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Emwas AH, Szczepski K, Al-Younis I, Lachowicz JI, Jaremko M. Fluxomics - New Metabolomics Approaches to Monitor Metabolic Pathways. Front Pharmacol 2022; 13:805782. [PMID: 35387341 PMCID: PMC8977530 DOI: 10.3389/fphar.2022.805782] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 01/24/2022] [Indexed: 12/18/2022] Open
Abstract
Fluxomics is an innovative -omics research field that measures the rates of all intracellular fluxes in the central metabolism of biological systems. Fluxomics gathers data from multiple different -omics fields, portraying the whole picture of molecular interactions. Recently, fluxomics has become one of the most relevant approaches to investigate metabolic phenotypes. Metabolic flux using 13C-labeled molecules is increasingly used to monitor metabolic pathways, to probe the corresponding gene-RNA and protein-metabolite interaction networks in actual time. Thus, fluxomics reveals the functioning of multi-molecular metabolic pathways and is increasingly applied in biotechnology and pharmacology. Here, we describe the main fluxomics approaches and experimental platforms. Moreover, we summarize recent fluxomic results in different biological systems.
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Affiliation(s)
- Abdul-Hamid Emwas
- King Abdullah University of Science and Technology, Core Labs, Thuwal, Saudi Arabia
| | - Kacper Szczepski
- Smart-Health Initiative (SHI) and Red Sea Research Center (RSRC), Biological and Environmental Sciences & Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Inas Al-Younis
- King Abdullah University of Science and Technology (KAUST), Biological and Environmental Sciences & Engineering Division (BESE), Thuwal, Saudi Arabia
| | - Joanna Izabela Lachowicz
- Department of Medical Sciences and Public Health, University of Cagliari, Cittadella Universitaria, Monserrato, Italy
| | - Mariusz Jaremko
- Smart-Health Initiative (SHI) and Red Sea Research Center (RSRC), Biological and Environmental Sciences & Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
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Asampille G, Cheredath A, Joseph D, Adiga SK, Atreya HS. The utility of nuclear magnetic resonance spectroscopy in assisted reproduction. Open Biol 2020; 10:200092. [PMID: 33142083 PMCID: PMC7729034 DOI: 10.1098/rsob.200092] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 10/13/2020] [Indexed: 12/21/2022] Open
Abstract
Infertility affects approximately 15-20% of individuals of reproductive age worldwide. Over the last 40 years, assisted reproductive technology (ART) has helped millions of childless couples. However, ART is limited by a low success rate and risk of multiple gestations. Devising methods for selecting the best gamete or embryo that increases the ART success rate and prevention of multiple gestation has become one of the key goals in ART today. Special emphasis has been placed on the development of non-invasive approaches, which do not require perturbing the embryonic cells, as the current morphology-based embryo selection approach has shortcomings in predicting the implantation potential of embryos. An observed association between embryo metabolism and viability has prompted researchers to develop metabolomics-based biomarkers. Nuclear magnetic resonance (NMR) spectroscopy provides a non-invasive approach for the metabolic profiling of tissues, gametes and embryos, with the key advantage of having a minimal sample preparation procedure. Using NMR spectroscopy, biologically important molecules can be identified and quantified in intact cells, extracts or secretomes. This, in turn, helps to map out the active metabolic pathways in a system. The present review covers the contribution of NMR spectroscopy in assisted reproduction at various stages of the process.
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Affiliation(s)
- Gitanjali Asampille
- Department of Clinical Embryology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India
| | - Aswathi Cheredath
- Department of Clinical Embryology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India
| | - David Joseph
- NMR Research Centre, Indian Institute of Science, Bangalore 560012, India
- Solid State and Structural Chemistry Unit, Indian Institute of Science, Bangalore 560012, India
| | - Satish K. Adiga
- Department of Clinical Embryology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India
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Wolfender JL, Nuzillard JM, van der Hooft JJJ, Renault JH, Bertrand S. Accelerating Metabolite Identification in Natural Product Research: Toward an Ideal Combination of Liquid Chromatography–High-Resolution Tandem Mass Spectrometry and NMR Profiling, in Silico Databases, and Chemometrics. Anal Chem 2018; 91:704-742. [DOI: 10.1021/acs.analchem.8b05112] [Citation(s) in RCA: 113] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Jean-Luc Wolfender
- School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, CMU, 1 Rue Michel Servet, 1211 Geneva 4, Switzerland
| | - Jean-Marc Nuzillard
- Institut de Chimie Moléculaire de Reims, UMR CNRS 7312, Université de Reims Champagne Ardenne, 51687 Reims Cedex 2, France
| | | | - Jean-Hugues Renault
- Institut de Chimie Moléculaire de Reims, UMR CNRS 7312, Université de Reims Champagne Ardenne, 51687 Reims Cedex 2, France
| | - Samuel Bertrand
- Groupe Mer, Molécules, Santé-EA 2160, UFR des Sciences Pharmaceutiques et Biologiques, Université de Nantes, 44035 Nantes, France
- ThalassOMICS Metabolomics Facility, Plateforme Corsaire, Biogenouest, 44035 Nantes, France
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The Oral Antimalarial Drug Tafenoquine Shows Activity against Trypanosoma brucei. Antimicrob Agents Chemother 2015. [PMID: 26195527 DOI: 10.1128/aac.00879-15] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
The protozoan parasite Trypanosoma brucei causes human African trypanosomiasis, or sleeping sickness, a neglected tropical disease that requires new, safer, and more effective treatments. Repurposing oral drugs could reduce both the time and cost involved in sleeping sickness drug discovery. Tafenoquine (TFQ) is an oral antimalarial drug belonging to the 8-aminoquinoline family which is currently in clinical phase III. We show here that TFQ efficiently kills different T. brucei spp. in the submicromolar concentration range. Our results suggest that TFQ accumulates into acidic compartments and induces a necrotic process involving cell membrane disintegration and loss of cytoplasmic content, leading to parasite death. Cell lysis is preceded by a wide and multitarget drug action, affecting the lysosome, mitochondria, and acidocalcisomes and inducing a depolarization of the mitochondrial membrane potential, elevation of intracellular Ca(2+), and production of reactive oxygen species. This is the first report of an 8-aminoquinoline demonstrating significant in vitro activity against T. brucei.
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Ferrer Valenzuela J, Pinuer LA, García Cancino A, Bórquez Yáñez R. Metabolic Fluxes in Lactic Acid Bacteria—A Review. FOOD BIOTECHNOL 2015. [DOI: 10.1080/08905436.2015.1027913] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Nikel PI, Chavarría M. Quantitative Physiology Approaches to Understand and Optimize Reducing Power Availability in Environmental Bacteria. SPRINGER PROTOCOLS HANDBOOKS 2015. [DOI: 10.1007/8623_2015_84] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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Steady-state and instationary modeling of proteinogenic and free amino acid isotopomers for flux quantification. Methods Mol Biol 2014; 1090:155-79. [PMID: 24222416 DOI: 10.1007/978-1-62703-688-7_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Metabolic flux analysis (MFA) is a powerful tool for exploring and quantifying carbon traffic in metabolic networks. Accurate flux quantification requires (1) high-quality isotopomer measurements, usually of biomass components including proteinogenic/free amino acids or central carbon metabolites, and (2) a mathematical model that relates the unknown fluxes to the measured isotopomers. Modeling requires a thorough knowledge of the structure of the underlying metabolic network, often available from many databases, as well as the ability to make reasonable assumptions that will enable simplification of the model. Here we describe a general methodology underlying computer-aided mathematical modeling of a flux-isotopomer relationship and some of the accompanying data-processing steps. One of two modeling strategies will need to be employed, depending on the type of isotope labeling experiment performed. These strategies-steady-state modeling and instationary modeling-have different experimental and computational demands. We discuss the concepts underlying these two types of modeling and demonstrate steady-state modeling in a step-by-step manner. Our methodology should be applicable to most isotope-assisted MFA applications and should serve as a general framework applicable to many realistic metabolic networks with little modification.
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Abstract
Metabolic flux analysis based on tracing patterns of stable isotopes, particularly (13)C, comprises a set of methodologies to experimentally quantify intracellular biochemical reaction rates, i.e., to measure carbon flux distributions through a metabolic network. This allows quantifying the response of a metabolic network to an environmental or genetic perturbation (i.e., the metabolic phenotype). Here, we describe a protocol based on growing yeast on a (13)C-labelled substrate and subsequent NMR detection of (13)C-patterns in proteinogenic amino acids. To calculate metabolic fluxes, we describe two complementary mathematical approaches using available software; namely, an approach based on the estimation of local ratios in network nodes, and a method based on a global iterative fitting approach. Furthermore, we consider specificities of these protocols for their application to the yeast Pichia pastoris growing on multicarbon substrates other than glucose (glycerol), as well as the case when methanol is used as co-substrate in combination with glucose or glycerol.
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Affiliation(s)
- Pau Ferrer
- Department of Chemical Engineering, Escola d'Enginyeria, Universitat Autònoma de Barcelona, Bellaterra (Cerdanyola del Vallès), Spain,
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