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Britt EC, Qing X, Votava JA, Lika J, Wagner AS, Shen S, Arp NL, Khan H, Schieke SM, Fletcher CD, Huttenlocher A, Fan J. Activation induces shift in nutrient utilization that differentially impacts cell functions in human neutrophils. Proc Natl Acad Sci U S A 2024; 121:e2321212121. [PMID: 39284072 DOI: 10.1073/pnas.2321212121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 07/29/2024] [Indexed: 09/25/2024] Open
Abstract
Neutrophils utilize a variety of metabolic sources to support their crucial functions as the first responders in innate immunity. Here, through in vivo and ex vivo isotopic tracing, we examined the contributions of different nutrients to neutrophil metabolism under specific conditions. Human peripheral blood neutrophils, in contrast to a neutrophil-like cell line, rely on glycogen storage as a major metabolic source under resting state but rapidly switch to primarily using extracellular glucose upon activation with various stimuli. This shift is driven by a substantial increase in glucose uptake, enabled by rapidly increased GLUT1 on cell membrane, that dominates the simultaneous increase in gross glycogen cycling capacity. Shifts in nutrient utilization impact neutrophil functions in a function-specific manner: oxidative burst depends on glucose utilization, whereas NETosis and phagocytosis can be flexibly supported by either glucose or glycogen, and neutrophil migration and fungal control are enhanced by the shift from glycogen utilization to glucose utilization. This work provides a quantitative and dynamic understanding of fundamental features in neutrophil metabolism and elucidates how metabolic remodeling shapes neutrophil functions, which has broad health relevance.
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Affiliation(s)
- Emily C Britt
- Morgridge Institute for Research, Madison, WI 53715
- Nutrition and Metabolism Graduate Program, University of Wisconsin-Madison, Madison, WI 53706
| | - Xin Qing
- Morgridge Institute for Research, Madison, WI 53715
- Nutrition and Metabolism Graduate Program, University of Wisconsin-Madison, Madison, WI 53706
| | | | - Jorgo Lika
- Morgridge Institute for Research, Madison, WI 53715
- Cell and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI 53706
- University of Wisconsin Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792
| | - Andrew S Wagner
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI 53706
| | - Simone Shen
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI 53706
| | - Nicholas L Arp
- Morgridge Institute for Research, Madison, WI 53715
- Cell and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI 53706
- University of Wisconsin Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792
| | - Hamidullah Khan
- Department of Dermatology, University of Wisconsin-Madison, Madison, WI 53715
- Department of Dermatology, Georgetown University Medical Center Washington DC VA Medical Center, Washington, DC 20036
| | - Stefan M Schieke
- Department of Dermatology, University of Wisconsin-Madison, Madison, WI 53715
- Department of Dermatology, Georgetown University Medical Center Washington DC VA Medical Center, Washington, DC 20036
| | | | - Anna Huttenlocher
- Cell and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI 53706
- University of Wisconsin Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI 53706
- University of Wisconsin Carbone Cancer Center, Madison, WI 53792
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI 53792
| | - Jing Fan
- Morgridge Institute for Research, Madison, WI 53715
- Nutrition and Metabolism Graduate Program, University of Wisconsin-Madison, Madison, WI 53706
- Cell and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI 53706
- University of Wisconsin Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI 53706
- University of Wisconsin Carbone Cancer Center, Madison, WI 53792
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Pranzini E, Ippolito L, Pardella E, Giannoni E, Chiarugi P. Adapt and shape: metabolic features within the metastatic niche. Trends Endocrinol Metab 2024:S1043-2760(24)00197-8. [PMID: 39122599 DOI: 10.1016/j.tem.2024.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/16/2024] [Accepted: 07/19/2024] [Indexed: 08/12/2024]
Abstract
The success of disseminating cancer cells (DTCs) at specific metastatic sites is influenced by several metabolic factors. Even before DTCs arrival, metabolic conditioning from the primary tumor participates in creating a favorable premetastatic niche at distant organs. In addition, DTCs adjust their metabolism to better survive along the metastatic journey and successfully colonize their ultimate destination. However, the idea that the environment of the target organs may metabolically impact the metastatic fate is often underestimated. Here, we review the coexistence of two distinct strategies by which cancer cells shape and/or adapt to the metabolic profile of colonized tissues, ultimately creating a proper soil for their seeding and proliferation.
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Affiliation(s)
- Erica Pranzini
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Viale Morgagni, 50, 50134 Firenze, (FI), Italy
| | - Luigi Ippolito
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Viale Morgagni, 50, 50134 Firenze, (FI), Italy
| | - Elisa Pardella
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Viale Morgagni, 50, 50134 Firenze, (FI), Italy
| | - Elisa Giannoni
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Viale Morgagni, 50, 50134 Firenze, (FI), Italy
| | - Paola Chiarugi
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Viale Morgagni, 50, 50134 Firenze, (FI), Italy.
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Verheijen FWM, Tran TNM, Chang J, Broere F, Zaal EA, Berkers CR. Deciphering metabolic crosstalk in context: lessons from inflammatory diseases. Mol Oncol 2024; 18:1759-1776. [PMID: 38275212 PMCID: PMC11223610 DOI: 10.1002/1878-0261.13588] [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: 07/17/2023] [Revised: 11/02/2023] [Accepted: 01/15/2024] [Indexed: 01/27/2024] Open
Abstract
Metabolism plays a crucial role in regulating the function of immune cells in both health and disease, with altered metabolism contributing to the pathogenesis of cancer and many inflammatory diseases. The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization of cells in tissues should be taken into account when studying immunometabolism. Here, we highlight challenges of investigating metabolic communication. Additionally, we review the capabilities and limitations of current technologies for studying metabolism in inflamed microenvironments, including single-cell omics techniques, flow cytometry-based methods (Met-Flow, single-cell energetic metabolism by profiling translation inhibition (SCENITH)), cytometry by time of flight (CyTOF), cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), and mass spectrometry imaging. Considering the importance of metabolism in regulating immune cells in diseased states, we also discuss the applications of metabolomics in clinical research, as well as some hurdles to overcome to implement these techniques in standard clinical practice. Finally, we provide a flowchart to assist scientists in designing effective strategies to unravel immunometabolism in disease-relevant contexts.
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Affiliation(s)
- Fenne W. M. Verheijen
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
- Division of Infectious Diseases and Immunology, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
| | - Thi N. M. Tran
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular ResearchUtrecht UniversityThe Netherlands
| | - Jung‐Chin Chang
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
| | - Femke Broere
- Division of Infectious Diseases and Immunology, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
| | - Esther A. Zaal
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
| | - Celia R. Berkers
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
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Tian C, Wang Q, Gao T, Sun H, Li J, He Y. Effects of Low-Salinity Stress on Histology and Metabolomics in the Intestine of Fenneropenaeus chinensis. Animals (Basel) 2024; 14:1880. [PMID: 38997992 PMCID: PMC11240639 DOI: 10.3390/ani14131880] [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: 05/15/2024] [Revised: 06/11/2024] [Accepted: 06/14/2024] [Indexed: 07/14/2024] Open
Abstract
Metabolomics has been used extensively to identify crucial molecules and biochemical effects induced by environmental factors. To understand the effects of acute low-salinity stress on Fenneropenaeus chinensis, intestinal histological examination and untargeted metabonomic analysis of F. chinensis were performed after exposure to a salinity of 15 ppt for 3, 7, and 14 d. The histological examination revealed that acute stress resulted in most epithelial cells rupturing, leading to the dispersion of nuclei in the intestinal lumen after 14 days. Metabolomics analysis identified numerous differentially expressed metabolites (DEMs) at different time points after exposure to low-salinity stress, in which some DEMs were steadily downregulated at the early stage of stress and then gradually upregulated. We further screened 14 overlapping DEMs, in which other DEMs decreased significantly during low-salinity stress, apart from L-palmitoylcarnitine and vitamin A, with enrichments in phenylalanine, tyrosine and tryptophan biosynthesis, fatty acid and retinol metabolism, and ABC transporters. ABC transporters exhibit significant abnormalities and play a vital role in low-salinity stress. This study provides valuable insights into the molecular mechanisms underlying the responses of F. chinensis to acute salinity stress.
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Affiliation(s)
- Caijuan Tian
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China
- Jiangsu Key Laboratory of Marine Biotechnology, Jiangsu Ocean University, Lianyungang 222005, China
| | - Qiong Wang
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao 266237, China
| | - Tian Gao
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China
- College of Fisheries and Life Science, Dalian Ocean University, Dalian 116023, China
| | - Huarui Sun
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China
- College of Fisheries and Life Science, Dalian Ocean University, Dalian 116023, China
| | - Jitao Li
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao 266237, China
| | - Yuying He
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao 266237, China
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Hilovsky D, Hartsell J, Young JD, Liu X. Stable Isotope Tracing Analysis in Cancer Research: Advancements and Challenges in Identifying Dysregulated Cancer Metabolism and Treatment Strategies. Metabolites 2024; 14:318. [PMID: 38921453 PMCID: PMC11205609 DOI: 10.3390/metabo14060318] [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: 05/07/2024] [Revised: 05/13/2024] [Accepted: 05/28/2024] [Indexed: 06/27/2024] Open
Abstract
Metabolic reprogramming is a hallmark of cancer, driving the development of therapies targeting cancer metabolism. Stable isotope tracing has emerged as a widely adopted tool for monitoring cancer metabolism both in vitro and in vivo. Advances in instrumentation and the development of new tracers, metabolite databases, and data analysis tools have expanded the scope of cancer metabolism studies across these scales. In this review, we explore the latest advancements in metabolic analysis, spanning from experimental design in stable isotope-labeling metabolomics to sophisticated data analysis techniques. We highlight successful applications in cancer research, particularly focusing on ongoing clinical trials utilizing stable isotope tracing to characterize disease progression, treatment responses, and potential mechanisms of resistance to anticancer therapies. Furthermore, we outline key challenges and discuss potential strategies to address them, aiming to enhance our understanding of the biochemical basis of cancer metabolism.
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Affiliation(s)
- Dalton Hilovsky
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC 27695, USA; (D.H.); (J.H.)
| | - Joshua Hartsell
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC 27695, USA; (D.H.); (J.H.)
| | - Jamey D. Young
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN 37212, USA
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37212, USA
| | - Xiaojing Liu
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC 27695, USA; (D.H.); (J.H.)
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Shan B, Guo C, Zhou H, Chen J. Tanshinone IIA alleviates pulmonary fibrosis by modulating glutamine metabolic reprogramming based on [U- 13C 5]-glutamine metabolic flux analysis. J Adv Res 2024:S2090-1232(24)00172-3. [PMID: 38697470 DOI: 10.1016/j.jare.2024.04.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 03/28/2024] [Accepted: 04/28/2024] [Indexed: 05/05/2024] Open
Abstract
INTRODUCTION Glutamine metabolic reprogramming, mediated by glutaminase (GLS), is an important signal during pulmonary fibrosis (PF) progression. Tanshinone IIA (Tan IIA) is a naturally lipophilic diterpene with antioxidant and antifibrotic properties. However, the potential mechanisms of Tan IIA for regulating glutamine metabolic reprogramming are not yet clear. OBJECTIVES This study aimed was to evaluate the role of Tan IIA in intervening in glutamine metabolic reprogramming to exert anti-PF and to explore the potential new mechanisms of metabolic regulation. METHODS Fibrotic characteristics was detected via immunofluorescence and western blotting analysis. Cell proliferation was examined with EdU Assay. Cell metabolites were labeled by using stable isotope [U-13C5]-glutamine. By utilizing 100% 13C glutamine tracers and employing network analysis to investigate the activation of metabolic pathways in fibroblasts, as well as evaluating the impact of Tan IIA on these pathways, we accurately quantified the absolute flux of glutaminolysis, proline synthesis, and the TCA cycle pathway using isotopomer network compartmental analysis (INCA), a user-friendly software tool for 13C metabolic flux analysis (13C-MFA). Molecular docking was used for identifying the binding of Tan IIA with target protein. RESULTS Tan IIA ameliorate TGF-β1-induced myofibroblast proliferation, reduce collagen I and III and α-SMA protein expression in MRC-5 and NIH-3T3 cells. Furthermore, Tan IIA regulate mitochondrial energy metabolism by modulating TGF-β1-stimulated glutamine metabolic reprogramming in NIH-3T3 cells and inhibiting GLS1 expression, which reduced the metabolic flux of glutamine into mitochondria in myofibroblasts, and also targeted inhibited the expression of Δ1-pyrroline-5-carboxylate synthase (P5CS), P5C reductase 1 (PYCR1), and phosphoserine aminotransferase 1 (PSAT1), and reduced proline hydroxylation and blocked the collagen synthesis pathway. CONCLUSION Tan IIA reverses glutamine metabolic reprogramming, reduces mitochondrial energy expenditure, and inhibits collagen matrix synthesis by modulating potential targets in glutamine metabolism. This novel perspective sheds light on the essential role of glutamine metabolic reprogramming in PF.
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Affiliation(s)
- Baixi Shan
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China; Department of Pharmacognosy, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Congying Guo
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China; Department of Pharmacognosy, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Haoyan Zhou
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China; Department of Pharmacognosy, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Jun Chen
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China; Department of Pharmacognosy, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China.
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7
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Lu W, McBride MJ, Lee WD, Xing X, Xu X, Li X, Oschmann AM, Shen Y, Bartman C, Rabinowitz JD. Selected Ion Monitoring for Orbitrap-Based Metabolomics. Metabolites 2024; 14:184. [PMID: 38668312 PMCID: PMC11051813 DOI: 10.3390/metabo14040184] [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: 02/14/2024] [Revised: 03/08/2024] [Accepted: 03/18/2024] [Indexed: 04/28/2024] Open
Abstract
Orbitrap mass spectrometry in full scan mode enables the simultaneous detection of hundreds of metabolites and their isotope-labeled forms. Yet, sensitivity remains limiting for many metabolites, including low-concentration species, poor ionizers, and low-fractional-abundance isotope-labeled forms in isotope-tracing studies. Here, we explore selected ion monitoring (SIM) as a means of sensitivity enhancement. The analytes of interest are enriched in the orbitrap analyzer by using the quadrupole as a mass filter to select particular ions. In tissue extracts, SIM significantly enhances the detection of ions of low intensity, as indicated by improved signal-to-noise (S/N) ratios and measurement precision. In addition, SIM improves the accuracy of isotope-ratio measurements. SIM, however, must be deployed with care, as excessive accumulation in the orbitrap of similar m/z ions can lead, via space-charge effects, to decreased performance (signal loss, mass shift, and ion coalescence). Ion accumulation can be controlled by adjusting settings including injection time and target ion quantity. Overall, we suggest using a full scan to ensure broad metabolic coverage, in tandem with SIM, for the accurate quantitation of targeted low-intensity ions, and provide methods deploying this approach to enhance metabolome coverage.
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Affiliation(s)
- Wenyun Lu
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, Princeton University, Princeton, NJ 08544, USA
| | - Matthew J. McBride
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
- Department of Chemical Biology, Ernest Mario School of Pharmacy, Rutgers University, Piscataway, NJ 08854, USA
| | - Won Dong Lee
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
| | - Xi Xing
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, Princeton University, Princeton, NJ 08544, USA
| | - Xincheng Xu
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Xi Li
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, Princeton University, Princeton, NJ 08544, USA
| | - Anna M. Oschmann
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Yihui Shen
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, Princeton University, Princeton, NJ 08544, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Caroline Bartman
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
- Department of Pharmacology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Joshua D. Rabinowitz
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; (W.L.)
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, Princeton University, Princeton, NJ 08544, USA
- Rutgers Cancer Institute of New Jersey (CINJ), Rutgers University, New Brunswick, NJ 08901, USA
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ 08544, USA
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Peper CJ, Kilgore MD, Jiang Y, Xiu Y, Xia W, Wang Y, Shi M, Zhou D, Dumont AS, Wang X, Liu N. Tracing the path of disruption: 13C isotope applications in traumatic brain injury-induced metabolic dysfunction. CNS Neurosci Ther 2024; 30:e14693. [PMID: 38544365 PMCID: PMC10973562 DOI: 10.1111/cns.14693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 02/25/2024] [Accepted: 03/12/2024] [Indexed: 05/14/2024] Open
Abstract
Cerebral metabolic dysfunction is a critical pathological hallmark observed in the aftermath of traumatic brain injury (TBI), as extensively documented in clinical investigations and experimental models. An in-depth understanding of the bioenergetic disturbances that occur following TBI promises to reveal novel therapeutic targets, paving the way for the timely development of interventions to improve patient outcomes. The 13C isotope tracing technique represents a robust methodological advance, harnessing biochemical quantification to delineate the metabolic trajectories of isotopically labeled substrates. This nuanced approach enables real-time mapping of metabolic fluxes, providing a window into the cellular energetic state and elucidating the perturbations in key metabolic circuits. By applying this sophisticated tool, researchers can dissect the complexities of bioenergetic networks within the central nervous system, offering insights into the metabolic derangements specific to TBI pathology. Embraced by both animal studies and clinical research, 13C isotope tracing has bolstered our understanding of TBI-induced metabolic dysregulation. This review synthesizes current applications of isotope tracing and its transformative potential in evaluating and addressing the metabolic sequelae of TBI.
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Affiliation(s)
- Charles J. Peper
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
| | - Mitchell D. Kilgore
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
| | - Yinghua Jiang
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
| | - Yuwen Xiu
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
| | - Winna Xia
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
| | - Yingjie Wang
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
| | - Mengxuan Shi
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
| | - Di Zhou
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
| | - Aaron S. Dumont
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
| | - Xiaoying Wang
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
- Neuroscience Program, Tulane Brain InstituteTulane UniversityNew OrleansLouisianaUSA
| | - Ning Liu
- Clinical Neuroscience Research Center, Departments of Neurosurgery and NeurologyTulane University School of MedicineNew OrleansLouisianaUSA
- Neuroscience Program, Tulane Brain InstituteTulane UniversityNew OrleansLouisianaUSA
- Tulane University Translational Sciences InstituteNew OrleansLouisianaUSA
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Andreyev AY, Yang H, Doulias P, Dolatabadi N, Zhang X, Luevanos M, Blanco M, Baal C, Putra I, Nakamura T, Ischiropoulos H, Tannenbaum SR, Lipton SA. Metabolic Bypass Rescues Aberrant S-nitrosylation-Induced TCA Cycle Inhibition and Synapse Loss in Alzheimer's Disease Human Neurons. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2306469. [PMID: 38235614 PMCID: PMC10966553 DOI: 10.1002/advs.202306469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 12/29/2023] [Indexed: 01/19/2024]
Abstract
In Alzheimer's disease (AD), dysfunctional mitochondrial metabolism is associated with synaptic loss, the major pathological correlate of cognitive decline. Mechanistic insight for this relationship, however, is still lacking. Here, comparing isogenic wild-type and AD mutant human induced pluripotent stem cell (hiPSC)-derived cerebrocortical neurons (hiN), evidence is found for compromised mitochondrial energy in AD using the Seahorse platform to analyze glycolysis and oxidative phosphorylation (OXPHOS). Isotope-labeled metabolic flux experiments revealed a major block in activity in the tricarboxylic acid (TCA) cycle at the α-ketoglutarate dehydrogenase (αKGDH)/succinyl coenzyme-A synthetase step, metabolizing α-ketoglutarate to succinate. Associated with this block, aberrant protein S-nitrosylation of αKGDH subunits inhibited their enzyme function. This aberrant S-nitrosylation is documented not only in AD-hiN but also in postmortem human AD brains versus controls, as assessed by two separate unbiased mass spectrometry platforms using both SNOTRAP identification of S-nitrosothiols and chemoselective-enrichment of S-nitrosoproteins. Treatment with dimethyl succinate, a cell-permeable derivative of a TCA substrate downstream to the block, resulted in partial rescue of mitochondrial bioenergetic function as well as reversal of synapse loss in AD-hiN. These findings have therapeutic implications that rescue of mitochondrial energy metabolism can ameliorate synaptic loss in hiPSC-based models of AD.
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Affiliation(s)
- Alexander Y. Andreyev
- Department of Molecular Medicine and Neurodegeneration New Medicines CenterThe Scripps Research InstituteLa JollaCA92037USA
| | - Hongmei Yang
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMA02139USA
- Northeast Asia Institute of Chinese MedicineChangchun University of Chinese MedicineChangchun130021China
- Present address:
The Public Experiment CenterChangchun University of Chinese MedicineChangchun130117China
| | - Paschalis‐Thomas Doulias
- Children's Hospital of Philadelphia Research Institute and Departments of Pediatrics and PharmacologyRaymond and Ruth Perelman School of Medicine at the University of PennsylvaniaPhiladelphiaPA19104USA
- Department of Chemistry and Institute of BiosciencesUniversity Research Center of IoanninaUniversity of IoanninaIoannina45110Greece
| | - Nima Dolatabadi
- Department of Molecular Medicine and Neurodegeneration New Medicines CenterThe Scripps Research InstituteLa JollaCA92037USA
| | - Xu Zhang
- Department of Molecular Medicine and Neurodegeneration New Medicines CenterThe Scripps Research InstituteLa JollaCA92037USA
| | - Melissa Luevanos
- Department of Molecular Medicine and Neurodegeneration New Medicines CenterThe Scripps Research InstituteLa JollaCA92037USA
| | - Mayra Blanco
- Department of Molecular Medicine and Neurodegeneration New Medicines CenterThe Scripps Research InstituteLa JollaCA92037USA
| | - Christine Baal
- Department of Molecular Medicine and Neurodegeneration New Medicines CenterThe Scripps Research InstituteLa JollaCA92037USA
| | - Ivan Putra
- Department of Molecular Medicine and Neurodegeneration New Medicines CenterThe Scripps Research InstituteLa JollaCA92037USA
| | - Tomohiro Nakamura
- Department of Molecular Medicine and Neurodegeneration New Medicines CenterThe Scripps Research InstituteLa JollaCA92037USA
| | - Harry Ischiropoulos
- Children's Hospital of Philadelphia Research Institute and Departments of Pediatrics and PharmacologyRaymond and Ruth Perelman School of Medicine at the University of PennsylvaniaPhiladelphiaPA19104USA
| | - Steven R. Tannenbaum
- Northeast Asia Institute of Chinese MedicineChangchun University of Chinese MedicineChangchun130021China
| | - Stuart A. Lipton
- Department of Molecular Medicine and Neurodegeneration New Medicines CenterThe Scripps Research InstituteLa JollaCA92037USA
- Department of NeurosciencesSchool of MedicineUniversity of California at San DiegoLa JollaCA92093USA
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10
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Chuang YM, Tzeng SF, Ho PC, Tsai CH. Immunosurveillance encounters cancer metabolism. EMBO Rep 2024; 25:471-488. [PMID: 38216787 PMCID: PMC10897436 DOI: 10.1038/s44319-023-00038-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 12/02/2023] [Accepted: 12/12/2023] [Indexed: 01/14/2024] Open
Abstract
Tumor cells reprogram nutrient acquisition and metabolic pathways to meet their energetic, biosynthetic, and redox demands. Similarly, metabolic processes in immune cells support host immunity against cancer and determine differentiation and fate of leukocytes. Thus, metabolic deregulation and imbalance in immune cells within the tumor microenvironment have been reported to drive immune evasion and to compromise therapeutic outcomes. Interestingly, emerging evidence indicates that anti-tumor immunity could modulate tumor heterogeneity, aggressiveness, and metabolic reprogramming, suggesting that immunosurveillance can instruct cancer progression in multiple dimensions. This review summarizes our current understanding of how metabolic crosstalk within tumors affects immunogenicity of tumor cells and promotes cancer progression. Furthermore, we explain how defects in the metabolic cascade can contribute to developing dysfunctional immune responses against cancers and discuss the contribution of immunosurveillance to these defects as a feedback mechanism. Finally, we highlight ongoing clinical trials and new therapeutic strategies targeting cellular metabolism in cancer.
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Affiliation(s)
- Yu-Ming Chuang
- Department of Fundamental Oncology, University of Lausanne, Lausanne, Switzerland
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland
| | - Sheue-Fen Tzeng
- Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan
| | - Ping-Chih Ho
- Department of Fundamental Oncology, University of Lausanne, Lausanne, Switzerland.
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.
| | - Chin-Hsien Tsai
- Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan.
- Department and Graduate Institute of Biochemistry, National Defense Medical Center, Taipei, Taiwan.
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11
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Altea-Manzano P, Fendt SM, Vera-Ramirez L. 13C Tracer Analysis and Metabolomics in Dormant Cancer Cells. Methods Mol Biol 2024; 2811:195-206. [PMID: 39037660 DOI: 10.1007/978-1-0716-3882-8_15] [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] [Indexed: 07/23/2024]
Abstract
Over the last two decades, major advances in the field of tumor dormancy have been made. Yet, it is not completely understood how dormant disseminated tumor cells survive and transition to a proliferative state to generate a metastatic lesion. On the other hand, metabolic rewiring has been shown to influence metastasis development through the modulation of both intracellular signaling and the crosstalk between metastatic cells and their microenvironment. Thus, studying the metabolic features of dormant disseminated tumor cells has gained importance in understanding the dormancy process. Here, we describe a method to perform metabolomics and 13C tracer analysis in 3D cultures of dormant breast cancer cells.
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Affiliation(s)
- Patricia Altea-Manzano
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium
- Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
- Laboratory of Metabolic Regulation and Signaling in Cancer, Andalusian Molecular Biology and Regenerative Medicine Centre (CABIMER) - Spanish National Research Council (CSIC), Seville, Spain
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.
- Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium.
| | - Laura Vera-Ramirez
- Department of Genomic Medicine, GENYO, Centre for Genomics and Oncology, Pfizer-University of Granada and Andalusian Regional Government, PTS, Granada, Spain.
- Department of Physiology, Institute of Nutrition and Food Technology "José Mataix Verdú", Biomedical Research Center, University of Granada, Granada, Spain.
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12
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Lakhani A, Kang DH, Kang YE, Park JO. Toward Systems-Level Metabolic Analysis in Endocrine Disorders and Cancer. Endocrinol Metab (Seoul) 2023; 38:619-630. [PMID: 37989266 PMCID: PMC10764991 DOI: 10.3803/enm.2023.1814] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 10/27/2023] [Accepted: 11/01/2023] [Indexed: 11/23/2023] Open
Abstract
Metabolism is a dynamic network of biochemical reactions that support systemic homeostasis amidst changing nutritional, environmental, and physical activity factors. The circulatory system facilitates metabolite exchange among organs, while the endocrine system finely tunes metabolism through hormone release. Endocrine disorders like obesity, diabetes, and Cushing's syndrome disrupt this balance, contributing to systemic inflammation and global health burdens. They accompany metabolic changes on multiple levels from molecular interactions to individual organs to the whole body. Understanding how metabolic fluxes relate to endocrine disorders illuminates the underlying dysregulation. Cancer is increasingly considered a systemic disorder because it not only affects cells in localized tumors but also the whole body, especially in metastasis. In tumorigenesis, cancer-specific mutations and nutrient availability in the tumor microenvironment reprogram cellular metabolism to meet increased energy and biosynthesis needs. Cancer cachexia results in metabolic changes to other organs like muscle, adipose tissue, and liver. This review explores the interplay between the endocrine system and systems-level metabolism in health and disease. We highlight metabolic fluxes in conditions like obesity, diabetes, Cushing's syndrome, and cancers. Recent advances in metabolomics, fluxomics, and systems biology promise new insights into dynamic metabolism, offering potential biomarkers, therapeutic targets, and personalized medicine.
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Affiliation(s)
- Aliya Lakhani
- Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA, USA
| | - Da Hyun Kang
- Department of Internal Medicine, Chungnam National University College of Medicine, Daejeon, Korea
| | - Yea Eun Kang
- Department of Internal Medicine, Chungnam National University College of Medicine, Daejeon, Korea
| | - Junyoung O. Park
- Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA, USA
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13
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Britt EC, Qing X, Votava JA, Lika J, Wagner A, Shen S, Arp NL, Khan H, Schieke SM, Fletcher CD, Huttenlocher A, Fan J. Activation induces shift in nutrient utilization that differentially impacts cell functions in human neutrophils. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.25.559385. [PMID: 37808750 PMCID: PMC10557599 DOI: 10.1101/2023.09.25.559385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Neutrophils - the first responders in innate immunity - perform a variety of effector functions associated with specific metabolic demand. To maintain fitness and support functions, neutrophils have been found to utilize extracellular glucose, intracellular glycogen, and other alternative substrates. However, the quantitative contribution of these nutrients under specific conditions and the relative dependence of various cell functions on specific nutrients remain unclear. Here, using ex vivo and in vivo isotopic tracing, we reveal that under resting condition, human peripheral blood neutrophils, in contrast to in vitro cultured human neutrophil-like cell lines, rely on glycogen as a major direct source of glycolysis and pentose phosphate pathway. Upon activation with a diversity of stimuli, neutrophils undergo a significant and often rapid nutrient preference shift, with glucose becoming the dominant metabolic source thanks to a multi-fold increase in glucose uptake mechanistically mediated by the phosphorylation and translocation of GLUT1. At the same time, cycling between gross glycogenesis and glycogenolysis is also substantially increased, while the net flux favors sustained or increased glycogen storage. The shift in nutrient utilization impacts neutrophil functions in a function-specific manner. The activation of oxidative burst specifically depends on the utilization of extracellular glucose rather than glycogen. In contrast, the release of neutrophil traps can be flexibly supported by either glucose or glycogen. Neutrophil migration and fungal control is promoted by the shift away from glycogen utilization. Together, these results quantitatively characterize fundamental features of neutrophil metabolism and elucidate how metabolic remodeling shapes neutrophil functions upon activation.
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Affiliation(s)
- Emily C. Britt
- Morgridge Institute for Research, Madison, WI, USA
- Department of Nutritional Sciences, University of Wisconsin–Madison, Madison, WI, USA
| | - Xin Qing
- Morgridge Institute for Research, Madison, WI, USA
- Department of Nutritional Sciences, University of Wisconsin–Madison, Madison, WI, USA
| | | | - Jorgo Lika
- Morgridge Institute for Research, Madison, WI, USA
- Cell and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA
- University of Wisconsin Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792
| | - Andrew Wagner
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI, USA
| | - Simone Shen
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI, USA
| | - Nicholas L. Arp
- Morgridge Institute for Research, Madison, WI, USA
- Cell and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA
- University of Wisconsin Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792
| | - Hamidullah Khan
- Department of Dermatology, University of Wisconsin-Madison, Madison, WI, USA. Department of Dermatology, Georgetown University Medical Center and Washington DC VA Medical Center, Washington, D.C., USA
| | - Stefan M. Schieke
- Department of Dermatology, University of Wisconsin-Madison, Madison, WI, USA. Department of Dermatology, Georgetown University Medical Center and Washington DC VA Medical Center, Washington, D.C., USA
| | | | - Anna Huttenlocher
- Cell and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA
- University of Wisconsin Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI, USA
- Comparative Biomedical Sciences Graduate Program, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | - Jing Fan
- Morgridge Institute for Research, Madison, WI, USA
- Department of Nutritional Sciences, University of Wisconsin–Madison, Madison, WI, USA
- Cell and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA
- University of Wisconsin Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792
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14
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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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15
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Doulias PT, Yang H, Andreyev AY, Dolatabadi N, Scott H, K Raspur C, Patel PR, Nakamura T, Tannenbaum SR, Ischiropoulos H, Lipton SA. S-Nitrosylation-mediated dysfunction of TCA cycle enzymes in synucleinopathy studied in postmortem human brains and hiPSC-derived neurons. Cell Chem Biol 2023; 30:965-975.e6. [PMID: 37478858 PMCID: PMC10530441 DOI: 10.1016/j.chembiol.2023.06.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 03/16/2023] [Accepted: 06/16/2023] [Indexed: 07/23/2023]
Abstract
A causal relationship between mitochondrial metabolic dysfunction and neurodegeneration has been implicated in synucleinopathies, including Parkinson disease (PD) and Lewy body dementia (LBD), but underlying mechanisms are not fully understood. Here, using human induced pluripotent stem cell (hiPSC)-derived neurons with mutation in the gene encoding α-synuclein (αSyn), we report the presence of aberrantly S-nitrosylated proteins, including tricarboxylic acid (TCA) cycle enzymes, resulting in activity inhibition assessed by carbon-labeled metabolic flux experiments. This inhibition principally affects α-ketoglutarate dehydrogenase/succinyl coenzyme-A synthetase, metabolizing α-ketoglutarate to succinate. Notably, human LBD brain manifests a similar pattern of aberrantly S-nitrosylated TCA enzymes, indicating the pathophysiological relevance of these results. Inhibition of mitochondrial energy metabolism in neurons is known to compromise dendritic length and synaptic integrity, eventually leading to neuronal cell death. Our evidence indicates that aberrant S-nitrosylation of TCA cycle enzymes contributes to this bioenergetic failure.
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Affiliation(s)
- Paschalis-Thomas Doulias
- Children's Hospital of Philadelphia Departments of Pediatrics and Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Chemistry and University Research Center of Ioannina, University of Ioannina, 45110 Ioannina, Greece
| | - Hongmei Yang
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Changchun University of Chinese Medicine, Changchun 130021, China
| | - Alexander Y Andreyev
- Neurodegeneration New Medicines Center, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Nima Dolatabadi
- Neurodegeneration New Medicines Center, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Henry Scott
- Neurodegeneration New Medicines Center, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Charlene K Raspur
- Neurodegeneration New Medicines Center, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Parth R Patel
- Neurodegeneration New Medicines Center, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Tomohiro Nakamura
- Neurodegeneration New Medicines Center, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Steven R Tannenbaum
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Harry Ischiropoulos
- Children's Hospital of Philadelphia Departments of Pediatrics and Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Stuart A Lipton
- Neurodegeneration New Medicines Center, The Scripps Research Institute, La Jolla, CA 92037, USA; Department of Neurosciences, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
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16
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Leitner BP, Lee WD, Zhu W, Zhang X, Gaspar RC, Li Z, Rabinowitz JD, Perry RJ. Tissue-specific reprogramming of glutamine metabolism maintains tolerance to sepsis. PLoS One 2023; 18:e0286525. [PMID: 37410734 PMCID: PMC10325078 DOI: 10.1371/journal.pone.0286525] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 05/17/2023] [Indexed: 07/08/2023] Open
Abstract
Reprogramming metabolism is of great therapeutic interest for reducing morbidity and mortality during sepsis-induced critical illness. Disappointing results from randomized controlled trials targeting glutamine and antioxidant metabolism in patients with sepsis have begged a deeper understanding of the tissue-specific metabolic response to sepsis. The current study sought to fill this gap. We analyzed skeletal muscle transcriptomics of critically ill patients, versus elective surgical controls, which revealed reduced expression of genes involved in mitochondrial metabolism and electron transport, with increases in glutathione cycling, glutamine, branched chain, and aromatic amino acid transport. We then performed untargeted metabolomics and 13C isotope tracing to analyze systemic and tissue specific metabolic phenotyping in a murine polymicrobial sepsis model. We found an increased number of correlations between the metabolomes of liver, kidney, and spleen, with loss of correlations between the heart and quadriceps and all other organs, pointing to a shared metabolic signature within vital abdominal organs, and unique metabolic signatures for muscles during sepsis. A lowered GSH:GSSG and elevated AMP:ATP ratio in the liver underlie the significant upregulation of isotopically labeled glutamine's contribution to TCA cycle anaplerosis and glutamine-derived glutathione biosynthesis; meanwhile, the skeletal muscle and spleen were the only organs where glutamine's contribution to the TCA cycle was significantly suppressed. These results highlight tissue-specific mitochondrial reprogramming to support liver energetic demands and antioxidant synthesis, rather than global mitochondrial dysfunction, as a metabolic consequence of sepsis.
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Affiliation(s)
- Brooks P. Leitner
- Department of Cellular & Molecular Physiology, Yale University, New Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale University, New Haven, Connecticut, United States of America
| | - Won D. Lee
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
- Department of Chemistry, Princeton University, Princeton, New Jersey, United States of America
| | - Wanling Zhu
- Department of Cellular & Molecular Physiology, Yale University, New Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale University, New Haven, Connecticut, United States of America
| | - Xinyi Zhang
- Department of Cellular & Molecular Physiology, Yale University, New Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale University, New Haven, Connecticut, United States of America
| | - Rafael C. Gaspar
- Department of Cellular & Molecular Physiology, Yale University, New Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale University, New Haven, Connecticut, United States of America
| | - Zongyu Li
- Department of Cellular & Molecular Physiology, Yale University, New Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale University, New Haven, Connecticut, United States of America
| | - Joshua D. Rabinowitz
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
- Department of Chemistry, Princeton University, Princeton, New Jersey, United States of America
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America
- Ludwig Institute for Cancer Research, Princeton Branch, Princeton, New Jersey, United States of America
| | - Rachel J. Perry
- Department of Cellular & Molecular Physiology, Yale University, New Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale University, New Haven, Connecticut, United States of America
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17
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Moiz B, Sriram G, Clyne AM. Interpreting metabolic complexity via isotope-assisted metabolic flux analysis. Trends Biochem Sci 2023; 48:553-567. [PMID: 36863894 PMCID: PMC10182253 DOI: 10.1016/j.tibs.2023.02.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 01/22/2023] [Accepted: 02/03/2023] [Indexed: 03/04/2023]
Abstract
Isotope-assisted metabolic flux analysis (iMFA) is a powerful method to mathematically determine the metabolic fluxome from experimental isotope labeling data and a metabolic network model. While iMFA was originally developed for industrial biotechnological applications, it is increasingly used to analyze eukaryotic cell metabolism in physiological and pathological states. In this review, we explain how iMFA estimates the intracellular fluxome, including data and network model (inputs), the optimization-based data fitting (process), and the flux map (output). We then describe how iMFA enables analysis of metabolic complexities and discovery of metabolic pathways. Our goal is to expand the use of iMFA in metabolism research, which is essential to maximizing the impact of metabolic experiments and continuing to advance iMFA and biocomputational techniques.
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Affiliation(s)
- Bilal Moiz
- Department of Bioengineering, University of Maryland, College Park, MD 20742, USA
| | - Ganesh Sriram
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD 20742, USA
| | - Alisa Morss Clyne
- Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
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18
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Lee WD, Liang L, AbuSalim J, Jankowski CS, Samarah LZ, Neinast MD, Rabinowitz JD. Impact of acute stress on murine metabolomics and metabolic flux. Proc Natl Acad Sci U S A 2023; 120:e2301215120. [PMID: 37186827 PMCID: PMC10214130 DOI: 10.1073/pnas.2301215120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 04/10/2023] [Indexed: 05/17/2023] Open
Abstract
Plasma metabolite concentrations and labeling enrichments are common measures of organismal metabolism. In mice, blood is often collected by tail snip sampling. Here, we systematically examined the effect of such sampling, relative to gold-standard sampling from an in-dwelling arterial catheter, on plasma metabolomics and stable isotope tracing. We find marked differences between the arterial and tail circulating metabolome, which arise from two major factors: handling stress and sampling site, whose effects were deconvoluted by taking a second arterial sample immediately after tail snip. Pyruvate and lactate were the most stress-sensitive plasma metabolites, rising ~14 and ~5-fold. Both acute handling stress and adrenergic agonists induce extensive, immediate production of lactate, and modest production of many other circulating metabolites, and we provide a reference set of mouse circulatory turnover fluxes with noninvasive arterial sampling to avoid such artifacts. Even in the absence of stress, lactate remains the highest flux circulating metabolite on a molar basis, and most glucose flux into the TCA cycle in fasted mice flows through circulating lactate. Thus, lactate is both a central player in unstressed mammalian metabolism and strongly produced in response to acute stress.
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Affiliation(s)
- Won Dong Lee
- Department of Chemistry, Princeton University, Princeton, NJ08544
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ08544
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ08544
| | - Lingfan Liang
- Department of Chemistry, Princeton University, Princeton, NJ08544
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ08544
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ08544
| | - Jenna AbuSalim
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ08544
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ08544
- Department of Molecular Biology, Princeton University, Princeton, NJ08544
| | - Connor S.R. Jankowski
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ08544
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ08544
- Department of Molecular Biology, Princeton University, Princeton, NJ08544
| | - Laith Z. Samarah
- Department of Chemistry, Princeton University, Princeton, NJ08544
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ08544
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ08544
| | - Michael D. Neinast
- Department of Chemistry, Princeton University, Princeton, NJ08544
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ08544
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ08544
| | - Joshua D. Rabinowitz
- Department of Chemistry, Princeton University, Princeton, NJ08544
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ08544
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ08544
- Department of Molecular Biology, Princeton University, Princeton, NJ08544
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19
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Lee G, Lee SM, Kim HU. A contribution of metabolic engineering to addressing medical problems: Metabolic flux analysis. Metab Eng 2023; 77:283-293. [PMID: 37075858 DOI: 10.1016/j.ymben.2023.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 03/20/2023] [Accepted: 04/12/2023] [Indexed: 04/21/2023]
Abstract
Metabolic engineering has served as a systematic discipline for industrial biotechnology as it has offered systematic tools and methods for strain development and bioprocess optimization. Because these metabolic engineering tools and methods are concerned with the biological network of a cell with emphasis on metabolic network, they have also been applied to a range of medical problems where better understanding of metabolism has also been perceived to be important. Metabolic flux analysis (MFA) is a unique systematic approach initially developed in the metabolic engineering community, and has proved its usefulness and potential when addressing a range of medical problems. In this regard, this review discusses the contribution of MFA to addressing medical problems. For this, we i) provide overview of the milestones of MFA, ii) define two main branches of MFA, namely constraint-based reconstruction and analysis (COBRA) and isotope-based MFA (iMFA), and iii) present successful examples of their medical applications, including characterizing the metabolism of diseased cells and pathogens, and identifying effective drug targets. Finally, synergistic interactions between metabolic engineering and biomedical sciences are discussed with respect to MFA.
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Affiliation(s)
- GaRyoung Lee
- Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Sang Mi Lee
- Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Hyun Uk Kim
- Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea; BioProcess Engineering Research Center and BioInformatics Research Center, KAIST, Daejeon, 34141, Republic of Korea.
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20
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Huang L, Drouin N, Causon J, Wegrzyn A, Castro-Perez J, Fleming R, Harms A, Hankemeier T. Reconstruction of Glutathione Metabolism in the Neuronal Model of Rotenone-Induced Neurodegeneration Using Mass Isotopologue Analysis with Hydrophilic Interaction Liquid Chromatography-Zeno High-Resolution Multiple Reaction Monitoring. Anal Chem 2023; 95:3255-3266. [PMID: 36735349 PMCID: PMC9933045 DOI: 10.1021/acs.analchem.2c04231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Accurate reconstruction of metabolic pathways is an important prerequisite for interpreting metabolomics changes and understanding the diverse biological processes in disease models. A tracer-based metabolomics strategy utilizes stable isotope-labeled precursors to resolve complex pathways by tracing the labeled atom(s) to downstream metabolites through enzymatic reactions. Isotope enrichment analysis is informative and achieved by counting total labeled atoms and acquiring the mass isotopologue distribution (MID) of the intact metabolite. However, quantitative analysis of labeled metabolite substructures/moieties (MS2 fragments) can offer more valuable insights into the reaction connections through measuring metabolite transformation. In order to acquire the isotopic labeling information at the intact metabolite and moiety level simultaneously, we developed a method that couples hydrophilic interaction liquid chromatography (HILIC) with Zeno trap-enabled high-resolution multiple reaction monitoring (MRMHR). The method enabled accurate and reproducible MID quantification for intact metabolites as well as their fragmented moieties, with notably high sensitivity in the MS2 fragmentation mode based on the measurement of 13C- or 15N-labeled cellular samples. The method was applied to human-induced pluripotent stem cell-derived neurons to trace the fate of 13C/15N atoms from D-13C6-glucose/L-15N2-glutamine added to the media. With the MID analysis of both intact metabolites and fragmented moieties, we validated the pathway reconstruction of de novo glutathione synthesis in mid-brain neurons. We discovered increased glutathione oxidization from both basal and newly synthesized glutathione pools under neuronal oxidative stress. Furthermore, the significantly decreased de novo glutathione synthesis was investigated and associated with altered activities of several key enzymes, as evidenced by suppressed glutamate supply via glucose metabolism and a diminished flux of glutathione synthetic reaction in the neuronal model of rotenone-induced neurodegeneration.
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Affiliation(s)
- Luojiao Huang
- Metabolomics
and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
| | - Nicolas Drouin
- Metabolomics
and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
| | | | - Agnieszka Wegrzyn
- Metabolomics
and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
| | | | - Ronan Fleming
- Metabolomics
and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands,School
of Medicine, National University of Ireland, University Rd, Galway H91 TK33, Ireland
| | - Amy Harms
- Metabolomics
and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
| | - Thomas Hankemeier
- Metabolomics
and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands,
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21
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Lackner M, Neef SK, Winter S, Beer-Hammer S, Nürnberg B, Schwab M, Hofmann U, Haag M. Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line. Front Mol Biosci 2022; 9:1004602. [PMID: 36310598 PMCID: PMC9614656 DOI: 10.3389/fmolb.2022.1004602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 09/28/2022] [Indexed: 11/17/2022] Open
Abstract
The combination of high-resolution LC-MS untargeted metabolomics with stable isotope-resolved tracing is a promising approach for the global exploration of metabolic pathway activities. In our established workflow we combine targeted isotopologue feature extraction with the non-targeted X13CMS routine. Metabolites, detected by X13CMS as differentially labeled between two biological conditions are subsequently integrated into the original targeted library. This strategy enables monitoring of changes in known pathways as well as the discovery of hitherto unknown metabolic alterations. Here, we demonstrate this workflow in a PTEN (phosphatase and tensin homolog) null breast cancer cell line (MDA-MB-468) exploring metabolic pathway activities in the absence and presence of the selective PI3Kβ inhibitor AZD8186. Cells were fed with [U-13C] glucose and treated for 1, 3, 6, and 24 h with 0.5 µM AZD8186 or vehicle, extracted by an optimized sample preparation protocol and analyzed by LC-QTOF-MS. Untargeted differential tracing of labels revealed 286 isotope-enriched features that were significantly altered between control and treatment conditions, of which 19 features could be attributed to known compounds from targeted pathways. Other 11 features were unambiguously identified based on data-dependent MS/MS spectra and reference substances. Notably, only a minority of the significantly altered features (11 and 16, respectively) were identified when preprocessing of the same data set (treatment vs. control in 24 h unlabeled samples) was performed with tools commonly used for label-free (i.e. w/o isotopic tracer) non-targeted metabolomics experiments (Profinder´s batch recursive feature extraction and XCMS). The structurally identified metabolites were integrated into the existing targeted isotopologue feature extraction workflow to enable natural abundance correction, evaluation of assay performance and assessment of drug-induced changes in pathway activities. Label incorporation was highly reproducible for the majority of isotopologues in technical replicates with a RSD below 10%. Furthermore, inter-day repeatability of a second label experiment showed strong correlation (Pearson R2 > 0.99) between tracer incorporation on different days. Finally, we could identify prominent pathway activity alterations upon PI3Kβ inhibition. Besides pathways in central metabolism, known to be changed our workflow revealed additional pathways, like pyrimidine metabolism or hexosamine pathway. All pathways identified represent key metabolic processes associated with cancer metabolism and therapy.
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Affiliation(s)
- Marcel Lackner
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Sylvia K. Neef
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Stefan Winter
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Sandra Beer-Hammer
- Department of Pharmacology, Experimental Therapy and Toxicology, Institute for Experimental and Clinical Pharmacology and Pharmacogenomics, Interfaculty Center for Pharmacogenomics and Drug Research (ICePhA), University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180), Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany
| | - Bernd Nürnberg
- Department of Pharmacology, Experimental Therapy and Toxicology, Institute for Experimental and Clinical Pharmacology and Pharmacogenomics, Interfaculty Center for Pharmacogenomics and Drug Research (ICePhA), University of Tübingen, Tübingen, Germany
| | - Matthias Schwab
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180), Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany
- Departments of Clinical Pharmacology and of Pharmacy and Biochemistry, University of Tübingen, Tübingen, Germany
| | - Ute Hofmann
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Mathias Haag
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
- *Correspondence: Mathias Haag,
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22
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Theillet FX, Luchinat E. In-cell NMR: Why and how? PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2022; 132-133:1-112. [PMID: 36496255 DOI: 10.1016/j.pnmrs.2022.04.002] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 04/19/2022] [Accepted: 04/27/2022] [Indexed: 06/17/2023]
Abstract
NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.
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Affiliation(s)
- Francois-Xavier Theillet
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France.
| | - Enrico Luchinat
- Dipartimento di Scienze e Tecnologie Agro-Alimentari, Alma Mater Studiorum - Università di Bologna, Piazza Goidanich 60, 47521 Cesena, Italy; CERM - Magnetic Resonance Center, and Neurofarba Department, Università degli Studi di Firenze, 50019 Sesto Fiorentino, Italy
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23
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Bae H, Lam K, Jang C. Metabolic flux between organs measured by arteriovenous metabolite gradients. Exp Mol Med 2022; 54:1354-1366. [PMID: 36075951 PMCID: PMC9534916 DOI: 10.1038/s12276-022-00803-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 02/15/2022] [Accepted: 03/04/2022] [Indexed: 12/15/2022] Open
Abstract
Mammalian organs convert dietary nutrients into circulating metabolites and share them to maintain whole-body metabolic homeostasis. While the concentrations of circulating metabolites have been frequently measured in a variety of pathophysiological conditions, the exchange flux of circulating metabolites between organs is not easily measurable due to technical difficulties. Isotope tracing is useful for measuring such fluxes for a metabolite of interest, but the shuffling of isotopic atoms between metabolites requires mathematical modeling. Arteriovenous metabolite gradient measurements can complement isotope tracing to infer organ-specific net fluxes of many metabolites simultaneously. Here, we review the historical development of arteriovenous measurements and discuss their advantages and limitations with key example studies that have revealed metabolite exchange flux between organs in diverse pathophysiological contexts.
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Affiliation(s)
- Hosung Bae
- Department of Biological Chemistry, Chao Family Comprehensive Cancer Center, University of California Irvine, Irvine, CA, USA
| | - Katie Lam
- Department of Biological Chemistry, Chao Family Comprehensive Cancer Center, University of California Irvine, Irvine, CA, USA
| | - Cholsoon Jang
- Department of Biological Chemistry, Chao Family Comprehensive Cancer Center, University of California Irvine, Irvine, CA, USA.
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24
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Zeng X, Xing X, Gupta M, Keber FC, Lopez JG, Lee YCJ, Roichman A, Wang L, Neinast MD, Donia MS, Wühr M, Jang C, Rabinowitz JD. Gut bacterial nutrient preferences quantified in vivo. Cell 2022; 185:3441-3456.e19. [PMID: 36055202 PMCID: PMC9450212 DOI: 10.1016/j.cell.2022.07.020] [Citation(s) in RCA: 65] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 06/02/2022] [Accepted: 07/21/2022] [Indexed: 12/12/2022]
Abstract
Great progress has been made in understanding gut microbiomes' products and their effects on health and disease. Less attention, however, has been given to the inputs that gut bacteria consume. Here, we quantitatively examine inputs and outputs of the mouse gut microbiome, using isotope tracing. The main input to microbial carbohydrate fermentation is dietary fiber and to branched-chain fatty acids and aromatic metabolites is dietary protein. In addition, circulating host lactate, 3-hydroxybutyrate, and urea (but not glucose or amino acids) feed the gut microbiome. To determine the nutrient preferences across bacteria, we traced into genus-specific bacterial protein sequences. We found systematic differences in nutrient use: most genera in the phylum Firmicutes prefer dietary protein, Bacteroides dietary fiber, and Akkermansia circulating host lactate. Such preferences correlate with microbiome composition changes in response to dietary modifications. Thus, diet shapes the microbiome by promoting the growth of bacteria that preferentially use the ingested nutrients.
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Affiliation(s)
- Xianfeng Zeng
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Xi Xing
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Meera Gupta
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Felix C Keber
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Jaime G Lopez
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Ying-Chiang J Lee
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
| | - Asael Roichman
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Lin Wang
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 5 Dong Dan San Tiao, Dongcheng District, Beijing 100005, China
| | - Michael D Neinast
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Mohamed S Donia
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
| | - Martin Wühr
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
| | - Cholsoon Jang
- Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA.
| | - Joshua D Rabinowitz
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Ludwig Institute for Cancer Research, Princeton Branch, Princeton University, Princeton, NJ 08544, USA.
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25
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Dong W, Rawat ES, Stephanopoulos G, Abu-Remaileh M. Isotope tracing in health and disease. Curr Opin Biotechnol 2022; 76:102739. [PMID: 35738210 PMCID: PMC9555185 DOI: 10.1016/j.copbio.2022.102739] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 04/16/2022] [Accepted: 04/27/2022] [Indexed: 11/16/2022]
Abstract
Biochemical characterization of metabolism provides molecular insights for understanding biology in health and disease. Over the past decades, metabolic perturbations have been implicated in cancer, neurodegeneration, and diabetes, among others. Isotope tracing is a technique that allows tracking of labeled atoms within metabolites through biochemical reactions. This technique has become an integral component of the contemporary metabolic research. Isotope tracing measures substrate contribution to downstream metabolites and indicates its utilization in cellular metabolic networks. In addition, isotopic labeling data are necessary for quantitative metabolic flux analysis. Here, we review recent work utilizing metabolic tracing to study health and disease, and highlight its application to interrogate subcellular, intercellular, and in vivo metabolism. We further discuss the current challenges and opportunities to expand the utility of isotope tracing to new research areas.
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Affiliation(s)
- Wentao Dong
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; The Institute for Chemistry, Engineering & Medicine for Human Health (ChEM-H), Stanford University, Stanford, CA 94305, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Eshaan S Rawat
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; The Institute for Chemistry, Engineering & Medicine for Human Health (ChEM-H), Stanford University, Stanford, CA 94305, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Gregory Stephanopoulos
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Monther Abu-Remaileh
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; The Institute for Chemistry, Engineering & Medicine for Human Health (ChEM-H), Stanford University, Stanford, CA 94305, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA.
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26
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Wang R, Yin Y, Li J, Wang H, Lv W, Gao Y, Wang T, Zhong Y, Zhou Z, Cai Y, Su X, Liu N, Zhu ZJ. Global stable-isotope tracing metabolomics reveals system-wide metabolic alternations in aging Drosophila. Nat Commun 2022; 13:3518. [PMID: 35725845 PMCID: PMC9209425 DOI: 10.1038/s41467-022-31268-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 06/09/2022] [Indexed: 11/21/2022] Open
Abstract
System-wide metabolic homeostasis is crucial for maintaining physiological functions of living organisms. Stable-isotope tracing metabolomics allows to unravel metabolic activity quantitatively by measuring the isotopically labeled metabolites, but has been largely restricted by coverage. Delineating system-wide metabolic homeostasis at the whole-organism level remains challenging. Here, we develop a global isotope tracing metabolomics technology to measure labeled metabolites with a metabolome-wide coverage. Using Drosophila as an aging model organism, we probe the in vivo tracing kinetics with quantitative information on labeling patterns, extents and rates on a metabolome-wide scale. We curate a system-wide metabolic network to characterize metabolic homeostasis and disclose a system-wide loss of metabolic coordinations that impacts both intra- and inter-tissue metabolic homeostasis significantly during Drosophila aging. Importantly, we reveal an unappreciated metabolic diversion from glycolysis to serine metabolism and purine metabolism as Drosophila aging. The developed technology facilitates a system-level understanding of metabolic regulation in living organisms.
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Affiliation(s)
- Ruohong Wang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
- University of Chinese Academy of Sciences, 100049, Beijing, People's Republic of China
| | - Yandong Yin
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
| | - Jingshu Li
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
- University of Chinese Academy of Sciences, 100049, Beijing, People's Republic of China
| | - Hongmiao Wang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
- University of Chinese Academy of Sciences, 100049, Beijing, People's Republic of China
| | - Wanting Lv
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
- University of Chinese Academy of Sciences, 100049, Beijing, People's Republic of China
| | - Yang Gao
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
- University of Chinese Academy of Sciences, 100049, Beijing, People's Republic of China
| | - Tangci Wang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
| | - Yedan Zhong
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
| | - Zhiwei Zhou
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
| | - Yuping Cai
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China
| | - Xiaoyang Su
- Metabolomics Shared Resource, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, 08901, USA
- Division of Endocrinology, Department of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Nan Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China.
| | - Zheng-Jiang Zhu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 200032, Shanghai, People's Republic of China.
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27
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Outilaft H, Bund C, Piotto M, Namer IJ. Analysis of Metabolic Pathways by 13C-Labeled Molecular Probes and HRMAS Nuclear Magnetic Resonance Spectroscopy: Isotopologue Identification and Quantification Methods for Medical Applications. Anal Chem 2022; 94:8226-8233. [DOI: 10.1021/acs.analchem.2c00214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Hassiba Outilaft
- MNMS-Platform, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, 1 avenue Molière, 67200 Strasbourg CEDEX, France
- ICube, Université de Strasbourg/CNRS, UMR 7357, 67091 Strasbourg CEDEX, France
| | - Caroline Bund
- MNMS-Platform, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, 1 avenue Molière, 67200 Strasbourg CEDEX, France
- ICube, Université de Strasbourg/CNRS, UMR 7357, 67091 Strasbourg CEDEX, France
- Service de Médecine Nucléaire et d’Imagerie Moléculaire, Institut de Cancérologie Strasbourg Europe, 67200 Strasbourg CEDEX, France
| | - Martial Piotto
- ICube, Université de Strasbourg/CNRS, UMR 7357, 67091 Strasbourg CEDEX, France
- Bruker BioSpin, 34 rue de l’industrie, 67166 Wissembourg, France
| | - Izzie J. Namer
- MNMS-Platform, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, 1 avenue Molière, 67200 Strasbourg CEDEX, France
- ICube, Université de Strasbourg/CNRS, UMR 7357, 67091 Strasbourg CEDEX, France
- Service de Médecine Nucléaire et d’Imagerie Moléculaire, Institut de Cancérologie Strasbourg Europe, 67200 Strasbourg CEDEX, France
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28
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Alarcon-Barrera JC, Kostidis S, Ondo-Mendez A, Giera M. Recent advances in metabolomics analysis for early drug development. Drug Discov Today 2022; 27:1763-1773. [PMID: 35218927 DOI: 10.1016/j.drudis.2022.02.018] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 01/25/2022] [Accepted: 02/21/2022] [Indexed: 12/25/2022]
Abstract
The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.
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Affiliation(s)
- Juan Carlos Alarcon-Barrera
- Center for Proteomics and Metabolomics, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333 ZA Leiden, the Netherlands; Clinical Research Group, School of Medicine and Health Sciences, Universidad del Rosario, Carrera 24 # 63C-69, Bogotá, Colombia
| | - Sarantos Kostidis
- Center for Proteomics and Metabolomics, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333 ZA Leiden, the Netherlands
| | - Alejandro Ondo-Mendez
- Clinical Research Group, School of Medicine and Health Sciences, Universidad del Rosario, Carrera 24 # 63C-69, Bogotá, Colombia
| | - Martin Giera
- Center for Proteomics and Metabolomics, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333 ZA Leiden, the Netherlands.
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29
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Uematsu S, Ohno S, Tanaka KY, Hatano A, Kokaji T, Ito Y, Kubota H, Hironaka KI, Suzuki Y, Matsumoto M, Nakayama KI, Hirayama A, Soga T, Kuroda S. Multi-omics-based label-free metabolic flux inference reveals obesity-associated dysregulatory mechanisms in liver glucose metabolism. iScience 2022; 25:103787. [PMID: 35243212 PMCID: PMC8859528 DOI: 10.1016/j.isci.2022.103787] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 12/01/2021] [Accepted: 01/13/2022] [Indexed: 02/07/2023] Open
Abstract
Glucose homeostasis is maintained by modulation of metabolic flux. Enzymes and metabolites regulate the involved metabolic pathways. Dysregulation of glucose homeostasis is a pathological event in obesity. Analyzing metabolic pathways and the mechanisms contributing to obesity-associated dysregulation in vivo is challenging. Here, we introduce OMELET: Omics-Based Metabolic Flux Estimation without Labeling for Extended Trans-omic Analysis. OMELET uses metabolomic, proteomic, and transcriptomic data to identify relative changes in metabolic flux, and to calculate contributions of metabolites, enzymes, and transcripts to the changes in metabolic flux. By evaluating the livers of fasting ob/ob mice, we found that increased metabolic flux through gluconeogenesis resulted primarily from increased transcripts, whereas that through the pyruvate cycle resulted from both increased transcripts and changes in substrates of metabolic enzymes. With OMELET, we identified mechanisms underlying the obesity-associated dysregulation of metabolic flux in the liver. We developed OMELET to infer metabolic flux from label-free multi-omic data Contributions of metabolites, enzymes, and transcripts for flux were inferred Gluconeogenic flux increased in fasting ob/ob mice by increased transcripts Increased pyruvate cycle fluxes were led by increased transcripts and substrates
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Affiliation(s)
- Saori Uematsu
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Satoshi Ohno
- Molecular Genetic Research Laboratory, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.,Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Kaori Y Tanaka
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Atsushi Hatano
- Department of Omics and Systems Biology, Graduate School of Medical and Dental Sciences, Niigata University, 757 Ichibancho, Asahimachi-dori, Chuo-ku, Niigata City, Niigata 951-8510, Japan
| | - Toshiya Kokaji
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yuki Ito
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan.,Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Hiroyuki Kubota
- Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Ken-Ichi Hironaka
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yutaka Suzuki
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Masaki Matsumoto
- Department of Omics and Systems Biology, Graduate School of Medical and Dental Sciences, Niigata University, 757 Ichibancho, Asahimachi-dori, Chuo-ku, Niigata City, Niigata 951-8510, Japan
| | - Keiichi I Nakayama
- Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Akiyoshi Hirayama
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Tomoyoshi Soga
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Shinya Kuroda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan.,Molecular Genetic Research Laboratory, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.,Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
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30
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Jung SM, Le J, Doxsey WG, Haley JA, Park G, Guertin DA, Jang C. Stable Isotope Tracing and Metabolomics to Study In Vivo Brown Adipose Tissue Metabolic Fluxes. Methods Mol Biol 2022; 2448:119-130. [PMID: 35167094 PMCID: PMC9924221 DOI: 10.1007/978-1-0716-2087-8_8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Brown adipose tissue (BAT) demonstrates extraordinary metabolic capacity. Previous research using conventional radio tracers reveals that BAT can act as a sink for a diverse menu of nutrients; still, the question of how BAT utilizes these nutrients remains unclear. Recent advances in mass spectrometry (MS) coupled to stable isotope tracing methods have greatly improved our understanding of metabolism in biology. Here, we have developed a BAT-tailored metabolomics and stable isotope tracing protocol using, as an example, the universally labeled 13C-glucose, a key nutrient heavily utilized by BAT. This method enables metabolic roadmaps to be drawn and pathway fluxes to be inferred for each nutrient tracer within BAT and its application could uncover new metabolic pathways not previously appreciated for BAT physiology.
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Affiliation(s)
- Su Myung Jung
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Department of Biological Sciences, Sungkyunkwan University, Suwon, South Korea
| | - Johnny Le
- Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA
| | - Will G Doxsey
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - John A Haley
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Grace Park
- Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA
| | - David A Guertin
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA.
| | - Cholsoon Jang
- Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA.
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31
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Gonçalves AC, Richiardone E, Jorge J, Polónia B, Xavier CPR, Salaroglio IC, Riganti C, Vasconcelos MH, Corbet C, Sarmento-Ribeiro AB. Impact of cancer metabolism on therapy resistance - Clinical implications. Drug Resist Updat 2021; 59:100797. [PMID: 34955385 DOI: 10.1016/j.drup.2021.100797] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Despite an increasing arsenal of anticancer therapies, many patients continue to have poor outcomes due to the therapeutic failures and tumor relapses. Indeed, the clinical efficacy of anticancer therapies is markedly limited by intrinsic and/or acquired resistance mechanisms that can occur in any tumor type and with any treatment. Thus, there is an urgent clinical need to implement fundamental changes in the tumor treatment paradigm by the development of new experimental strategies that can help to predict the occurrence of clinical drug resistance and to identify alternative therapeutic options. Apart from mutation-driven resistance mechanisms, tumor microenvironment (TME) conditions generate an intratumoral phenotypic heterogeneity that supports disease progression and dismal outcomes. Tumor cell metabolism is a prototypical example of dynamic, heterogeneous, and adaptive phenotypic trait, resulting from the combination of intrinsic [(epi)genetic changes, tissue of origin and differentiation dependency] and extrinsic (oxygen and nutrient availability, metabolic interactions within the TME) factors, enabling cancer cells to survive, metastasize and develop resistance to anticancer therapies. In this review, we summarize the current knowledge regarding metabolism-based mechanisms conferring adaptive resistance to chemo-, radio-and immunotherapies as well as targeted therapies. Furthermore, we report the role of TME-mediated intratumoral metabolic heterogeneity in therapy resistance and how adaptations in amino acid, glucose, and lipid metabolism support the growth of therapy-resistant cancers and/or cellular subpopulations. We also report the intricate interplay between tumor signaling and metabolic pathways in cancer cells and discuss how manipulating key metabolic enzymes and/or providing dietary changes may help to eradicate relapse-sustaining cancer cells. Finally, in the current era of personalized medicine, we describe the strategies that may be applied to implement metabolic profiling for tumor imaging, biomarker identification, selection of tailored treatments and monitoring therapy response during the clinical management of cancer patients.
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Affiliation(s)
- Ana Cristina Gonçalves
- Laboratory of Oncobiology and Hematology (LOH) and University Clinic of Hematology, Faculty of Medicine (FMUC), University of Coimbra, Coimbra, Portugal; Coimbra Institute for Clinical and Biomedical Research (iCBR) - Group of Environment Genetics and Oncobiology (CIMAGO), FMUC, University of Coimbra, Portugal; Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal
| | - Elena Richiardone
- Pole of Pharmacology and Therapeutics (FATH), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Belgium
| | - Joana Jorge
- Laboratory of Oncobiology and Hematology (LOH) and University Clinic of Hematology, Faculty of Medicine (FMUC), University of Coimbra, Coimbra, Portugal; Coimbra Institute for Clinical and Biomedical Research (iCBR) - Group of Environment Genetics and Oncobiology (CIMAGO), FMUC, University of Coimbra, Portugal; Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal
| | - Bárbara Polónia
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135, Porto, Portugal; Cancer Drug Resistance Group, IPATIMUP - Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal
| | - Cristina P R Xavier
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135, Porto, Portugal; Cancer Drug Resistance Group, IPATIMUP - Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal
| | | | - Chiara Riganti
- Department of Oncology, School of Medicine, University of Torino, Italy
| | - M Helena Vasconcelos
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135, Porto, Portugal; Cancer Drug Resistance Group, IPATIMUP - Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal; Department of Biological Sciences, FFUP - Faculty of Pharmacy of the University of Porto, Porto, Portugal
| | - Cyril Corbet
- Pole of Pharmacology and Therapeutics (FATH), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Belgium.
| | - Ana Bela Sarmento-Ribeiro
- Laboratory of Oncobiology and Hematology (LOH) and University Clinic of Hematology, Faculty of Medicine (FMUC), University of Coimbra, Coimbra, Portugal; Coimbra Institute for Clinical and Biomedical Research (iCBR) - Group of Environment Genetics and Oncobiology (CIMAGO), FMUC, University of Coimbra, Portugal; Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal; Hematology Service, Centro Hospitalar e Universitário de Coimbra (CHUC), Coimbra, Portugal.
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32
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Geeraerts X, Fernández-Garcia J, Hartmann FJ, de Goede KE, Martens L, Elkrim Y, Debraekeleer A, Stijlemans B, Vandekeere A, Rinaldi G, De Rycke R, Planque M, Broekaert D, Meinster E, Clappaert E, Bardet P, Murgaski A, Gysemans C, Nana FA, Saeys Y, Bendall SC, Laoui D, Van den Bossche J, Fendt SM, Van Ginderachter JA. Macrophages are metabolically heterogeneous within the tumor microenvironment. Cell Rep 2021; 37:110171. [DOI: 10.1016/j.celrep.2021.110171] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 08/26/2021] [Accepted: 12/03/2021] [Indexed: 12/13/2022] Open
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33
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Zheng B, Zhou X, Hu X, Chen Y, Xie J, Yu Q. Advances in the regulation of natural polysaccharides on human health: The role of apoptosis/autophagy pathway. Crit Rev Food Sci Nutr 2021:1-12. [PMID: 34711083 DOI: 10.1080/10408398.2021.1995844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Due to the multiple biological activities of polysaccharides, their great potential as "natural drugs" for many diseases has been the subject of continuous exploration in the field of food and nutrition. Apoptosis and autophagy play a key role in mammalian growth, development and maintenance of cellular homeostasis. Recent studies suggest that apoptosis/autophagy may be the key regulatory target for the beneficial effects of polysaccharides. However, the regulation of apoptosis and autophagy by polysaccharides is not consistent in different disease models. Therefore, this review outlined the relationship between apoptosis/autophagy and some common human diseases, then discussed the role of apoptosis/autophagy pathway in the regulation of human health by polysaccharides, Furthermore, the application of visualization, imaging and multi-omics techniques was proposed in the future trend. The present review may be beneficial to accelerate our understanding of the anti-disease mechanisms of polysaccharides, and promote the development and utilization of polysaccharides.
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Affiliation(s)
- Bing Zheng
- State Key Laboratory of Food Science and Technology, China-Canada Joint Lab of Food Science and Technology (Nanchang), Nanchang University, Nanchang, China
| | - Xingtao Zhou
- State Key Laboratory of Food Science and Technology, China-Canada Joint Lab of Food Science and Technology (Nanchang), Nanchang University, Nanchang, China
| | - Xiaobo Hu
- State Key Laboratory of Food Science and Technology, China-Canada Joint Lab of Food Science and Technology (Nanchang), Nanchang University, Nanchang, China
| | - Yi Chen
- State Key Laboratory of Food Science and Technology, China-Canada Joint Lab of Food Science and Technology (Nanchang), Nanchang University, Nanchang, China
| | - Jianhua Xie
- State Key Laboratory of Food Science and Technology, China-Canada Joint Lab of Food Science and Technology (Nanchang), Nanchang University, Nanchang, China
| | - Qiang Yu
- State Key Laboratory of Food Science and Technology, China-Canada Joint Lab of Food Science and Technology (Nanchang), Nanchang University, Nanchang, China
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34
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van Gastel N, Spinelli JB, Haigis MC, Scadden DT. Analysis of Leukemia Cell Metabolism through Stable Isotope Tracing in Mice. Bio Protoc 2021; 11:e4171. [PMID: 34722818 DOI: 10.21769/bioprotoc.4171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 06/10/2021] [Accepted: 06/15/2021] [Indexed: 11/02/2022] Open
Abstract
Once thought to be a mere consequence of the state of a cell, intermediary metabolism is now recognized as a key regulator of mammalian cell fate and function. In addition, cell metabolism is often disturbed in malignancies such as cancer, and targeting metabolic pathways can provide new therapeutic options. Cell metabolism is mostly studied in cell cultures in vitro, using techniques such as metabolomics, stable isotope tracing, and biochemical assays. Increasing evidence however shows that the metabolic profile of cells is highly dependent on the microenvironment, and metabolic vulnerabilities identified in vitro do not always translate to in vivo settings. Here, we provide a detailed protocol on how to perform in vivo stable isotope tracing in leukemia cells in mice, focusing on glutamine metabolism in acute myeloid leukemia (AML) cells. This method allows studying the metabolic profile of leukemia cells in their native bone marrow niche.
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Affiliation(s)
- Nick van Gastel
- de Duve Institute, Brussels, Belgium.,Department of Stem Cell and Regenerative Biology, Harvard Stem Cell Institute, Harvard University, Cambridge, MA, USA
| | - Jessica B Spinelli
- Department of Cell Biology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA.,Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Marcia C Haigis
- Department of Cell Biology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - David T Scadden
- Department of Stem Cell and Regenerative Biology, Harvard Stem Cell Institute, Harvard University, Cambridge, MA, USA.,Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA
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35
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Kwong GA, Ghosh S, Gamboa L, Patriotis C, Srivastava S, Bhatia SN. Synthetic biomarkers: a twenty-first century path to early cancer detection. Nat Rev Cancer 2021; 21:655-668. [PMID: 34489588 PMCID: PMC8791024 DOI: 10.1038/s41568-021-00389-3] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/14/2021] [Indexed: 02/08/2023]
Abstract
Detection of cancer at an early stage when it is still localized improves patient response to medical interventions for most cancer types. The success of screening tools such as cervical cytology to reduce mortality has spurred significant interest in new methods for early detection (for example, using non-invasive blood-based or biofluid-based biomarkers). Yet biomarkers shed from early lesions are limited by fundamental biological and mass transport barriers - such as short circulation times and blood dilution - that limit early detection. To address this issue, synthetic biomarkers are being developed. These represent an emerging class of diagnostics that deploy bioengineered sensors inside the body to query early-stage tumours and amplify disease signals to levels that could potentially exceed those of shed biomarkers. These strategies leverage design principles and advances from chemistry, synthetic biology and cell engineering. In this Review, we discuss the rationale for development of biofluid-based synthetic biomarkers. We examine how these strategies harness dysregulated features of tumours to amplify detection signals, use tumour-selective activation to increase specificity and leverage natural processing of bodily fluids (for example, blood, urine and proximal fluids) for easy detection. Finally, we highlight the challenges that exist for preclinical development and clinical translation of synthetic biomarker diagnostics.
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Affiliation(s)
- Gabriel A Kwong
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory School of Medicine, Atlanta, GA, USA.
- Parker H. Petit Institute of Bioengineering and Bioscience, Atlanta, GA, USA.
- Institute for Electronics and Nanotechnology, Georgia Tech, Atlanta, GA, USA.
- The Georgia Immunoengineering Consortium, Emory University and Georgia Tech, Atlanta, GA, USA.
- Winship Cancer Institute, Emory University, Atlanta, GA, USA.
| | - Sharmistha Ghosh
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Lena Gamboa
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory School of Medicine, Atlanta, GA, USA
| | - Christos Patriotis
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sudhir Srivastava
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Sangeeta N Bhatia
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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36
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Gebert N, Rahman S, Lewis CA, Ori A, Cheng CW. Identifying Cell-Type-Specific Metabolic Signatures Using Transcriptome and Proteome Analyses. Curr Protoc 2021; 1:e245. [PMID: 34516047 PMCID: PMC8722675 DOI: 10.1002/cpz1.245] [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] [Indexed: 06/13/2023]
Abstract
Studies in various tissues have revealed a central role of metabolic pathways in regulating adult stem cell function in tissue regeneration and tumor initiation. The unique metabolic dependences or preferences of adult stem cells, therefore, are emerging as a new category of therapeutic target. Recently, advanced methods including high-resolution metabolomics, proteomics, and transcriptomics have been developed to address the growing interest in stem cell metabolism. A practical framework integrating the omics analyses is needed to systematically perform metabolic characterization in a cell-type-specific manner. Here, we leverage recent advances in transcriptomics and proteomics research to identify cell-type-specific metabolic features by reconstructing cell identity using genes and the encoded enzymes involved in major metabolic pathways. We provide protocols for cell isolation, transcriptome and proteome analyses, and metabolite profiling and measurement. The workflow for mapping cell-type-specific metabolic signatures presented here, although initially developed for intestinal crypt cells, can be easily implemented for cell populations in other tissues, and is highly compatible with most public datasets. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Intestinal crypt isolation and cell population purification Basic Protocol 2: Transcriptome analyses for cell-type-specific metabolic gene expression Basic Protocol 3: Proteome analyses for cell-type-specific metabolic enzyme levels Basic Protocol 4: Metabolite profiling and measurement.
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Affiliation(s)
- Nadja Gebert
- Leibniz Institute on Aging—Fritz Lipmann Institute (FLI), Jena, Germany
- Max-Delbrück-Centrum für Molekulare Medizin in der Helmholtz-Gemeinschaft (MDC), Berlin-Buch, Germany
| | - Shahadat Rahman
- Columbia Stem Cell Initiative, Department of Genetics and Development, Columbia University Irving Medical Center, New York, New York
| | - Caroline A. Lewis
- Whitehead Institute for Biomedical Research, Cambridge, Massachusetts
| | - Alessandro Ori
- Leibniz Institute on Aging—Fritz Lipmann Institute (FLI), Jena, Germany
| | - Chia-Wei Cheng
- Columbia Stem Cell Initiative, Department of Genetics and Development, Columbia University Irving Medical Center, New York, New York
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37
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Sheldon RD, Ma EH, DeCamp LM, Williams KS, Jones RG. Interrogating in vivo T-cell metabolism in mice using stable isotope labeling metabolomics and rapid cell sorting. Nat Protoc 2021; 16:4494-4521. [PMID: 34349284 DOI: 10.1038/s41596-021-00586-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 05/31/2021] [Indexed: 11/10/2022]
Abstract
T cells are integral players in the adaptive immune system that readily adapt their metabolism to meet their energetic and biosynthetic needs. A major hurdle to understand physiologic T-cell metabolism has been the differences between in vitro cell culture conditions and the complex in vivo milieu. To address this, we have developed a protocol that merges traditional immunology infection models with whole-body metabolite infusion and mass-spectrometry-based metabolomic profiling to assess T-cell metabolism in vivo. In this protocol, pathogen-infected mice are infused via the tail vein with an isotopically labeled metabolite (2-6 h), followed by rapid magnetic bead isolation to purify T-cell populations (<1 h) and then stable isotope labeling analysis conducted by mass spectrometry (~1-2 d). This procedure enables researchers to evaluate metabolic substrate utilization into central carbon metabolic pathways (i.e., glycolysis and the tricarboxylic acid cycle) by specific T-cell subpopulations in the context of physiological immune responses in vivo.
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Affiliation(s)
- Ryan D Sheldon
- Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI, USA.,Metabolomics and Bioenergetics Core Facility, Van Andel Institute, Grand Rapids, MI, USA
| | - Eric H Ma
- Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI, USA
| | - Lisa M DeCamp
- Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI, USA
| | - Kelsey S Williams
- Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI, USA
| | - Russell G Jones
- Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI, USA.
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38
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Grima-Reyes M, Martinez-Turtos A, Abramovich I, Gottlieb E, Chiche J, Ricci JE. Physiological impact of in vivo stable isotope tracing on cancer metabolism. Mol Metab 2021; 53:101294. [PMID: 34256164 PMCID: PMC8358691 DOI: 10.1016/j.molmet.2021.101294] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 06/30/2021] [Accepted: 07/08/2021] [Indexed: 11/25/2022] Open
Abstract
Background There is growing interest in the analysis of tumor metabolism to identify cancer-specific metabolic vulnerabilities and therapeutic targets. Finding of such candidate metabolic pathways mainly relies on the highly sensitive identification and quantitation of numerous metabolites and metabolic fluxes using metabolomics and isotope tracing analyses. However, nutritional requirements and metabolic routes used by cancer cells cultivated in vitro do not always reflect the metabolic demands of malignant cells within the tumor milieu. Therefore, to understand how the metabolism of tumor cells in its physiological environment differs from that of normal cells, these analyses must be performed in vivo. Scope of Review This review covers the physiological impact of the exogenous administration of a stable isotope tracer into cancer animal models. We discuss specific aspects of in vivo isotope tracing protocols based on discrete bolus injections of a labeled metabolite: the tracer administration per se and the fasting period prior to it. In addition, we illustrate the complex physiological scenarios that arise when studying tumor metabolism – by isotopic labeling in animal models fed with a specific amino acid restricted diet. Finally, we provide strategies to minimize these limitations. Major Conclusions There is growing evidence that metabolic dependencies in cancers are influenced by tissue environment, cancer lineage, and genetic events. An increasing number of studies describe discrepancies in tumor metabolic dependencies when studied in in vitro settings or in vivo models, including cancer patients. Therefore, in-depth in vivo profiling of tumor metabolic routes within the appropriate pathophysiological environment will be key to identify relevant alterations that contribute to cancer onset and progression. In vivo isotope tracing is the state-of-the-art approach to study tumor metabolism. In vivo tracer administration challenges the physiological metabolism of mice. Interorgan conversion of the tracer might confound tumor labeling patterns. Mouse fasting before in vivo tracing impacts on systemic and tumor metabolism. Optimization is key to minimize physiological alterations linked to in vivo tracing.
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Affiliation(s)
- Manuel Grima-Reyes
- Université Côte d'Azur, INSERM, C3M, Nice, France; Equipe labellisée LIGUE Contre le Cancer, Nice, France
| | - Adriana Martinez-Turtos
- Université Côte d'Azur, INSERM, C3M, Nice, France; Equipe labellisée LIGUE Contre le Cancer, Nice, France
| | - Ifat Abramovich
- Ruth and Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel
| | - Eyal Gottlieb
- Ruth and Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel
| | - Johanna Chiche
- Université Côte d'Azur, INSERM, C3M, Nice, France; Equipe labellisée LIGUE Contre le Cancer, Nice, France
| | - Jean-Ehrland Ricci
- Université Côte d'Azur, INSERM, C3M, Nice, France; Equipe labellisée LIGUE Contre le Cancer, Nice, France.
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39
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Naser FJ, Jackstadt MM, Fowle-Grider R, Spalding JL, Cho K, Stancliffe E, Doonan SR, Kramer ET, Yao L, Krasnick B, Ding L, Fields RC, Kaufman CK, Shriver LP, Johnson SL, Patti GJ. Isotope tracing in adult zebrafish reveals alanine cycling between melanoma and liver. Cell Metab 2021; 33:1493-1504.e5. [PMID: 33989520 PMCID: PMC9275394 DOI: 10.1016/j.cmet.2021.04.014] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 02/08/2021] [Accepted: 04/19/2021] [Indexed: 12/29/2022]
Abstract
The cell-intrinsic nature of tumor metabolism has become increasingly well characterized. The impact that tumors have on systemic metabolism, however, has received less attention. Here, we used adult zebrafish harboring BRAFV600E-driven melanoma to study the effect of cancer on distant tissues. By applying metabolomics and isotope tracing, we found that melanoma consume ~15 times more glucose than other tissues measured. Despite this burden, circulating glucose levels were maintained in disease animals by a tumor-liver alanine cycle. Excretion of glucose-derived alanine from tumors provided a source of carbon for hepatic gluconeogenesis and allowed tumors to remove excess nitrogen from branched-chain amino acid catabolism, which we found to be activated in zebrafish and human melanoma. Pharmacological inhibition of the tumor-liver alanine cycle in zebrafish reduced tumor burden. Our findings underscore the significance of metabolic crosstalk between tumors and distant tissues and establish the adult zebrafish as an attractive model to study such processes.
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Affiliation(s)
- Fuad J Naser
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Madelyn M Jackstadt
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Ronald Fowle-Grider
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Jonathan L Spalding
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO, USA
| | - Kevin Cho
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Ethan Stancliffe
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Steven R Doonan
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Eva T Kramer
- Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA; Division of Medical Oncology, Washington University in St. Louis, St. Louis, MO, USA; Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO, USA
| | - Lijun Yao
- Department of Genetics, Washington University in St. Louis, St. Louis, MO, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Bradley Krasnick
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, USA; Department of Surgery, Washington University in St. Louis, St. Louis, MO, USA
| | - Li Ding
- Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Ryan C Fields
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, USA; Department of Surgery, Washington University in St. Louis, St. Louis, MO, USA
| | - Charles K Kaufman
- Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA; Division of Medical Oncology, Washington University in St. Louis, St. Louis, MO, USA; Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Leah P Shriver
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Stephen L Johnson
- Department of Genetics, Washington University in St. Louis, St. Louis, MO, USA; Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO, USA
| | - Gary J Patti
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, USA.
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40
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Rao Y, Gammon ST, Sutton MN, Zacharias NM, Bhattacharya P, Piwnica-Worms D. Excess exogenous pyruvate inhibits lactate dehydrogenase activity in live cells in an MCT1-dependent manner. J Biol Chem 2021; 297:100775. [PMID: 34022218 PMCID: PMC8233206 DOI: 10.1016/j.jbc.2021.100775] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 04/27/2021] [Accepted: 05/11/2021] [Indexed: 12/21/2022] Open
Abstract
Cellular pyruvate is an essential metabolite at the crossroads of glycolysis and oxidative phosphorylation, capable of supporting fermentative glycolysis by reduction to lactate mediated by lactate dehydrogenase (LDH) among other functions. Several inherited diseases of mitochondrial metabolism impact extracellular (plasma) pyruvate concentrations, and [1-13C]pyruvate infusion is used in isotope-labeled metabolic tracing studies, including hyperpolarized magnetic resonance spectroscopic imaging. However, how these extracellular pyruvate sources impact intracellular metabolism is not clear. Herein, we examined the effects of excess exogenous pyruvate on intracellular LDH activity, extracellular acidification rates (ECARs) as a measure of lactate production, and hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates across a panel of tumor and normal cells. Combined LDH activity and LDHB/LDHA expression analysis intimated various heterotetrameric isoforms comprising LDHA and LDHB in tumor cells, not only canonical LDHA. Millimolar concentrations of exogenous pyruvate induced substrate inhibition of LDH activity in both enzymatic assays ex vivo and in live cells, abrogated glycolytic ECAR, and inhibited hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates in cellulo. Of importance, the extent of exogenous pyruvate-induced inhibition of LDH and glycolytic ECAR in live cells was highly dependent on pyruvate influx, functionally mediated by monocarboxylate transporter-1 localized to the plasma membrane. These data provided evidence that highly concentrated bolus injections of pyruvate in vivo may transiently inhibit LDH activity in a tissue type- and monocarboxylate transporter-1-dependent manner. Maintaining plasma pyruvate at submillimolar concentrations could potentially minimize transient metabolic perturbations, improve pyruvate therapy, and enhance quantification of metabolic studies, including hyperpolarized [1-13C]pyruvate magnetic resonance spectroscopic imaging and stable isotope tracer experiments.
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Affiliation(s)
- Yi Rao
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Seth T Gammon
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Margie N Sutton
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Niki M Zacharias
- Department of Urology, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Pratip Bhattacharya
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - David Piwnica-Worms
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA.
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41
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Abstract
Altered metabolic activity contributes to the pathogenesis of a number of diseases, including diabetes, heart failure, cancer, fibrosis and neurodegeneration. These diseases, and organismal metabolism more generally, are only partially recapitulated by cell culture models. Accordingly, it is important to measure metabolism in vivo. Over the past century, researchers studying glucose homeostasis have developed strategies for the measurement of tissue-specific and whole-body metabolic activity (pathway fluxes). The power of these strategies has been augmented by recent advances in metabolomics technologies. Here, we review techniques for measuring metabolic fluxes in intact mammals and discuss how to analyse and interpret the results. In tandem, we describe important findings from these techniques, and suggest promising avenues for their future application. Given the broad importance of metabolism to health and disease, more widespread application of these methods holds the potential to accelerate biomedical progress.
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Affiliation(s)
- Caroline R Bartman
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
- Department of Chemistry, Princeton University, Princeton, NJ, USA
| | - Tara TeSlaa
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
- Department of Chemistry, Princeton University, Princeton, NJ, USA
| | - Joshua D Rabinowitz
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.
- Department of Chemistry, Princeton University, Princeton, NJ, USA.
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42
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Yoon SJ, Lee CB, Chae SU, Jo SJ, Bae SK. The Comprehensive "Omics" Approach from Metabolomics to Advanced Omics for Development of Immune Checkpoint Inhibitors: Potential Strategies for Next Generation of Cancer Immunotherapy. Int J Mol Sci 2021; 22:6932. [PMID: 34203237 PMCID: PMC8268114 DOI: 10.3390/ijms22136932] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 06/24/2021] [Accepted: 06/25/2021] [Indexed: 12/11/2022] Open
Abstract
In the past decade, immunotherapies have been emerging as an effective way to treat cancer. Among several categories of immunotherapies, immune checkpoint inhibitors (ICIs) are the most well-known and widely used options for cancer treatment. Although several studies continue, this treatment option has yet to be developed into a precise application in the clinical setting. Recently, omics as a high-throughput technique for understanding the genome, transcriptome, proteome, and metabolome has revolutionized medical research and led to integrative interpretation to advance our understanding of biological systems. Advanced omics techniques, such as multi-omics, single-cell omics, and typical omics approaches, have been adopted to investigate various cancer immunotherapies. In this review, we highlight metabolomic studies regarding the development of ICIs involved in the discovery of targets or mechanisms of action and assessment of clinical outcomes, including drug response and resistance and propose biomarkers. Furthermore, we also discuss the genomics, proteomics, and advanced omics studies providing insights and comprehensive or novel approaches for ICI development. The overview of ICI studies suggests potential strategies for the development of other cancer immunotherapies using omics techniques in future studies.
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Affiliation(s)
| | | | | | | | - Soo Kyung Bae
- College of Pharmacy and Integrated Research Institute of Pharmaceutical Sciences, The Catholic University of Korea, 43 Jibong-ro, Wonmi-gu, Bucheon 14662, Korea; (S.J.Y.); (C.B.L.); (S.U.C.); (S.J.J.)
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43
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Abstract
The expanding field of stem cell metabolism has been supported by technical advances in metabolite profiling and novel functional analyses. While use of these methodologies has been fruitful, many challenges are posed by the intricacies of culturing stem cells in vitro, along with the distinctive scarcity of adult tissue stem cells and the complexities of their niches in vivo. This review provides an examination of the methodologies used to characterize stem cell metabolism, highlighting their utility while placing a sharper focus on their limitations and hurdles the field needs to overcome for the optimal study of stem cell metabolic networks.
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44
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Egami R, Kokaji T, Hatano A, Yugi K, Eto M, Morita K, Ohno S, Fujii M, Hironaka KI, Uematsu S, Terakawa A, Bai Y, Pan Y, Tsuchiya T, Ozaki H, Inoue H, Uda S, Kubota H, Suzuki Y, Matsumoto M, Nakayama KI, Hirayama A, Soga T, Kuroda S. Trans-omic analysis reveals obesity-associated dysregulation of inter-organ metabolic cycles between the liver and skeletal muscle. iScience 2021; 24:102217. [PMID: 33748705 PMCID: PMC7961104 DOI: 10.1016/j.isci.2021.102217] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 02/01/2021] [Accepted: 02/18/2021] [Indexed: 12/12/2022] Open
Abstract
Systemic metabolic homeostasis is regulated by inter-organ metabolic cycles involving multiple organs. Obesity impairs inter-organ metabolic cycles, resulting in metabolic diseases. The systemic landscape of dysregulated inter-organ metabolic cycles in obesity has yet to be explored. Here, we measured the transcriptome, proteome, and metabolome in the liver and skeletal muscle and the metabolome in blood of fasted wild-type and leptin-deficient obese (ob/ob) mice, identifying components with differential abundance and differential regulation in ob/ob mice. By constructing and evaluating the trans-omic network controlling the differences in metabolic reactions between fasted wild-type and ob/ob mice, we provided potential mechanisms of the obesity-associated dysfunctions of metabolic cycles between liver and skeletal muscle involving glucose-alanine, glucose-lactate, and ketone bodies. Our study revealed obesity-associated systemic pathological mechanisms of dysfunction of inter-organ metabolic cycles. Multi-omic data in liver and skeletal muscle of WT and ob/ob mice were measured We developed the trans-omic network of differentially regulated metabolic reactions Dysregulation of inter-organ metabolic cycles associated with obesity was revealed
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Affiliation(s)
- Riku Egami
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Toshiya Kokaji
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Atsushi Hatano
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.,Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,Department of Omics and Systems Biology, Graduate School of Medical and Dental Sciences, Niigata University, 757 Ichibancho, Asahimachi-dori, Chuo-ku, Niigata City, Niigata 951-8510, Japan
| | - Katsuyuki Yugi
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.,Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan.,PRESTO, Japan Science and Technology Agency, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Miki Eto
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Keigo Morita
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Satoshi Ohno
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.,Molecular Genetics Research Laboratory, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Masashi Fujii
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.,Molecular Genetics Research Laboratory, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.,Department of Mathematical and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, 1-3-1 Kagamiyama, Higashi-hiroshima City, Hiroshima, 739-8526, Japan
| | - Ken-Ichi Hironaka
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Saori Uematsu
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Akira Terakawa
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yunfan Bai
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Yifei Pan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Takaho Tsuchiya
- Bioinformatics Laboratory, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan.,Center for Artificial Intelligence Research, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Haruka Ozaki
- Bioinformatics Laboratory, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan.,Center for Artificial Intelligence Research, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Hiroshi Inoue
- Metabolism and Nutrition Research Unit, Institute for Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8641, Japan
| | - Shinsuke Uda
- Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Hiroyuki Kubota
- Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Yutaka Suzuki
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Masaki Matsumoto
- Department of Omics and Systems Biology, Graduate School of Medical and Dental Sciences, Niigata University, 757 Ichibancho, Asahimachi-dori, Chuo-ku, Niigata City, Niigata 951-8510, Japan
| | - Keiichi I Nakayama
- Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Akiyoshi Hirayama
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata, 997-0052, Japan
| | - Tomoyoshi Soga
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata, 997-0052, Japan
| | - Shinya Kuroda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan.,Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.,Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Bunkyo-ku, Tokyo 113-0033, Japan
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45
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Metabolic Reprogramming in Anticancer Drug Resistance: A Focus on Amino Acids. Trends Cancer 2021; 7:682-699. [PMID: 33736962 DOI: 10.1016/j.trecan.2021.02.004] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 02/12/2021] [Accepted: 02/16/2021] [Indexed: 11/22/2022]
Abstract
Overcoming anticancer drug resistance is a major challenge in cancer therapy, requiring innovative strategies that consider the extensive tumor heterogeneity and adaptability. We provide recent evidence highlighting the key role of amino acid (AA) metabolic reprogramming in cancer cells and the supportive microenvironment in driving resistance to anticancer therapies. AAs sustain the acquisition of anticancer resistance by providing essential building blocks for biosynthetic pathways and for maintaining a balanced redox status, and modulating the epigenetic profile of both malignant and non-malignant cells. In addition, AAs support the reduced intrinsic susceptibility of cancer stem cells to antineoplastic therapies. These findings shed new light on the possibility of targeting nonresponding tumors by modulating AA availability through pharmacological or dietary interventions.
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46
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Broadfield LA, Duarte JAG, Schmieder R, Broekaert D, Veys K, Planque M, Vriens K, Karasawa Y, Napolitano F, Fujita S, Fujii M, Eto M, Holvoet B, Vangoitsenhoven R, Fernandez-Garcia J, Van Elsen J, Dehairs J, Zeng J, Dooley J, Rubio RA, van Pelt J, Grünewald TGP, Liston A, Mathieu C, Deroose CM, Swinnen JV, Lambrechts D, di Bernardo D, Kuroda S, De Bock K, Fendt SM. Fat Induces Glucose Metabolism in Nontransformed Liver Cells and Promotes Liver Tumorigenesis. Cancer Res 2021; 81:1988-2001. [PMID: 33687947 DOI: 10.1158/0008-5472.can-20-1954] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 01/27/2021] [Accepted: 03/02/2021] [Indexed: 12/21/2022]
Abstract
Hepatic fat accumulation is associated with diabetes and hepatocellular carcinoma (HCC). Here, we characterize the metabolic response that high-fat availability elicits in livers before disease development. After a short term on a high-fat diet (HFD), otherwise healthy mice showed elevated hepatic glucose uptake and increased glucose contribution to serine and pyruvate carboxylase activity compared with control diet (CD) mice. This glucose phenotype occurred independently from transcriptional or proteomic programming, which identifies increased peroxisomal and lipid metabolism pathways. HFD-fed mice exhibited increased lactate production when challenged with glucose. Consistently, administration of an oral glucose bolus to healthy individuals revealed a correlation between waist circumference and lactate secretion in a human cohort. In vitro, palmitate exposure stimulated production of reactive oxygen species and subsequent glucose uptake and lactate secretion in hepatocytes and liver cancer cells. Furthermore, HFD enhanced the formation of HCC compared with CD in mice exposed to a hepatic carcinogen. Regardless of the dietary background, all murine tumors showed similar alterations in glucose metabolism to those identified in fat exposed nontransformed mouse livers, however, particular lipid species were elevated in HFD tumor and nontumor-bearing HFD liver tissue. These findings suggest that fat can induce glucose-mediated metabolic changes in nontransformed liver cells similar to those found in HCC. SIGNIFICANCE: With obesity-induced hepatocellular carcinoma on a rising trend, this study shows in normal, nontransformed livers that fat induces glucose metabolism similar to an oncogenic transformation.
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Affiliation(s)
- Lindsay A Broadfield
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.,Department of Oncology, Laboratory of Cellular Metabolism and Metabolic Regulation, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - João André Gonçalves Duarte
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.,Department of Oncology, Laboratory of Cellular Metabolism and Metabolic Regulation, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Roberta Schmieder
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.,Department of Oncology, Laboratory of Cellular Metabolism and Metabolic Regulation, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Dorien Broekaert
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.,Department of Oncology, Laboratory of Cellular Metabolism and Metabolic Regulation, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Koen Veys
- Department of Oncology (KU Leuven) and Center for Cancer Biology (VIB), Laboratory of Angiogenesis and Vascular Metabolism, Leuven, Belgium
| | - Mélanie Planque
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.,Department of Oncology, Laboratory of Cellular Metabolism and Metabolic Regulation, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Kim Vriens
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.,Department of Oncology, Laboratory of Cellular Metabolism and Metabolic Regulation, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Yasuaki Karasawa
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan.,Department of Neurosurgery, University of Tokyo Hospital, Tokyo, Japan.,Department of Rehabilitation, University of Tokyo Hospital, Tokyo, Japan
| | - Francesco Napolitano
- Telethon Institute of Genetics and Medicine (TIGEM), System Biology and Bioinformatics Laboratory and High Content Screening Facility, Naples, Italy
| | - Suguru Fujita
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan
| | - Masashi Fujii
- Department of Mathematical and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan
| | - Miki Eto
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan
| | - Bryan Holvoet
- Department of Imaging and Pathology, Nuclear Medicine and Molecular Imaging, KU Leuven, Belgium
| | | | - Juan Fernandez-Garcia
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.,Department of Oncology, Laboratory of Cellular Metabolism and Metabolic Regulation, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Joke Van Elsen
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.,Department of Oncology, Laboratory of Cellular Metabolism and Metabolic Regulation, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Jonas Dehairs
- Department of Oncology, Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, Leuven, Belgium
| | - Jia Zeng
- School of Life Science, Hunan University of Science and Technology, Xiangtan, Hunan, China
| | - James Dooley
- Department of Microbiology and Immunology, KU Leuven; and Translational Immunology Laboratory, Leuven, Belgium
| | - Rebeca Alba Rubio
- Max-Eder Research Group for Pediatric Sarcoma Biology, Institute of Pathology, Faculty of Medicine, Munich, Germany
| | - Jos van Pelt
- Department of Oncology, Laboratory of Clinical Digestive Oncology, KU, Leuven, Belgium
| | - Thomas G P Grünewald
- Max-Eder Research Group for Pediatric Sarcoma Biology, Institute of Pathology, Faculty of Medicine, Munich, Germany.,Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany.,Division of Translational Pediatric Sarcoma Research, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany.,Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Adrian Liston
- Department of Microbiology and Immunology, KU Leuven; and Translational Immunology Laboratory, Leuven, Belgium
| | - Chantal Mathieu
- Department of Endocrinology, UZ Gasthuisberg KU Leuven, Leuven, Belgium
| | - Christophe M Deroose
- Department of Imaging and Pathology, Nuclear Medicine and Molecular Imaging, KU Leuven, Belgium
| | - Johannes V Swinnen
- Department of Oncology, Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, Leuven, Belgium
| | - Diether Lambrechts
- Department of Human Genetics, Laboratory of Translational Genetics, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium
| | - Diego di Bernardo
- Telethon Institute of Genetics and Medicine (TIGEM), System Biology and Bioinformatics Laboratory and High Content Screening Facility, Naples, Italy.,Department of Chemical, Materials and Industrial Production Engineering, University of Naples Federico II, Naples, Italy
| | - Shinya Kuroda
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan
| | - Katrien De Bock
- Department of Health Sciences and Technology, Laboratory of Exercise and Health, ETH Zurich, Zurich, Switzerland
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium. .,Department of Oncology, Laboratory of Cellular Metabolism and Metabolic Regulation, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
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47
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Liang L, Sun F, Wang H, Hu Z. Metabolomics, metabolic flux analysis and cancer pharmacology. Pharmacol Ther 2021; 224:107827. [PMID: 33662451 DOI: 10.1016/j.pharmthera.2021.107827] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Revised: 02/19/2021] [Accepted: 02/23/2021] [Indexed: 02/07/2023]
Abstract
Metabolic reprogramming is a hallmark of cancer and increasing evidence suggests that reprogrammed cell metabolism supports tumor initiation, progression, metastasis and drug resistance. Understanding metabolic dysregulation may provide therapeutic targets and facilitate drug research and development for cancer therapy. Metabolomics enables the high-throughput characterization of a large scale of small molecule metabolites in cells, tissues and biofluids, while metabolic flux analysis (MFA) tracks dynamic metabolic activities using stable isotope tracer methods. Recent advances in metabolomics and MFA technologies make them powerful tools for metabolic profiling and characterizing metabolic activities in health and disease, especially in cancer research. In this review, we introduce recent advances in metabolomics and MFA analytical technologies, and provide the first comprehensive summary of the most commonly used isotope tracing methods. In addition, we highlight how metabolomics and MFA are applied in cancer pharmacology studies particularly for discovering targetable metabolic vulnerabilities, understanding the mechanisms of drug action and drug resistance, exploring potential strategies with dietary intervention, identifying cancer biomarkers, as well as enabling precision treatment with pharmacometabolomics.
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Affiliation(s)
- Lingfan Liang
- School of Pharmaceutical Sciences; Tsinghua-Peking Joint Center for Life Sciences; Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing 100084, China
| | - Fei Sun
- School of Pharmaceutical Sciences; Tsinghua-Peking Joint Center for Life Sciences; Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing 100084, China
| | - Hongbo Wang
- Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China.
| | - Zeping Hu
- School of Pharmaceutical Sciences; Tsinghua-Peking Joint Center for Life Sciences; Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing 100084, China.
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48
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Abstract
Metastasis formation is the major cause of death in most patients with cancer. Despite extensive research, targeting metastatic seeding and colonization is still an unresolved challenge. Only recently, attention has been drawn to the fact that metastasizing cancer cells selectively and dynamically adapt their metabolism at every step during the metastatic cascade. Moreover, many metastases display different metabolic traits compared with the tumours from which they originate, enabling survival and growth in the new environment. Consequently, the stage-dependent metabolic traits may provide therapeutic windows for preventing or reducing metastasis, and targeting the new metabolic traits arising in established metastases may allow their eradication.
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Affiliation(s)
- Gabriele Bergers
- Laboratory of Tumor Microenvironment and Therapeutic Resistance, VIB-KU Leuven Center for Cancer Biology, Department of Oncology, KU Leuven, Leuven, Belgium.
- UCSF Comprehensive Cancer Center, Department of Neurological Surgery, UCSF, San Francisco, CA, USA.
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium.
- Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium.
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Karta J, Bossicard Y, Kotzamanis K, Dolznig H, Letellier E. Mapping the Metabolic Networks of Tumor Cells and Cancer-Associated Fibroblasts. Cells 2021; 10:304. [PMID: 33540679 PMCID: PMC7912987 DOI: 10.3390/cells10020304] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 01/20/2021] [Accepted: 01/26/2021] [Indexed: 12/12/2022] Open
Abstract
Metabolism is considered to be the core of all cellular activity. Thus, extensive studies of metabolic processes are ongoing in various fields of biology, including cancer research. Cancer cells are known to adapt their metabolism to sustain high proliferation rates and survive in unfavorable environments with low oxygen and nutrient concentrations. Hence, targeting cancer cell metabolism is a promising therapeutic strategy in cancer research. However, cancers consist not only of genetically altered tumor cells but are interwoven with endothelial cells, immune cells and fibroblasts, which together with the extracellular matrix (ECM) constitute the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), which are linked to poor prognosis in different cancer types, are one important component of the TME. CAFs play a significant role in reprogramming the metabolic landscape of tumor cells, but how, and in what manner, this interaction takes place remains rather unclear. This review aims to highlight the metabolic landscape of tumor cells and CAFs, including their recently identified subtypes, in different tumor types. In addition, we discuss various in vitro and in vivo metabolic techniques as well as different in silico computational tools that can be used to identify and characterize CAF-tumor cell interactions. Finally, we provide our view on how mapping the complex metabolic networks of stromal-tumor metabolism will help in finding novel metabolic targets for cancer treatment.
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Affiliation(s)
- Jessica Karta
- Molecular Disease Mechanisms Group, Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine, University of Luxembourg, 6 avenue du Swing, L-4367 Belval, Luxembourg; (J.K.); (Y.B.); (K.K.)
| | - Ysaline Bossicard
- Molecular Disease Mechanisms Group, Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine, University of Luxembourg, 6 avenue du Swing, L-4367 Belval, Luxembourg; (J.K.); (Y.B.); (K.K.)
| | - Konstantinos Kotzamanis
- Molecular Disease Mechanisms Group, Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine, University of Luxembourg, 6 avenue du Swing, L-4367 Belval, Luxembourg; (J.K.); (Y.B.); (K.K.)
| | - Helmut Dolznig
- Tumor Stroma Interaction Group, Institute of Medical Genetics, Medical University of Vienna, Währinger Strasse 10, 1090 Vienna, Austria;
| | - Elisabeth Letellier
- Molecular Disease Mechanisms Group, Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine, University of Luxembourg, 6 avenue du Swing, L-4367 Belval, Luxembourg; (J.K.); (Y.B.); (K.K.)
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Kaymak I, Williams KS, Cantor JR, Jones RG. Immunometabolic Interplay in the Tumor Microenvironment. Cancer Cell 2021; 39:28-37. [PMID: 33125860 PMCID: PMC7837268 DOI: 10.1016/j.ccell.2020.09.004] [Citation(s) in RCA: 179] [Impact Index Per Article: 59.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 07/22/2020] [Accepted: 09/08/2020] [Indexed: 12/14/2022]
Abstract
Immune cells' metabolism influences their differentiation and function. Given that a complex interplay of environmental factors within the tumor microenvironment (TME) can have a profound impact on the metabolic activities of immune, stromal, and tumor cell types, there is emerging interest to advance understanding of these diverse metabolic phenotypes in the TME. Here, we discuss cell-extrinsic contributions to the metabolic activities of immune cells. Then, considering recent technical advances in experimental systems and metabolic profiling technologies, we propose future directions to better understand how immune cells meet their metabolic demands in the TME, which can be leveraged for therapeutic benefit.
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Affiliation(s)
- Irem Kaymak
- Metabolic and Nutritional Programming, Center for Cancer and Cell Biology, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Kelsey S Williams
- Metabolic and Nutritional Programming, Center for Cancer and Cell Biology, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Jason R Cantor
- Morgridge Institute for Research, Madison, WI 53715, USA; Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA; Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA; Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Russell G Jones
- Metabolic and Nutritional Programming, Center for Cancer and Cell Biology, Van Andel Institute, Grand Rapids, MI 49503, USA.
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