bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2021–10–10
eleven papers selected by
Giovanny Rodríguez Blanco, University of Edinburgh



  1. 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
    DOI:  https://doi.org/10.1152/ajpcell.00613.2020
  2. Int J Biol Macromol. 2021 Oct 05. pii: S0141-8130(21)02116-4. [Epub ahead of print]192 45-54
      Reprogrammed cell metabolism is a well-accepted hallmark of cancer. Metabolism changes provide energy and precursors for macromolecule biosynthesis to satisfy the survival needs of cancer cells. The specific changes in different aspects of lipid metabolism in cancer cells have been focused in recent years. These changes can affect cell growth, proliferation, differentiation and motility through affecting membranes synthesis, energy homeostasis and cell signaling. The tumor suppressor p53 plays vital roles in the control of cell proliferation, senescence, DNA repair, and cell death in cancer through various transcriptional and non-transcriptional activities. Accumulating evidences indicate that p53 also regulates cellular metabolism, which appears to contribute to its tumor suppressive functions. Particularly the role of p53 in regulating lipid metabolism has gained more and more attention in recent decades. In this review, we summarize recent advances in the function of p53 on lipid metabolism in cancer. Further understanding and research on the role of p53 in lipid metabolism regulation will provide a potential therapeutic window for cancer treatment.
    Keywords:  Cancer; Fatty acid oxidation; Ferroptosis; Lipid metabolism; p53
    DOI:  https://doi.org/10.1016/j.ijbiomac.2021.09.188
  3. 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.
    DOI:  https://doi.org/10.1021/acs.analchem.1c01507
  4. Curr Opin Chem Biol. 2021 Sep 29. pii: S1367-5931(21)00111-3. [Epub ahead of print]65 145-153
      Exploring the lipids of bacteria presents a predicament that may not be broadly recognized in a field dominated by the biology and biochemistry of eukaryotic - and especially, mammalian - lipids. Bacteria make multifarious metabolites that contain fatty acyl chains of unusual length and unsaturation attached to assorted headgroups, including sugars and fatty alcohols. Lipid profiling approaches developed for eukaryotic lipids often fail to detect, resolve, or identify bacterial lipids due to their wide range of polarities (including very hydrophobic species) and diverse positional and stereochemical variations. Global lipid profiling, or lipidomics, of bacteria has thus developed as a separate mission with methodological and scientific considerations tailored to the biology of these organisms. In this review, we summarize findings primarily from the last three years that exemplify recent advances and continuing challenges to learning about bacterial lipids.
    Keywords:  Bacteria; Lipidomics; Lipids; Mass spectrometry
    DOI:  https://doi.org/10.1016/j.cbpa.2021.08.003
  5. 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
    DOI:  https://doi.org/10.1016/j.jbiosc.2021.09.009
  6. Nat Rev Nephrol. 2021 Oct 06.
      Dyslipidaemia is a hallmark of chronic kidney disease (CKD). The severity of dyslipidaemia not only correlates with CKD stage but is also associated with CKD-associated cardiovascular disease and mortality. Understanding how lipids are dysregulated in CKD is, however, challenging owing to the incredible diversity of lipid structures. CKD-associated dyslipidaemia occurs as a consequence of complex interactions between genetic, environmental and kidney-specific factors, which to understand, requires an appreciation of perturbations in the underlying network of genes, proteins and lipids. Modern lipidomic technologies attempt to systematically identify and quantify lipid species from biological systems. The rapid development of a variety of analytical platforms based on mass spectrometry has enabled the identification of complex lipids at great precision and depth. Insights from lipidomics studies to date suggest that the overall architecture of free fatty acid partitioning between fatty acid oxidation and complex lipid fatty acid composition is an important driver of CKD progression. Available evidence suggests that CKD progression is associated with metabolic inflexibility, reflecting a diminished capacity to utilize free fatty acids through β-oxidation, and resulting in the diversion of accumulating fatty acids to complex lipids such as triglycerides. This effect is reversed with interventions that improve kidney health, suggesting that targeting of lipid abnormalities could be beneficial in preventing CKD progression.
    DOI:  https://doi.org/10.1038/s41581-021-00488-2
  7. 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.
    DOI:  https://doi.org/10.1021/acs.analchem.1c02463
  8. STAR Protoc. 2021 Dec 17. 2(4): 100848
      About 150 modifications have been identified in RNA species. Besides their regulatory roles in the intracellular gene expression, abundant modified RNA nucleosides are catabolized from RNA and released into extracellular fluids, which can impact extracellular signaling as ligands for receptors. Here, we describe a protocol to prepare samples from biological specimens, including cultured cells, extracellular fluid, and tissues, to measure both intracellular and extracellular RNA modifications using mass spectrometry. For complete details on the use and execution of this protocol, please refer to Ogawa et al. (2021).
    Keywords:  Mass Spectrometry; Metabolism; Metabolomics; Molecular Biology; Signal Transduction
    DOI:  https://doi.org/10.1016/j.xpro.2021.100848
  9. Methods Mol Biol. 2022 ;2370 3-23
      Glycosylation is important in biology, contributing to both protein conformation and function. Structurally, glycosylation is complex and diverse. This complexity is reflected in the topology, composition, monosaccharide linkages, and isomerism of each oligosaccharide. Glycoanalytics is a discipline that addresses the understanding and characterization of this complexity and its correlation with biology. It includes analytical steps such as sample preparation, instrument measurements, and data analyses. Of these, data analysis has emerged as a critical bottleneck because data collection has increasingly become high-throughput. This has resulted in data-rich workflows that lack rapid and automated data analytics. To address this issue, the field has been developing software for interpretation of quantitative glycomics studies. Here, we describe a protocol using available informatics tools for analysis of data from analysis of released glycans using high-/ultraperformance liquid chromatography (H/UPLC) coupled with mass spectrometry (MS).
    Keywords:  Bioinformatics; Glycoanalytics; Glycosylation; Mass spectrometry
    DOI:  https://doi.org/10.1007/978-1-0716-1685-7_1
  10. Anal Bioanal Chem. 2021 Oct 07.
      Metabolic markers, offering sensitive information on biological dysfunction, play important roles in diagnosing and treating cancers. However, the discovery of effective markers is limited by the lack of well-established metabolite selection approaches. Here, we propose a network-based strategy to uncover the metabolic markers with potential clinical availability for non-small cell lung cancer (NSCLC). First, an integrated mass spectrometry-based untargeted metabolomics was used to profile the plasma samples from 43 NSCLC patients and 43 healthy controls. We found that a series of 39 metabolites were altered significantly. Relying on the human metabolic network assembled from Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we mapped these differential metabolites to the network and constructed an NSCLC-related disease module containing 23 putative metabolic markers. By measuring the PageRank centrality of molecules in this module, we computationally evaluated the network-based importance of the 23 metabolites and demonstrated that the metabolism pathways of aromatic amino acids and long-chain fatty acids provided potential molecular targets of NSCLC (i.e., IL4l1 and ACOT2). Combining network-based ranking and support-vector machine modeling, we further found a panel of eight metabolites (i.e., pyruvate, tryptophan, and palmitic acid) that showed a high capability to differentiate patients from controls (accuracy > 97.7%). In summary, we present a meaningful network method for metabolic marker discovery and have identified eight strong candidate metabolites for NSCLC diagnosis.
    Keywords:  Centrality; Lung cancer; Mass spectrometry; Metabolomics; Network medicine
    DOI:  https://doi.org/10.1007/s00216-021-03699-5
  11. Anal Chem. 2021 Oct 08.
      N-linked protein glycosylation is a key regulator in various biological functions. Previous studies have shown that aberrant glycosylation is associated with many diseases. Therefore, it is essential to elucidate protein modifications of glycosylation by quantitatively profiling intact N-linked glycopeptides. Data-independent acquisition (DIA) mass spectrometry (MS) is a cost-effective, flexible, and high-throughput method for global proteomics. However, substantial challenges are still present in the quantitative analysis of intact glycopeptides with high accuracy at high throughput. In this study, we have established a novel integrated platform for the DIA analysis of intact glycopeptides isolated from complex samples. The established analysis platform utilizes a well-designed DIA-MS method for raw data collection, a spectral library constructed specifically for intact glycopeptide quantification providing accurate results by the inclusion of Y ions for quantification and filtering of quantified intact glycopeptides with low-quality MS2 spectra automatically using a set of criteria. Intact glycopeptides isolated from human serum were used to evaluate the performance of the integrated platform. By utilizing 100 isolation windows for DIA data acquisition, a well-constructed human serum spectral library containing 1123 nonredundant intact glycopeptides with Y ions, and automated data inspection, 620 intact glycopeptides were quantified with high confidence from DIA-MS. In summary, our integrated platform can serve as a reliable quantitative tool for characterizing intact glycopeptides isolated from complex biological samples to assist our understanding of biological functions of N-linked glycosylation.
    DOI:  https://doi.org/10.1021/acs.analchem.1c01659