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Lindeque JZ. Targeted analysis of organic acids with GC-MS/MS: Challenges and prospects. Anal Biochem 2024; 694:115620. [PMID: 39029642 DOI: 10.1016/j.ab.2024.115620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 07/01/2024] [Accepted: 07/13/2024] [Indexed: 07/21/2024]
Abstract
GC-MS/MS combines the superior chromatographic resolution of GC with the specific and sensitive detection of tandem MS. On paper, it is an ideal system for the routine analyses of organic acids, yet very few studies have used and published such methods. This is likely due to several challenges highlighted in this communication. Briefly, the combination of EI ionization with MRM detection provides arguably insufficient specificity when targeting organic acids. Moreover, the narrow peaks generally produced by GC can lead to inaccurate quantification when the mass spectrometer's cycle time is too long. Potential solutions to these problems are discussed.
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Affiliation(s)
- Jeremie Zander Lindeque
- Human Metabolomics, Faculty of Natural and Agricultural Sciences, North-West University, 11 Hoffman Street, Potchefstroom, 2531, South Africa.
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2
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Kinslow CJ, Ll MB, Cai Y, Yan J, Lorkiewicz PK, Al-Attar A, Tan J, Higashi RM, Lane AN, Fan TWM. Stable isotope-resolved metabolomics analyses of metabolic phenotypes reveal variable glutamine metabolism in different patient-derived models of non-small cell lung cancer from a single patient. Metabolomics 2024; 20:87. [PMID: 39068202 PMCID: PMC11317205 DOI: 10.1007/s11306-024-02126-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 05/02/2024] [Indexed: 07/30/2024]
Abstract
INTRODUCTION Stable isotope tracers have been increasingly used in preclinical cancer model systems, including cell culture and mouse xenografts, to probe the altered metabolism of a variety of cancers, such as accelerated glycolysis and glutaminolysis and generation of oncometabolites. Comparatively little has been reported on the fidelity of the different preclinical model systems in recapitulating the aberrant metabolism of tumors. OBJECTIVES We have been developing several different experimental model systems for systems biochemistry analyses of non-small cell lung cancer (NSCLC1) using patient-derived tissues to evaluate appropriate models for metabolic and phenotypic analyses. METHODS To address the issue of fidelity, we have carried out a detailed Stable Isotope-Resolved Metabolomics study of freshly resected tissue slices, mouse patient derived xenografts (PDXs), and cells derived from a single patient using both 13C6-glucose and 13C5,15N2-glutamine tracers. RESULTS Although we found similar glucose metabolism in the three models, glutamine utilization was markedly higher in the isolated cell culture and in cell culture-derived xenografts compared with the primary cancer tissue or direct tissue xenografts (PDX). CONCLUSIONS This suggests that caution is needed in interpreting cancer biochemistry using patient-derived cancer cells in vitro or in xenografts, even at very early passage, and that direct analysis of patient derived tissue slices provides the optimal model for ex vivo metabolomics. Further research is needed to determine the generality of these observations.
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Affiliation(s)
- Connor J Kinslow
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA
- Department of Radiation Oncology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 622 West 168th Street, BNH B-11, New York, NY, 10032, USA
| | - Michael Bousamra Ll
- Department of Cardiovascular and Thoracic Surgery, University of Louisville, Louisville, KY, 40202, USA
- AMG Cardiothoracic Surgical Associates SE MI, 22201 Moross Rd. #352, Detroit, MI, 48236, USA
| | - Yihua Cai
- Immuno-Oncology Program, James Graham Brown Cancer Center, University of Louisville, Louisville, KY, 40202, USA
- Center for Cellular Engineering, Department of Transfusion Medicine, NIH Clinical Center, Bethesda, MD, 20892, USA
| | - Jun Yan
- Immuno-Oncology Program, James Graham Brown Cancer Center, University of Louisville, Louisville, KY, 40202, USA
- Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, University of Louisville, Louisville, KY, 40202, USA
| | - Pawel K Lorkiewicz
- Department of Chemistry, University of Louisville, Louisville, KY, 40202, USA
| | - Ahmad Al-Attar
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA
- Dept. Pathology, U. Mass Memorial Medical Center, University of Massachusetts, Worcester, MA, 01605, USA
| | - Jinlian Tan
- The Department of Oral Immunology and Infection Disease, School of Dentistry, University of Louisville, 501 South Preston, St. Louisville, KY, 40202, USA
| | - Richard M Higashi
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA
| | - Andrew N Lane
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.
| | - Teresa W-M Fan
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.
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3
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Lane AN, Higashi RM, Fan TWM. Challenges of Spatially Resolved Metabolism in Cancer Research. Metabolites 2024; 14:383. [PMID: 39057706 PMCID: PMC11278851 DOI: 10.3390/metabo14070383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Revised: 06/28/2024] [Accepted: 07/07/2024] [Indexed: 07/28/2024] Open
Abstract
Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies.
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Affiliation(s)
- Andrew N. Lane
- Department of Toxicology and Cancer Biology and Markey Cancer Center, University of Kentucky, 789 S. Limestone St., Lexington, KY 40536, USA; (R.M.H.); (T.W.-M.F.)
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4
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Vera-Siguenza E, Escribano-Gonzalez C, Serrano-Gonzalo I, Eskla KL, Spill F, Tennant D. Mathematical reconstruction of the metabolic network in an in-vitro multiple myeloma model. PLoS Comput Biol 2023; 19:e1011374. [PMID: 37713666 PMCID: PMC10503963 DOI: 10.1371/journal.pcbi.1011374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 07/19/2023] [Indexed: 09/17/2023] Open
Abstract
It is increasingly apparent that cancer cells, in addition to remodelling their metabolism to survive and proliferate, adapt and manipulate the metabolism of other cells. This property may be a telling sign that pre-clinical tumour metabolism studies exclusively utilising in-vitro mono-culture models could prove to be limited for uncovering novel metabolic targets able to translate into clinical therapies. Although this is increasingly recognised, and work towards addressing the issue is becoming routinary much remains poorly understood. For instance, knowledge regarding the biochemical mechanisms through which cancer cells manipulate non-cancerous cell metabolism, and the subsequent impact on their survival and proliferation remains limited. Additionally, the variations in these processes across different cancer types and progression stages, and their implications for therapy, also remain largely unexplored. This study employs an interdisciplinary approach that leverages the predictive power of mathematical modelling to enrich experimental findings. We develop a functional multicellular in-silico model that facilitates the qualitative and quantitative analysis of the metabolic network spawned by an in-vitro co-culture model of bone marrow mesenchymal stem- and myeloma cell lines. To procure this model, we devised a bespoke human genome constraint-based reconstruction workflow that combines aspects from the legacy mCADRE & Metabotools algorithms, the novel redHuman algorithm, along with 13C-metabolic flux analysis. Our workflow transforms the latest human metabolic network matrix (Recon3D) into two cell-specific models coupled with a metabolic network spanning a shared growth medium. When cross-validating our in-silico model against the in-vitro model, we found that the in-silico model successfully reproduces vital metabolic behaviours of its in-vitro counterpart; results include cell growth predictions, respiration rates, as well as support for observations which suggest cross-shuttling of redox-active metabolites between cells.
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Affiliation(s)
- Elias Vera-Siguenza
- Institute of Metabolism and Systems Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
- Watson School of Mathematics, University of Birmingham, Birmingham, United Kingdom
| | - Cristina Escribano-Gonzalez
- Institute of Metabolism and Systems Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Irene Serrano-Gonzalo
- Instituto de Investigación Sanitaria Aragón, Fundación Española para el Estudio y Terapéutica de la enfermedad de Gaucher y otras Lisosomales, Zaragoza, España
| | - Kattri-Liis Eskla
- Institute of Metabolism and Systems Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Fabian Spill
- Watson School of Mathematics, University of Birmingham, Birmingham, United Kingdom
| | - Daniel Tennant
- Institute of Metabolism and Systems Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
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5
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Fan TWM, Sun Q, Higashi RM. Ultrahigh resolution MS 1/MS 2-based reconstruction of metabolic networks in mammalian cells reveals changes for selenite and arsenite action. J Biol Chem 2022; 298:102586. [PMID: 36223837 PMCID: PMC9667311 DOI: 10.1016/j.jbc.2022.102586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 10/03/2022] [Accepted: 10/05/2022] [Indexed: 11/13/2022] Open
Abstract
Metabolic networks are complex, intersecting, and composed of numerous enzyme-catalyzed biochemical reactions that transfer various molecular moieties among metabolites. Thus, robust reconstruction of metabolic networks requires metabolite moieties to be tracked, which cannot be readily achieved with mass spectrometry (MS) alone. We previously developed an Ion Chromatography-ultrahigh resolution-MS1/data independent-MS2 method to track the simultaneous incorporation of the heavy isotopes 13C and 15N into the moieties of purine/pyrimidine nucleotides in mammalian cells. Ultrahigh resolution-MS1 resolves and counts multiple tracer atoms in intact metabolites, while data independent-tandem MS (MS2) determines isotopic enrichment in their moieties without concern for the numerous mass isotopologue source ions to be fragmented. Together, they enabled rigorous MS-based reconstruction of metabolic networks at specific enzyme levels. We have expanded this approach to trace the labeled atom fate of [13C6]-glucose in 3D A549 spheroids in response to the anticancer agent selenite and that of [13C5,15N2]-glutamine in 2D BEAS-2B cells in response to arsenite transformation. We deduced altered activities of specific enzymes in the Krebs cycle, pentose phosphate pathway, gluconeogenesis, and UDP-GlcNAc synthesis pathways elicited by the stressors. These metabolic details help elucidate the resistance mechanism of 3D versus 2D A549 cultures to selenite and metabolic reprogramming that can mediate the transformation of BEAS-2B cells by arsenite.
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Affiliation(s)
- Teresa W-M Fan
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, Kentucky, USA; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky, USA; Markey Cancer Center, University of Kentucky, Lexington, Kentucky, USA.
| | - Qiushi Sun
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, Kentucky, USA
| | - Richard M Higashi
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, Kentucky, USA; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky, USA; Markey Cancer Center, University of Kentucky, Lexington, Kentucky, USA
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6
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Flight RM, Mitchell JM, Moseley HNB. Scan-Centric, Frequency-Based Method for Characterizing Peaks from Direct Injection Fourier Transform Mass Spectrometry Experiments. Metabolites 2022; 12:metabo12060515. [PMID: 35736448 PMCID: PMC9228344 DOI: 10.3390/metabo12060515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 05/20/2022] [Accepted: 05/30/2022] [Indexed: 11/16/2022] Open
Abstract
We present a novel, scan-centric method for characterizing peaks from direct injection multi-scan Fourier transform mass spectra of complex samples that utilizes frequency values derived directly from the spacing of raw m/z points in spectral scans. Our peak characterization method utilizes intensity-independent noise removal and normalization of scan-level data to provide a much better fit of relative intensity to natural abundance probabilities for low abundance isotopologues that are not present in all of the acquired scans. Moreover, our method calculates both peak- and scan-specific statistics incorporated within a series of quality control steps that are designed to robustly derive peak centers, intensities, and intensity ratios with their scan-level variances. These cross-scan characterized peaks are suitable for use in our previously published peak assignment methodology, Small Molecule Isotope Resolved Formula Enumeration (SMIRFE).
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Affiliation(s)
- Robert M. Flight
- Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA; (R.M.F.); (J.M.M.)
- Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA
- Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY 40536, USA
| | - Joshua M. Mitchell
- Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA; (R.M.F.); (J.M.M.)
- Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA
- Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY 40536, USA
| | - Hunter N. B. Moseley
- Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA; (R.M.F.); (J.M.M.)
- Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA
- Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY 40536, USA
- Institute for Biomedical Informatics, University of Kentucky, Lexington, KY 40536, USA
- Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY 40536, USA
- Correspondence:
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7
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Koley S, Chu KL, Gill SS, Allen DK. An efficient LC-MS method for isomer separation and detection of sugars, phosphorylated sugars, and organic acids. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:2938-2952. [PMID: 35560196 DOI: 10.1093/jxb/erac062] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Accepted: 02/15/2022] [Indexed: 06/15/2023]
Abstract
Assessing central carbon metabolism in plants can be challenging due to the dynamic range in pool sizes, with low levels of important phosphorylated sugars relative to more abundant sugars and organic acids. Here, we report a sensitive liquid chromatography-mass spectrometry method for analysing central metabolites on a hybrid column, where both anion-exchange and hydrophilic interaction chromatography (HILIC) ligands are embedded in the stationary phase. The liquid chromatography method was developed for enhanced selectivity of 27 central metabolites in a single run with sensitivity at femtomole levels observed for most phosphorylated sugars. The method resolved phosphorylated hexose, pentose, and triose isomers that are otherwise challenging. Compared with a standard HILIC approach, these metabolites had improved peak areas using our approach due to ion enhancement or low ion suppression in the biological sample matrix. The approach was applied to investigate metabolism in high lipid-producing tobacco leaves that exhibited increased levels of acetyl-CoA, a precursor for oil biosynthesis. The application of the method to isotopologue detection and quantification was considered through evaluating 13C-labeled seeds from Camelina sativa. The method provides a means to analyse intermediates more comprehensively in central metabolism of plant tissues.
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Affiliation(s)
- Somnath Koley
- Donald Danforth Plant Science Center, St Louis, MO 63132, USA
| | - Kevin L Chu
- Donald Danforth Plant Science Center, St Louis, MO 63132, USA
- United States Department of Agriculture-Agriculture Research Service, Donald Danforth Plant Science Center, St Louis, MO 63132, USA
| | - Saba S Gill
- Donald Danforth Plant Science Center, St Louis, MO 63132, USA
- United States Department of Agriculture-Agriculture Research Service, Donald Danforth Plant Science Center, St Louis, MO 63132, USA
| | - Doug K Allen
- Donald Danforth Plant Science Center, St Louis, MO 63132, USA
- United States Department of Agriculture-Agriculture Research Service, Donald Danforth Plant Science Center, St Louis, MO 63132, USA
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8
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Chacko S, Haseeb YB, Haseeb S. Metabolomics Work Flow and Analytics in Systems Biology. Curr Mol Med 2021; 22:870-881. [PMID: 34923941 DOI: 10.2174/1566524022666211217102105] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 08/26/2021] [Accepted: 09/24/2021] [Indexed: 11/22/2022]
Abstract
Metabolomics is an omics approach of systems biology that involves the development and assessment of large-scale, comprehensive biochemical analysis tools for metabolites in biological systems. This review describes the metabolomics workflow and provides an overview of current analytic tools used for the quantification of metabolic profiles. We explain analytic tools such as mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, ionization techniques, and approaches for data extraction and analysis.
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Affiliation(s)
- Sanoj Chacko
- Division of Cardiology, Queen's University, Kingston, Ontario, Canada
| | - Yumna B Haseeb
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, Ontario, Canada
| | - Sohaib Haseeb
- Division of Cardiology, Queen's University, Kingston, Ontario, Canada
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9
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Sun Q, Fan TWM, Lane AN, Higashi RM. An Ion Chromatography-Ultrahigh-Resolution-MS 1/Data-Independent High-Resolution MS 2 Method for Stable Isotope-Resolved Metabolomics Reconstruction of Central Metabolic Networks. Anal Chem 2021; 93:2749-2757. [PMID: 33482055 DOI: 10.1021/acs.analchem.0c03070] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
The metabolome comprises a complex network of interconnecting enzyme-catalyzed reactions that involve transfers of numerous molecular subunits. Thus, the reconstruction of metabolic networks requires metabolite substructures to be tracked. Subunit tracking can be achieved by tracing stable isotopes through metabolic transformations using NMR and ultrahigh -resolution (UHR)-mass spectrometry (MS). UHR-MS1 readily resolves and counts isotopic labels in metabolites but requires tandem MS to help identify isotopic enrichment in substructures. However, it is challenging to perform chromatography-based UHR-MS1 with its long acquisition time, while acquiring MS2 data on many coeluting labeled isotopologues for each metabolite. We have developed an ion chromatography (IC)-UHR-MS1/data-independent(DI)-HR-MS2 method to trace the fate of 13C atoms from [13C6]-glucose ([13C6]-Glc) in 3D A549 spheroids in response to anticancer selenite and simultaneously 13C/15N atoms from [13C5,15N2]-glutamine ([13C5,15N2]-Gln) in 2D BEAS-2B cells in response to arsenite transformation. This method retains the complete isotopologue distributions of metabolites via UHR-MS1 while simultaneously acquiring substructure label information via DI-MS2. These details in metabolite labeling patterns greatly facilitate rigorous reconstruction of multiple, intersecting metabolic pathways of central metabolism, which are illustrated here for the purine/pyrimidine nucleotide biosynthesis. The pathways reconstructed based on subunit-level isotopologue analysis further reveal specific enzyme-catalyzed reactions that are impacted by selenite or arsenite treatments.
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Affiliation(s)
- Qiushi Sun
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, Kentucky 40536, United States
| | - Teresa W-M Fan
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, Kentucky 40536, United States.,Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky 40536, United States.,Markey Cancer Center, University of Kentucky, Lexington, Kentucky 40536, United States
| | - Andrew N Lane
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, Kentucky 40536, United States.,Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky 40536, United States.,Markey Cancer Center, University of Kentucky, Lexington, Kentucky 40536, United States
| | - Richard M Higashi
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, Kentucky 40536, United States.,Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky 40536, United States.,Markey Cancer Center, University of Kentucky, Lexington, Kentucky 40536, United States
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10
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Zhang Y, Gao B, Valdiviez L, Zhu C, Gallagher T, Whiteson K, Fiehn O. Comparing Stable Isotope Enrichment by Gas Chromatography with Time-of-Flight, Quadrupole Time-of-Flight, and Quadrupole Mass Spectrometry. Anal Chem 2021; 93:2174-2182. [PMID: 33434014 PMCID: PMC10782559 DOI: 10.1021/acs.analchem.0c04013] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Stable isotope tracers are applied for in vivo and in vitro studies to reveal the activity of enzymes and intracellular metabolic pathways. Most often, such tracers are used with gas chromatography coupled to mass spectrometry (GC-MS) owing to its ease of operation and reproducible mass spectral databases. Differences in isotope tracer performance of the classic GC-quadrupole MS instrument and newer time-of-flight instruments are not well studied. Here, we used three commercially available instruments for the analysis of identical samples from a stable isotope labeling study that used [U-13C6] d-glucose to investigate the metabolism of the bacterium Rothia mucilaginosa with respect to 29 amino acids and hydroxyl acids involved in primary metabolism. The prokaryote R. mucilaginosa belongs to the family of Micrococcaceae and is present and metabolically active in the airways and sputum of cystic fibrosis patients. Overall, all three GC-MS instruments (low-resolution GC-SQ MS, low-resolution GC-TOF MS, and high-resolution GC-QTOF MS) can be used to perform stable isotope tracing studies for glycolytic intermediates, tricarboxylic acid (TCA) metabolites, and amino acids, yielding similar biological results, with high-resolution GC-QTOF MS offering additional capabilities to identify the chemical structures of unknown compounds that might show significant isotope enrichments in biological studies.
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Affiliation(s)
- Ying Zhang
- West Coast Metabolomics Center, University of California, Davis, 95616, CA, USA
- Department of Chemistry, University of California, Davis, 95616, CA, USA
| | - Bei Gao
- Department of Medicine, University of California, San Diego, San Diego, 92093, CA, USA
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Luis Valdiviez
- West Coast Metabolomics Center, University of California, Davis, 95616, CA, USA
| | - Chao Zhu
- College of Medicine & Nursing, Dezhou University, De Zhou, Shandong, 253023, China
| | - Tara Gallagher
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA, USA
| | - Katrine Whiteson
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, 95616, CA, USA
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11
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Capellades J, Junza A, Samino S, Brunner JS, Schabbauer G, Vinaixa M, Yanes O. Exploring the Use of Gas Chromatography Coupled to Chemical Ionization Mass Spectrometry (GC-CI-MS) for Stable Isotope Labeling in Metabolomics. Anal Chem 2021; 93:1242-1248. [PMID: 33369389 DOI: 10.1021/acs.analchem.0c02998] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Isotopic-labeling experiments have been valuable to monitor the flux of metabolic reactions in biological systems, which is crucial to understand homeostatic alterations with disease. Experimental determination of metabolic fluxes can be inferred from a characteristic rearrangement of stable isotope tracers (e.g., 13C or 15N) that can be detected by mass spectrometry (MS). Metabolites measured are generally members of well-known metabolic pathways, and most of them can be detected using both gas chromatography (GC)-MS and liquid chromatography (LC)-MS. In here, we show that GC methods coupled to chemical ionization (CI) MS have a clear advantage over alternative methodologies due to GC's superior chromatography separation efficiency and the fact that CI is a soft ionization technique that yields identifiable protonated molecular ion peaks. We tested diverse GC-CI-MS setups, including methane and isobutane reagent gases, triple quadrupole (QqQ) MS in SIM mode, or selected ion clusters using optimized narrow windows (∼10 Da) in scan mode, and standard full scan methods using high resolution GC-(q)TOF and GC-Orbitrap systems. Isobutane as a reagent gas in combination with both low-resolution (LR) and high-resolution (HR) MS showed the best performance, enabling precise detection of isotopologues in most metabolic intermediates of central carbon metabolism. Finally, with the aim of overcoming manual operations, we developed an R-based tool called isoSCAN that automatically quantifies all isotopologues of intermediate metabolites of glycolysis, TCA cycle, amino acids, pentose phosphate pathway, and urea cycle, from LRMS and HRMS data.
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Affiliation(s)
- Jordi Capellades
- Department of Electronic Engineering, Universitat Rovira i Virgili, Tarragona, Spain.,CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Metabolomics Platform, Reus, Spain
| | - Alexandra Junza
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
| | - Sara Samino
- Department of Electronic Engineering, Universitat Rovira i Virgili, Tarragona, Spain.,CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
| | - Julia S Brunner
- Institute for Vascular Biology, Centre for Physiology and Pharmacology, Medical University Vienna, 1090 Vienna, Austria.,Christian Doppler Laboratory for Arginine Metabolism in Rheumatoid Arthritis and Multiple Sclerosis, 1090 Vienna, Austria
| | - Gernot Schabbauer
- Institute for Vascular Biology, Centre for Physiology and Pharmacology, Medical University Vienna, 1090 Vienna, Austria.,Christian Doppler Laboratory for Arginine Metabolism in Rheumatoid Arthritis and Multiple Sclerosis, 1090 Vienna, Austria
| | - Maria Vinaixa
- Department of Electronic Engineering, Universitat Rovira i Virgili, Tarragona, Spain.,CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Metabolomics Platform, Reus, Spain
| | - Oscar Yanes
- Department of Electronic Engineering, Universitat Rovira i Virgili, Tarragona, Spain.,CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Metabolomics Platform, Reus, Spain
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12
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Crooks DR, Maio N, Lang M, Ricketts CJ, Vocke CD, Gurram S, Turan S, Kim YY, Cawthon GM, Sohelian F, De Val N, Pfeiffer RM, Jailwala P, Tandon M, Tran B, Fan TWM, Lane AN, Ried T, Wangsa D, Malayeri AA, Merino MJ, Yang Y, Meier JL, Ball MW, Rouault TA, Srinivasan R, Linehan WM. Mitochondrial DNA alterations underlie an irreversible shift to aerobic glycolysis in fumarate hydratase-deficient renal cancer. Sci Signal 2021; 14:14/664/eabc4436. [PMID: 33402335 DOI: 10.1126/scisignal.abc4436] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Understanding the mechanisms of the Warburg shift to aerobic glycolysis is critical to defining the metabolic basis of cancer. Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is an aggressive cancer characterized by biallelic inactivation of the gene encoding the Krebs cycle enzyme fumarate hydratase, an early shift to aerobic glycolysis, and rapid metastasis. We observed impairment of the mitochondrial respiratory chain in tumors from patients with HLRCC. Biochemical and transcriptomic analyses revealed that respiratory chain dysfunction in the tumors was due to loss of expression of mitochondrial DNA (mtDNA)-encoded subunits of respiratory chain complexes, caused by a marked decrease in mtDNA content and increased mtDNA mutations. We demonstrated that accumulation of fumarate in HLRCC tumors inactivated the core factors responsible for replication and proofreading of mtDNA, leading to loss of respiratory chain components, thereby promoting the shift to aerobic glycolysis and disease progression in this prototypic model of glucose-dependent human cancer.
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Affiliation(s)
- Daniel R Crooks
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Nunziata Maio
- Molecular Medicine Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20892, USA
| | - Martin Lang
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Christopher J Ricketts
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Cathy D Vocke
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Sandeep Gurram
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Sevilay Turan
- Sequencing Facility, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21701, USA
| | - Yun-Young Kim
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - G Mariah Cawthon
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Ferri Sohelian
- Electron Microscopy Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21702, USA
| | - Natalia De Val
- Electron Microscopy Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21702, USA
| | - Ruth M Pfeiffer
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA
| | - Parthav Jailwala
- CCR Collaborative Bioinformatics Resource (CCBR), Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21702, USA.,Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21702, USA
| | - Mayank Tandon
- CCR Collaborative Bioinformatics Resource (CCBR), Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21702, USA.,Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21702, USA
| | - Bao Tran
- Sequencing Facility, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21701, USA
| | - Teresa W-M Fan
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology and Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA
| | - Andrew N Lane
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology and Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA
| | - Thomas Ried
- Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Darawalee Wangsa
- Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Ashkan A Malayeri
- Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA
| | - Maria J Merino
- Genitourinary Pathology Section, Laboratory of Pathology, National Cancer Institute, Bethesda, MD 20892, USA
| | - Youfeng Yang
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Jordan L Meier
- Epigenetics and Metabolism Section, Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, MD 21702, USA
| | - Mark W Ball
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Tracey A Rouault
- Molecular Medicine Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20892, USA
| | - Ramaprasad Srinivasan
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - W Marston Linehan
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
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13
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Merino MJ, Ricketts CJ, Moreno V, Yang Y, Fan TW, Lane AN, Meltzer PS, Vocke CD, Crooks DR, Linehan WM. Multifocal Renal Cell Carcinomas With Somatic IDH2 Mutation: Report of a Previously Undescribed Neoplasm. Am J Surg Pathol 2021; 45:137-142. [PMID: 33165095 PMCID: PMC7736215 DOI: 10.1097/pas.0000000000001611] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Renal cell carcinoma (RCC) is a heterogenous disease composed of several different cancer types characterized by distinct histologies and genetic alterations, including mutation of the Krebs cycle enzyme genes for fumarate hydratase and succinate dehydrogenase (SDH). This report describes a patient with multifocal renal tumors that presented with a novel, biphasic histologic morphology with one component consisting of small cells growing in a diffuse pattern occasionally forming glandular and cystic structures, reminiscent of type 1 papillary RCC, and the other component having larger cells with abundant eosinophilic and clear cytoplasm and appearing in a solid pattern of growth. Genetic analysis of multiple tumors showed that all had a somatic mutation of the IDH2 gene that created the known pathogenic, gain-of-function p.R172M alteration that results in abnormal accumulation of the oncometabolite 2-hydroxyglutarate (2-HG). Analysis of multiple tumors demonstrated highly elevated levels of 2-HG and a CpG island methylator phenotype that is characteristic of 2-HG-related inhibition of the Ten-eleven translocation (TET) family of DNA demethylases. In combination with fumarate hydratase-deficient and succinate dehydrogenase-deficient RCCs that have increased levels of the fumarate and succinate oncometabolites, respectively, the mutation of isocitrate dehydrogenase 2 represents the third Krebs cycle enzyme alteration to be associated with oncometabolite-induced RCC tumorigenesis. This study associates the discovery of a new histologic presentation of RCC with the first report of an IDH2 gain-of-function mutation in RCC.
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Affiliation(s)
- Maria J. Merino
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Christopher J. Ricketts
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Vanessa Moreno
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Ye Yang
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Teresa W.M. Fan
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology and Markey Cancer Center, University of Kentucky, Lexington, Kentucky 40536, USA
| | - Andrew N. Lane
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology and Markey Cancer Center, University of Kentucky, Lexington, Kentucky 40536, USA
| | - Paul S. Meltzer
- Genetics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Cathy D. Vocke
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Daniel R. Crooks
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - W. Marston Linehan
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
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14
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Maniam S, Maniam S. Cancer Cell Metabolites: Updates on Current Tracing Methods. Chembiochem 2020; 21:3476-3488. [PMID: 32639076 DOI: 10.1002/cbic.202000290] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 07/07/2020] [Indexed: 12/15/2022]
Abstract
Cancer is the second leading cause of death-1 in 6 deaths globally is due to cancer. Cancer metabolism is a complex and one of the most actively researched area in cancer biology. Metabolic reprogramming in cancer cells entails activities that involve several enzymes and metabolites to convert nutrient into building blocks that alter energy metabolism to fuel rapid cell division. Metabolic dependencies in cancer generate signature metabolites that have key regulatory roles in tumorigenesis. In this minireview, we highlight recent advances in the popular methods ingrained in biochemistry research such as stable and flux isotope analysis, as well as radioisotope labeling, which are valuable in elucidating cancer metabolites. These methods together with analytical tools such as chromatography, nuclear magnetic resonance spectroscopy and mass spectrometry have helped to bring about exploratory work in understanding the role of important as well as obscure metabolites in cancer cells. Information obtained from these analyses significantly contribute in the diagnosis and prognosis of tumors leading to potential therapeutic targets for cancer therapy.
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Affiliation(s)
- Subashani Maniam
- School of Applied Science, RMIT University, 240 La Trobe Street, Melbourne, VIC 3001, Australia
| | - Sandra Maniam
- Department of Human Anatomy, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
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15
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Letertre MPM, Dervilly G, Giraudeau P. Combined Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry Approaches for Metabolomics. Anal Chem 2020; 93:500-518. [PMID: 33155816 DOI: 10.1021/acs.analchem.0c04371] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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16
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Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective. Metabolites 2020; 10:metabo10060249. [PMID: 32549391 PMCID: PMC7345423 DOI: 10.3390/metabo10060249] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 06/02/2020] [Accepted: 06/04/2020] [Indexed: 12/11/2022] Open
Abstract
The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.
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17
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Sun Q, Fan TWM, Lane AN, Higashi RM. Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks. Trends Analyt Chem 2020; 123:115676. [PMID: 32483395 PMCID: PMC7263348 DOI: 10.1016/j.trac.2019.115676] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.
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Affiliation(s)
- Qiushi Sun
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, KY, 40539, USA
| | - Teresa W-M. Fan
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, KY, 40539, USA
- Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40539, USA
- Markey Cancer Center, University of Kentucky, Lexington, KY, 40539, USA
| | - Andrew N. Lane
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, KY, 40539, USA
- Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40539, USA
- Markey Cancer Center, University of Kentucky, Lexington, KY, 40539, USA
| | - Richard M. Higashi
- Center for Environmental and Systems Biochemistry (CESB), University of Kentucky, Lexington, KY, 40539, USA
- Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40539, USA
- Markey Cancer Center, University of Kentucky, Lexington, KY, 40539, USA
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18
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APOE alters glucose flux through central carbon pathways in astrocytes. Neurobiol Dis 2020; 136:104742. [PMID: 31931141 DOI: 10.1016/j.nbd.2020.104742] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 01/04/2020] [Accepted: 01/08/2020] [Indexed: 02/02/2023] Open
Abstract
The Apolipoprotein E (APOE) gene is a major genetic risk factor associated with Alzheimer's disease (AD). APOE encodes for three main isoforms in humans (E2, E3, and E4). Homozygous E4 individuals have more than a 10-fold higher risk for developing late-onset AD, while E2 carriers are protected. A hallmark of AD is a reduction in cerebral glucose metabolism, alluding to a strong metabolic component in disease onset and progression. Interestingly, E4 individuals display a similar regional pattern of cerebral glucose hypometabolism decades prior to disease onset. Mapping this metabolic landscape may help elucidate the underlying biological mechanism of APOE-associated risk for AD. Efficient metabolic coupling of neurons and glia is necessary for proper neuronal function, and disruption in glial energy distribution has been proposed to contribute to neuronal cell death and AD pathology. One important function of astrocytes - canonically the primary source of apolipoprotein E in the brain - is to provide metabolic substrates (lactate, lipids, amino acids and neurotransmitters) to neurons. Here we investigate the effects of APOE on astrocyte glucose metabolism in vitro utilizing scintillation proximity assays, stable isotope tracer metabolomics, and gene expression analyses. Glucose uptake is impaired in E4 astrocytes relative to E2 or E3 with specific alterations in central carbon metabolism. Using stable isotope labeled glucose [U-13C] allowed analyses of astrocyte-specific deep metabolic networks affected by APOE, and provided insight to the effects downstream of glucose uptake. Enrichment of 13C in early steps of glycolysis was lowest in E4 astrocytes (highest in E2), while synthesis of lactate from glucose was highest in E4 astrocytes (lowest in E2). We observed an increase in glucose flux through the pentose phosphate pathway (PPP), with downstream increases in gluconeogenesis, lipid, and de novo nucleotide biosynthesis in E4 astrocytes. There was also a marked increase in 13C enrichment in the TCA cycle of E4 astrocytes - whose substrates were also incorporated into biosynthetic pathways at a higher rate. Pyruvate carboxylase (PC) and pyruvate dehydrogenase (PDH) are the two main enzymes controlling pyruvate entry to the TCA cycle. PC gene expression is increased in E4 astrocytes and the activity relative to PDH was also increased, compared to E2 or E3. Decreased enrichment in the TCA cycle of E2 and E3 astrocytes is suggestive of increased oxidation and non-glucose derived anaplerosis, which could be fueling mitochondrial ATP production. Conversely, E4 astrocytes appear to increase carbon flux into the TCA cycle to fuel cataplerosis. Together, these data demonstrate clear APOE isoform-specific effects on glucose utilization in astrocytes, including E4-associated increases in lactate synthesis, PPP flux, and de novo biosynthesis pathways.
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19
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Selivanov VA, Marin S, Tarragó-Celada J, Lane AN, Higashi RM, Fan TWM, de Atauri P, Cascante M. Software Supporting a Workflow of Quantitative Dynamic Flux Maps Estimation in Central Metabolism from SIRM Experimental Data. Methods Mol Biol 2020; 2088:271-298. [PMID: 31893378 DOI: 10.1007/978-1-0716-0159-4_12] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.
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Affiliation(s)
- Vitaly A Selivanov
- Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain. .,Institute of Biomedicine of Universitat de Barcelona (IBUB), Barcelona, Spain. .,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. .,INB-Bioinformatics Platform Metabolomics Node, Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
| | - Silvia Marin
- Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.,Institute of Biomedicine of Universitat de Barcelona (IBUB), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Josep Tarragó-Celada
- Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.,Institute of Biomedicine of Universitat de Barcelona (IBUB), Barcelona, Spain
| | - Andrew N Lane
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA.,Center for Environment and Systems Biochemistry and the Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY, USA.,Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, USA
| | - Richard M Higashi
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA.,Center for Environment and Systems Biochemistry and the Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY, USA.,Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, USA
| | - Teresa W-M Fan
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA.,Center for Environment and Systems Biochemistry and the Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY, USA.,Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, USA
| | - Pedro de Atauri
- Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.,Institute of Biomedicine of Universitat de Barcelona (IBUB), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.,INB-Bioinformatics Platform Metabolomics Node, Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Marta Cascante
- Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain. .,Institute of Biomedicine of Universitat de Barcelona (IBUB), Barcelona, Spain. .,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. .,INB-Bioinformatics Platform Metabolomics Node, Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
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20
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Mitchell JM, Flight RM, Moseley HNB. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal Chem 2019; 91:8933-8940. [PMID: 31260262 DOI: 10.1021/acs.analchem.9b00748] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Improvements in Fourier transform mass spectrometry (FT-MS) enable increasingly more complex experiments in the field of metabolomics. What is directly detected in FT-MS spectra are spectral features (peaks) that correspond to sets of adducted and charged forms of specific molecules in the sample. The robust assignment of these features is an essential step for MS-based metabolomics experiments, but the sheer complexity of what is detected and a variety of analytically introduced variance, errors, and artifacts has hindered the systematic analysis of complex patterns of observed peaks with respect to isotope content. We have developed a method called SMIRFE that detects small biomolecules and determines their elemental molecular formula (EMF) using detected sets of isotopologue peaks sharing the same EMF. SMIRFE does not use a database of known metabolite formulas; instead a nearly comprehensive search space of all isotopologues within a mass range is constructed and used for assignment. This search space can be tailored for different isotope labeling patterns expected in different stable isotope tracing experiments. Using consumer-level computing equipment, a large search space of 2000 Da was constructed, and assignment performance was evaluated and validated using verified assignments on a pair of peak lists derived from spectra containing unlabeled and 15N-labeled versions of amino acids derivatized using ethylchloroformate. SMIRFE identified 18 of 18 predicted derivatized EMFs, and each assignment was evaluated statistically and assigned an e-value representing the probability to occur by chance.
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21
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Kang WY, Thompson PT, El-Amouri SS, Fan TWM, Lane AN, Higashi RM. Improved segmented-scan spectral stitching for stable isotope resolved metabolomics (SIRM) by ultra-high-resolution Fourier transform mass spectrometry. Anal Chim Acta 2019; 1080:104-115. [PMID: 31409459 DOI: 10.1016/j.aca.2019.06.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 05/30/2019] [Accepted: 06/08/2019] [Indexed: 12/25/2022]
Abstract
We have implemented a linear ion trap (LIT)-based SIM-stitching method for ultra-high-resolution Fourier transform mass spectrometry (FTMS) that increases the S/N over a wide m/z range compared to non-segmented wide full-scan (WFS) spectra. Here we described an improved segmented spectral scan stitching method that was based on quadrupole mass filter (QMF)-SIM, which overcame previous limitations of ion signal loss in LIT. This allowed for accurate representation of isotopologue distributions, both at natural abundance and in stable isotope-resolved metabolomics (SIRM)-based experiments. We also introduced a new spectral binning method that provided more precise and resolution-independent bins for irreversibly noise-suppressed FTMS spectra. We demonstrated a substantial improvement in S/N and sensitivity (typically > 10-fold) for 13C labeled lipid extracts of human macrophages grown as three-dimensional (3D) cell culture, with detection of an increased number of 13C isotopologue ions. The method also enabled analysis of extracts from very limited biological samples.
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Affiliation(s)
- Woo-Young Kang
- Center for Environmental and Systems Biochemistry (CESB), Markey Cancer Center, Department of Toxicology and Cancer Biology, University of Kentucky, United States
| | - Patrick T Thompson
- Center for Environmental and Systems Biochemistry (CESB), Markey Cancer Center, Department of Toxicology and Cancer Biology, University of Kentucky, United States
| | - Salim S El-Amouri
- Center for Environmental and Systems Biochemistry (CESB), Markey Cancer Center, Department of Toxicology and Cancer Biology, University of Kentucky, United States
| | - Teresa W M Fan
- Center for Environmental and Systems Biochemistry (CESB), Markey Cancer Center, Department of Toxicology and Cancer Biology, University of Kentucky, United States
| | - Andrew N Lane
- Center for Environmental and Systems Biochemistry (CESB), Markey Cancer Center, Department of Toxicology and Cancer Biology, University of Kentucky, United States
| | - Richard M Higashi
- Center for Environmental and Systems Biochemistry (CESB), Markey Cancer Center, Department of Toxicology and Cancer Biology, University of Kentucky, United States.
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22
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Crooks DR, Fan TWM, Linehan WM. Metabolic Labeling of Cultured Mammalian Cells for Stable Isotope-Resolved Metabolomics: Practical Aspects of Tissue Culture and Sample Extraction. Methods Mol Biol 2019; 1928:1-27. [PMID: 30725447 PMCID: PMC8195444 DOI: 10.1007/978-1-4939-9027-6_1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Stable isotope-resolved metabolomics (SIRM) methods are used increasingly by cancer researchers to probe metabolic pathways and identify vulnerabilities in cancer cells. Analytical and computational advances are being made constantly, but tissue culture and sample extraction procedures are often variable and not elaborated in the literature. This chapter discusses basic aspects of tissue culture practices as they relate to the use of stable isotope tracers and provides a detailed metabolic labeling and metabolite extraction procedure designed to maximize the amount of information that can be obtained from a single tracer experiment.
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Affiliation(s)
- Daniel R Crooks
- Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Teresa W-M Fan
- Department of Toxicology and Cancer Biology, Center for Environmental and Systems Biochemistry, Markey Cancer Center, and University of Kentucky, Lexington, KY, USA.
| | - W Marston Linehan
- Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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23
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Lane AN, Higashi RM, Fan TWM. NMR and MS-based Stable Isotope-Resolved Metabolomics and Applications in Cancer Metabolism. Trends Analyt Chem 2018; 120. [PMID: 32523238 DOI: 10.1016/j.trac.2018.11.020] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
There is considerable interest in defining metabolic reprogramming in human diseases, which is recognized as a hallmark of human cancer. Although radiotracers have a long history in specific metabolic studies, stable isotope-enriched precursors coupled with modern high resolution mass spectrometry and NMR spectroscopy have enabled systematic mapping of metabolic networks and fluxes in cells, tissues and living organisms including humans. These analytical platforms are high in information content, are complementary and cross-validating in terms of compound identification, quantification, and isotope labeling pattern analysis of a large number of metabolites simultaneously. Furthermore, new developments in chemoselective derivatization and in vivo spectroscopy enable tracking of labile/low abundance metabolites and metabolic kinetics in real-time. Here we review developments in Stable Isotope Resolved Metabolomics (SIRM) and recent applications in cancer metabolism using a wide variety of stable isotope tracers that probe both broad and specific aspects of cancer metabolism required for proliferation and survival.
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Affiliation(s)
- Andrew N Lane
- Center for Environmental and Systems Biochemistry, Dept. Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, 789 S. Limestone St., Lexington, KY 40536 USA
| | - Richard M Higashi
- Center for Environmental and Systems Biochemistry, Dept. Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, 789 S. Limestone St., Lexington, KY 40536 USA
| | - Teresa W-M Fan
- Center for Environmental and Systems Biochemistry, Dept. Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, 789 S. Limestone St., Lexington, KY 40536 USA
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24
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Systems biology primer: the basic methods and approaches. Essays Biochem 2018; 62:487-500. [PMID: 30287586 DOI: 10.1042/ebc20180003] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 08/22/2018] [Accepted: 08/24/2018] [Indexed: 12/16/2022]
Abstract
Systems biology is an integrative discipline connecting the molecular components within a single biological scale and also among different scales (e.g. cells, tissues and organ systems) to physiological functions and organismal phenotypes through quantitative reasoning, computational models and high-throughput experimental technologies. Systems biology uses a wide range of quantitative experimental and computational methodologies to decode information flow from genes, proteins and other subcellular components of signaling, regulatory and functional pathways to control cell, tissue, organ and organismal level functions. The computational methods used in systems biology provide systems-level insights to understand interactions and dynamics at various scales, within cells, tissues, organs and organisms. In recent years, the systems biology framework has enabled research in quantitative and systems pharmacology and precision medicine for complex diseases. Here, we present a brief overview of current experimental and computational methods used in systems biology.
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Mitchell JM, Flight RM, Wang QJ, Higashi RM, Fan TWM, Lane AN, Moseley HNB. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics 2018; 14:125. [PMID: 30830442 PMCID: PMC6153687 DOI: 10.1007/s11306-018-1426-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 09/05/2018] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Direct injection Fourier-transform mass spectrometry (FT-MS) allows for the high-throughput and high-resolution detection of thousands of metabolite-associated isotopologues. However, spectral artifacts can generate large numbers of spectral features (peaks) that do not correspond to known compounds. Misassignment of these artifactual features creates interpretive errors and limits our ability to discern the role of representative features within living systems. OBJECTIVES Our goal is to develop rigorous methods that identify and handle spectral artifacts within the context of high-throughput FT-MS-based metabolomics studies. RESULTS We observed three types of artifacts unique to FT-MS that we named high peak density (HPD) sites: fuzzy sites, ringing and partial ringing. While ringing artifacts are well-known, fuzzy sites and partial ringing have not been previously well-characterized in the literature. We developed new computational methods based on comparisons of peak density within a spectrum to identify regions of spectra with fuzzy sites. We used these methods to identify and eliminate fuzzy site artifacts in an example dataset of paired cancer and non-cancer lung tissue samples and evaluated the impact of these artifacts on classification accuracy and robustness. CONCLUSION Our methods robustly identified consistent fuzzy site artifacts in our FT-MS metabolomics spectral data. Without artifact identification and removal, 91.4% classification accuracy was achieved on an example lung cancer dataset; however, these classifiers rely heavily on artifactual features present in fuzzy sites. Proper removal of fuzzy site artifacts produces a more robust classifier based on non-artifactual features, with slightly improved accuracy of 92.4% in our example analysis.
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Affiliation(s)
- Joshua M Mitchell
- Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY, USA
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
- Center for Environment and Systems Biochemistry and the Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY, USA
| | - Robert M Flight
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
- Center for Environment and Systems Biochemistry and the Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY, USA
| | - Qing Jun Wang
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
- Department of Ophthalmology and Visual Sciences, University of Kentucky, Lexington, KY, USA
| | - Richard M Higashi
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
- Center for Environment and Systems Biochemistry and the Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY, USA
- Department of Toxicology & Cancer Biology, University of Kentucky, Lexington, KY, USA
| | - Teresa W-M Fan
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
- Center for Environment and Systems Biochemistry and the Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY, USA
- Department of Toxicology & Cancer Biology, University of Kentucky, Lexington, KY, USA
| | - Andrew N Lane
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
- Center for Environment and Systems Biochemistry and the Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY, USA
- Department of Toxicology & Cancer Biology, University of Kentucky, Lexington, KY, USA
| | - Hunter N B Moseley
- Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY, USA.
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA.
- Center for Environment and Systems Biochemistry and the Resource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY, USA.
- Institute for Biomedical Informatics, University of Kentucky, Lexington, KY, USA.
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Tebani A, Afonso C, Bekri S. Advances in metabolome information retrieval: turning chemistry into biology. Part II: biological information recovery. J Inherit Metab Dis 2018; 41:393-406. [PMID: 28842777 PMCID: PMC5959951 DOI: 10.1007/s10545-017-0080-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2017] [Revised: 07/27/2017] [Accepted: 07/28/2017] [Indexed: 12/11/2022]
Abstract
This work reports the second part of a review intending to give the state of the art of major metabolic phenotyping strategies. It particularly deals with inherent advantages and limits regarding data analysis issues and biological information retrieval tools along with translational challenges. This Part starts with introducing the main data preprocessing strategies of the different metabolomics data. Then, it describes the main data analysis techniques including univariate and multivariate aspects. It also addresses the challenges related to metabolite annotation and characterization. Finally, functional analysis including pathway and network strategies are discussed. The last section of this review is devoted to practical considerations and current challenges and pathways to bring metabolomics into clinical environments.
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Affiliation(s)
- Abdellah Tebani
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000, Rouen, France
- Normandie Université, UNIROUEN, CHU Rouen, IRIB, INSERM U1245, 76000, Rouen, France
- Normandie Université, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000, Rouen, France
| | - Carlos Afonso
- Normandie Université, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000, Rouen, France
| | - Soumeya Bekri
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000, Rouen, France.
- Normandie Université, UNIROUEN, CHU Rouen, IRIB, INSERM U1245, 76000, Rouen, France.
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27
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Crooks DR, Maio N, Lane AN, Jarnik M, Higashi RM, Haller RG, Yang Y, Fan TWM, Linehan WM, Rouault TA. Acute loss of iron-sulfur clusters results in metabolic reprogramming and generation of lipid droplets in mammalian cells. J Biol Chem 2018. [PMID: 29523684 DOI: 10.1074/jbc.ra118.001885] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Iron-sulfur (Fe-S) clusters are ancient cofactors in cells and participate in diverse biochemical functions, including electron transfer and enzymatic catalysis. Although cell lines derived from individuals carrying mutations in the Fe-S cluster biogenesis pathway or siRNA-mediated knockdown of the Fe-S assembly components provide excellent models for investigating Fe-S cluster formation in mammalian cells, these experimental strategies focus on the consequences of prolonged impairment of Fe-S assembly. Here, we constructed and expressed dominant-negative variants of the primary Fe-S biogenesis scaffold protein iron-sulfur cluster assembly enzyme 2 (ISCU2) in human HEK293 cells. This approach enabled us to study the early metabolic reprogramming associated with loss of Fe-S-containing proteins in several major cellular compartments. Using multiple metabolomics platforms, we observed a ∼12-fold increase in intracellular citrate content in Fe-S-deficient cells, a surge that was due to loss of aconitase activity. The excess citrate was generated from glucose-derived acetyl-CoA, and global analysis of cellular lipids revealed that fatty acid biosynthesis increased markedly relative to cellular proliferation rates in Fe-S-deficient cells. We also observed intracellular lipid droplet accumulation in both acutely Fe-S-deficient cells and iron-starved cells. We conclude that deficient Fe-S biogenesis and acute iron deficiency rapidly increase cellular citrate concentrations, leading to fatty acid synthesis and cytosolic lipid droplet formation. Our findings uncover a potential cause of cellular steatosis in nonadipose tissues.
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Affiliation(s)
- Daniel R Crooks
- Urologic Oncology Branch, Center for Cancer Research, NCI, National Institutes of Health, Bethesda, Maryland 20892
| | - Nunziata Maio
- Section on Human Iron Metabolism, National Institutes of Health, Bethesda, Maryland 20892
| | - Andrew N Lane
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology, and Markey Cancer Center, University of Kentucky, Lexington, Kentucky 40536
| | - Michal Jarnik
- Section on Cell Biology and Metabolism, Eunice Kennedy Shriver NICHD, National Institutes of Health, Bethesda, Maryland 20892
| | - Richard M Higashi
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology, and Markey Cancer Center, University of Kentucky, Lexington, Kentucky 40536
| | - Ronald G Haller
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, Texas 75390; Veterans Affairs North Texas Medical Center, Dallas, Texas 75216; Neuromuscular Center, Institute for Exercise and Environmental Medicine, Dallas, Texas 75231
| | - Ye Yang
- Urologic Oncology Branch, Center for Cancer Research, NCI, National Institutes of Health, Bethesda, Maryland 20892
| | - Teresa W-M Fan
- Center for Environmental and Systems Biochemistry, Department of Toxicology and Cancer Biology, and Markey Cancer Center, University of Kentucky, Lexington, Kentucky 40536
| | - W Marston Linehan
- Urologic Oncology Branch, Center for Cancer Research, NCI, National Institutes of Health, Bethesda, Maryland 20892
| | - Tracey A Rouault
- Section on Human Iron Metabolism, National Institutes of Health, Bethesda, Maryland 20892.
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Rosato A, Tenori L, Cascante M, De Atauri Carulla PR, Martins Dos Santos VAP, Saccenti E. From correlation to causation: analysis of metabolomics data using systems biology approaches. Metabolomics 2018; 14:37. [PMID: 29503602 PMCID: PMC5829120 DOI: 10.1007/s11306-018-1335-y] [Citation(s) in RCA: 123] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 01/31/2018] [Indexed: 12/26/2022]
Abstract
INTRODUCTION Metabolomics is a well-established tool in systems biology, especially in the top-down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches. OBJECTIVES This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods. METHODS We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis. RESULTS We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner. CONCLUSIONS Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.
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Affiliation(s)
- Antonio Rosato
- Magnetic Resonance Center and Department of Chemistry "Ugo Schiff", University of Florence, Florence, Italy.
| | - Leonardo Tenori
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Marta Cascante
- CIBER de Enfermedades hepáticas y digestivas (CIBERHD, Madrid) and Department of Biochemistry and Molecular Biomedicine, Universitat de Barcelona, Barcelona, Spain
| | - Pedro Ramon De Atauri Carulla
- CIBER de Enfermedades hepáticas y digestivas (CIBERHD, Madrid) and Department of Biochemistry and Molecular Biomedicine, Universitat de Barcelona, Barcelona, Spain
| | - Vitor A P Martins Dos Santos
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, The Netherlands
- LifeGlimmer GmbH, Berlin, Germany
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, The Netherlands.
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Lane AN, Tan J, Wang Y, Yan J, Higashi RM, Fan TWM. Probing the metabolic phenotype of breast cancer cells by multiple tracer stable isotope resolved metabolomics. Metab Eng 2017; 43:125-136. [PMID: 28163219 PMCID: PMC5540847 DOI: 10.1016/j.ymben.2017.01.010] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Revised: 01/20/2017] [Accepted: 01/24/2017] [Indexed: 12/12/2022]
Abstract
Breast cancers vary by their origin and specific set of genetic lesions, which gives rise to distinct phenotypes and differential response to targeted and untargeted chemotherapies. To explore the functional differences of different breast cell types, we performed Stable Isotope Resolved Metabolomics (SIRM) studies of one primary breast (HMEC) and three breast cancer cells (MCF-7, MDAMB-231, and ZR75-1) having distinct genotypes and growth characteristics, using 13C6-glucose, 13C-1+2-glucose, 13C5,15N2-Gln, 13C3-glycerol, and 13C8-octanoate as tracers. These tracers were designed to probe the central energy producing and anabolic pathways (glycolysis, pentose phosphate pathway, Krebs Cycle, glutaminolysis, nucleotide synthesis and lipid turnover). We found that glycolysis was not associated with the rate of breast cancer cell proliferation, glutaminolysis did not support lipid synthesis in primary breast or breast cancer cells, but was a major contributor to pyrimidine ring synthesis in all cell types; anaplerotic pyruvate carboxylation was activated in breast cancer versus primary cells. We also found that glucose metabolism in individual breast cancer cell lines differed between in vitro cultures and tumor xenografts, but not the metabolic distinctions between cell lines, which may reflect the influence of tumor architecture/microenvironment.
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Affiliation(s)
- Andrew N Lane
- J.G. Brown Cancer Center, University of Louisville, Louisville, KY, United States; Dept. Chemistry and Center for Regulatory and Environmental Analytical Metabolomics, University of Louisville, Louisville, KY, United States.
| | - Julie Tan
- J.G. Brown Cancer Center, University of Louisville, Louisville, KY, United States.
| | - Yali Wang
- J.G. Brown Cancer Center, University of Louisville, Louisville, KY, United States.
| | - Jun Yan
- J.G. Brown Cancer Center, University of Louisville, Louisville, KY, United States
| | - Richard M Higashi
- Dept. Chemistry and Center for Regulatory and Environmental Analytical Metabolomics, University of Louisville, Louisville, KY, United States
| | - Teresa W-M Fan
- J.G. Brown Cancer Center, University of Louisville, Louisville, KY, United States; Dept. Chemistry and Center for Regulatory and Environmental Analytical Metabolomics, University of Louisville, Louisville, KY, United States.
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30
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Bruntz RC, Lane AN, Higashi RM, Fan TWM. Exploring cancer metabolism using stable isotope-resolved metabolomics (SIRM). J Biol Chem 2017; 292:11601-11609. [PMID: 28592486 PMCID: PMC5512057 DOI: 10.1074/jbc.r117.776054] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Metabolic reprogramming is a hallmark of cancer. The changes in metabolism are adaptive to permit proliferation, survival, and eventually metastasis in a harsh environment. Stable isotope-resolved metabolomics (SIRM) is an approach that uses advanced approaches of NMR and mass spectrometry to analyze the fate of individual atoms from stable isotope-enriched precursors to products to deduce metabolic pathways and networks. The approach can be applied to a wide range of biological systems, including human subjects. This review focuses on the applications of SIRM to cancer metabolism and its use in understanding drug actions.
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Affiliation(s)
- Ronald C Bruntz
- Center for Environmental and Systems Biochemistry, Markey Cancer Center, Lexington, Kentucky 40506; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky 40506
| | - Andrew N Lane
- Center for Environmental and Systems Biochemistry, Markey Cancer Center, Lexington, Kentucky 40506; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky 40506.
| | - Richard M Higashi
- Center for Environmental and Systems Biochemistry, Markey Cancer Center, Lexington, Kentucky 40506; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky 40506
| | - Teresa W-M Fan
- Center for Environmental and Systems Biochemistry, Markey Cancer Center, Lexington, Kentucky 40506; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky 40506.
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31
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Marshall DD, Powers R. Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2017; 100:1-16. [PMID: 28552170 PMCID: PMC5448308 DOI: 10.1016/j.pnmrs.2017.01.001] [Citation(s) in RCA: 133] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2016] [Revised: 01/04/2017] [Accepted: 01/08/2017] [Indexed: 05/02/2023]
Abstract
Metabolomics is undergoing tremendous growth and is being employed to solve a diversity of biological problems from environmental issues to the identification of biomarkers for human diseases. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the analytical tools that are routinely, but separately, used to obtain metabolomics data sets due to their versatility, accessibility, and unique strengths. NMR requires minimal sample handling without the need for chromatography, is easily quantitative, and provides multiple means of metabolite identification, but is limited to detecting the most abundant metabolites (⩾1μM). Conversely, mass spectrometry has the ability to measure metabolites at very low concentrations (femtomolar to attomolar) and has a higher resolution (∼103-104) and dynamic range (∼103-104), but quantitation is a challenge and sample complexity may limit metabolite detection because of ion suppression. Consequently, liquid chromatography (LC) or gas chromatography (GC) is commonly employed in conjunction with MS, but this may lead to other sources of error. As a result, NMR and mass spectrometry are highly complementary, and combining the two techniques is likely to improve the overall quality of a study and enhance the coverage of the metabolome. While the majority of metabolomic studies use a single analytical source, there is a growing appreciation of the inherent value of combining NMR and MS for metabolomics. An overview of the current state of utilizing both NMR and MS for metabolomics will be presented.
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Affiliation(s)
- Darrell D Marshall
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States.
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32
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Yang Y, Fan TWM, Lane AN, Higashi RM. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM). Anal Chim Acta 2017; 976:63-73. [PMID: 28576319 DOI: 10.1016/j.aca.2017.04.014] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Revised: 04/02/2017] [Accepted: 04/03/2017] [Indexed: 12/29/2022]
Abstract
Amino acids have crucial roles in central metabolism, both anabolic and catabolic. To elucidate these roles, steady-state concentrations of amino acids alone are insufficient, as each amino acid participates in multiple pathways and functions in a complex network, which can also be compartmentalized. Stable Isotope-Resolved Metabolomics (SIRM) is an approach that uses atom-resolved tracking of metabolites through biochemical transformations in cells, tissues, or whole organisms. Using different elemental stable isotopes to label multiple metabolite precursors makes it possible to resolve simultaneously the utilization of these precursors in a single experiment. Conversely, a single precursor labeled with two (or more) different elemental isotopes can trace the allocation of e.g. C and N atoms through the network. Such dual-label experiments however challenge the resolution of conventional mass spectrometers, which must distinguish the neutron mass differences among different elemental isotopes. This requires ultrahigh resolution Fourier transform mass spectrometry (UHR-FTMS). When combined with direct infusion nano-electrospray ion source (nano-ESI), UHR-FTMS can provide rapid, global, and quantitative analysis of all possible mass isotopologues of metabolites. Unfortunately, very low mass polar metabolites such as amino acids can be difficult to analyze by current models of UHR-FTMS, plus the high salt content present in typical cell or tissue polar extracts may cause unacceptable ion suppression for sources such as nano-ESI. Here we describe a modified method of ethyl chloroformate (ECF) derivatization of amino acids to enable rapid quantitative analysis of stable isotope labeled amino acids using nano-ESI UHR-FTMS. This method showed excellent linearity with quantifiable limits in the low nanomolar range represented in microgram quantities of biological specimens, which results in extracts with total analyte abundances in the low to sub-femtomole range. We have applied this method to profile amino acids and their labeling patterns in 13C and 2H doubly labeled PC9 cell extracts, cancerous and non-cancerous tissue extracts from a lung cancer patient and their protein hydrolysates as well as plasma extracts from mice fed with a liquid diet containing 13C6-glucose (Glc). The multi-element isotopologue distributions provided key insights into amino acid metabolism and intracellular pools in human lung cancer tissues in high detail. The 13C labeling of Asp and Glu revealed de novo synthesis of these amino acids from 13C6-Glc via the Krebs cycle, specifically the elevated level of 13C3-labeled Asp and Glu in cancerous versus non-cancerous lung tissues was consistent with enhanced pyruvate carboxylation. In addition, tracking the fate of double tracers, (13C6-Glc + 2H2-Gly or 13C6-Glc + 2H3-Ser) in PC9 cells clearly resolved pools of Ser and Gly synthesized de novo from 13C6-Glc (13C3-Ser and 13C2-Gly) versus Ser and Gly derived from external sources (2H3-Ser, 2H2-Gly). Moreover the complex 2H labeling patterns of the latter were results of Ser and Gly exchange through active Ser-Gly one-carbon metabolic pathway in PC9 cells.
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Affiliation(s)
- Ye Yang
- Center for Environmental and Systems Biochemistry, University of Kentucky, Lexington, KY, 40539, USA; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40539, USA
| | - Teresa W-M Fan
- Center for Environmental and Systems Biochemistry, University of Kentucky, Lexington, KY, 40539, USA; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40539, USA.
| | - Andrew N Lane
- Center for Environmental and Systems Biochemistry, University of Kentucky, Lexington, KY, 40539, USA; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40539, USA
| | - Richard M Higashi
- Center for Environmental and Systems Biochemistry, University of Kentucky, Lexington, KY, 40539, USA; Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40539, USA.
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Lane AN, Fan TWM. NMR-based Stable Isotope Resolved Metabolomics in systems biochemistry. Arch Biochem Biophys 2017; 628:123-131. [PMID: 28263717 DOI: 10.1016/j.abb.2017.02.009] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Revised: 02/24/2017] [Accepted: 02/27/2017] [Indexed: 01/23/2023]
Abstract
Metabolism is the basic activity of live cells, and monitoring the metabolic state provides a dynamic picture of the cells or tissues, and how they respond to external changes, for in disease or treatment with drugs. NMR is an extremely versatile analytical tool that can be applied to a wide range of biochemical problems. Despite its modest sensitivity its versatility make it an ideal tool for analyzing biochemical dynamics both in vitro and in vivo, especially when coupled with its isotope editing capabilities, from which isotope distributions can be readily determined. These are critical for any analyses of flux in live organisms. This review focuses on the utility of NMR spectroscopy in metabolomics, with an emphasis on NMR applications in stable isotope-enriched tracer research for elucidating biochemical pathways and networks with examples from nucleotide biochemistry. The knowledge gained from this area of research provides a ready link to genomic, epigenomic, transcriptomic, and proteomic information to achieve systems biochemical understanding of living cells and organisms.
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Affiliation(s)
- Andrew N Lane
- Center for Environmental Systems Biochemistry, University of Kentucky, USA; Department of Toxicology and Cancer Biology, University of Kentucky, USA.
| | - Teresa W-M Fan
- Center for Environmental Systems Biochemistry, University of Kentucky, USA; Department of Toxicology and Cancer Biology, University of Kentucky, USA
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34
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Metabolomics: A Primer. Trends Biochem Sci 2017; 42:274-284. [PMID: 28196646 DOI: 10.1016/j.tibs.2017.01.004] [Citation(s) in RCA: 229] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Revised: 11/13/2016] [Accepted: 01/12/2017] [Indexed: 02/08/2023]
Abstract
Metabolomics generates a profile of small molecules that are derived from cellular metabolism and can directly reflect the outcome of complex networks of biochemical reactions, thus providing insights into multiple aspects of cellular physiology. Technological advances have enabled rapid and increasingly expansive data acquisition with samples as small as single cells; however, substantial challenges in the field remain. In this primer we provide an overview of metabolomics, especially mass spectrometry (MS)-based metabolomics, which uses liquid chromatography (LC) for separation, and discuss its utilities and limitations. We identify and discuss several areas at the frontier of metabolomics. Our goal is to give the reader a sense of what might be accomplished when conducting a metabolomics experiment, now and in the near future.
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Selivanov VA, Benito A, Miranda A, Aguilar E, Polat IH, Centelles JJ, Jayaraman A, Lee PWN, Marin S, Cascante M. MIDcor, an R-program for deciphering mass interferences in mass spectra of metabolites enriched in stable isotopes. BMC Bioinformatics 2017; 18:88. [PMID: 28158972 PMCID: PMC5291980 DOI: 10.1186/s12859-017-1513-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Accepted: 01/31/2017] [Indexed: 12/26/2022] Open
Abstract
Background Tracing stable isotopes, such as 13C using various mass spectrometry (MS) methods provides a valuable information necessary for the study of biochemical processes in cells. However, extracting such information requires special care, such as a correction for naturally occurring isotopes, or overlapping mass spectra of various components of the cell culture medium. Developing a method for a correction of overlapping peaks is the primary objective of this study. Results Our computer program-MIDcor (free at https://github.com/seliv55/mid_correct) written in the R programming language, corrects the raw MS spectra both for the naturally occurring isotopes and for the overlapping of peaks corresponding to various substances. To this end, the mass spectra of unlabeled metabolites measured in two media are necessary: in a minimal medium containing only derivatized metabolites and chemicals for derivatization, and in a complete cell incubated medium. The MIDcor program calculates the difference (D) between the theoretical and experimentally measured spectra of metabolites containing only the naturally occurring isotopes. The result of comparison of D in the two media determines a way of deciphering the true spectra. (1) If D in the complete medium is greater than that in the minimal medium in at least one peak, then unchanged D is subtracted from the raw spectra of the labeled metabolite. (2) If D does not depend on the medium, then the spectrum probably overlaps with a derivatized fragment of the same metabolite, and D is modified proportionally to the metabolite labeling. The program automatically reaches a decision regarding the way of correction. For some metabolites/fragments in the case (2) D was found to decrease when the tested substance was 13C labeled, and this isotopic effect also can be corrected automatically, if the user provides a measured spectrum of the substance in which the 13C labeling is known a priori. Conclusion Using the developed program improves the reliability of stable isotope tracer data analysis. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1513-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Vitaly A Selivanov
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain. .,Institute of Biomedicine of the Universitat de Barcelona (IBUB) and Associated Unit to CSIC, Barcelona, Spain.
| | - Adrián Benito
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain.,Institute of Biomedicine of the Universitat de Barcelona (IBUB) and Associated Unit to CSIC, Barcelona, Spain
| | - Anibal Miranda
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain.,Institute of Biomedicine of the Universitat de Barcelona (IBUB) and Associated Unit to CSIC, Barcelona, Spain
| | - Esther Aguilar
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain.,Institute of Biomedicine of the Universitat de Barcelona (IBUB) and Associated Unit to CSIC, Barcelona, Spain
| | - Ibrahim Halil Polat
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain.,Institute of Biomedicine of the Universitat de Barcelona (IBUB) and Associated Unit to CSIC, Barcelona, Spain
| | - Josep J Centelles
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain.,Institute of Biomedicine of the Universitat de Barcelona (IBUB) and Associated Unit to CSIC, Barcelona, Spain
| | - Anusha Jayaraman
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain.,Institute of Biomedicine of the Universitat de Barcelona (IBUB) and Associated Unit to CSIC, Barcelona, Spain
| | - Paul W N Lee
- Department of Pediatrics, Harbor-UCLA Medical Center, Research and Education Institute, Torrance, CA, 90502, USA
| | - Silvia Marin
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain.,Institute of Biomedicine of the Universitat de Barcelona (IBUB) and Associated Unit to CSIC, Barcelona, Spain
| | - Marta Cascante
- Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain. .,Institute of Biomedicine of the Universitat de Barcelona (IBUB) and Associated Unit to CSIC, Barcelona, Spain.
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Dehairs J, Derua R, Rueda-Rincon N, Swinnen JV. Lipidomics in drug development. DRUG DISCOVERY TODAY. TECHNOLOGIES 2015; 13:33-38. [PMID: 26190681 DOI: 10.1016/j.ddtec.2015.03.002] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2014] [Revised: 03/25/2015] [Accepted: 03/26/2015] [Indexed: 06/04/2023]
Abstract
Numerous human pathologies, including common conditions such as obesity, diabetes, cardiovascular disease, cancer, inflammatory disease and neurodegeneration, involve changes in lipid metabolism. Likewise, a growing number of drugs are being developed that directly or indirectly affect lipid metabolic pathways. Instead of classical and cumbrous radiochemical analyses, lipid profiling by mass spectrometry (MS)-based lipidomics holds great potential as companion diagnostic in several steps along the drug development process. In this review we describe some typical lipidomics set-ups and illustrate how these technologies can be implemented in target discovery, compound screening, in vitro and in vivo preclinical testing, toxicity testing of drugs, and prediction and monitoring of response.
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Affiliation(s)
- Jonas Dehairs
- KU Leuven - University of Leuven, Department of Oncology, Laboratory of Lipid Metabolism and Cancer, B-3000 Leuven, Belgium
| | - Rita Derua
- KU Leuven - University of Leuven, Department of Cellular and Molecular Medicine, Laboratory of Protein Phosphorylation and Proteomics, B-3000 Leuven, Belgium
| | - Natalia Rueda-Rincon
- KU Leuven - University of Leuven, Department of Oncology, Laboratory of Lipid Metabolism and Cancer, B-3000 Leuven, Belgium
| | - Johannes V Swinnen
- KU Leuven - University of Leuven, Department of Oncology, Laboratory of Lipid Metabolism and Cancer, B-3000 Leuven, Belgium.
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Hines KM, Ford GC, Klaus KA, Irving BA, Ford BL, Johnson KL, Lanza IR, Nair KS. Application of high-resolution mass spectrometry to measure low abundance isotope enrichment in individual muscle proteins. Anal Bioanal Chem 2015; 407:4045-52. [PMID: 25832482 PMCID: PMC4539943 DOI: 10.1007/s00216-015-8641-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2014] [Revised: 03/11/2015] [Accepted: 03/12/2015] [Indexed: 10/23/2022]
Abstract
Stable isotope-labeled amino acids have long been used to measure the fractional synthesis rate of proteins, although the mass spectrometry platforms used for such analyses have changed throughout the years. More recently, tandem mass spectrometers such as triple quadrupoles have been accepted as the standard platform for enrichment measurement due to their sensitivity and the enhanced specificity offered by multiple reaction monitoring (MRM) experiments. The limit in the utility of such platforms for enrichment analysis occurs when measuring very low levels of enrichment from small amounts of sample, particularly proteins isolated from two-dimensional gel electrophoresis (2D-GE), where interference from contaminant ions impacts the sensitivity of the measurement. We therefore applied a high-resolution orbitrap mass spectrometer to the analysis of [ring-(13)C6]-phenylalanine enrichment in individual muscle proteins isolated with 2D-GE. Comparison of samples analyzed on both platforms revealed that the high-resolution MS has significantly improved sensitivity relative to the triple quadrupole MS at very low-level enrichments due to its ability to resolve interferences in the m/z dimension. At higher enrichment levels, enrichment measurements from the orbitrap platform showed significant correlation (R (2) > 0.5) with those of the triple quadrupole platform. Together, these results indicate that high-resolution MS platforms such as the orbitrap are not only as capable of performing isotope enrichment measurements as the more commonly preferred triple quadrupole instruments, but offer unparalleled advantages in terms of mass accuracy and sensitivity in the presence of similar-mass contaminants.
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Affiliation(s)
- Kelly M. Hines
- Metabolomics Resource Core, Mayo Clinic, Rochester, MN 55905, USA
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, MN 55905, USA
| | - G. Charles Ford
- Metabolomics Resource Core, Mayo Clinic, Rochester, MN 55905, USA
| | - Katherine A. Klaus
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, MN 55905, USA
| | - Brian A. Irving
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, MN 55905, USA
| | - Beverly L. Ford
- Metabolomics Resource Core, Mayo Clinic, Rochester, MN 55905, USA
| | - Kenneth L. Johnson
- Medical Genome Facility Proteomics Core, Mayo Clinic, Rochester, MN 55905
| | - Ian R. Lanza
- Metabolomics Resource Core, Mayo Clinic, Rochester, MN 55905, USA
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, MN 55905, USA
| | - K. Sreekumaran Nair
- Metabolomics Resource Core, Mayo Clinic, Rochester, MN 55905, USA
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, MN 55905, USA
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38
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Lane AN, Fan TWM. Regulation of mammalian nucleotide metabolism and biosynthesis. Nucleic Acids Res 2015; 43:2466-85. [PMID: 25628363 PMCID: PMC4344498 DOI: 10.1093/nar/gkv047] [Citation(s) in RCA: 563] [Impact Index Per Article: 62.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2014] [Revised: 12/21/2014] [Accepted: 01/12/2015] [Indexed: 12/25/2022] Open
Abstract
Nucleotides are required for a wide variety of biological processes and are constantly synthesized de novo in all cells. When cells proliferate, increased nucleotide synthesis is necessary for DNA replication and for RNA production to support protein synthesis at different stages of the cell cycle, during which these events are regulated at multiple levels. Therefore the synthesis of the precursor nucleotides is also strongly regulated at multiple levels. Nucleotide synthesis is an energy intensive process that uses multiple metabolic pathways across different cell compartments and several sources of carbon and nitrogen. The processes are regulated at the transcription level by a set of master transcription factors but also at the enzyme level by allosteric regulation and feedback inhibition. Here we review the cellular demands of nucleotide biosynthesis, their metabolic pathways and mechanisms of regulation during the cell cycle. The use of stable isotope tracers for delineating the biosynthetic routes of the multiple intersecting pathways and how these are quantitatively controlled under different conditions is also highlighted. Moreover, the importance of nucleotide synthesis for cell viability is discussed and how this may lead to potential new approaches to drug development in diseases such as cancer.
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Affiliation(s)
- Andrew N Lane
- Graduate Center of Toxicology and Markey Cancer Center, University of Kentucky, Biopharm Complex, 789 S. Limestone St, Lexington, KY 40536, USA
| | - Teresa W-M Fan
- Graduate Center of Toxicology and Markey Cancer Center, University of Kentucky, Biopharm Complex, 789 S. Limestone St, Lexington, KY 40536, USA
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