bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022–01–23
sixteen papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh
  1. MSLibrarian: Optimized Predicted Spectral Libraries for Data-Independent Acquisition Proteomics.
  2. Histone acetyltransferase NAA40 modulates acetyl-CoA levels and lipid synthesis.
  3. Isomer-selective analysis of inositol phosphates with differential isotope labelling by phosphate methylation using liquid chromatography with tandem mass spectrometry.
  4. Prostate cancer cell proliferation is influenced by LDL-cholesterol availability and cholesteryl ester turnover.
  5. Opening the Random Forest Black Box of the Metabolome by the Application of Surrogate Minimal Depth.
  6. Identification and Distribution of Sterols, Bile Acids, and Acylcarnitines by LC-MS/MS in Humans, Mice, and Pigs-A Qualitative Analysis.
  7. Sapienic Acid Metabolism Influences Membrane Plasticity and Protein Signaling in Breast Cancer Cell Lines.
  8. Interactions with stromal cells promote a more oxidized cancer cell redox state in pancreatic tumors.
  9. Automated Sample Preparation and Data Collection Workflow for High-Throughput In Vitro Metabolomics.
  10. Targeting glutamine metabolism network for the treatment of therapy-resistant prostate cancer.
  11. Circulating metabolite homeostasis achieved through mass action.
  12. Enzymatic transfer of acetate on histones from lysine reservoir sites to lysine activating sites.
  13. Lineage-specific silencing of PSAT1 induces serine auxotrophy and sensitivity to dietary serine starvation in luminal breast tumors.
  14. Twins labeling derivatization-based LC-MS/MS strategy for absolute quantification of paired prototypes and modified metabolites.
  15. A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research.
  16. Identification and characterization of post-translational modifications: Clinical implications.
  1. J Proteome Res. 2022 Jan 19.
    MSLibrarian: Optimized Predicted Spectral Libraries for Data-Independent Acquisition Proteomics.
    Marc Isaksson, Christofer Karlsson, Thomas Laurell, Agnete Kirkeby, Moritz Heusel.
      Data-independent acquisition-mass spectrometry (DIA-MS) is the method of choice for deep, consistent, and accurate single-shot profiling in bottom-up proteomics. While classic workflows for targeted quantification from DIA-MS data require auxiliary data-dependent acquisition (DDA) MS analysis of subject samples to derive prior-knowledge spectral libraries, library-free approaches based on in silico prediction promise deep DIA-MS profiling with reduced experimental effort and cost. Coverage and sensitivity in such analyses are however limited, in part, by the large library size and persistent deviations from the experimental data. We present MSLibrarian, a new workflow and tool to obtain optimized predicted spectral libraries by the integrated usage of spectrum-centric DIA data interpretation via the DIA-Umpire approach to inform and calibrate the in silico predicted library and analysis approach. Predicted-vs-observed comparisons enabled optimization of intensity prediction parameters, calibration of retention time prediction for deviating chromatographic setups, and optimization of the library scope and sample representativeness. Benchmarking via a dedicated ground-truth-embedded experiment of species-mixed proteins and quantitative ratio-validation confirmed gains of up to 13% on peptide and 8% on protein level at equivalent FDR control and validation criteria. MSLibrarian is made available as an open-source R software package, including step-by-step user instructions, at https://github.com/MarcIsak/MSLibrarian.
    Keywords:  R-software; data-independent acquisition; deep-learning; proteomics; spectral predictions
    DOI:  https://doi.org/10.1021/acs.jproteome.1c00796
  2. BMC Biol. 2022 Jan 20. 20(1): 22
    Histone acetyltransferase NAA40 modulates acetyl-CoA levels and lipid synthesis.
    Evelina Charidemou, Maria A Tsiarli, Andria Theophanous, Vural Yilmaz, Chrysoula Pitsouli, Katerina Strati, Julian L Griffin, Antonis Kirmizis.
       BACKGROUND: Epigenetic regulation relies on the activity of enzymes that use sentinel metabolites as cofactors to modify DNA or histone proteins. Thus, fluctuations in cellular metabolite levels have been reported to affect chromatin modifications. However, whether epigenetic modifiers also affect the levels of these metabolites and thereby impinge on downstream metabolic pathways remains largely unknown. Here, we tested this notion by investigating the function of N-alpha-acetyltransferase 40 (NAA40), the enzyme responsible for N-terminal acetylation of histones H2A and H4, which has been previously implicated with metabolic-associated conditions such as age-dependent hepatic steatosis and calorie-restriction-mediated longevity.
    RESULTS: Using metabolomic and lipidomic approaches, we found that depletion of NAA40 in murine hepatocytes leads to significant increase in intracellular acetyl-CoA levels, which associates with enhanced lipid synthesis demonstrated by upregulation in de novo lipogenesis genes as well as increased levels of diglycerides and triglycerides. Consistently, the increase in these lipid species coincide with the accumulation of cytoplasmic lipid droplets and impaired insulin signalling indicated by decreased glucose uptake. However, the effect of NAA40 on lipid droplet formation is independent of insulin. In addition, the induction in lipid synthesis is replicated in vivo in the Drosophila melanogaster larval fat body. Finally, supporting our results, we find a strong association of NAA40 expression with insulin sensitivity in obese patients.
    CONCLUSIONS: Overall, our findings demonstrate that NAA40 affects the levels of cellular acetyl-CoA, thereby impacting lipid synthesis and insulin signalling. This study reveals a novel path through which histone-modifying enzymes influence cellular metabolism with potential implications in metabolic disorders.
    Keywords:  Drosophila melanogaster; Epigenetics; Fat body; Histone acetyltransferases; Lipid metabolism; Metabolic disorders; NAA40; acetyl-CoA
    DOI:  https://doi.org/10.1186/s12915-021-01225-8
  3. Anal Chim Acta. 2022 Jan 25. pii: S0003-2670(21)01112-0. [Epub ahead of print]1191 339286
    Isomer-selective analysis of inositol phosphates with differential isotope labelling by phosphate methylation using liquid chromatography with tandem mass spectrometry.
    Peng Li, Meinrad Gawaz, Madhumita Chatterjee, Michael Lämmerhofer.
      Inositol phosphates belong to a family of structurally diverse signaling molecules playing crucial role in Ca2+ release from intracellular storage vesicles. There are many possibilities of phosphorylation, including their degree and position. Inositol (1,4,5) trisphosphate has been well recognized as the most important second messenger among this family. It remains a challenge to analyse the entire inositol phosphate metabolite family due to its structural complexity, high polarity, and high phosphate density. In this study, we have established an improved UHPLC-ESI-MS/MS method based on a differential isotope labelling methylation strategy. An SPE extraction kit composed of TiO2 and PTFE filter was employed for sample preparation which provided good extraction performance. Samples were methylated (light label) to neutralize the phosphate groups and give better performance in liquid chromatography. Regioisomers and inositol phosphates differing in their number of phosphate residues were successfully separated after optimization on a core-shell cholesterylether-bonded RP-type column (Cosmocore 2.6Cholester) using methanol as organic modifier. Triple quadrupole MS detection was based on selected reaction monitoring (SRM) acquisition with characteristic fragments. Stable isotope labeling methylation was performed to generate internal standards (heavy label). Limits of quantification from 0.32 to 0.89 pmol on column was achieved. This method was validated to be suitable for inositol phosphate profiling in biological samples. After application in cultured HeLa cells, NIST SRM1950 plasma, and human platelets, distinct inositol profiles were obtained. This newly established method exhibited improved analytical performance, holding the potential to advance the understanding of inositol phosphate signaling.
    Keywords:  Derivatization; Inositol phosphate; Isotope labeling; Metal oxide-based affinity chromatography; Solid-phase extraction; Targeted metabolomics
    DOI:  https://doi.org/10.1016/j.aca.2021.339286
  4. Cancer Metab. 2022 Jan 15. 10(1): 1
    Prostate cancer cell proliferation is influenced by LDL-cholesterol availability and cholesteryl ester turnover.
    Nikki L Raftopulos, Tinashe C Washaya, Andreas Niederprüm, Antonia Egert, Mariam F Hakeem-Sanni, Bianca Varney, Atqiya Aishah, Mariya L Georgieva, Ellinor Olsson, Diandra Z Dos Santos, Zeyad D Nassar, Blake J Cochran, Shilpa R Nagarajan, Meghna S Kakani, Jordan F Hastings, David R Croucher, Kerry-Anne Rye, Lisa M Butler, Thomas Grewal, Andrew J Hoy.
       BACKGROUND: Prostate cancer growth is driven by androgen receptor signaling, and advanced disease is initially treatable by depleting circulating androgens. However, prostate cancer cells inevitably adapt, resulting in disease relapse with incurable castrate-resistant prostate cancer. Androgen deprivation therapy has many side effects, including hypercholesterolemia, and more aggressive and castrate-resistant prostate cancers typically feature cellular accumulation of cholesterol stored in the form of cholesteryl esters. As cholesterol is a key substrate for de novo steroidogenesis in prostate cells, this study hypothesized that castrate-resistant/advanced prostate cancer cell growth is influenced by the availability of extracellular, low-density lipoprotein (LDL)-derived, cholesterol, which is coupled to intracellular cholesteryl ester homeostasis.
    METHODS: C4-2B and PC3 prostate cancer cells were cultured in media supplemented with fetal calf serum (FCS), charcoal-stripped FCS (CS-FCS), lipoprotein-deficient FCS (LPDS), or charcoal-stripped LPDS (CS-LPDS) and analyzed by a variety of biochemical techniques. Cell viability and proliferation were measured by MTT assay and Incucyte, respectively.
    RESULTS: Reducing lipoprotein availability led to a reduction in cholesteryl ester levels and cell growth in C4-2B and PC3 cells, with concomitant reductions in PI3K/mTOR and p38MAPK signaling. This reduced growth in LPDS-containing media was fully recovered by supplementation of exogenous low-density lipoprotein (LDL), but LDL only partially rescued growth of cells cultured with CS-LPDS. This growth pattern was not associated with changes in androgen receptor signaling but rather increased p38MAPK and MEK1/ERK/MSK1 activation. The ability of LDL supplementation to rescue cell growth required cholesterol esterification as well as cholesteryl ester hydrolysis activity. Further, growth of cells cultured in low androgen levels (CS-FCS) was suppressed when cholesteryl ester hydrolysis was inhibited.
    CONCLUSIONS: Overall, these studies demonstrate that androgen-independent prostate cancer cell growth can be influenced by extracellular lipid levels and LDL-cholesterol availability and that uptake of extracellular cholesterol, through endocytosis of LDL-derived cholesterol and subsequent delivery and storage in the lipid droplet as cholesteryl esters, is required to support prostate cancer cell growth. This provides new insights into the relationship between extracellular cholesterol, intracellular cholesterol metabolism, and prostate cancer cell growth and the potential mechanisms linking hypercholesterolemia and more aggressive prostate cancer.
    Keywords:  ACAT1; Cell proliferation; Cholesteryl ester; HSL; LDL; LDL-cholesterol; Prostate cancer; nCEH1
    DOI:  https://doi.org/10.1186/s40170-021-00278-1
  5. Metabolites. 2021 Dec 21. pii: 5. [Epub ahead of print]12(1):
    Opening the Random Forest Black Box of the Metabolome by the Application of Surrogate Minimal Depth.
    Soeren Wenck, Marina Creydt, Jule Hansen, Florian Gärber, Markus Fischer, Stephan Seifert.
      For the untargeted analysis of the metabolome of biological samples with liquid chromatography-mass spectrometry (LC-MS), high-dimensional data sets containing many different metabolites are obtained. Since the utilization of these complex data is challenging, different machine learning approaches have been developed. Those methods are usually applied as black box classification tools, and detailed information about class differences that result from the complex interplay of the metabolites are not obtained. Here, we demonstrate that this information is accessible by the application of random forest (RF) approaches and especially by surrogate minimal depth (SMD) that is applied to metabolomics data for the first time. We show this by the selection of important features and the evaluation of their mutual impact on the multi-level classification of white asparagus regarding provenance and biological identity. SMD enables the identification of multiple features from the same metabolites and reveals meaningful biological relations, proving its high potential for the comprehensive utilization of high-dimensional metabolomics data.
    Keywords:  LC-MS; characterization; chemometrics; classification; feature relations; feature selection; machine learning; metabolomics; random forest; surrogate minimal depth; white asparagus
    DOI:  https://doi.org/10.3390/metabo12010005
  6. Metabolites. 2022 Jan 07. pii: 49. [Epub ahead of print]12(1):
    Identification and Distribution of Sterols, Bile Acids, and Acylcarnitines by LC-MS/MS in Humans, Mice, and Pigs-A Qualitative Analysis.
    Ambrin Farizah Babu, Ville Mikael Koistinen, Soile Turunen, Gloria Solano-Aguilar, Joseph F Urban, Iman Zarei, Kati Hanhineva.
      Sterols, bile acids, and acylcarnitines are key players in human metabolism. Precise annotations of these metabolites with mass spectrometry analytics are challenging because of the presence of several isomers and stereoisomers, variability in ionization, and their relatively low concentrations in biological samples. Herein, we present a sensitive and simple qualitative LC-MS/MS (liquid chromatography with tandem mass spectrometry) method by utilizing a set of pure chemical standards to facilitate the identification and distribution of sterols, bile acids, and acylcarnitines in biological samples including human stool and plasma; mouse ileum, cecum, jejunum content, duodenum content, and liver; and pig bile, proximal colon, cecum, heart, stool, and liver. With this method, we detected 24 sterol, 32 bile acid, and 27 acylcarnitine standards in one analysis that were separated within 13 min by reversed-phase chromatography. Further, we observed different sterol, bile acid, and acylcarnitine profiles for the different biological samples across the different species. The simultaneous detection and annotation of sterols, bile acids, and acylcarnitines from reference standards and biological samples with high precision represents a valuable tool for screening these metabolites in routine scientific research.
    Keywords:  LC–MS/MS; acylcarnitine; annotation; bile acid; sterol
    DOI:  https://doi.org/10.3390/metabo12010049
  7. Cells. 2022 Jan 11. pii: 225. [Epub ahead of print]11(2):
    Sapienic Acid Metabolism Influences Membrane Plasticity and Protein Signaling in Breast Cancer Cell Lines.
    Ertan Küçüksayan, Anna Sansone, Chryssostomos Chatgilialoglu, Tomris Ozben, Demet Tekeli, Günel Talibova, Carla Ferreri.
      The importance of sapienic acid (6c-16:1), a monounsaturated fatty acid of the n-10 family formed from palmitic acid by delta-6 desaturase, and of its metabolism to 8c-18:1 and sebaleic acid (5c,8c-18:2) has been recently assessed in cancer. Data are lacking on the association between signaling cascades and exposure to sapienic acid comparing cell lines of the same cancer type. We used 50 μM sapienic acid supplementation, a non-toxic concentration, to cultivate MCF-7 and 2 triple-negative breast cancer cells (TNBC), MDA-MB-231 and BT-20. We followed up for three hours regarding membrane fatty acid remodeling by fatty acid-based membrane lipidome analysis and expression/phosphorylation of EGFR (epithelial growth factor receptor), mTOR (mammalian target of rapamycin) and AKT (protein kinase B) by Western blotting as an oncogenic signaling cascade. Results evidenced consistent differences among the three cell lines in the metabolism of n-10 fatty acids and signaling. Here, a new scenario is proposed for the role of sapienic acid: one based on changes in membrane composition and properties, and the other based on changes in expression/activation of growth factors and signaling cascades. This knowledge can indicate additional players and synergies in breast cancer cell metabolism, inspiring translational applications of tailored membrane lipid strategies to assist pharmacological interventions.
    Keywords:  breast cancer; cancer signaling activation; fatty acid supplementation; membrane fatty acids; membrane lipidome; membrane remodeling
    DOI:  https://doi.org/10.3390/cells11020225
  8. Sci Adv. 2022 Jan 21. 8(3): eabg6383
    Interactions with stromal cells promote a more oxidized cancer cell redox state in pancreatic tumors.
    Rupsa Datta, Sharanya Sivanand, Allison N Lau, Logan V Florek, Anna M Barbeau, Jeffrey Wyckoff, Melissa C Skala, Matthew G Vander Heiden.
      Access to electron acceptors supports oxidized biomass synthesis and can be limiting for cancer cell proliferation, but how cancer cells overcome this limitation in tumors is incompletely understood. Nontransformed cells in tumors can help cancer cells overcome metabolic limitations, particularly in pancreatic cancer, where pancreatic stellate cells (PSCs) promote cancer cell proliferation and tumor growth. However, whether PSCs affect the redox state of cancer cells is not known. By taking advantage of the endogenous fluorescence properties of reduced nicotinamide adenine dinucleotide and oxidized flavin adenine dinucleotide cofactors we use optical imaging to assess the redox state of pancreatic cancer cells and PSCs and find that direct interactions between PSCs and cancer cells promote a more oxidized state in cancer cells. This suggests that metabolic interaction between cancer cells and PSCs is a mechanism to overcome the redox limitations of cell proliferation in pancreatic cancer.
    DOI:  https://doi.org/10.1126/sciadv.abg6383
  9. Metabolites. 2022 Jan 08. pii: 52. [Epub ahead of print]12(1):
    Automated Sample Preparation and Data Collection Workflow for High-Throughput In Vitro Metabolomics.
    Julia M Malinowska, Taina Palosaari, Jukka Sund, Donatella Carpi, Gavin R Lloyd, Ralf J M Weber, Maurice Whelan, Mark R Viant.
      Regulatory bodies have started to recognise the value of in vitro screening and metabolomics as two types of new approach methodologies (NAMs) for chemical risk assessments, yet few high-throughput in vitro toxicometabolomics studies have been reported. A significant challenge is to implement automated sample preparation of the low biomass samples typically used for in vitro screening. Building on previous work, we have developed, characterised and demonstrated an automated sample preparation and analysis workflow for in vitro metabolomics of HepaRG cells in 96-well microplates using a Biomek i7 Hybrid Workstation (Beckman Coulter) and Orbitrap Elite (Thermo Scientific) high-resolution nanoelectrospray direct infusion mass spectrometry (nESI-DIMS), across polar metabolites and lipids. The experimental conditions evaluated included the day of metabolite extraction, order of extraction of samples in 96-well microplates, position of the 96-well microplate on the instrument's deck and well location within a microplate. By using the median relative standard deviation (mRSD (%)) of spectral features, we have demonstrated good repeatability of the workflow (final mRSD < 30%) with a low percentage of features outside the threshold applied for statistical analysis. To improve the quality of the automated workflow further, small method modifications were made and then applied to a large cohort study (4860 sample infusions across three nESI-DIMS assays), which confirmed very high repeatability of the whole workflow from cell culturing to metabolite measurements, whilst providing a significant improvement in sample throughput. It is envisioned that the automated in vitro metabolomics workflow will help to advance the application of metabolomics (as a part of NAMs) in chemical safety, primarily as an approach for high throughput screening and prioritisation.
    Keywords:  automation; direct infusion mass spectrometry; high-throughput screening; in vitro metabolomics; sample preparation
    DOI:  https://doi.org/10.3390/metabo12010052
  10. Oncogene. 2022 Jan 20.
    Targeting glutamine metabolism network for the treatment of therapy-resistant prostate cancer.
    Lingfan Xu, Bing Zhao, William Butler, Huan Xu, Nan Song, Xufeng Chen, J Spencer Hauck, Xia Gao, Hong Zhang, Jeff Groth, Qing Yang, Yue Zhao, David Moon, Daniel George, Yinglu Zhou, Yiping He, Jiaoti Huang.
      Advanced and aggressive prostate cancer (PCa) depends on glutamine for survival and proliferation. We have previously shown that inhibition of glutaminase 1, which catalyzes the rate-limiting step of glutamine catabolism, achieves significant therapeutic effect; however, therapy resistance is inevitable. Here we report that while the glutamine carbon is critical to PCa survival, a parallel pathway of glutamine nitrogen catabolism that actively contributes to pyrimidine assembly is equally important for PCa cells. Importantly, we demonstrate a reciprocal feedback mechanism between glutamine carbon and nitrogen pathways which leads to therapy resistance when one of the two pathways is inhibited. Combination treatment to inhibit both pathways simultaneously yields better clinical outcome for advanced PCa patients.
    DOI:  https://doi.org/10.1038/s41388-021-02155-z
  11. Nat Metab. 2022 Jan 20.
    Circulating metabolite homeostasis achieved through mass action.
    Xiaoxuan Li, Sheng Hui, Emily T Mirek, William O Jonsson, Tracy G Anthony, Won Dong Lee, Xianfeng Zeng, Cholsoon Jang, Joshua D Rabinowitz.
      Homeostasis maintains serum metabolites within physiological ranges. For glucose, this requires insulin, which suppresses glucose production while accelerating its consumption. For other circulating metabolites, a comparable master regulator has yet to be discovered. Here we show that, in mice, many circulating metabolites are cleared via the tricarboxylic acid cycle (TCA) cycle in linear proportionality to their circulating concentration. Abundant circulating metabolites (essential amino acids, serine, alanine, citrate, 3-hydroxybutyrate) were administered intravenously in perturbative amounts and their fluxes were measured using isotope labelling. The increased circulating concentrations induced by the perturbative infusions hardly altered production fluxes while linearly enhancing consumption fluxes and TCA contributions. The same mass action relationship between concentration and consumption flux largely held across feeding, fasting and high- and low-protein diets, with amino acid homeostasis during fasting further supported by enhanced endogenous protein catabolism. Thus, despite the copious regulatory machinery in mammals, circulating metabolite homeostasis is achieved substantially through mass action-driven oxidation.
    DOI:  https://doi.org/10.1038/s42255-021-00517-1
  12. Sci Adv. 2022 Jan 21. 8(3): eabj5688
    Enzymatic transfer of acetate on histones from lysine reservoir sites to lysine activating sites.
    Mariel Mendoza, Gabor Egervari, Simone Sidoli, Greg Donahue, Desi C Alexander, Payel Sen, Benjamin A Garcia, Shelley L Berger.
      Histone acetylation is governed by nuclear acetyl-CoA pools generated, in part, from local acetate by metabolic enzyme acetyl-CoA synthetase 2 (ACSS2). We hypothesize that during gene activation, a local transfer of intact acetate occurs via sequential action of epigenetic and metabolic enzymes. Using stable isotope labeling, we detect transfer between histone acetylation sites both in vitro using purified mammalian enzymes and in vivo using quiescence exit in Saccharomyces cerevisiae as a change-of-state model. We show that Acs2, the yeast ortholog of ACSS2, is recruited to chromatin during quiescence exit and observe dynamic histone acetylation changes proximal to Acs2 peaks. We find that Acs2 is preferentially associated with the most up-regulated genes, suggesting that acetyl group transfer plays an important role in gene activation. Overall, our data reveal direct transfer of acetate between histone lysine residues to facilitate rapid transcriptional induction, an exchange that may be critical during changes in nutrient availability.
    DOI:  https://doi.org/10.1126/sciadv.abj5688
  13. Cell Rep. 2022 Jan 18. pii: S2211-1247(21)01793-9. [Epub ahead of print]38(3): 110278
    Lineage-specific silencing of PSAT1 induces serine auxotrophy and sensitivity to dietary serine starvation in luminal breast tumors.
    Bo-Hyun Choi, Vipin Rawat, Jenny Högström, Philippa A Burns, Kelly O Conger, Mete Emir Ozgurses, Jaymin M Patel, Tejas S Mehta, Angelica Warren, Laura M Selfors, Taru Muranen, Jonathan L Coloff.
      A major challenge of targeting metabolism for cancer therapy is pathway redundancy, in which multiple sources of critical nutrients can limit the effectiveness of some metabolism-targeted therapies. Here, we analyze lineage-dependent gene expression in human breast tumors to identify differences in metabolic gene expression that may limit pathway redundancy and create therapeutic vulnerabilities. We find that the serine synthesis pathway gene PSAT1 is the most depleted metabolic gene in luminal breast tumors relative to basal tumors. Low PSAT1 prevents de novo serine biosynthesis and sensitizes luminal breast cancer cells to serine and glycine starvation in vitro and in vivo. This PSAT1 expression disparity preexists in the putative cells of origin of basal and luminal tumors and is due to luminal-specific hypermethylation of the PSAT1 gene. Our data demonstrate that luminal breast tumors are auxotrophic for serine and may be uniquely sensitive to therapies targeting serine availability.
    Keywords:  PHGDH; PSAT1; auxotrophy; breast cancer; diet; luminal tumors; serine; tumor metabolism
    DOI:  https://doi.org/10.1016/j.celrep.2021.110278
  14. Anal Chim Acta. 2022 Feb 08. pii: S0003-2670(21)01225-3. [Epub ahead of print]1193 339399
    Twins labeling derivatization-based LC-MS/MS strategy for absolute quantification of paired prototypes and modified metabolites.
    Wei Li, Pei Zhang, Xiaoying Hou, Tian Tang, Siqi Li, Ruiqi Sun, Zunjian Zhang, Fengguo Xu.
      Modified metabolites play significant roles in disease occurrence, progression and diagnosis. Sensitive and accurate analytical methods for the quantification of these metabolites are therefore of great importance. In this study, a liquid chromatography tandem mass spectrometry (LC-MS/MS) method was developed for the simultaneous measurement of 13 pairs of prototypes and their modified forms covering nucleobases, nucleosides and amino acids. In order to improve the quantification sensitivity and accuracy, two structure analogs named N-dimethyl-amino naphthalene-1-sulfonyl chloride (Dns-Cl) and N-diethyl-amino naphthalene-1-sulfonyl chloride (Dens-Cl) were introduced for twins labeling derivatization. Dns-labeling was utilized to react with target analytes while the Dens-labeling of standard compounds provided one-to-one internal standards. With the introduce of naphthalene and easily ionizable moiety tertiary ammonium, chromatography retention and separation of these polar metabolites were notably improved on C18 columns and the detection sensitivity was increased up to 400 folds. The method is sensitive with the lower limit of quantification (LLOQ) values of 0.002-0.5 μg/mL. Comparisons of the performance of twins labeling derivatization and traditional chemical isotope labeling (CIL) derivatization verified the ability of our method in the absolute quantification. The established method was applied to human lung adenocarcinoma cell line A549 and its cisplatin resistant derivative A549/DDP. Significant shifts in 12 metabolites as well as 9 modified-to-prototypical ratios in A549/DDP were observed, demonstrating the utility of our method and the potential role of modified metabolites in mediating anticancer drug resistance. The method can be easily extended to determine other types of modified metabolites in various biological matrices, which will greatly expand our knowledge on these metabolites.
    Keywords:  Cisplatin; Drug resistance; LC-MS/MS; Metabolomics; Modified metabolites; Twins labeling derivatization
    DOI:  https://doi.org/10.1016/j.aca.2021.339399
  15. Metabolites. 2022 Jan 17. pii: 87. [Epub ahead of print]12(1):
    A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research.
    Xinsong Du, Juan J Aristizabal-Henao, Timothy J Garrett, Mathias Brochhausen, William R Hogan, Dominick J Lemas.
      Clinical metabolomics emerged as a novel approach for biomarker discovery with the translational potential to guide next-generation therapeutics and precision health interventions. However, reproducibility in clinical research employing metabolomics data is challenging. Checklists are a helpful tool for promoting reproducible research. Existing checklists that promote reproducible metabolomics research primarily focused on metadata and may not be sufficient to ensure reproducible metabolomics data processing. This paper provides a checklist including actions that need to be taken by researchers to make computational steps reproducible for clinical metabolomics studies. We developed an eight-item checklist that includes criteria related to reusable data sharing and reproducible computational workflow development. We also provided recommended tools and resources to complete each item, as well as a GitHub project template to guide the process. The checklist is concise and easy to follow. Studies that follow this checklist and use recommended resources may facilitate other researchers to reproduce metabolomics results easily and efficiently.
    Keywords:  checklist; clinical research; metabolomics; reproducibility; reproducible workflow; reusable data
    DOI:  https://doi.org/10.3390/metabo12010087
  16. Mol Aspects Med. 2022 Jan 12. pii: S0098-2997(22)00003-6. [Epub ahead of print] 101066
    Identification and characterization of post-translational modifications: Clinical implications.
    Juliane Hermann, Leon Schurgers, Vera Jankowski.
      Post-translational modifications (PTMs) generate marginally modified isoforms of native peptides, proteins and lipoproteins thereby regulating protein functions, molecular interactions, and localization. With a key role in functional proteomics, post-translational modifications are recently also associated with the onsets and progressions of various diseases, such as cancer, cardiovascular, renal, and metabolic diseases. With the impact of post-translational modifications becoming increasingly clear, its reliable detection and quantification remain a major obstacle in the translation of these novel pathological markers into clinical diagnosis. While current antibody-based clinical diagnostics struggle to detect and quantify these marginal protein and lipoprotein alterations, state-of-the-art mass spectrometric, proteomic approaches provide the mass accuracy and resolving power necessary to isolate, identify and quantify novel and pathological post-translational modifications; however clinical translation of mass spectrometric applications are still facing major challenges. Here we review the status quo of the clinical translation of mass-spectrometric applications as novel diagnostic tools for the identification and quantification of post-translational modifications and focus on the emerging role of mass spectrometric methods in the clinical assessment of PTMs in disease states.
    DOI:  https://doi.org/10.1016/j.mam.2022.101066
This page is being maintained by Thomas Krichel. It was last updated on 2024‒11‒22 at 4:19.