bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2020‒10‒25
twenty papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

  1. Anal Chem. 2020 Oct 21.
      Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is an established tool in drug development, which enables visualization of drugs and drug metabolites at spatial localizations in tissue sections from different organs. However, robust and accurate quantitation by MALDI-MSI still remains a challenge. We present a quantitative MALDI-MSI method using two instruments with different types of mass analyzers, i.e., time-of-flight (TOF) and Fourier transform ion cyclotron resonance (FTICR) MS, for mapping levels of the in vivo-administered drug citalopram, a selective serotonin reuptake inhibitor, in mouse brain tissue sections. Six different methods for applying calibration standards and an internal standard were evaluated. The optimized method was validated according to authorities' guidelines and requirements, including selectivity, accuracy, precision, recovery, calibration curve, sensitivity, reproducibility, and stability parameters. We showed that applying a dilution series of calibration standards followed by a homogeneously applied, stable, isotopically labeled standard for normalization and a matrix on top of the tissue section yielded similar results to those from the reference method using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The validation results were within specified limits and the brain concentrations for TOF MS (51.1 ± 4.4 pmol/mg) and FTICR MS (56.9 ± 6.0 pmol/mg) did not significantly differ from those of the cross-validated LC-MS/MS method (55.0 ± 4.9 pmol/mg). The effect of in vivo citalopram administration on the serotonin neurotransmitter system was studied in the hippocampus, a brain region that is the principal target of the serotonergic afferents along with the limbic system, and it was shown that serotonin was significantly increased (2-fold), but its metabolite 5-hydroxyindoleacetic acid was not. This study makes a substantial step toward establishing MALDI-MSI as a fully quantitative validated method.
  2. Anal Chim Acta. 2020 Nov 01. pii: S0003-2670(20)30887-4. [Epub ahead of print]1136 115-124
      Lipids are an important class of biomolecules, and play many essential functions in biology. Ion mobility-mass spectrometry (IM-MS) has emerged as a promising technology for lipidomics by providing a holistic and multi-dimensional characterization of lipid structures. However, the lipid identification using the multi-dimensional match (i.e., MS1, retention time, collision cross section, and MS/MS spectra) gives multiple lipid candidates, and often over-reports the structural information. Here, we developed a lipid identification strategy that integrated library-based match and rule-based refinement for accurate lipid structural elucidation in IM-MS based lipidomics. The new strategy took the advantage of multi-dimensional information for high-coverage identification, while it also utilized the fragmentation rules to determine the accurate structural information. We demonstrated that the combined strategy accurately determined the lipid structures as lipid species level, fatty acyl level, or fatty acyl position level for different lipid classes in the lipid standard mixture and various biological samples. The combined strategy efficiently reduced the redundancy and improved the accuracy for different lipid classes, and identified a total of 440-960 lipid species in various biological samples. Finally, we performed quantitative lipidomics analysis of NIST SRM 1950 human plasma using IM-MS technology. The measured concentrations of most quantified lipids (>80%) were highly consistent with values reported from other independent laboratories. In summary, the developed lipid identification strategy allowed for the accurate identification of lipid structures, and facilitated accurate lipid quantification in IM-MS based untargeted lipidomics.
    Keywords:  Ion mobility-mass spectrometry; Library-based 4D match; Lipidomics; Quantification; Rule-based refinement
  3. Anal Bioanal Chem. 2020 Oct 23.
      A hydrophobic gadolinium-based magnetic ionic liquid (MIL) was investigated for the first time as an extraction solvent in dispersive liquid-liquid microextraction (DLLME). The tested MIL was composed of trihexyl(tetradecyl)phosphonium cations and paramagnetic gadolinium chloride anions. The prepared MIL showed low water miscibility, reasonable viscosity, markedly high magnetic susceptibility, adequate chemical stability, low UV background, and compatibility with reversed-phase HPLC solvents. These features resulted in a more efficient extraction than the corresponding iron or manganese analogues. Accordingly, the overall method sensitivity and reproducibility were improved, and the analysis time was reduced. The applicability of the proposed MIL was examined through the microextraction of four sartan antihypertensive drugs from aqueous samples followed by reversed-phase HPLC with UV detection at 240 nm. The DLLME procedures were optimized for disperser solvent type, MIL mass, disperser solvent volume, as well as acid, base, and salt addition. The limits of quantitation (LOQs) obtained with the analysis of 1.2-mL samples after DLLME and HPLC were 80, 30, 40, and 160 ng/mL for azilsartan medoxomil, irbesartan, telmisartan, and valsartan, respectively. Correlation coefficients were greater than 0.9988 and RSD values were in the range of 2.48-4.07%. Under the optimized microextraction conditions and using a 5-mL sample volume, enrichment factors were raised from about 40 for all sartans using a 1.2-mL sample to 175, 176, 169, and 103 for azilsartan medoxomil, irbesartan, valsartan, and telmisartan, respectively. The relative extraction recoveries for the studied sartans in river water varied from 82.5 to 101.48% at a spiked concentration of 0.5 μg/mL for telmisartan and irbesartan and 1 μg/mL for azilsartan medoxomil and valsartan. Graphical abstract.
    Keywords:  Dispersive liquid–liquid microextraction; High-performance liquid chromatography; Magnetic ionic liquids; Sartans
  4. J Chromatogr Sci. 2020 Oct 20. pii: bmaa048. [Epub ahead of print]
      Sex steroid hormones are potential biomarkers of reproductive function in teleost fish, but their measurement continues to rely on antibody-based assays. The objective of this study was to optimize a robust and simultaneous liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for measurement of eight steroid hormones (cortisol, 11-ketotestosterone, estradiol, 17α-ethynyl estradiol, estrone, estriol, progesterone and testosterone) in fish plasma. The extraction was followed by liquid-liquid extraction with tert-butyl methyl ether and time scheduled multi-reaction monitoring (sMRM) was used for quantitation of steroids. Validation of method performance using charcoal-stripped human plasma showed extraction recoveries for eight steroids ranged from 85.5 to 108.2% with matrix effects > 80%. The limits of quantitation were 0.01 pg/μL for testosterone, 0.05 pg/μL for cortisol and progesterone, 0.1 pg/μL for 11-ketotestosterone, estradiol and estrone, 0.125 pg/μL for estriol and 0.25 pg/μL for 17α-ethynyl estradiol. The proposed method was applied to plasma samples of largemouth bass (Micropterus salmoides) collected from contaminated (Lake Apopka) and reference sites (Wildcate Lake) in Florida. Concentrations of testosterone, cortisol, estradiol and estrone were significantly different in female fish, but plasma concentration of cortisol was only statistically different in male fish between two sites (P < 0.05). This study demonstrates the application of a robust LC-MS/MS analysis for a range of sex steroid hormones representative of endocrine function in a top predator, largemouth bass.
  5. Metabolites. 2020 Oct 16. pii: E415. [Epub ahead of print]10(10):
      Metabolomics analysis of biological samples is widely applied in medical and natural sciences. Assigning the correct chemical structure in the metabolite identification process is required to draw the correct biological conclusions and still remains a major challenge in this research field. Several metabolite tandem mass spectrometry (MS/MS) fragmentation spectra libraries have been developed that are either based on computational methods or authentic libraries. These libraries are limited due to the high number of structurally diverse metabolites, low commercial availability of these compounds, and the increasing number of newly discovered metabolites. Phase II modification of xenobiotics is a compound class that is underrepresented in these databases despite their importance in diet, drug, or microbiome metabolism. The O-sulfated metabolites have been described as a signature for the co-metabolism of bacteria and their human host. Herein, we have developed a straightforward chemical synthesis method for rapid preparation of sulfated metabolite standards to obtain mass spectrometric fragmentation pattern and retention time information. We report the preparation of 38 O-sulfated alcohols and phenols for the determination of their MS/MS fragmentation pattern and chromatographic properties. Many of these metabolites are regioisomers that cannot be distinguished solely by their fragmentation pattern. We demonstrate that the versatility of this method is comparable to standard chemical synthesis. This comprehensive metabolite library can be applied for co-injection experiments to validate metabolites in different human sample types to explore microbiota-host co-metabolism, xenobiotic, and diet metabolism.
    Keywords:  chemical synthesis; metabolomics; microbiome; phase II metabolism; structure validation; sulfated metabolites
  6. Anal Chim Acta. 2020 Nov 01. pii: S0003-2670(20)30889-8. [Epub ahead of print]1136 42-50
      Unstable tissue components (metabolites) are not easily captured and evaluated by traditional metabolomics methods. In this study, a comprehensive investigation of various sampling methods and storage conditions on the metabolomic profile of fish muscle was performed based on in vivo and ex vivo sampling. The GlobalStd algorithm and structure/reaction directed analysis under a linear mixed model were used to investigate the distinctive influences of these factors on the metabolomic profiles of fish tissue obtained via untargeted LC-MS analysis. Immediate analysis of samples yielded different metabolomic profiles compared to that of stored samples. Storage time was found to affect the metabolomic profile in a complex way, whereas storage temperature was shown to not substantially change this pattern. At the reaction level, metabolites involved in homologous series with butylation were shown stable during storage. Overall, our findings demonstrate that immediate instrumental analysis after in vivo solid phase microextraction (SPME) sampling and a reverse time series experimental design should be the preferred approaches for metabolomic profiling if unstable compounds are of interest.
    Keywords:  Extraction; LC-MS; Mass spectrum; Metabolomics; SPME; Sample preparation; Storage; Unstable compounds
  7. Mass Spectrom Rev. 2020 Oct 23.
      Developments in mass spectrometry technologies have driven a widespread interest and expanded their use in cancer-related research and clinical applications. In this review, we highlight the developments in mass spectrometry methods and instrumentation applied to direct tissue analysis that have been tailored at enhancing performance in clinical research as well as facilitating translation and implementation of mass spectrometry in clinical settings, with a focus on cancer-related studies. Notable studies demonstrating the capabilities of direct mass spectrometry analysis in biomarker discovery, cancer diagnosis and prognosis, tissue analysis during oncologic surgeries, and other clinically relevant problems that have the potential to substantially advance cancer patient care are discussed. Key challenges that need to be addressed before routine clinical implementation including regulatory efforts are also discussed. Overall, the studies highlighted in this review demonstrate the transformative potential of mass spectrometry technologies to advance clinical research and care for cancer patients.© 2020 Wiley Periodicals, Inc. Mass Spec Rev.
  8. J Sep Sci. 2020 Oct 21.
      While Supercritical fluid chromatography was developed over fifty years ago, it is only over the past fifteen to twenty years that it has become routinely utilized. Along with the commercialization of a new generation of instruments, during the last twenty years supercritical fluid chromatography has improved performance, reliability and robustness. SFC is fully compatible with mass spectrometric techniques. This review compiles the application of supercritical fluid chromatography separations coupled to MS instrumentation for the exploration, profiling and quantitation of metabolites during the last two decades. The selection of metabolites chosen for this article have direct applications in preclinical models of disease and clinical applications as potential biomarkers of disease including lipids, steroid hormones, bile acids, polar metabolites, peptides, and proteins. This article is protected by copyright. All rights reserved.
    Keywords:  Biomarkers discovery; metabolomics; supercritical fluid
  9. Anal Chim Acta. 2020 Nov 01. pii: S0003-2670(20)30985-5. [Epub ahead of print]1136 187-195
      Long chain unsaturated fatty acids (LCUFAs) are emerging as critical contributors to inflammation and its resolution. Sensitive and accurate measurement of LCUFAs in biological samples is thus of great value in disease diagnosis and prognosis. In this work, a fluorous-derivatization approach for UPLC-MS/MS quantification of LCUFAs was developed by employing a pair of fluorous reagents, namely 3-(perfluorooctyl)-propylamine (PFPA) and 2-(perfluorooctyl)-ethylamine (PFEA). With this method, the LCUFAs in biological samples were perfluoroalkylated with PFPA and specifically retained on a fluorous-phase LC column, which largely reduced matrix interferences-induced quantitation deviation. Moreover, PFEA-labeled LCUFAs standards were introduced as one-to-one internal standards to farthest ensure unbiased results. Application of the proposed method enabled a reliable determination of eight typical LCUFAs with high sensitivity (LLOQ ranged from 30 amol to 6.25 fmol) and low matrix interferences (almost less than 10%). Such a high sensitivity could facilitate the determination of small-volume and low-concentration bio-samples. Further metabolic characterization of these targeted LCUFAs was monitored in OVA-induce asthma mice, requiring only 5 μL serum sample. Our results showed that asthmatic attack led to significant disturbances not only in the concentrations but also in the ratio among these LCUFAs. In view of the favorable advantages in sensitivity and accuracy, the present fluorous-paired derivatization approach will be expected to serve as a new avenue for dissecting the physiological and clinical implications of LCUFAs, thereby shedding light on the management of diseases related to their disturbances.
    Keywords:  Fluorous derivatization; High accuracy and sensitivity; LC-MS analysis; Long chain unsaturated fatty acids
  10. J Chromatogr B Analyt Technol Biomed Life Sci. 2020 Oct 06. pii: S1570-0232(20)31270-8. [Epub ahead of print]1158 122394
      Vitamin D status is typically assessed by the measurement of 25-hydroxyvitamin D (25(OH)D). However, in selected patient groups the sole determination of 25(OH)D has been proven insufficient for this purpose. The simultaneous measurement of additional vitamin D metabolites may provide useful information for a better evaluation of the vitamin D status. Therefore, we developed and validated a liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the simultaneous determination of 25(OH)D3, 25(OH)D2, 24,25(OH)2D3 and additionally 25,26(OH)2D3, which was identified with a synthesized pure substance. Pure and deuterated substances were used to prepare calibrators and internal standards for all target metabolites. Pre-analytical sample preparation comprised protein precipitation followed by liquid-liquid-extraction and derivatization with 4-Phenyl-1,2,4-triazole-3,5-dione (PTAD) using 50 µL sample volume. Samples were analyzed on an Agilent HPLC 1260 system equipped with a silica-based Kinetex® 5 µm F5 100 Å core-shell column (150 × 4.6 mm) coupled to a Sciex 4500 mass spectrometer. For all four metabolites, limit of detection (LoD) and limit of quantification (LoQ) ranged from 0.3 to 1.5 nmol/L and 1.0 to 3.1 nmol/L, respectively. Recovery varied between 76.1 % and 84.3 %. Intra- and inter-assay imprecision were <8.6 % and <11.5 %, respectively. The analysis of external and internal quality control samples showed good accuracy for 25(OH)D3, 25(OH)D2, 24(R),25(OH)2D3 and 25,26(OH)2D3. Method comparison studies with human samples that were also analyzed with two other LC-MS/MS methods showed close agreement. Finally, the present method has been shown capable of identifying patients with 24-hydroxylase deficiency, which proves its clinical utility.
    Keywords:  24,25-dihydroxyvitamin D; 25,26-dihydroxyvitamin D; LC-MS/MS; Vitamin D deficiency; Vitamin D metabolite ratio
  11. Anal Chim Acta. 2020 Nov 01. pii: S0003-2670(20)30984-3. [Epub ahead of print]1136 168-177
      Global profiling of the metabolome and lipidome of specific brain regions is essential to understanding the cellular and molecular mechanisms regulating brain activity. Given the limited amount of starting material, conventional mouse studies comparing brain regions have mainly targeted a set of known metabolites in large brain regions (e.g., cerebrum, cortex). In this work, we developed a multimodal analytical pipeline enabling parallel analyses of metabolomic and lipidomic profiles from anatomically distinct mouse brain regions starting with less than 0.2 mg of protein content. This analytical pipeline is composed of (1) sonication-based tissue homogenization, (2) parallel metabolite and lipid extraction, (3) BCA-based sample normalization, (4) ultrahigh performance liquid chromatography-mass spectrometry-based multimodal metabolome and lipidome profiling, (5) streamlined data processing, and (6) chord plot-based data visualization. We applied this pipeline to the study of four brain regions in males including the amygdala, dorsal hippocampus, nucleus accumbens and ventral tegmental area. With this novel approach, we detected over 5000 metabolic and 6000 lipid features, among which 134 metabolites and 479 lipids were directly confirmed via automated MS2 spectral matching. Interestingly, our analysis identified unique metabolic and lipid profiles in each brain regions. Furthermore, we identified functional relationships amongst metabolic and lipid subclasses, potentially underlying cellular and functional differences across all four brain regions. Overall, our novel workflow generates comprehensive region-specific metabolomic and lipidomic profiles using very low amount of brain sub-regional tissue sample, which could be readily integrated with region-specific genomic, transcriptomic, and proteomic data to reveal novel insights into the molecular mechanisms underlying the activity of distinct brain regions.
    Keywords:  Brain regions; Lipidomics; Liquid chromatography-mass spectrometry; Metabolic patterns; Metabolomics; Parallel profiling
  12. Talanta. 2021 Jan 01. pii: S0039-9140(20)30787-6. [Epub ahead of print]221 121496
      Aim and novelty of this work are the development of a simple and straightforward analytical procedure for multiclass determination of steroid hormones in human plasma. The method entails a single pre-treatment step based on solid-phase extraction using a recently proposed sorbent phase (HA-C@silica). This is easily prepared with good reproducibility via pyrolysis of humic acids onto silica, and not yet tested in biological fluids. It proved to be advantageous as it showed poor affinity for the protein matrix constituents while quantitatively extracting and pre-concentrating the target analytes. Indeed, as demonstrated in bovine serum albumin solution, up to ca. 90% protein is not retained by the sorbent, similarly to the behaviour of restricted access carbon nanotubes, tested for comparison. The high albumin exclusion allowed a satisfactory clean-up avoiding protein precipitation and centrifugation before extraction. The extraction procedure, optimized by a chemometric approach (23 experimental design) in BSA solution, provided quantitative recovery (76-119%, n = 3) for all steroids working with 1:8-diluted plasma (2 mL) and 100 mg HA-C@silica. Before analytes elution by 1 mL methanol-acetonitrile (1:1, v/v), selective washings (2% v/v formic acid and 30% v/v methanol) were applied to remove the small fraction of retained proteins, thus obtaining very clean SPE extracts to be analyzed by HPLC-ESI-MS/MS. This allowed identification/quantification (MRM mode) at few ng mL-1 by a single chromatographic run. The procedure was verified in blank-certified foetal bovine serum (spikes 10-100 ng mL-1), obtaining good recovery and suitable inter-day precision (RSDs < 15%, n = 3). The analytical method, applied to real plasma samples analysis, is appealing in terms of sample throughput, extraction efficiency and clean-up.
    Keywords:  Bioanalysis; Clean-up; Hormones; Human plasma; LC-MS; Solid-phase extraction
  13. J Chromatogr B Analyt Technol Biomed Life Sci. 2020 Oct 08. pii: S1570-0232(20)31273-3. [Epub ahead of print]1158 122397
      Treatment of multidrug-resistant tuberculosis (MDR-TB) is challenging due to high treatment failure rate and adverse drug events. This study aimed to develop and validate a simple LC-MS/MS method for simultaneous measurement of five TB drugs in human plasma and to facilitate therapeutic drug monitoring (TDM) in MDR-TB treatment to increase efficacy and reduce toxicity. Moxifloxacin, levofloxacin, prothionamide, pyrazinamide and ethambutol were prepared in blank plasma from healthy volunteers and extracted using protein precipitation reagent containing trichloroacetic acid. Separation was achieved on an Atlantis T3 column with gradient of 0.1% formic acid in water and acetonitrile. Drug concentrations were determined by dynamic multiple reaction monitoring in positive ion mode on a LC-MS/MS system. The method was validated according to the United States' Food and Drug Administration (FDA) guideline for bioanalytical method validation. The calibration curves for moxifloxacin, levofloxacin, prothionamide, pyrazinamide and ethambutol were linear, with the correlation coefficient values above 0.993, over a range of 0.1-5, 0.4-40, 0.2-10, 2-100 and 0.2-10 mg/L, respectively. Validation showed the method to be accurate and precise with bias from 6.5% to 18.3% for lower limit of quantification and -5.8% to 14.6% for LOW, medium (MED) and HIGH drug levels, and with coefficient of variations within 11.4% for all levels. Regarding dilution integrity, the bias was within 7.2% and the coefficient of variation was within 14.9%. Matrix effect (95.7%-112.5%) and recovery (91.4%-109.7%) for all drugs could be well compensated by their isotope-labelled internal standards. A benchtop stability test showed that the degradation of prothionamide was over 15% after placement at room temperature for 72 h. Clinical samples (n = 224) from a cohort study were analyzed and all concentrations were within the analytical range. The signal of prothionamide was suppressed in samples with hemolysis which was solved by sample dilution. As the method is robust and sample preparation is simple, it can easily be implemented to facilitate TDM in programmatic MDR-TB treatment.
    Keywords:  Antituberculosis drugs; Human plasma; LC-MS/MS; Quantitative drug analysis; Therapeutic drug monitoring
  14. Clin Biochem. 2020 Oct 20. pii: S0009-9120(20)30871-7. [Epub ahead of print]
      OBJECTIVE: To verify a rapid and sensitive ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the quantification of catecholamines and their metabolites, and to validate its efficiency for the diagnosis of phaeochromocytomas and paragangliomas (PPGLs).METHODS: Plasma samples were pretreated with solid-phase extraction, followed by a 3-min UPLC-MS/MS analysis to quantify epinephrine (E), norepinephrine (NE), dopamine (DA), metanephrine (MN), normetanephrine (NMN) and 3-methoxytyramine (3-MT), simultaneously. The UPLC-MS/MS method was comprehensively verified and its diagnostic efficiency on PPGLs was tested using 7 PPGLs and 408 non-PPGLs patient plasma samples.
    RESULTS: Using the developed method, the limit of detections (LODs) of the 6 analytes ranged from 0.0002 nmol/L (MN) to 0.0250 nmol/L (NE), while the lower limit of measuring intervals (LLMIs) ranged from 0.05 nmol/L (E, MN and NMN) to 0.10 nmol/L (NE and DA). The reportable ranges were 0.05-30.00 nmol/L for E, MN and NMN, 0.10-30.00 nmol/L for NE and DA, 1.00-300.00 pg/mL for 3-MT. No significant matrix effect was detected after correcting using internal standard. Besides, intra-day and inter-day precision were also within acceptance criteria with coefficient of variations (CVs) ≤15% and recoveries ranged from 95% to 115% for all the 6 analytes. The carryover effect was lower than 10%. Its diagnostic efficiency for PPGLs was significantly increased, the areas under the receiver operating characteristic (ROC) curves were increased from 68.7%-89.1% (using E, NE and DA) to 75.2%-99.9% (using MN, NMN and 3-MT).
    CONCLUSION: This study verified a rapid UPLC-MS/MS method for the determination of catecholamines and their metabolites in human plasma. It showed high diagnostic efficiency and will serve as an important tool to avoid the risk for missing patients with PPGLs.
    Keywords:  PPGLs; UPLC-MS/MS; catecholamine; diagnostic efficiency
  15. J Mass Spectrom. 2020 Oct 14. e4666
      The spatial resolution of microdissection-based analytical methods to detect ocular lens glucose uptake, transport and metabolism are poor, whereas the multiplexing capability of fluorescence microscopy-based approaches to simultaneously detect multiple glucose metabolites is limited in comparison with mass spectrometry-based methods. To better understand lens glucose transport and metabolism, a more highly spatially resolved technique that maintains the fragile ocular lens tissue is required. In this study, a sample preparation method for matrix-assisted laser desorption/ionisation imaging mass spectrometry (MALDI IMS) analysis of ocular lens glucose uptake and metabolism has been evaluated and optimised. Matrix choice, tissue preparation and normalisation strategy were determined using negative ion mode MALDI-Fourier transform-ion cyclotron resonance MS of bovine lens tissue and validation performed using gas chromatography-MS. An internal standard was applied concurrently with N-(1-naphthyl)ethylenediamine dihydrochloride (NEDC) matrix to limit cracking of the fresh frozen lens tissue sections. MALDI IMS data were collected at a variety of spatial resolutions to detect both endogenous lens metabolites and stable isotopically labelled glucose introduced by ex vivo lens culture. Using this approach, initial steps in important metabolic processes that are linked to diabetic cataract formation were spatially mapped in the bovine lens. In the future, this method can be applied to study the dynamics of glucose uptake, transport and metabolic flux to aid in the study of diabetic lens cataract pathophysiology.
    Keywords:  MALDI imaging; glucose; lens; metabolites
  16. J Mass Spectrom. 2020 Sep 29. e4658
      Metabolism is the set of life-sustaining reactions in organisms. These biochemical reactions are organized in metabolic pathways, in which one metabolite is converted through a series of steps catalyzed by enzymes in another chemical compound. Metabolic reactions are categorized as catabolic, the breaking down of metabolites to produce energy, and/or anabolic, the synthesis of compounds that consume energy. The balance between catabolism of the preferential fuel substrate and anabolism defines the overall metabolism of a cell or tissue. Metabolomics is a powerful tool to gain new insights contributing to the identification of complex molecular mechanisms in the field of biomedical research, both basic and translational. The enormous potential of this kind of analyses consists of two key aspects: (i) the possibility of performing so-called targeted and untargeted experiments through which it is feasible to verify or formulate a hypothesis, respectively, and (ii) the opportunity to run either steady-state analyses to have snapshots of the metabolome at a given time under different experimental conditions or dynamic analyses through the use of labeled tracers. In this review, we will highlight the most important practical (e.g., different sample extraction approaches) and conceptual steps to consider for metabolomic analysis, describing also the main application contexts in which it is used. In addition, we will provide some insights into the most innovative approaches and progress in the field of data analysis and processing, highlighting how this part is essential for the proper extrapolation and interpretation of data.
  17. ACS Pharmacol Transl Sci. 2020 Oct 09. 3(5): 987-996
      Ivacaftor-tezacaftor and ivacaftor-tezacaftor-elexacaftor are new breakthrough cystic fibrosis (CF) drug combinations that directly modulate the activity and trafficking of the defective CF transmembrane conductance regulator protein (CFTR) underlying the CF disease state. Currently, in the hospital setting, there are no therapeutic drug monitoring assays for these very expensive, albeit, life-saving drugs. A rapid and precise novel method for the quantification of ivacaftor, its metabolites, tezacaftor, and elexacaftor, in human plasma was developed and validated using multiple reaction monitoring mass spectrometry (MRM/MS). The MRM/MS analytical method was validated at a concentration range of 0.0025-1 μg/mL for ivacaftor, ivacaftor-M1, ivacaftor-M6, tezacaftor, and elexacaftor in human plasma. The method displayed good accuracy (90.62-94.51%) and reproducibility (99.91-100%) including at low concentrations 0.01 μg/mL. With a mobile phase consisting of [acetonitrile/water]/0.1% formic acid (70:30 v/v) at a flow rate of 0.5 mL/min, a linear correlation was observed over a concentration range of 0.0025-1 μg/mL in human plasma for ivacaftor (R 2 = 0.9865105), ivacaftor-M1 (R 2 = 0.9852684), ivacaftor-M6 (R 2 = 0.9911764), tezacaftor (R 2 = 0.98742470), and elexacaftor (R 2 = 0.9897608). The reported method can accurately quantify ivacaftor, ivacaftor-M1, ivacaftor-M6, tezacaftor, and elexacaftor at low concentrations in human plasma. We have established a cost-efficient and timely method for measuring ivacaftor, its metabolites, and tezacaftor with or without elexacaftor in human plasma suitable for high-throughput applications in the hospital settings or clinical trials.
  18. Metabolomics. 2020 Oct 21. 16(11): 117
      INTRODUCTION: Despite the availability of several pre-processing software, poor peak integration remains a prevalent problem in untargeted metabolomics data generated using liquid chromatography high-resolution mass spectrometry (LC-MS). As a result, the output of these pre-processing software may retain incorrectly calculated metabolite abundances that can perpetuate in downstream analyses.OBJECTIVES: To address this problem, we propose a computational methodology that combines machine learning and peak quality metrics to filter out low quality peaks.
    METHODS: Specifically, we comprehensively and systematically compared the performance of 24 different classifiers generated by combining eight classification algorithms and three sets of peak quality metrics on the task of distinguishing reliably integrated peaks from poorly integrated ones. These classifiers were compared to using a residual standard deviation (RSD) cut-off in pooled quality-control (QC) samples, which aims to remove peaks with analytical error.
    RESULTS: The best performing classifier was found to be a combination of the AdaBoost algorithm and a set of 11 peak quality metrics previously explored in untargeted metabolomics and proteomics studies. As a complementary approach, applying our framework to peaks retained after filtering by 30% RSD across pooled QC samples was able to further distinguish poorly integrated peaks that were not removed from filtering alone. An R implementation of these classifiers and the overall computational approach is available as the MetaClean package at .
    CONCLUSION: Our work represents an important step forward in developing an automated tool for filtering out unreliable peak integrations in untargeted LC-MS metabolomics data.
    Keywords:  Machine learning; Metabolomics; Peak integration; Pre-processing; Quality control; Untargeted
  19. Metabolites. 2020 Oct 16. pii: E416. [Epub ahead of print]10(10):
      Preprocessing data in a reproducible and robust way is one of the current challenges in untargeted metabolomics workflows. Data curation in liquid chromatography-mass spectrometry (LC-MS) involves the removal of biologically non-relevant features (retention time, m/z pairs) to retain only high-quality data for subsequent analysis and interpretation. The present work introduces TidyMS, a package for the Python programming language for preprocessing LC-MS data for quality control (QC) procedures in untargeted metabolomics workflows. It is a versatile strategy that can be customized or fit for purpose according to the specific metabolomics application. It allows performing quality control procedures to ensure accuracy and reliability in LC-MS measurements, and it allows preprocessing metabolomics data to obtain cleaned matrices for subsequent statistical analysis. The capabilities of the package are shown with pipelines for an LC-MS system suitability check, system conditioning, signal drift evaluation, and data curation. These applications were implemented to preprocess data corresponding to a new suite of candidate plasma reference materials developed by the National Institute of Standards and Technology (NIST; hypertriglyceridemic, diabetic, and African-American plasma pools) to be used in untargeted metabolomics studies in addition to NIST SRM 1950 Metabolites in Frozen Human Plasma. The package offers a rapid and reproducible workflow that can be used in an automated or semi-automated fashion, and it is an open and free tool available to all users.
    Keywords:  Python; data cleaning; data curation; preprocessing; quality control; reference materials; signal drift; system suitability; untargeted metabolomics
  20. Anal Chem. 2020 Oct 19.
      Spectral similarity comparison through tandem mass spectrometry (MS2) is a powerful approach to annotate known and unknown metabolic features in mass spectrometry (MS)-based untargeted metabolomics. In this work, we proposed the concept of hypothetical neutral loss (HNL), which is the mass difference between a pair of fragment ions in a MS2 spectrum. We demonstrated that HNL values contain core structural information that can be used to accurately assess the structural similarity between two MS2 spectra. We then developed the Core Structure-based Search (CSS) algorithm based on HNL values. CSS was validated with sets of hundreds of randomly selected metabolites and their reference MS2 spectra, showing significantly improved correlation between spectral and structural similarities. Compared to state-of-the-art spectral similarity algorithms, CSS generates better ranking of structurally relevant chemicals among false positives. Combining CSS, HNL library, and biotransformation database, we further developed Metabolite core structure-based Search (McSearch), a novel computational solution to facilitate the annotation of unknown metabolites using the reference MS2 spectra of their structural analogs. McSearch generates better results in the Critical Assessment of Small Molecule Identification (CASMI) 2017 data set than conventional unknown feature annotation programs. McSearch was also tested in experimental MS2 data of xenobiotic metabolite derivatives belonging to three different metabolic pathways. Our results confirmed that McSearch can better capture the underlying structural similarity between MS2 spectra. Overall, this work provides a novel direction for metabolite annotation via HNL values, paving the way for annotating metabolites using their structurally similar compounds.