bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2021‒03‒28
sixteen papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

  1. J Chromatogr A. 2021 Mar 09. pii: S0021-9673(21)00171-0. [Epub ahead of print]1642 462047
      As the reliance on metabolic biomarkers within drug discovery and development increases, there is also an increased demand for global metabolomics methods to provide broad metabolome coverage and sensitivity towards differences in metabolite expression and reproducibility. A systematic approach is necessary for the development, and evaluation, of metabolomics methods using either conventional techniques or when establishing new methods that allow for additional gains in sensitivity and a reduction in requirements for amounts of a biological sample, such as those seen with methods based on microseparations. We developed a novel standard mixture and used a systematic approach for the development and optimization of optimal, ion-pair free, liquid chromatography-mass spectrometry (LC-MS) global profiling methods. These methods were scaled-down to microflow-based LC separations and compared with analytical flow ion-pairing reagent containing methods. Average peak volume improvements of 7- and 22-fold were observed in the positive and negative ionization mode microflow methods as compared to the ion-pairing reagent analytical flow methods, respectively. The linear range of the newly developed microflow methods showed up to a 10-fold increase in the lower limit of detection in the negative ionization mode. The developed microflow LC-MS methods were further evaluated using wild-type mouse plasma where up to a 9-fold increase in peak volume was observed.
    Keywords:  Increased sensitivity in metabolomics; LC-MS; Metabolic profiling; Metabolomics; Microbore columns; Microflow LC
  2. J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Mar 01. pii: S1570-0232(21)00088-X. [Epub ahead of print]1171 122608
      Antidepressants are widely used nowadays. Due to the potential detrimental consequences and involvement in forensic cases, therapeutic drug monitoring of antidepressants is desired. Herein we report a method for sensitive determination of 13 commonly used antidepressants in blood. An ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method with supported liquid extraction (SLE) was developed for analysis of imipramine, desipramine, fluoxetine, norfluoxetine, paroxetine, maprotiline, sertraline, citalopram, clomipramine, trazodone, doxepin, clozapine and amitriptyline in this study. The limits of detection (LODs) are in the range of 0.0003-0.003 ng/mL, which are lower than other reported methods by several orders of magnitude. The linear ranges are 0.01-200 ng/mL for norfluoxetine, paroxetine and doxepin, while the linear ranges are 0.001-200 ng/mL for the rest antidepressants. The correlation coefficients are over 0.99. Extraction recoveries (ER) ranging in 82.4-101.5% were obtained for the target analytes. The intra-day relative standard deviations (RSDs) range in 4.5-10.3% and inter-day RSDs range in 5.1-12.7%. Reasonable values of matrix effect (ME) ranging in 82.5-110.4% were obtained for quality control samples. The present methodology was used for the analysis of antidepressants in real cases and is expected to have a wide usage for analysis of antidepressants in biomedical area and forensic practice.
    Keywords:  Antidepressants; Supported liquid extraction; Tandem mass spectrometry; Ultra-high performance liquid chromatography
  3. Res Vet Sci. 2021 Mar 18. pii: S0034-5288(21)00085-0. [Epub ahead of print]136 343-350
      Steroid concentrations in serum are fluctuating during pregnancy of many mammal species. The current knowledge about endocrinology of gestation is mainly based on immunoassays. However, the lack of specificity of these assays hampers the reliability of the results. In the present work, we developed and validated a methodology associating liquid chromatography (LC) and mass spectrometry (MS) to simultaneously quantify, with high specificity and accuracy, estrone-3-sulfate (E3S), progesterone (PRO), estrone (E1) and estradiol (E2) in serum of two different mammal species. The sample preparation procedure is based on a simple protein precipitation and a derivatization with dansyl chloride. After the chromatographical separation, compounds were analyzed with a triple-quadrupole mass spectrometer operating in multiple reaction monitoring. Mare and American bison serum samples were analyzed with the validated method and results were compared with concentrations measured with commercial radioimmunoassay (RIA), enzyme linked immunosorbent assay (ELISA) and chemiluminescent microparticle immunoassay (CMIA). Following these criterions: relative standard deviation <15% and relative bias <15%, lower limits of quantification of 0.5 ng/mL (E3S), 0.1 ng/mL (PRO) and 2 pg/mL (E1 and E2) were achieved. Most of the comparison between immunoassays and LC-MS showed poor correlation and proportional differences. Our LC-MS method is able to simultaneously quantify several steroid hormones with high specificity, accuracy and sensitivity in serum of two different mammal species. Our method constitutes a useful and performant tool for veterinary clinicians and LC-MS should thus be used to update and refine the current knowledge about the endocrinology of pregnancy in mammals.
    Keywords:  Estrogens; Immunoassays; LC-MS; Mammals; Progesterone
  4. J Open Source Softw. 2020 ;pii: 2410. [Epub ahead of print]5(54):
      Metabolomics involves the comprehensive measurement of metabolites from a biological system. The resulting metabolite profiles are influenced by genetics, lifestyle, biological stresses, disease, diet and the environment and therefore provides a more holistic biological readout of the pathological condition of the organism (Beger et al., 2016; Wishart, 2016). The challenge for metabolomics is that no single analytical platform can provide a truly comprehensive coverage of the metabolome. The most commonly used platforms are based on mass-spectrometry (MS) and nuclear magnetic resonance (NMR). Investigators are increasingly using both methods to increase the metabolite coverage. The challenge for this type of multi-platform approach is that the data structure may be very different in these two platforms. For example, NMR data may be reported as a list of spectral features, e.g., bins or peaks with arbitrary intensity units or more directly with named metabolites reported in concentration units ranging from micromolar to millimolar. Some MS approaches can also provide data in the form of identified metabolite concentrations, but given the superior sensitivity of MS, the concentrations can be several orders of magnitude lower than for NMR. Other MS approaches yield data in the form of arbitrary response units where the dynamic range can be more than 6 orders of magnitude. Importantly, the variability and reproducibility of the data may differ across platforms. Given the diversity of data structures (i.e., magnitude and dynamic range) integrating the data from multiple platforms can be challenging. This often leads investigators to analyze the datasets separately, which prevents the observation of potentially interesting relationships and correlations between metabolites detected on different platforms. Viime (VIsualization and Integration of Metabolomics Experiments) is an open-source, web-based application designed to integrate metabolomics data from multiple platforms. The workflow of Viime for data integration and visualization is shown in Figure 1.
  5. Eur J Mass Spectrom (Chichester). 2021 Mar 21. 14690667211003196
      Aminoglycosides are a class of broad-spectrum antibiotics with several clinical uses. Owing to the ototoxicity and nephrotoxicity of aminoglycosides, therapeutic drug monitoring is required. This study aimed to devise a high-throughput method for identification and quantitative determination of aminoglycoside antibiotics in human plasma samples using ultra-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry (UPLC-Q-ToF-MS). Plasma samples (100 µL) spiked with five aminoglycosides (streptomycin, spectinomycin, amikacin, kanamycin, and gentamycin) and an internal standard (ribostamycin) were diluted and centrifuged in aqueous formic acid and acetonitrile. The clear supernatant extract was evaporated and reconstituted in the mobile phase, of which 4 µL was subjected to UPLC-Q-ToF-MS. Prominent peaks were observed for the drugs within 3 min. The recoveries of five aminoglycosides from plasma samples were 92.6-120%. The regression equations showed excellent linearity (0.9999 ≥ r2 ≥ 0.9987) within the range of 1.0-100 µg/mL, and detection limits of 0.5-2.0 µg/mL. The coefficients of the intra- and inter-day variations for five drugs were less than 11.8%, while the accuracy of quantitation was in the range of 89-111%. In this study, a novel method was presented for identification and determination of aminoglycosides in human plasma samples using UPLC-Q-ToF-MS analysis. This method can be applied to high-throughput analysis used for clinical and environmental purposes.
    Keywords:  Aminoglycoside antibiotics; UPLC–QToF- MS; human plasma; identification and determination; therapeutic drug monitoring (TDM)
  6. J Pharm Biomed Anal. 2021 Mar 16. pii: S0731-7085(21)00140-0. [Epub ahead of print]198 114028
      Cortisol is a steroid hormone that is frequently measured as a marker of stress, inflammation, and immune function. While commonly analyzed in saliva, hair, blood plasma and urine, a recent trend towards whole blood-based at-home collection devices has emerged, which necessitates development of more sensitive assays for cortisol in whole blood. To support the implementation of a patient-centric sampling approach in a drug development program, a fit-for-purpose surrogate analyte-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for cortisol in whole blood was developed using 13C3-cortisol as a surrogate analyte and cortisol-d6 as the internal standard. The surrogate analyte approach was chosen due to a lack of available cortisol-free whole blood and the absence of appropriately representative surrogate matrices. Samples were prepared using supported liquid extraction, and the LC-MS/MS analysis consisted of a 4.00 min analytical run. The method demonstrated linearity between 0.500 and 500 ng/mL of 13C3-cortisol, and accuracy, precision and robustness were all acceptable per current regulatory guidance for bioanalytical method validation of chromatographic assays for cortisol- and 13C3-cortisol-based quality control (QC) samples when quantified against a 13C3-cortisol calibration curve. The acceptable robustness of cortisol-based QCs when quantified against a 13C3-cortisol-based calibration curve also suggests parallelism between the analytes. These results indicate a viable surrogate analyte method, that is fit-for-purpose to analyze whole blood cortisol levels using a surrogate analyte LC-MS/MS approach. Evaluation of patient samples showed very promising comparability between whole blood and plasma cortisol concentrations, suggesting that whole blood could be used in place of or in addition to a plasma-based sampling protocol in clinical trials analyzing cortisol. Overall, this method presents a novel tool that is a first step in supporting the trend towards sample miniaturization and at-home sample collection, and may be readily used in clinical and diagnostic settings.
    Keywords:  Bioanalysis; Cortisol; LC-MS/MS; Supported liquid extraction; Surrogate analyte; Whole blood
  7. J Sep Sci. 2021 Mar 24.
      Hydrophilic interaction liquid chromatography is an alternative LC mode for separation of polar compounds. In the recent years, this LC mode has been recognized as an important solution for the analysis of compounds not amenable to reverse phase chromatography. In this work, we evaluated three different hydrophilic LC stationary phases for the determination of 14 highly polar anionic molecules including pesticides such as glyphosate, glufosinate, ethephon and fosetyl, their main metabolites, and bromide, chlorate and perchlorate. Several mobile phase compositions were evaluated combined with different gradients for the chromatographic run. The two columns that presented the best results were used to assess the performance for the determination of the 14 compounds in challenging highly complex feed materials. Very different matrix effects were observed for most of the compounds in each column, suggesting that different interactions can occur. Using isotopically labelled internal standards, acceptable quantitative performance and identification could be achieved down to 0.02 mg kg-1 (the lowest level tested) for most compounds. While one column was found to be favourable in terms of scope (suited for all 14 compounds), the other one was more suited for quantification and identification at lower levels, however, not for all analytes tested. This article is protected by copyright. All rights reserved.
    Keywords:  glyphosate; hydrophilic interaction chromatography; isotopically labelled standards; polar pesticides
  8. J Anal Toxicol. 2021 Mar 23. pii: bkab030. [Epub ahead of print]
      BACKGROUND: In recent years, the surge in use and of clinical trials involving tetrahydrocannabinol (THC) and cannabidiol (CBD) has increased the need for sensitive and specific analytical assays to measure said compounds in patients, to establish dose-effect relationships and to gain knowledge of their pharmacokinetics and metabolism. We developed and validated an online extraction high-performance liquid chromatography- tandem mass spectrometry (LC-MS/MS) method for simultaneous quantification of 17 cannabinoids and metabolites including THC and its metabolites, CBD and its metabolites and other minor cannabinoids in human plasma.METHODS: CBD-glucuronide (CBD-gluc) standard was produced in-house by isolation of CBD-gluc from urine of patients using pure CBD oil. For calibration standards and quality control samples, human plasma was spiked with cannabinoids at varying concentrations within the working range of the respective compound and 200 µL was extracted using a simple one-step protein precipitation procedure. The extracts were analyzed using online trapping LC/LC-atmospheric pressure chemical ionization (APCI)-MS/MS running in the positive multiple reaction monitoring (MRM) mode.
    RESULTS: The lower limit of quantification ranged from 0.78 ng/mL to 7.8 ng/mL and the upper limits of quantification were between 100 ng/mL and 2000 ng/mL. Inter-day analytical accuracy and imprecision ranged from 90.4 to 111% and from 3.1 to 17.4%, respectively. The analysis of plasma samples collected during clinical studies showed that (3R-trans)-Cannabidiol-7-oic Acid (7-CBD-COOH) was the major human metabolite with 5960% of CBD followed by 7-hydroxy-CBD (177%), CBD-gluc (157%) and 6α-hydroxy-CBD (39.8%); 6β-hydroxy-CBD was not detected in any of the samples.
    CONCLUSIONS: In the present study, we developed and validated a robust LC-MS/MS assay for the simultaneous quantification of cannabinoids and their metabolites, which has been used to measure >5,000 samples in clinical studies. Moreover, we were able to quantify CBD-gluc and showed that 7-CBD-COOH, 7-hydroxy-CBD and CBD-gluc are the major CBD metabolites in human plasma.
    Keywords:  Cannabidiol; LC-MS/MS; metabolites
  9. Anal Bioanal Chem. 2021 Mar 24.
      Data normalization is an essential part of a large-scale untargeted mass spectrometry metabolomics analysis. Autoscaling, Pareto scaling, range scaling, and level scaling methods for liquid chromatography-mass spectrometry data processing were compared with the most common normalization methods, including quantile normalization, probabilistic quotient normalization, and variance stabilizing normalization. These methods were tested on eight datasets from various clinical studies. The efficiency of the data normalization was assessed by the distance between clusters corresponding to batches and the distance between clusters corresponding to clinical groups in the space of principal components, as well as by the number of features with a pairwise statistically significant difference between the batches and the number of features with a pairwise statistically significant difference between clinical groups. Autoscaling demonstrated the most effective reduction in interbatch variation and can be preferable to probabilistic quotient or quantile normalization in liquid chromatography-mass spectrometry data.
    Keywords:  Interbatch correction; Liquid chromatography-mass spectrometry; Normalization; Scaling
  10. Anal Chim Acta. 2021 Apr 22. pii: S0003-2670(21)00168-9. [Epub ahead of print]1155 338342
      Spatially resolved metabolomics offers unprecedented opportunities for elucidating metabolic mechanisms during cancer progression. It facilitated the discovery of aberrant cellular metabolism with clinical application potential. Here, we developed a novel strategy to discover cancer tissue relevant metabolic signatures by high spatially resolved metabolomics combined with a multicellular tumor spheroid (MCTS) in vitro model. Esophageal cancer MCTS were generated using KYSE-30 human esophageal cancer cells to fully mimic the 3D microenvironment under physiological conditions. Then, the spatial features and temporal variation of metabolites and metabolic pathways in MCTS were accurately mapped by using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) with a spatial resolution at ∼12 μm. Metabolites, such as glutamate, tyrosine, inosine and various types of lipids displayed heterogeneous distributions in different microregions inside the MCTS, revealing the metabolic heterogenicity of cancer cells under different proliferative states. Subsequently, through joint analysis of metabolomic data of clinical cancer tissue samples, cancer tissue relevant metabolic signatures in esophageal cancer MCTS were identified, including glutamine metabolism, fatty acid metabolism, de novo synthesis phosphatidylcholine (PC) and phosphatidylethanolamine (PE), etc. In addition, the abnormal expression of the involved metabolic enzymes, i.e., GLS, FASN, CHKA and cPLA2, was further confirmed and showed similar tendencies in esophageal cancer MCTS and cancer tissues. The MALDI-MSI combined with MCTS approach offers molecular insights into cancer metabolism with real-word relevance, which would potentially benefit the biomarker discovery and metabolic mechanism studies.
    Keywords:  Cancer metabolism; Esophageal cancer; Mass spectrometry imaging; Multicellular tumor spheroids; Spatially resolved metabolomics
  11. Brief Bioinform. 2021 Mar 24. pii: bbab073. [Epub ahead of print]
      Metabolomics, the comprehensive study of the metabolome, and lipidomics-the large-scale study of pathways and networks of cellular lipids-are major driving forces in enabling personalized medicine. Complicated and error-prone data analysis still remains a bottleneck, however, especially for identifying novel metabolites. Comparing experimental mass spectra to curated databases containing reference spectra has been the gold standard for identification of compounds, but constructing such databases is a costly and time-demanding task. Many software applications try to circumvent this process by utilizing cutting-edge advances in computational methods-including quantum chemistry and machine learning-and simulate mass spectra by performing theoretical, so called in silico fragmentations of compounds. Other solutions concentrate directly on experimental spectra and try to identify structural properties by investigating reoccurring patterns and the relationships between them. The considerable progress made in the field allows recent approaches to provide valuable clues to expedite annotation of experimental mass spectra. This review sheds light on individual strengths and weaknesses of these tools, and attempts to evaluate them-especially in view of lipidomics, when considering complex mixtures found in biological samples as well as mass spectrometer inter-instrument variability.
    Keywords:  machine learning; mass spectrometry; metabolomics; quantum chemistry
  12. J Steroid Biochem Mol Biol. 2021 Mar 20. pii: S0960-0760(21)00073-X. [Epub ahead of print] 105880
      Steroids play an important role in cell regulation and homeostasis. Many diseases like Alzheimer's disease or Smith-Lemli-Opitz syndrome are known to be associated with deviations in the steroid profile. Most published methods only allow the analysis of small subgroups of steroids and cannot give an overview of the total steroid profile. We developed and validated a method that allows the analysis of free neutral steroids, including intermediates of cholesterol biosynthesis, free oxysterols, C19 and C21 steroids, free steroid acids, including bile acids, and sterol sulfates using gas chromatography-mass spectrometry. Samples were analyzed in scan mode for screening purposes and in dynamic multiple reaction monitoring mode for highly sensitive quantitative analysis. The method was validated for mouse brain and liver tissue and consists of sample homogenization, lipid extraction, steroid group separation, deconjugation, derivatization and gas chromatography-mass spectrometry analysis. We applied the method on brain and liver samples of mice (10 months and 3 weeks old) and cultured N2a cells and report the endogenous concentrations of 29 physiological steroids.
    Keywords:  Screening method; bile acids; deconjugation, gas chromatography-mass spectrometry; group separation; steroid profiling
  13. Anal Bioanal Chem. 2021 Mar 26.
      Mass spectrometry imaging (MSI) provides insight into the molecular distribution of a broad range of compounds and, therefore, is frequently applied in the pharmaceutical industry. Pharmacokinetic and toxicological studies deploy MSI to localize potential drugs and their metabolites in biological tissues but currently require other analytical tools to quantify these pharmaceutical compounds in the same tissues. Quantitative mass spectrometry imaging (Q-MSI) is a field with challenges due to the high biological variability in samples combined with the limited sample cleanup and separation strategies available prior to MSI. In consequence, more selectivity in MSI instruments is required. This can be provided by multiple reaction monitoring (MRM) which uses specific precursor ion-product ion transitions. This targeted approach is in particular suitable for pharmaceutical compounds because their molecular identity is known prior to analysis. In this work, we compared different analytical platforms to assess the performance of MRM detection compared to other MS instruments/MS modes used in a Q-MSI workflow for two drug candidates (A and B). Limit of detection (LOD), linearity, and precision and accuracy of high and low quality control (QC) samples were compared between MS instruments/modes. MRM mode on a triple quadrupole mass spectrometer (QqQ) provided the best overall performance with the following results for compounds A and B: LOD 35.5 and 2.5 μg/g tissue, R2 0.97 and 0.98 linearity, relative standard deviation QC <13.6%, and 97-112% accuracy. Other MS modes resulted in LOD 6.7-569.4 and 2.6-119.1 μg/g tissue, R2 0.86-0.98 and 0.86-0.98 linearity, relative standard deviation QC < 19.4 and < 37.5%, and 70-356% and 64-398% accuracy for drug candidates A and B, respectively. In addition, we propose an optimized 3D printed mimetic tissue model to increase the overall analytical throughput of our approach for large animal studies. The MRM imaging platform was applied as proof-of-principle for quantitative detection of drug candidates A and B in four dog livers and compared to LC-MS. The Q-MSI concentrations differed <3.5 times with the concentrations observed by LC-MS. Our presented MRM-based Q-MSI approach provides a more selective and high-throughput analytical platform due to MRM specificity combined with an optimized 3D printed mimetic tissue model.
    Keywords:  Absolute quantification; Desorption electrospray ionization; MRM based drug imaging; MSI comparison; Mimetic tissue model
  14. J Environ Sci Health B. 2021 Mar 24. 1-8
      The objective of this study consists of being able to develop a precise, reliable, easy, cheap and quick method to identify and quantify the presence of pesticide metabolites and their parents in human urine. In order to reach our purpose we selected the pesticides and their metabolites with intended uses on permanent crops such as orchards and vineyard. The activity planning started with the identification of the target list carried out by UHPLC-MS/MS and GC-MS/MS, succeeded by several tests oriented to determine the best sample treatment having recourse to instrumental analysis in the range 5-100 ng/mL. Several purifications were also investigated combining different adsorbents (PSA, EMR-lipid and final polish pouch). The use of formic acid during the extraction step has no impact on the recoveries, whereas the PSA adsorbent in the cleanup step negatively affects the results for all investigated metabolites. Any substantial differences were not observed in urine matrix for parent compounds achieving recoveries higher than 80% and RSD less than 20%. The final polish in combination or not with Enhanced Matrix Removal EMR-lipid did not show statistically significant difference in term of trueness and precision for both metabolites and parents, as evaluated by one-way ANOVA. The 3-OH THPI was the most critical compound with not acceptable results for linearity, trueness and precision.
    Keywords:  Pesticide residue; human exposure; mass spectrometry; multi–metabolite method (MmM)
  15. Eur J Mass Spectrom (Chichester). 2021 Mar 21. 14690667211002777
      This paper demonstrates direct detection of stimulants such as amphetamine, methamphetamine and cocaine spiked with untreated urine and a real world sample using surface ionization mass spectrometry. Spiked samples were analyzed without preliminary chromatographic separation and extraction procedure using the developed method. Moreover, in order to check the analytical capabilities of the method non-extracted real world sample was analyzed. After liquid-liquid extraction, the same sample was analyzed using the method for comparative study. Limit of detection of spiked samples was in the range of 10 pg (10 ng/ml) to 100 pg (100 ng/ml). Linear ranges of samples were two orders of magnitude or more than two orders of magnitude. It was revealed these spiked samples and real world sample can be analyzed without preliminary chromatographic separation and preliminary extraction procedure due to high selectivity of the method and the presence of the indicator lines of studied analytes in the mass spectra. The surface ionization mass spectrometry data was attested by the GC/MS analysis of these samples.
    Keywords:  GC/MS; Surface ionization mass spectrometry; biofluid; real-world sample; spiked samples; stimulants
  16. Food Chem. 2021 Mar 08. pii: S0308-8146(21)00503-3. [Epub ahead of print]354 129497
      Aflatoxin B1 is the potential chemical contaminant of most concern during the production and storage of fermented tea. In this work, a simple, fast, sensitive, accurate, and inexpensive method has been developed and validated for the simultaneous detection of four aflatoxins in fermented tea based on a modified sample pretreatment method and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Aflatoxins were extracted using acetonitrile and purified using mixed fillers (carboxyl multiwalled carbon nanotubes, hydrophilic-lipophilic balance, silica gel). Under optimum LC-MS conditions, the limits of quantification (LOQs) were 0.02-0.5 µg·kg-1. Recoveries from aflatoxins-fortified tea samples (1-12 µg·kg-1) were in the range of 78.94-105.23% with relative standard deviations (RSDs) less than 18.20%. The proposed method was applied successfully to determine aflatoxin levels in fermented tea samples.
    Keywords:  Aflatoxins; Liquid chromatography-tandem mass spectrometry; Matrix effects; One-step purification; Tea