1
|
Nikolka F, Karagöz MS, Nassef MZ, Hiller K, Steinert M, Cordes T. The Virulence Factor Macrophage Infectivity Potentiator (Mip) Influences Branched-Chain Amino Acid Metabolism and Pathogenicity of Legionella pneumophila. Metabolites 2023; 13:834. [PMID: 37512541 PMCID: PMC10386555 DOI: 10.3390/metabo13070834] [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: 04/28/2023] [Revised: 06/15/2023] [Accepted: 07/03/2023] [Indexed: 07/30/2023] Open
Abstract
Legionella pneumophila (Lp) is a common etiological agent of bacterial pneumonia that causes Legionnaires' disease (LD). The bacterial membrane-associated virulence factor macrophage infectivity potentiator (Mip) exhibits peptidyl-prolyl-cis/trans-isomerase (PPIase) activity and contributes to the intra- and extracellular pathogenicity of Lp. Though Mip influences disease outcome, little is known about the metabolic consequences of altered Mip activity during infections. Here, we established a metabolic workflow and applied mass spectrometry approaches to decipher how Mip activity influences metabolism and pathogenicity. Impaired Mip activity in genetically engineered Lp strains decreases intracellular replication in cellular infection assays, confirming the contribution of Mip for Lp pathogenicity. We observed that genetic and chemical alteration of Mip using the PPIase inhibitors rapamycin and FK506 induces metabolic reprogramming in Lp, specifically branched-chain amino acid (BCAA) metabolism. Rapamycin also inhibits PPIase activity of mammalian FK506 binding proteins, and we observed that rapamycin induces a distinct metabolic signature in human macrophages compared to bacteria, suggesting potential involvement of Mip in normal bacteria and in infection. Our metabolic studies link Mip to alterations in BCAA metabolism and may help to decipher novel disease mechanisms associated with LD.
Collapse
Affiliation(s)
- Fabian Nikolka
- Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, 38106 Braunschweig, Germany
| | - Mustafa Safa Karagöz
- Institut für Mikrobiologie, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, 38106 Braunschweig, Germany
| | - Mohamed Zakaria Nassef
- Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, 38106 Braunschweig, Germany
| | - Karsten Hiller
- Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, 38106 Braunschweig, Germany
| | - Michael Steinert
- Institut für Mikrobiologie, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, 38106 Braunschweig, Germany
| | - Thekla Cordes
- Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, 38106 Braunschweig, Germany
- Research Group Cellular Metabolism in Infection, Helmholtz Centre for Infection Research, 38124 Braunschweig, Germany
| |
Collapse
|
2
|
Audano M, Pedretti S, Ligorio S, Giavarini F, Caruso D, Mitro N. Investigating metabolism by mass spectrometry: From steady state to dynamic view. JOURNAL OF MASS SPECTROMETRY : JMS 2021; 56:e4658. [PMID: 33084147 DOI: 10.1002/jms.4658] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 09/10/2020] [Accepted: 09/14/2020] [Indexed: 06/11/2023]
Abstract
Metabolism is the set of life-sustaining reactions in organisms. These biochemical reactions are organized in metabolic pathways, in which one metabolite is converted through a series of steps catalyzed by enzymes in another chemical compound. Metabolic reactions are categorized as catabolic, the breaking down of metabolites to produce energy, and/or anabolic, the synthesis of compounds that consume energy. The balance between catabolism of the preferential fuel substrate and anabolism defines the overall metabolism of a cell or tissue. Metabolomics is a powerful tool to gain new insights contributing to the identification of complex molecular mechanisms in the field of biomedical research, both basic and translational. The enormous potential of this kind of analyses consists of two key aspects: (i) the possibility of performing so-called targeted and untargeted experiments through which it is feasible to verify or formulate a hypothesis, respectively, and (ii) the opportunity to run either steady-state analyses to have snapshots of the metabolome at a given time under different experimental conditions or dynamic analyses through the use of labeled tracers. In this review, we will highlight the most important practical (e.g., different sample extraction approaches) and conceptual steps to consider for metabolomic analysis, describing also the main application contexts in which it is used. In addition, we will provide some insights into the most innovative approaches and progress in the field of data analysis and processing, highlighting how this part is essential for the proper extrapolation and interpretation of data.
Collapse
Affiliation(s)
- Matteo Audano
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Silvia Pedretti
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Simona Ligorio
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Flavio Giavarini
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Donatella Caruso
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Nico Mitro
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| |
Collapse
|
3
|
Cordes T, Metallo CM. Exploring the evolutionary roots and physiological function of itaconate. Curr Opin Biotechnol 2020; 68:144-150. [PMID: 33296743 DOI: 10.1016/j.copbio.2020.11.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 10/22/2020] [Accepted: 11/03/2020] [Indexed: 02/06/2023]
Abstract
New small molecules are continuing to emerge as metabolically derived regulators of cell function. Itaconate is a recent example where endogenous mammalian synthesis was demonstrated only seven years ago. Since then, interest in the biochemistry and therapeutic potential of itaconate has grown dramatically. Itaconate is an unsaturated dicarboxylic acid that has antimicrobial properties and modulates metabolic pathways throughout the cell. Naturally occurring mutations of enzymes involved in human itaconate synthesis and degradation pathways are associated with disease susceptibility and immunity. Here, we highlight recent discoveries on itaconate metabolism and discuss the relevance of its evolutionary origin to its function in mammals. We also consider the therapeutic relevance of itaconate metabolism and its derivatives for treating metabolic and inflammatory diseases.
Collapse
Affiliation(s)
- Thekla Cordes
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, 92093 La Jolla, CA, USA.
| | - Christian M Metallo
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, 92093 La Jolla, CA, USA.
| |
Collapse
|
4
|
Quek LE, Krycer JR, Ohno S, Yugi K, Fazakerley DJ, Scalzo R, Elkington SD, Dai Z, Hirayama A, Ikeda S, Shoji F, Suzuki K, Locasale JW, Soga T, James DE, Kuroda S. Dynamic 13C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin. iScience 2020; 23:100855. [PMID: 32058966 PMCID: PMC7005519 DOI: 10.1016/j.isci.2020.100855] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 11/26/2019] [Accepted: 01/15/2020] [Indexed: 12/22/2022] Open
Abstract
Cellular metabolism is dynamic, but quantifying non-steady metabolic fluxes by stable isotope tracers presents unique computational challenges. Here, we developed an efficient 13C-tracer dynamic metabolic flux analysis (13C-DMFA) framework for modeling central carbon fluxes that vary over time. We used B-splines to generalize the flux parameterization system and to improve the stability of the optimization algorithm. As proof of concept, we investigated how 3T3-L1 cultured adipocytes acutely metabolize glucose in response to insulin. Insulin rapidly stimulates glucose uptake, but intracellular pathways responded with differing speeds and magnitudes. Fluxes in lower glycolysis increased faster than those in upper glycolysis. Glycolysis fluxes rose disproportionally larger and faster than the tricarboxylic acid cycle, with lactate a primary glucose end product. The uncovered array of flux dynamics suggests that glucose catabolism is additionally regulated beyond uptake to help shunt glucose into appropriate pathways. This work demonstrates the value of using dynamic intracellular fluxes to understand metabolic function and pathway regulation.
Collapse
Affiliation(s)
- Lake-Ee Quek
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Mathematics and Statistics, The University of Sydney, Sydney, NSW 2006, Australia.
| | - James R Krycer
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
| | - Satoshi Ohno
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Katsuyuki Yugi
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan; YCI Laboratory for Trans-Omics, Young Chief Investigator Program, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045 Japan
| | - Daniel J Fazakerley
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
| | - Richard Scalzo
- Faculty of Engineering and Information Technologies, The University of Sydney, Sydney, NSW 2006, Australia
| | - Sarah D Elkington
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
| | - Ziwei Dai
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Duke University, Durham, NC 27710, USA
| | - Akiyoshi Hirayama
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan; AMED-CREST, AMED, 1-7-1 Otemachi, Chiyoda-Ku, Tokyo 100-0004, Japan
| | - Satsuki Ikeda
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan
| | - Futaba Shoji
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan
| | - Kumi Suzuki
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan
| | - Jason W Locasale
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Duke University, Durham, NC 27710, USA
| | - Tomoyoshi Soga
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan; AMED-CREST, AMED, 1-7-1 Otemachi, Chiyoda-Ku, Tokyo 100-0004, Japan
| | - David E James
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia; Sydney Medical School, The University of Sydney, Sydney, NSW 2006, Australia.
| | - Shinya Kuroda
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan; CREST, Japan Science and Technology Agency, Bunkyo-ku, Tokyo 113-0033, Japan.
| |
Collapse
|
5
|
Delfarah A, Parrish S, Junge JA, Yang J, Seo F, Li S, Mac J, Wang P, Fraser SE, Graham NA. Inhibition of nucleotide synthesis promotes replicative senescence of human mammary epithelial cells. J Biol Chem 2019; 294:10564-10578. [PMID: 31138644 DOI: 10.1074/jbc.ra118.005806] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Revised: 05/18/2019] [Indexed: 12/15/2022] Open
Abstract
Cellular senescence is a mechanism by which cells permanently withdraw from the cell cycle in response to stresses including telomere shortening, DNA damage, or oncogenic signaling. Senescent cells contribute to both age-related degeneration and hyperplastic pathologies, including cancer. In culture, normal human epithelial cells enter senescence after a limited number of cell divisions, known as replicative senescence. Here, to investigate how metabolic pathways regulate replicative senescence, we used LC-MS-based metabolomics to analyze senescent primary human mammary epithelial cells (HMECs). We did not observe significant changes in glucose uptake or lactate secretion in senescent HMECs. However, analysis of intracellular metabolite pool sizes indicated that senescent cells exhibit depletion of metabolites from nucleotide synthesis pathways. Furthermore, stable isotope tracing with 13C-labeled glucose or glutamine revealed a dramatic blockage of flux of these two metabolites into nucleotide synthesis pathways in senescent HMECs. To test whether cellular immortalization would reverse these observations, we expressed telomerase in HMECs. In addition to preventing senescence, telomerase expression maintained metabolic flux from glucose into nucleotide synthesis pathways. Finally, we investigated whether inhibition of nucleotide synthesis in proliferating HMECs is sufficient to induce senescence. In proliferating HMECs, both pharmacological and genetic inhibition of ribonucleotide reductase regulatory subunit M2 (RRM2), a rate-limiting enzyme in dNTP synthesis, induced premature senescence with concomitantly decreased metabolic flux from glucose into nucleotide synthesis. Taken together, our results suggest that nucleotide synthesis inhibition plays a causative role in the establishment of replicative senescence in HMECs.
Collapse
Affiliation(s)
- Alireza Delfarah
- From the Mork Family Department of Chemical Engineering and Materials Science
| | - Sydney Parrish
- From the Mork Family Department of Chemical Engineering and Materials Science
| | - Jason A Junge
- the Translational Imaging Center, Molecular and Computational Biology, and
| | - Jesse Yang
- From the Mork Family Department of Chemical Engineering and Materials Science
| | - Frances Seo
- From the Mork Family Department of Chemical Engineering and Materials Science
| | - Si Li
- From the Mork Family Department of Chemical Engineering and Materials Science
| | - John Mac
- From the Mork Family Department of Chemical Engineering and Materials Science
| | - Pin Wang
- From the Mork Family Department of Chemical Engineering and Materials Science
| | - Scott E Fraser
- the Translational Imaging Center, Molecular and Computational Biology, and
| | - Nicholas A Graham
- From the Mork Family Department of Chemical Engineering and Materials Science, .,the Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California 90089
| |
Collapse
|
6
|
Cordes T, Metallo CM. Quantifying Intermediary Metabolism and Lipogenesis in Cultured Mammalian Cells Using Stable Isotope Tracing and Mass Spectrometry. Methods Mol Biol 2019; 1978:219-241. [PMID: 31119666 DOI: 10.1007/978-1-4939-9236-2_14] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Metabolism plays a central role in virtually all diseases, including diabetes, cancer, and neurodegeneration. Detailed analysis is required to identify the specific metabolic pathways dysregulated in the context of a given disease or biological perturbation. Measurement of metabolite concentrations can provide some insights into altered pathway activity or enzyme function, but since most biochemicals are metabolized by various enzymes in distinct pathways within cells and tissues, these approaches are somewhat limited. By applying metabolic tracers to a biological system, one can visualize pathway-specific information depending on the tracer used and analytes measured. To this end, stable isotope tracers and mass spectrometry are emerging as important tools for the examination of metabolic pathways and fluxes in cultured mammalian cells and other systems. Here, we describe a detailed workflow for quantifying metabolic processes in mammalian cell cultures using stable isotopes and gas chromatography coupled to mass spectrometry (GC-MS). As a case study, we apply 13C isotopic labeled glucose and glutamine to a cancer cell line to quantify substrate utilization for TCA metabolism and lipogenesis. Guidelines are also provided for interpretation of data and considerations for application to other cell systems. Ultimately, this approach provides a robust and precise method for quantifying stable isotope labeling in metabolite pools that can be applied to diverse biological systems.
Collapse
Affiliation(s)
- Thekla Cordes
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Christian M Metallo
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
- Moores Cancer Center, University of California San Diego, La Jolla, CA, USA.
- Diabetes and Endocrinology Research Center, University of California San Diego, La Jolla, CA, USA.
- Institute of Engineering in Medicine, University of California San Diego, La Jolla, CA, USA.
| |
Collapse
|
7
|
Okahashi N, Maeda K, Kawana S, Iida J, Shimizu H, Matsuda F. Sugar phosphate analysis with baseline separation and soft ionization by gas chromatography-negative chemical ionization-mass spectrometry improves flux estimation of bidirectional reactions in cancer cells. Metab Eng 2018; 51:43-49. [PMID: 30176394 DOI: 10.1016/j.ymben.2018.08.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 07/31/2018] [Accepted: 08/29/2018] [Indexed: 11/16/2022]
Abstract
Precise measurement of sugar phosphates in glycolysis and the pentose phosphate (PP) pathway for 13C-metabolic flux analysis (13C-MFA) is needed to understand cancer-specific metabolism. Although various analytical methods have been proposed, analysis of sugar phosphates is challenging because of the structural similarity of various isomers and low intracellular abundance. In this study, gas chromatography-negative chemical ionization-mass spectrometry (GC-NCI-MS) is applied to sugar phosphate analysis with o-(2,3,4,5,6-pentafluorobenzyl) oxime (PFBO) and trimethylsilyl (TMS) derivatization. Optimization of the GC temperature gradient achieved baseline separation of sugar phosphates in 31 min. Mass spectra showed the predominant generation of fragment ions containing all carbon atoms in the sugar phosphate backbone. The limit of detection of pentose 5-phosphates and hexose 6-phosphates was 10 nM. The method was applied to 13C-labeling measurement of sugar phosphates for 13C-MFA of the MCF-7 human breast cancer cell line. 13C-labeling of sugar phosphates for 13C-MFA improved the estimation of the net flux and reversible flux of bidirectional reactions in glycolysis and the PP pathway.
Collapse
Affiliation(s)
- Nobuyuki Okahashi
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan.
| | - Kousuke Maeda
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan.
| | - Shuichi Kawana
- Analytical and Measuring Instruments Division, Shimadzu Corporation, 1 Nishinokyo Kuwabara-cho, Nakagyo-ku, Kyoto, Japan.
| | - Junko Iida
- Analytical and Measuring Instruments Division, Shimadzu Corporation, 1 Nishinokyo Kuwabara-cho, Nakagyo-ku, Kyoto, Japan; Osaka University Shimadzu Analytical Innovation Research Laboratory, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, Japan.
| | - Hiroshi Shimizu
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan.
| | - Fumio Matsuda
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan.
| |
Collapse
|
8
|
Badur MG, Metallo CM. Reverse engineering the cancer metabolic network using flux analysis to understand drivers of human disease. Metab Eng 2018; 45:95-108. [PMID: 29199104 PMCID: PMC5927620 DOI: 10.1016/j.ymben.2017.11.013] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Revised: 10/11/2017] [Accepted: 11/29/2017] [Indexed: 12/16/2022]
Abstract
Metabolic dysfunction has reemerged as an essential hallmark of tumorigenesis, and metabolic phenotypes are increasingly being integrated into pre-clinical models of disease. The complexity of these metabolic networks requires systems-level interrogation, and metabolic flux analysis (MFA) with stable isotope tracing present a suitable conceptual framework for such systems. Here we review efforts to elucidate mechanisms through which metabolism influences tumor growth and survival, with an emphasis on applications using stable isotope tracing and MFA. Through these approaches researchers can now quantify pathway fluxes in various in vitro and in vivo contexts to provide mechanistic insights at molecular and physiological scales respectively. Knowledge and discoveries in cancer models are paving the way toward applications in other biological contexts and disease models. In turn, MFA approaches will increasingly help to uncover new therapeutic opportunities that enhance human health.
Collapse
Affiliation(s)
- Mehmet G Badur
- Department of Bioengineering, University of California, San Diego, La Jolla, USA
| | - Christian M Metallo
- Department of Bioengineering, University of California, San Diego, La Jolla, USA; Moores Cancer Center, University of California, San Diego, La Jolla, USA; Diabetes and Endocrinology Research Center, University of California, San Diego, La Jolla, USA; Institute of Engineering in Medicine, University of California, San Diego, La Jolla, USA.
| |
Collapse
|
9
|
Papoutsakis ET, Titchener-Hooker N. Editorial overview: Biotechnology and bioprocess engineering. Curr Opin Chem Eng 2016. [DOI: 10.1016/j.coche.2016.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
|