bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2021‒10‒10
twelve papers selected by
Sofia Costa
Icahn School of Medicine at Mount Sinai

  1. Anal Chim Acta. 2021 Nov 01. pii: S0003-2670(21)00842-4. [Epub ahead of print]1184 339016
      Sulfur-containing metabolites are related to several physiologic disorders and metabolic diseases. In this study, a simultaneous identification and quantification strategy in one batch for determination of sulfhydryl-containing metabolites was developed using stable isotope labeling combined with liquid chromatography-tandem mass spectrometry (SIL-LC-MS). In the proposed method, a pair of isotope labeling reagents, D0/D5-N-ethylmaleimide (D0/D5-NEM), was used to derivatize sulfhydryl-containing metabolites in blood and plasma of normal- and high-fat-diet (NFD and HFD) hamsters for reduced (-SH) and total (-SH, -S-S-, S-glutathionylated proteins) analysis. Quality control (QC) samples and test samples were prepared for LC-MS analysis. First, both QC samples and stable isotope labeled internal standards were used to monitor the status of the instrument and ensure the reliability of the analysis. Subsequently, an inhouse database containing 45 sulfhydryl-containing metabolites was established by MS1 based on QC samples. Then, qualitatively differential sulfhydryl-containing metabolites were found by MS2 between the NFD and HFD hamsters of the test samples, including 3 in reduced and 8 in total analysis of blood samples, and 2 in reduced and 2 in total analysis of plasma samples. Next, in quantitative analysis, satisfied linearities for 6 sulfhydryl-containing metabolites were obtained with the correlation coefficient (R2) > 0.99 and absolute quantification was carried out. The results showed that glutathione and cysteine have different concentrations in blood and plasma of hamsters. Finally, the correlation of sulfhydryl-containing metabolites with blood lipid and oxidative stress levels was determined, which provided insight into the hyperlipidemia-related oxidative stress. Taken together, the developed method of simultaneous identification with the inhouse database and MS2 and quantification with standards in one batch provides a promising strategy for the analysis of sulfhydryl-containing metabolites in biological samples, which may promote the in-depth investigation on sulfhydryl-containing metabolites and related diseases.
    Keywords:  Hyperlipidemia; Identification; Oxidative stress; Quantification; Stable isotope labeling; Sulfhydryl-containing metabolites
  2. Anal Chem. 2021 Oct 04.
      Stable isotope-resolved metabolomics (SIRM) can provide metabolic conversion information of specific targets; it is a powerful tool for cell metabolism studies. The common analytical platform for SIRM is chromatography-mass spectrometry, which requires a large number of cells and is not suitable for precious rare cell analysis. To study a small number of cells, we established a novel SIRM method using chip-based nanoelectrospray mass spectrometry (MS). 13C-glutamine was taken as an example; the unlabeled and 13C-labeled cells were cultured and extracted in a 96-well plate and then directly injected into MS and analyzed in full scan mode and parallel reaction monitoring (PRM) mode targeting 44 glutamine-derived metabolites and their isotopologues. To define focused metabolite-related MS2 fragments produced in the PRM, a new strategy was proposed including MS2 exact m/z matching, MS2 false positive filtering, and MS2 fragment grouping to remove the interfering MS2 ions. In total, 292 and 349 pairs of paired MS2 ions were obtained in positive and negative ionization modes, respectively. By searching spectra databases, 31 targeted metabolites with their isotopologues were identified and their characteristic product ions were confirmed for MS2 quantification. The relative quantification was achieved by MS2 quantification, which showed better sensitivity and accuracy than common MS1-based quantification. Finally, this method was applied to isocitrate dehydrogenase I-mutated glioma cells for revealing the effects of triptolide on glioma cell metabolism using U-13C-glutamine as a labeling substrate.
  3. J Biosci Bioeng. 2021 Oct 04. pii: S1389-1723(21)00241-3. [Epub ahead of print]
      The production of chemicals and fuels from renewable resources using engineered microbes is an attractive alternative for current fossil-dependent industries. Metabolic engineering has contributed to pathway engineering for the production of chemicals and fuels by various microorganisms. Recently, dynamic metabolic engineering harnessing synthetic biological tools has become a next-generation strategy in this field. The dynamic regulation of metabolic flux during fermentation optimizes metabolic states according to each fermentation stage such as cell growth phase and compound production phase. However, it is necessary to repeat the evaluation and redesign of the dynamic regulation system to achieve the practical use of engineered microbes. In this study, we performed quantitative metabolome analysis to investigate the effects of dynamic metabolic flux regulation on engineered Escherichia coli for γ-amino butyrate (GABA) fermentation. We prepared a stable isotope-labeled internal standard mixture (SILIS) for the stable isotope dilution method (SIDM), a mass spectrometry-based quantitative metabolome analysis method. We found multiple candidate bottlenecks for GABA production. Some metabolic reactions in the GABA production pathway should be engineered for further improvement in the direct GABA fermentation with dynamic metabolic engineering strategy.
    Keywords:  Escherichia coli; Fermentation; GABA; Metabolic engineering; Pathway engineering; Quantitative metabolomics; Stable isotope dilution; Synthetic biology; Synthetic genetic circuit
  4. Am J Physiol Cell Physiol. 2021 Oct 06.
      Cells regulate their cell volume, but cell volumes may change in response to metabolic and other perturbations. Many metabolomics experiments use cultured cells to measure changes in metabolites in response to physiological and other experimental perturbations, but the metabolomics workflow by mass spectrometry only determines total metabolite amounts in cell culture extracts. To convert metabolite amount to metabolite concentration requires knowledge of the number and volume of the cells. Measuring only metabolite amount can lead to incorrect or skewed results in cell culture experiments because cell size may change due to experimental conditions independent of change in metabolite concentration. We have developed a novel method to determine cell volume in cell culture experiments using a pair of stable isotopically labeled phenylalanine internal standards incorporated within the normal liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics workflow. This method relies on the flooding-dose technique where the intracellular concentration of a particular compound (in this case phenylalanine) is forced to equal its extracellular concentration. We illustrate the LC-MS/MS technique for two different mammalian cell lines. Although the method is applicable in general for determining cell volume, the major advantage of the method is its seamless incorporation within the normal metabolomics workflow.
    Keywords:  cell culture; flooding dose; liquid chromatography-mass spectrometry; method; stable isotopes
  5. Anal Chem. 2021 Oct 08.
      The chemical derivatization of multiple lipid classes was developed using benzoyl chloride as a nonhazardous derivatization agent at ambient conditions. The derivatization procedure was optimized with standards for 4 nonpolar and 8 polar lipid classes and measured by reversed-phase ultrahigh-performance liquid chromatography-tandem mass spectrometry. The derivatization and nonderivatization approaches were compared on the basis of the calibration curves of 22 internal standards from 12 lipid classes. The new method decreased the limit of detection 9-fold for monoacylglycerols (0.9-1.0 nmol/mL), 6.5-fold for sphingoid base (0.2 nmol/mL), and 3-fold for diacylglycerols (0.9 nmol/mL). The sensitivity expressed by the ratio of calibration slopes was increased 2- to 10-fold for almost all investigated lipid classes and even more than 100-fold for monoacylglycerols. Moreover, the benzoylation reaction produces a more stable derivative of cholesterol in comparison to the easily in-source fragmented nonderivatized form and enabled the detection of fatty acids in a positive ion mode, which does not require polarity switching as for the nonderivatized form. The intralaboratory comparison with an additional operator without previous derivatization experiences shows the simplicity, robustness, and reproducibility. The stability of the derivatives was determined by periodical measurements during a one month period and five freeze/thaw cycles. The fully optimized derivatization method was applied to human plasma, which allows the detection of 169 lipid species from 11 lipid classes using the high confidence level of identification in reversed-phase (RP)-ultra high performance liquid chromatography (UHPLC)/mass spectrometry (MS). Generally, we detected more lipid species for monoacylglycerols, diacylglycerols, and sphingoid bases in comparison with previously reported papers without the derivatization.
  6. Rapid Commun Mass Spectrom. 2021 Oct 06. e9206
      RATIONALE: Non-target screening techniques using high resolution mass spectrometers become more and more important for environmental sciences. Highly reliable and sophisticated software solutions are required to deal with the large amount of data obtained from such analyses.METHODS: Processing of high-resolution LC-HRMS data was performed upon conversion into an open, xml-based data format followed by an automated assignment of chromatographic peaks using the open-source programming language R. Raw data from three different LC-HRMS systems were processed as a proof of principle.
    RESULTS: Within this manuscript we present a simple and straightforward algorithm to extract chromatographic peaks from previously m/z-centroided data based on the open-source programming language R and C++. The working principle and processing parameters are explained in detail. A ready-to-use script is provided in the SI.
    CONCLUSIONS: The developed algorithm enables a comprehensible automated peak picking of non-target LC-MS data. Application to three completely different HRMS raw data files showed reasonable false positives and false negatives detection and moderate calculation times.
  7. Bioanalysis. 2021 Oct 04.
      Aims: A chiral HPLC-MS/MS method for quantitation of an active metabolite (M2) of abrocitinib was validated in human plasma. Methods: Protein precipitation extraction and normal phase LC with baseline separation of five analytes (abrocitinib; isomeric metabolites M1, M2, M3 and M4) were achieved followed by mass spectrometric quantitation of M2 using positive-mode APCI. Results: With a 5-5000 ng/ml assay range using 100 μl K2EDTA aliquot, the assay provided short (17-min) runtime and robust separation up to approximately 330 injections on one column. Interday and intraday accuracy ranged from -6.80% to 13.4%; between-day and within-day precision was ≤10.4%. Conclusion: The method was used in multiple clinical studies, with excellent run passing rate and incurred sample reproducibility.
    Keywords:  APCI; abrocitinib metabolite; enantioseparation; human plasma
  8. Anal Chim Acta. 2021 Oct 16. pii: S0003-2670(21)00794-7. [Epub ahead of print]1182 338968
      Optimal handling is the most important means to ensure adequate sample quality. We aimed to investigate whether pre-centrifugation delay time and temperature could be accurately predicted and to what extent variability induced by pre-centrifugation management can be adjusted for. We used untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics to predict and evaluate the influence of pre-centrifugation temperature and delayed time on plasma samples. Pre-centrifugation temperature (4, 25 and 37 °C; classification rate 87%) and time (5-210 min; Q2 = 0.82) were accurately predicted using Random Forest (RF). Metabolites uniquely reflecting temperature and temperature-time interactions were discovered using a combination of RF and generalized linear models. Time-related metabolite profiles suggested a perturbed stability of the metabolome at all temperatures in the investigated time period (5-210 min), and the variation at 4 °C was observed in particular before 90 min. Fourteen and eight metabolites were selected and validated for accurate prediction of pre-centrifugation temperature (classification rate 94%) and delay time (Q2 = 0.90), respectively. In summary, the metabolite profile was rapidly affected by pre-centrifugation delay at all temperatures and thus the pre-centrifugation delay should be as short as possible for metabolomics analysis. The metabolite panels provided accurate predictions of pre-centrifugation delay time and temperature in healthy individuals in a separate validation sample. Such predictions could potentially be useful for assessing legacy samples where relevant metadata is lacking. However, validation in larger populations and different phenotypes, including disease states, is needed.
    Keywords:  Biobank; Machine learning; Plasma; Pre-centrifugation management; Sample quality; Untargeted metabolomics
  9. Crit Rev Anal Chem. 2021 Oct 03. 1-13
      There is an ever-growing interest in metabolomic profiling using noninvasive, real-time techniques that avoid sample manipulation and are painless for the patients. In this context, breath analysis is gaining much attention, and several ionization techniques have been developed to get insights in real-time into metabolic status by analyzing breath through mass spectrometry, such as Proton transfer reaction mass spectrometry (PTR-MS), Selected ion flow tube mass spectrometry (SIFT-MS), and Secondary electrospray ionization mass spectrometry (SESI-MS). SESI-MS is the most recently developed analytical platform displaying particular adequate characteristics for breath analysis, such as the low detection limits, and the detection of low volatility species, which tend to present a higher biological significance. Here, we review the SESI technology development, the different SESI configurations developed, and the standardization procedures described to translate SESI into the clinical environment. Finally, SESI main applications described in the literature with prompt translation into the clinical environment, namely, biomarker discovery or pharmacokinetics and drug monitoring are revised.
    Keywords:  Biomarker discovery; Breath analysis; Drug monitoring; Mass spectrometry; Metabolomics; Secondary Electrospray Ionization (SESI)
  10. Nat Prod Rep. 2021 Oct 06.
      Covering: 2016 up to 2021Mass spectrometry (MS) is an essential technology in natural products research with MS fragmentation (MS/MS) approaches becoming a key tool. Recent advancements in MS yield dense metabolomics datasets which have been, conventionally, used by individual labs for individual projects; however, a shift is brewing. The movement towards open MS data (and other structural characterization data) and accessible data mining tools is emerging in natural products research. Over the past 5 years, this movement has rapidly expanded and evolved with no slowdown in sight; the capabilities of today vastly exceed those of 5 years ago. Herein, we address the analysis of individual datasets, a situation we are calling the '2021 status quo', and the emergent framework to systematically capture sample information (metadata) and perform repository-scale analyses. We evaluate public data deposition, discuss the challenges of working in the repository scale, highlight the challenges of metadata capture and provide illustrative examples of the power of utilizing repository data and the tools that enable it. We conclude that the advancements in MS data collection must be met with advancements in how we utilize data; therefore, we argue that open data and data mining is the next evolution in obtaining the maximum potential in natural products research.
  11. Anal Chem. 2021 Oct 07.
      Advances in ambient ionization techniques have facilitated the direct analysis of complex mixtures without sample preparation. Significant attention has been given to innovating ionization methods so that multiple options are now available, allowing for ready selection of the best methods for particular analyte classes. These ambient techniques are commonly implemented on benchtop systems, but their potential application with miniature mass spectrometers for in situ measurements is even more powerful. These applications require that attention be paid to tailoring the mass spectrometric methodology for the on-site operation. In this study, combinations of scan modes are employed to efficiently determine what tandem mass spectrometry (MS/MS) operations are most useful for detecting sulfonamides using a miniature ion trap after ionization. First, mixtures of representative sulfonamide antibiotics were interrogated using a 2D MS/MS scan on a benchtop ion trap in order to determine which class-specific fragments (ionic or neutral) are shared between the sulfonamides and thus have diagnostic value. Then, three less-used combination scans were recorded: (i) a simultaneous precursor ion scan was used to detect both analytes and an internal standard in a single ion injection event to optimize quantitative performance; (ii) a simultaneous precursor/neutral loss scan was used to improve detection limits; and finally, (iii) the simultaneous precursor/neutral loss scan was implemented in a miniature mass spectrometer and representative sulfonamides were detected at concentrations as low as 100 ng/mL by nano-electrospray and 0.5 ng absolute by paper spray ionization, although improvements in the stability of the home-built instrumentation are needed to further optimize performance.