CE-MS); extraction; gas chromatography–mass spectrometry (GC-MS); human milk; liquid chromatography–mass spectrometry (LC-MS); metabolome; nuclear magnetic resonance (NMR); sampling
    DOI:  https://doi.org/10.3390/metabo10020043
  6. J Steroid Biochem Mol Biol. 2020 Jan 17. pii: S0960-0760(19)30473-X. [Epub ahead of print] 105598
    Hurst EA, Homer NZ, Denham SG, MacFarlane E, Campbell S, Boswinkel M, Mellanby RJ.
      Hypovitaminosis D and hypervitaminosis D are well recognised disorders in dogs. Hypovitaminosis D can occur following consumption of a diet inadequately supplemented with vitamin D or as a sequelae of severe intestinal disease. Hypervitaminosis D may occur as a result of consuming proprietary dog foods over-supplemented with vitamin D or through ingestion of vitamin D containing medicinal products or rodenticides. Consequently, there is a clear need to establish a methodology that can accurately quantify vitamin D metabolites across a broad dynamic range in dogs. The existence of C3-epimers of vitamin D metabolites has yet to be elucidated in dogs, yet are known to interfere with the analysis of vitamin D and have unknown biological activity in other species. Here, we describe the development and validation of a sensitive, specific and robust analytical liquid chromatography tandem mass spectrometry (LC-MS/MS) assay capable of separating and accurately measuring 25-hydroxyvitamin-D2/3 (25(OH)D2/3) and 3-epi-25-hydroxyvitamin-D2/3 (3-epi-25(OH)D2/3). We describe a simplified workflow utilising supported liquid extraction (SLE) without derivatization that provides good linearity (mean r > 0.996) and accuracy across a broad dynamic range of 4 - 500 nmol/L for D3 metabolites and 7.8 - 500 nmol/L for D2 metabolites. Upon application of this assay to 117 canine serum samples, 25(OH)D3 was detectable in all samples with a median concentration of 82.1 nmol/L (inter-quartile range (IQR) 59.7 - 101.8 nmol/L). 3-epi-25(OH)D3 could be detected in 87.2% of the study population, with a median concentration of 5.2 nmol/L (2.4 - 8.1 nmol/L). However, 3-epi-25(OH)D3 was quantified below the LLOQ in 40.2% of these samples. 3-epi-25(OH)D3 contributed on average 6.3% to 25(OH)D3 status (contribution ranges from 0 - 23.8%) and a positive correlation was detected between 25(OH)D3 and 3-epi-25(OH)D3 concentrations. Free 25(OH)D was also measured using an immunoassay with a median concentration of 15.2 pmol/L (12.5 - 23.2 pmol/L), and this metabolite was also positively correlated to both 3-epi-25(OH)D3 and 25(OH)D3 concentrations. D2 metabolites were not detected in canine serum as expected. Vitamin D metabolite concentrations were variable between individuals, and research into the causes of this variation should include factors such as breed, age, sex and neuter status to determine the impact of genetic and hormonal factors. Given the clinical importance of vitamin D in dogs, and the immense potential for utilising this species as a model for human disease, further elucidation of the vitamin D pathway in this species would provide immense clinical and research benefit.
    Keywords:  25-hydroxyvitamin-D; C3-epi-25-hydroxyvitamin-D; Free 25-hydroxyvitamin-D; Liquid chromatography tandem mass spectrometry; canine
    DOI:  https://doi.org/10.1016/j.jsbmb.2020.105598
  7. J Chromatogr A. 2020 Jan 10. pii: S0021-9673(20)30034-0. [Epub ahead of print] 460869
    Ye K, Jiang Q, Lu Y, Wen X, Yang J.
      Prostaglandins (PGs) are vitally important unsaturated fatty acids involved in arachidonic acid (AA) metabolism, participating in numerous pathophysiological processes, especially in maintaining the homeostasis of uterus. Therefore, quantitative analysis of PGs is of great importance for uncovering potential mechanisms of PGs related diseases. However, methods for determining PGs in uterine samples have not been reported. In this study, an ultra high-performance liquid chromatography/mass spectrometry (UHPLC-MS/MS) method was established to quantify PGs in uterine samples, using N,N-Dimethylethylenediamine (DMED) and N,N-Diethylethylenediamine (DEED) as derivatization reagents. The derivatization could be finished at 37 °C for 30 min catalyzed by 1-N,N,N',N'-Tetramethyl-O-(7-azabenzotriazol-1-yl) uronium hexafluorophosphate (HATU). This is a mild condition suitable for most of biological samples. The DMED labeling of PGs could significantly enhance their response compared to those of underived ones. This method exhibited excellent linearity (R2 > 0.997) and precision for the determination of PGs in uterine samples (CV ≤ 12.9%). The extraction recoveries of PGs were ranged from 83.0 to 100% and matrix effects were ranged from 86.3 to 106%, indicating DEED labeled standards could be used as internal standards for PGs quantification. With the proposed method, we successfully quantified PGs in rat uterus. The results showed their levels were significant changed in abnormal uterine bleeding (AUB) rats, suggesting that PGs might be involved in the pathological process of AUB. This established analogous reagents derivatization based UHPLC-MS/MS method could be used as a powerful tool to monitor PGs, providing insights to the precise mechanism of PG action on the endometrium.
    Keywords:  Analogous reagents derivatization; N, N-Dimethylethylenediamine; Prostaglandin; UHPLC-MS; Uterus
    DOI:  https://doi.org/10.1016/j.chroma.2020.460869
  8. Trends Biochem Sci. 2020 Jan 16. pii: S0968-0004(19)30263-4. [Epub ahead of print]
    Fernández-García J, Altea-Manzano P, Pranzini E, Fendt SM.
      Metabolism is at the cornerstone of all cellular functions and mounting evidence of its deregulation in different diseases emphasizes the importance of a comprehensive understanding of metabolic regulation at the whole-organism level. Stable-isotope measurements are a powerful tool for probing cellular metabolism and, as a result, are increasingly used to study metabolism in in vivo settings. The additional complexity of in vivo metabolic measurements requires paying special attention to experimental design and data interpretation. Here, we review recent work where in vivo stable-isotope measurements have been used to address relevant biological questions within an in vivo context, summarize different experimental and data interpretation approaches and their limitations, and discuss future opportunities in the field.
    Keywords:  in vivo metabolism; metabolic models; stable-isotope tracers; tracer analysis
    DOI:  https://doi.org/10.1016/j.tibs.2019.12.002
  9. Nucleic Acids Res. 2020 Jan 20. pii: gkz1209. [Epub ahead of print]
    Singh U, Hur M, Dorman K, Wurtele ES.
      The diverse and growing omics data in public domains provide researchers with tremendous opportunity to extract hidden, yet undiscovered, knowledge. However, the vast majority of archived data remain unused. Here, we present MetaOmGraph (MOG), a free, open-source, standalone software for exploratory analysis of massive datasets. Researchers, without coding, can interactively visualize and evaluate data in the context of its metadata, honing-in on groups of samples or genes based on attributes such as expression values, statistical associations, metadata terms and ontology annotations. Interaction with data is easy via interactive visualizations such as line charts, box plots, scatter plots, histograms and volcano plots. Statistical analyses include co-expression analysis, differential expression analysis and differential correlation analysis, with significance tests. Researchers can send data subsets to R for additional analyses. Multithreading and indexing enable efficient big data analysis. A researcher can create new MOG projects from any numerical data; or explore an existing MOG project. MOG projects, with history of explorations, can be saved and shared. We illustrate MOG by case studies of large curated datasets from human cancer RNA-Seq, where we identify novel putative biomarker genes in different tumors, and microarray and metabolomics data from Arabidopsis thaliana. MOG executable and code: http://metnetweb.gdcb.iastate.edu/ and https://github.com/urmi-21/MetaOmGraph/.
    DOI:  https://doi.org/10.1093/nar/gkz1209
  10. Database (Oxford). 2020 Jan 01. pii: baz139. [Epub ahead of print]2020
    Kuo TC, Tan CE, Wang SY, Lin OA, Su BH, Hsu MT, Lin J, Cheng YY, Chen CS, Yang YC, Chen KH, Lin SW, Ho CC, Kuo CH, Tseng YJ.
      Breathomics is a special branch of metabolomics that quantifies volatile organic compounds (VOCs) from collected exhaled breath samples. Understanding how breath molecules are related to diseases, mechanisms and pathways identified from experimental analytical measurements is challenging due to the lack of an organized resource describing breath molecules, related references and biomedical information embedded in the literature. To provide breath VOCs, related references and biomedical information, we aim to organize a database composed of manually curated information and automatically extracted biomedical information. First, VOCs-related disease information was manually organized from 207 literature linked to 99 VOCs and known Medical Subject Headings (MeSH) terms. Then an automated text mining algorithm was used to extract biomedical information from this literature. In the end, the manually curated information and auto-extracted biomedical information was combined to form a breath molecule database-the Human Breathomics Database (HBDB). We first manually curated and organized disease information including MeSH term from 207 literatures associated with 99 VOCs. Then, an automatic pipeline of text mining approach was used to collect 2766 literatures and extract biomedical information from breath researches. We combined curated information with automatically extracted biomedical information to assemble a breath molecule database, the HBDB. The HBDB is a database that includes references, VOCs and diseases associated with human breathomics. Most of these VOCs were detected in human breath samples or exhaled breath condensate samples. So far, the database contains a total of 913 VOCs in relation to human exhaled breath researches reported in 2766 publications. The HBDB is the most comprehensive HBDB of VOCs in human exhaled breath to date. It is a useful and organized resource for researchers and clinicians to identify and further investigate potential biomarkers from the breath of patients. Database URL: https://hbdb.cmdm.tw.
    DOI:  https://doi.org/10.1093/database/baz139