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Quinn A, El Chazli Y, Escrig S, Daraspe J, Neuschwander N, McNally A, Genoud C, Meibom A, Engel P. Host-derived organic acids enable gut colonization of the honey bee symbiont Snodgrassella alvi. Nat Microbiol 2024; 9:477-489. [PMID: 38225461 DOI: 10.1038/s41564-023-01572-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 11/30/2023] [Indexed: 01/17/2024]
Abstract
Diverse bacteria can colonize the animal gut using dietary nutrients or by engaging in microbial crossfeeding interactions. Less is known about the role of host-derived nutrients in enabling gut bacterial colonization. Here we examined metabolic interactions within the evolutionary ancient symbiosis between the honey bee (Apis mellifera) and the core gut microbiota member Snodgrassella alvi. This betaproteobacterium is incapable of metabolizing saccharides, yet colonizes the honey bee gut in the presence of a sugar-only diet. Using comparative metabolomics, 13C-tracers and nanoscale secondary ion mass spectrometry (NanoSIMS), we show in vivo that S. alvi grows on host-derived organic acids, including citrate, glycerate and 3-hydroxy-3-methylglutarate, which are actively secreted by the host into the gut lumen. S. alvi also modulates tryptophan metabolism in the gut by converting kynurenine to anthranilate. These results suggest that S. alvi is adapted to a specific metabolic niche in the honey bee gut that depends on host-derived nutritional resources.
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Affiliation(s)
- Andrew Quinn
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Yassine El Chazli
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Stéphane Escrig
- Laboratory for Biological Geochemistry, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jean Daraspe
- Electron Microscopy Facility, University of Lausanne, Lausanne, Switzerland
| | - Nicolas Neuschwander
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Aoife McNally
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Christel Genoud
- Electron Microscopy Facility, University of Lausanne, Lausanne, Switzerland
| | - Anders Meibom
- Laboratory for Biological Geochemistry, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Center for Advanced Surface Analysis, Institute of Earth Sciences, University of Lausanne, Lausanne, Switzerland
| | - Philipp Engel
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.
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Lugar DJ, Sriram G. Isotope-assisted metabolic flux analysis as an equality-constrained nonlinear program for improved scalability and robustness. PLoS Comput Biol 2022; 18:e1009831. [PMID: 35324890 PMCID: PMC8947808 DOI: 10.1371/journal.pcbi.1009831] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 01/12/2022] [Indexed: 01/11/2023] Open
Abstract
Stable isotope-assisted metabolic flux analysis (MFA) is a powerful method to estimate carbon flow and partitioning in metabolic networks. At its core, MFA is a parameter estimation problem wherein the fluxes and metabolite pool sizes are model parameters that are estimated, via optimization, to account for measurements of steady-state or isotopically-nonstationary isotope labeling patterns. As MFA problems advance in scale, they require efficient computational methods for fast and robust convergence. The structure of the MFA problem enables it to be cast as an equality-constrained nonlinear program (NLP), where the equality constraints are constructed from the MFA model equations, and the objective function is defined as the sum of squared residuals (SSR) between the model predictions and a set of labeling measurements. This NLP can be solved by using an algebraic modeling language (AML) that offers state-of-the-art optimization solvers for robust parameter estimation and superior scalability to large networks. When implemented in this manner, the optimization is performed with no distinction between state variables and model parameters. During each iteration of such an optimization, the system state is updated instead of being calculated explicitly from scratch, and this occurs concurrently with improvement in the model parameter estimates. This optimization approach starkly contrasts with traditional “shooting” methods where the state variables and model parameters are kept distinct and the system state is computed afresh during each iteration of a stepwise optimization. Our NLP formulation uses the MFA modeling framework of Wiechert et al. [1], which is amenable to incorporation of the model equations into an NLP. The NLP constraints consist of balances on either elementary metabolite units (EMUs) or cumomers. In this formulation, both the steady-state and isotopically-nonstationary MFA (inst-MFA) problems may be solved as an NLP. For the inst-MFA case, the ordinary differential equation (ODE) system describing the labeling dynamics is transcribed into a system of algebraic constraints for the NLP using collocation. This large-scale NLP may be solved efficiently using an NLP solver implemented on an AML. In our implementation, we used the reduced gradient solver CONOPT, implemented in the General Algebraic Modeling System (GAMS). The NLP framework is particularly advantageous for inst-MFA, scaling well to large networks with many free parameters, and having more robust convergence properties compared to the shooting methods that compute the system state and sensitivities at each iteration. Additionally, this NLP approach supports the use of tandem-MS data for both steady-state and inst-MFA when the cumomer framework is used. We assembled a software, eiFlux, written in Python and GAMS that uses the NLP approach and supports both steady-state and inst-MFA. We demonstrate the effectiveness of the NLP formulation on several examples, including a genome-scale inst-MFA model, to highlight the scalability and robustness of this approach. In addition to typical inst-MFA applications, we expect that this framework and our associated software, eiFlux, will be particularly useful for applying inst-MFA to complex MFA models, such as those developed for eukaryotes (e.g. algae) and co-cultures with multiple cell types. Isotope-assisted metabolic flux analysis (MFA) is a computationally intensive parameter estimation problem. Isotopically nonstationary MFA (inst-MFA) represents the most computationally burdensome MFA application. We present the formulation of the steady-state and inst-MFA problems as equality-constrained nonlinear programs (NLPs), solved by a state-of-the-art solver implemented in an algebraic modeling language. We show that this formulation leads to robust convergence properties compared to traditional approaches, particularly for inst-MFA. We developed a software, eiFlux that uses the NLP formulation to perform both steady-state and inst-MFA. We demonstrate the application of eiFlux on several examples, including a genome-scale inst-MFA model, and show that it has robust optimal convergence even when started from a very poor initial guess for the parameters. eiFlux is implemented using the Python programming language and the General Algebraic Modeling System (GAMS), using the CONOPT solver. eiFlux is available upon request, pending institutional approval, and is free for academic use.
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Affiliation(s)
- Daniel J. Lugar
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, Maryland, United States of America
| | - Ganesh Sriram
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, Maryland, United States of America
- * E-mail:
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3
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Wiechert W, Nöh K. Quantitative Metabolic Flux Analysis Based on Isotope Labeling. Metab Eng 2021. [DOI: 10.1002/9783527823468.ch3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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4
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Chung J, Sriram G, Keefer CL. Nanoparticle technology improves in-vitro attachment of cattle (Bos taurus) trophectoderm cells. Biotechnol Lett 2020; 42:2083-2089. [PMID: 32494995 DOI: 10.1007/s10529-020-02926-w] [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] [Received: 10/23/2019] [Accepted: 05/26/2020] [Indexed: 11/28/2022]
Abstract
The bovine cell line, cow trophectoderm-1 (CT-1), provides an excellent in-vitro cell culture model to study early embryonic development. Obtaining consistent attachment and outgrowth, however, is difficult because enzymatic disassociation into single cells is detrimental; therefore, CT-1 cells must be passaged in clumps, which do not attach readily to the surface of the dish. We tested whether magnetic nanoparticles, NanoShuttle™-PL, could be used to improve cell attachment and subsequent proliferation of the cattle trophectoderm cell line without altering cellular metabolism or immunofluorescent detection of the lineage marker Caudal Type Homeobox 2 (CDX2). Confluency was achieved more consistently by using the NanoShuttle™-PL system to magnetically force attachment (75-100% of wells) as compared to the control (11%). Moreover, there were no alterations in characteristic morphology, nuclear-localized expression of the trophectoderm marker CDX2, or glycolytic metabolism. By enhancing attachment, magnetic nanoparticles improved culture efficiency and reproducibility in an anchorage-dependent cell line that otherwise was recalcitrant to efficient passaging.
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Affiliation(s)
- Jaewook Chung
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Ganesh Sriram
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA
| | - Carol L Keefer
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
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5
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Dynamic 13C Labeling of Fast Turnover Metabolites for Analysis of Metabolic Fluxes and Metabolite Channeling. Methods Mol Biol 2019; 1859:301-316. [PMID: 30421238 DOI: 10.1007/978-1-4939-8757-3_18] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
Abstract
Dynamic or isotopically nonstationary 13C labeling experiments are a powerful tool not only for precise carbon flux quantification (e.g., metabolic flux analysis of photoautotrophic organisms) but also for the investigation of pathway bottlenecks, a cell's phenotype, and metabolite channeling. In general, isotopically nonstationary metabolic flux analysis requires three main components: (1) transient isotopic labeling experiments; (2) metabolite quenching and isotopomer analysis using LC-MS; (3) metabolic network construction and flux quantification. Labeling dynamics of key metabolites from 13C-pulse experiments allow flux estimation of key central pathways by solving ordinary differential equations to fit time-dependent isotopomer distribution data. Additionally, it is important to provide biomass requirements, carbon uptake rates, specific growth rates, and carbon excretion rates to properly and precisely balance the metabolic network. Labeling dynamics through cascade metabolites may also identify channeling phenomena in which metabolites are passed between enzymes without mixing with the bulk phase. In this chapter, we outline experimental protocols to probe metabolic pathways through dynamic labeling. We describe protocols for labeling experiments, metabolite quenching and extraction, LC-MS analysis, computational flux quantification, and metabolite channeling observations.
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6
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Zhang X, Misra A, Nargund S, Coleman GD, Sriram G. Concurrent isotope-assisted metabolic flux analysis and transcriptome profiling reveal responses of poplar cells to altered nitrogen and carbon supply. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 93:472-488. [PMID: 29193384 DOI: 10.1111/tpj.13792] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 11/15/2017] [Accepted: 11/23/2017] [Indexed: 05/20/2023]
Abstract
Reduced nitrogen is indispensable to plants. However, its limited availability in soil combined with the energetic and environmental impacts of nitrogen fertilizers motivates research into molecular mechanisms toward improving plant nitrogen use efficiency (NUE). We performed a systems-level investigation of this problem by employing multiple 'omics methodologies on cell suspensions of hybrid poplar (Populus tremula × Populus alba). Acclimation and growth of the cell suspensions in four nutrient regimes ranging from abundant to deficient supplies of carbon and nitrogen revealed that cell growth under low-nitrogen levels was associated with substantially higher NUE. To investigate the underlying metabolic and molecular mechanisms, we concurrently performed steady-state 13 C metabolic flux analysis with multiple isotope labels and transcriptomic profiling with cDNA microarrays. The 13 C flux analysis revealed that the absolute flux through the oxidative pentose phosphate pathway (oxPPP) was substantially lower (~threefold) under low-nitrogen conditions. Additionally, the flux partitioning ratio between the tricarboxylic acid cycle and anaplerotic pathways varied from 84%:16% under abundant carbon and nitrogen to 55%:45% under deficient carbon and nitrogen. Gene expression data, together with the flux results, suggested a plastidic localization of the oxPPP as well as transcriptional regulation of certain metabolic branchpoints, including those between glycolysis and the oxPPP. The transcriptome data also indicated that NUE-improving mechanisms may involve a redirection of excess carbon to aromatic metabolic pathways and extensive downregulation of potentially redundant genes (in these heterotrophic cells) that encode photosynthetic and light-harvesting proteins, suggesting the recruitment of these proteins as nitrogen sinks in nitrogen-abundant conditions.
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Affiliation(s)
- Xiaofeng Zhang
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA
| | - Ashish Misra
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA
| | - Shilpa Nargund
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA
| | - Gary D Coleman
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, 20742, USA
| | - Ganesh Sriram
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA
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7
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Lima VF, de Souza LP, Williams TCR, Fernie AR, Daloso DM. Gas Chromatography-Mass Spectrometry-Based 13C-Labeling Studies in Plant Metabolomics. Methods Mol Biol 2018; 1778:47-58. [PMID: 29761430 DOI: 10.1007/978-1-4939-7819-9_4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/09/2022]
Abstract
Stable-isotope labeling analysis has been used to discover new metabolic pathways and their key regulatory points in a wide range of organisms. Given the complexity of the plant metabolic network, this analysis provides information complementary to that obtained from metabolite profiling that can be used to understand how plants cope with adverse conditions, and how metabolism varies between different cells, tissues, and organs. Here we describe the experimental procedures from sample harvesting and extraction to mass spectral analysis and interpretation that allow the researcher to perform 13C-labeling experiments. A wide range of plant material, from single cells to whole plants, can be used to investigate the metabolic fate of the 13C from a predefined tracer. Thus, a key point of this analysis is to choose the correct biological system, the substrate and the condition to be investigated; all of which implicitly relies on the biological question to be investigated. Rapid sample quenching and a careful data analysis are also critical points in such studies. By contrast to other metabolomic approaches, stable-isotope labeling can provide information concerning the fluxes through metabolic networks, which is essential for understanding and manipulating metabolic phenotypes and therefore of pivotal importance for both systems biology and plant metabolic engineering.
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Affiliation(s)
- Valéria F Lima
- Departamento de Bioquímica e Biologia Molecular, Universidade Federal do Ceará, Fortaleza, CE, Brazil
| | | | | | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany
| | - Danilo M Daloso
- Departamento de Bioquímica e Biologia Molecular, Universidade Federal do Ceará, Fortaleza, CE, Brazil.
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8
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Dumschott K, Richter A, Loescher W, Merchant A. Post photosynthetic carbon partitioning to sugar alcohols and consequences for plant growth. PHYTOCHEMISTRY 2017; 144:243-252. [PMID: 28985572 DOI: 10.1016/j.phytochem.2017.09.019] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 09/22/2017] [Accepted: 09/26/2017] [Indexed: 05/06/2023]
Abstract
The occurrence of sugar alcohols is ubiquitous among plants. Physiochemical properties of sugar alcohols suggest numerous primary and secondary functions in plant tissues and are often well documented. In addition to functions arising from physiochemical properties, the synthesis of sugar alcohols may have significant influence over photosynthetic, respiratory, and developmental processes owing to their function as a large sink for photosynthates. Sink strength is demonstrated by the high concentrations of sugar alcohols found in plant tissues and their ability to be readily transported. The plant scale distribution and physiochemical function of these compounds renders them strong candidates for functioning as stress metabolites. Despite this, several aspects of sugar alcohol biosynthesis and function are poorly characterised namely: 1) the quantitative characterisation of carbon flux into the sugar alcohol pool; 2) the molecular control governing sugar alcohol biosynthesis on a quantitative basis; 3) the role of sugar alcohols in plant growth and ecology; and 4) consequences of sugar alcohol synthesis for yield production and yield quality. We highlight the need to adopt new approaches to investigating sugar alcohol biosynthesis using modern technologies in gene expression, metabolic flux analysis and agronomy. Combined, these approaches will elucidate the impact of sugar alcohol biosynthesis on growth, stress tolerance, yield and yield quality.
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Affiliation(s)
- Kathryn Dumschott
- Faculty of Agriculture and Environment, The University of Sydney, Sydney, NSW, 2006, Australia.
| | - Andreas Richter
- Department of Microbiology and Ecosystem Science, University of Vienna, Vienna, Austria
| | - Wayne Loescher
- Department of Horticulture, Michigan State University, MI, USA
| | - Andrew Merchant
- Faculty of Agriculture and Environment, The University of Sydney, Sydney, NSW, 2006, Australia
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Robaina-Estévez S, Daloso DM, Zhang Y, Fernie AR, Nikoloski Z. Resolving the central metabolism of Arabidopsis guard cells. Sci Rep 2017; 7:8307. [PMID: 28814793 PMCID: PMC5559522 DOI: 10.1038/s41598-017-07132-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 06/23/2017] [Indexed: 12/22/2022] Open
Abstract
Photosynthesis and water use efficiency, key factors affecting plant growth, are directly controlled by microscopic and adjustable pores in the leaf-the stomata. The size of the pores is modulated by the guard cells, which rely on molecular mechanisms to sense and respond to environmental changes. It has been shown that the physiology of mesophyll and guard cells differs substantially. However, the implications of these differences to metabolism at a genome-scale level remain unclear. Here, we used constraint-based modeling to predict the differences in metabolic fluxes between the mesophyll and guard cells of Arabidopsis thaliana by exploring the space of fluxes that are most concordant to cell-type-specific transcript profiles. An independent 13C-labeling experiment using isolated mesophyll and guard cells was conducted and provided support for our predictions about the role of the Calvin-Benson cycle in sucrose synthesis in guard cells. The combination of in silico with in vivo analyses indicated that guard cells have higher anaplerotic CO2 fixation via phosphoenolpyruvate carboxylase, which was demonstrated to be an important source of malate. Beyond highlighting the metabolic differences between mesophyll and guard cells, our findings can be used in future integrated modeling of multi-cellular plant systems and their engineering towards improved growth.
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Affiliation(s)
- Semidán Robaina-Estévez
- Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Golm, Germany
- Bioinformatics Group, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Golm, Germany
| | - Danilo M Daloso
- Central Metabolism Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Golm, Germany
- Departamento de Bioquímica e Biologia Molecular, Universidade Federal do Ceará, Fortaleza, CE, Brazil
| | - Youjun Zhang
- Central Metabolism Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Golm, Germany
| | - Alisdair R Fernie
- Central Metabolism Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Golm, Germany
| | - Zoran Nikoloski
- Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Golm, Germany.
- Bioinformatics Group, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Golm, Germany.
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10
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Abernathy MH, Yu J, Ma F, Liberton M, Ungerer J, Hollinshead WD, Gopalakrishnan S, He L, Maranas CD, Pakrasi HB, Allen DK, Tang YJ. Deciphering cyanobacterial phenotypes for fast photoautotrophic growth via isotopically nonstationary metabolic flux analysis. BIOTECHNOLOGY FOR BIOFUELS 2017; 10:273. [PMID: 29177008 PMCID: PMC5691832 DOI: 10.1186/s13068-017-0958-y] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 11/06/2017] [Indexed: 05/09/2023]
Abstract
BACKGROUND Synechococcus elongatus UTEX 2973 is the fastest growing cyanobacterium characterized to date. Its genome was found to be 99.8% identical to S. elongatus 7942 yet it grows twice as fast. Current genome-to-phenome mapping is still poorly performed for non-model organisms. Even for species with identical genomes, cell phenotypes can be strikingly different. To understand Synechococcus 2973's fast-growth phenotype and its metabolic features advantageous to photo-biorefineries, 13C isotopically nonstationary metabolic flux analysis (INST-MFA), biomass compositional analysis, gene knockouts, and metabolite profiling were performed on both strains under various growth conditions. RESULTS The Synechococcus 2973 flux maps show substantial carbon flow through the Calvin cycle, glycolysis, photorespiration and pyruvate kinase, but minimal flux through the malic enzyme and oxidative pentose phosphate pathways under high light/CO2 conditions. During fast growth, its pool sizes of key metabolites in central pathways were lower than suboptimal growth. Synechococcus 2973 demonstrated similar flux ratios to Synechococcus 7942 (under fast growth conditions), but exhibited greater carbon assimilation, higher NADPH concentrations, higher energy charge (relative ATP ratio over ADP and AMP), less accumulation of glycogen, and potentially metabolite channeling. Furthermore, Synechococcus 2973 has very limited flux through the TCA pathway with small pool sizes of acetyl-CoA/TCA intermediates under all growth conditions. CONCLUSIONS This study employed flux analysis to investigate phenotypic heterogeneity among two cyanobacterial strains with near-identical genome background. The flux/metabolite profiling, biomass composition analysis, and genetic modification results elucidate a highly effective metabolic topology for CO2 assimilatory and biosynthesis in Synechococcus 2973. Comparisons across multiple Synechococcus strains indicate faster metabolism is also driven by proportional increases in both photosynthesis and key central pathway fluxes. Moreover, the flux distribution in Synechococcus 2973 supports the use of its strong sugar phosphate pathways for optimal bio-productions. The integrated methodologies in this study can be applied for characterizing non-model microbial metabolism.
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Affiliation(s)
- Mary H. Abernathy
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
| | - Jingjie Yu
- Department of Biology, Temple University, Philadelphia, PA 19122 USA
| | - Fangfang Ma
- Donald Danforth Plant Science Center, St. Louis, MO 63132 USA
| | - Michelle Liberton
- Department of Biology, Washington University, St. Louis, MO 63130 USA
| | - Justin Ungerer
- Department of Biology, Washington University, St. Louis, MO 63130 USA
| | - Whitney D. Hollinshead
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
| | - Saratram Gopalakrishnan
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802 USA
| | - Lian He
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
| | - Costas D. Maranas
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802 USA
| | - Himadri B. Pakrasi
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
- Department of Biology, Washington University, St. Louis, MO 63130 USA
| | - Doug K. Allen
- Donald Danforth Plant Science Center, St. Louis, MO 63132 USA
- United States Department of Agriculture, Agricultural Research Service, St. Louis, MO 63132 USA
| | - Yinjie J. Tang
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
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He L, Xiu Y, Jones JA, Baidoo EE, Keasling JD, Tang YJ, Koffas MA. Deciphering flux adjustments of engineered E. coli cells during fermentation with changing growth conditions. Metab Eng 2017; 39:247-256. [DOI: 10.1016/j.ymben.2016.12.008] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Revised: 12/12/2016] [Accepted: 12/20/2016] [Indexed: 11/30/2022]
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12
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Bacher A, Chen F, Eisenreich W. Decoding Biosynthetic Pathways in Plants by Pulse-Chase Strategies Using (13)CO₂ as a Universal Tracer †. Metabolites 2016; 6:E21. [PMID: 27429012 PMCID: PMC5041120 DOI: 10.3390/metabo6030021] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Revised: 07/03/2016] [Accepted: 07/04/2016] [Indexed: 01/14/2023] Open
Abstract
(13)CO₂ pulse-chase experiments monitored by high-resolution NMR spectroscopy and mass spectrometry can provide (13)C-isotopologue compositions in biosynthetic products. Experiments with a variety of plant species have documented that the isotopologue profiles generated with (13)CO₂ pulse-chase labeling are directly comparable to those that can be generated by the application of [U-(13)C₆]glucose to aseptically growing plants. However, the application of the (13)CO₂ labeling technology is not subject to the experimental limitations that one has to take into account for experiments with [U-(13)C₆]glucose and can be applied to plants growing under physiological conditions, even in the field. In practical terms, the results of biosynthetic studies with (13)CO₂ consist of the detection of pairs, triples and occasionally quadruples of (13)C atoms that have been jointly contributed to the target metabolite, at an abundance that is well above the stochastic occurrence of such multiples. Notably, the connectivities of jointly transferred (13)C multiples can have undergone modification by skeletal rearrangements that can be diagnosed from the isotopologue data. As shown by the examples presented in this review article, the approach turns out to be powerful in decoding the carbon topology of even complex biosynthetic pathways.
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Affiliation(s)
- Adelbert Bacher
- Lehrstuhl für Biochemie, Technische Universität München, 85748 Garching, Germany.
| | - Fan Chen
- Lehrstuhl für Biochemie, Technische Universität München, 85748 Garching, Germany.
| | - Wolfgang Eisenreich
- Lehrstuhl für Biochemie, Technische Universität München, 85748 Garching, Germany.
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13
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DeGennaro CM, Savir Y, Springer M. Identifying Metabolic Subpopulations from Population Level Mass Spectrometry. PLoS One 2016; 11:e0151659. [PMID: 26986964 PMCID: PMC4795775 DOI: 10.1371/journal.pone.0151659] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2015] [Accepted: 03/02/2016] [Indexed: 12/25/2022] Open
Abstract
Metabolism underlies many important cellular decisions, such as the decisions to proliferate and differentiate, and defects in metabolic signaling can lead to disease and aging. In addition, metabolic heterogeneity can have biological consequences, such as differences in outcomes and drug susceptibilities in cancer and antibiotic treatments. Many approaches exist for characterizing the metabolic state of a population of cells, but technologies for measuring metabolism at the single cell level are in the preliminary stages and are limited. Here, we describe novel analysis methodologies that can be applied to established experimental methods to measure metabolic variability within a population. We use mass spectrometry to analyze amino acid composition in cells grown in a mixture of (12)C- and (13)C-labeled sugars; these measurements allow us to quantify the variability in sugar usage and thereby infer information about the behavior of cells within the population. The methodologies described here can be applied to a large range of metabolites and macromolecules and therefore have the potential for broad applications.
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Affiliation(s)
- Christine M. DeGennaro
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, 02115, United States of America
| | - Yonatan Savir
- Department of Physiology, Biophysics and Systems Biology, Faculty of Medicine, Technion, Haifa, 31096, Israel
| | - Michael Springer
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, 02115, United States of America
- * E-mail:
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14
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Dersch LM, Beckers V, Wittmann C. Green pathways: Metabolic network analysis of plant systems. Metab Eng 2016; 34:1-24. [DOI: 10.1016/j.ymben.2015.12.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Revised: 11/30/2015] [Accepted: 12/01/2015] [Indexed: 12/18/2022]
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Allen DK. Quantifying plant phenotypes with isotopic labeling & metabolic flux analysis. Curr Opin Biotechnol 2015; 37:45-52. [PMID: 26613198 DOI: 10.1016/j.copbio.2015.10.002] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Revised: 10/04/2015] [Accepted: 10/06/2015] [Indexed: 12/14/2022]
Abstract
Analyses of metabolic flux using stable isotopes in plants have traditionally been restricted to tissues with presumed homogeneous cell populations and long metabolic steady states such as developing seeds, cell suspensions, or cultured roots and root tips. It is now possible to describe these and other metabolically more dynamic tissues such as leaves in greater detail using novel methods in mass spectrometry, isotope labeling strategies, and transient labeling-based flux analyses. Such studies are necessary for a systems level description of plant function that more closely represents biological reality, and provides insights into the genes that will need to be modified as natural resources become ever more limited and environments change.
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Affiliation(s)
- Doug K Allen
- United States Department of Agriculture-Agricultural Research Service, Plant Genetics Research Unit, 975 North Warson Road, St. Louis, MO 63132, United States; Donald Danforth Plant Science Center, 975 North Warson Road, St. Louis, MO 63132, United States.
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16
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Fluxes through plant metabolic networks: measurements, predictions, insights and challenges. Biochem J 2015; 465:27-38. [PMID: 25631681 DOI: 10.1042/bj20140984] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Although the flows of material through metabolic networks are central to cell function, they are not easy to measure other than at the level of inputs and outputs. This is particularly true in plant cells, where the network spans multiple subcellular compartments and where the network may function either heterotrophically or photoautotrophically. For many years, kinetic modelling of pathways provided the only method for describing the operation of fragments of the network. However, more recently, it has become possible to map the fluxes in central carbon metabolism using the stable isotope labelling techniques of metabolic flux analysis (MFA), and to predict intracellular fluxes using constraints-based modelling procedures such as flux balance analysis (FBA). These approaches were originally developed for the analysis of microbial metabolism, but over the last decade, they have been adapted for the more demanding analysis of plant metabolic networks. Here, the principal features of MFA and FBA as applied to plants are outlined, followed by a discussion of the insights that have been gained into plant metabolic networks through the application of these time-consuming and non-trivial methods. The discussion focuses on how a system-wide view of plant metabolism has increased our understanding of network structure, metabolic perturbations and the provision of reducing power and energy for cell function. Current methodological challenges that limit the scope of plant MFA are discussed and particular emphasis is placed on the importance of developing methods for cell-specific MFA.
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17
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Antoniewicz MR. Methods and advances in metabolic flux analysis: a mini-review. J Ind Microbiol Biotechnol 2015; 42:317-25. [PMID: 25613286 DOI: 10.1007/s10295-015-1585-x] [Citation(s) in RCA: 145] [Impact Index Per Article: 16.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Accepted: 01/09/2015] [Indexed: 01/12/2023]
Abstract
Metabolic flux analysis (MFA) is one of the pillars of metabolic engineering. Over the past three decades, it has been widely used to quantify intracellular metabolic fluxes in both native (wild type) and engineered biological systems. Through MFA, changes in metabolic pathway fluxes are quantified that result from genetic and/or environmental interventions. This information, in turn, provides insights into the regulation of metabolic pathways and may suggest new targets for further metabolic engineering of the strains. In this mini-review, we discuss and classify the various methods of MFA that have been developed, which include stoichiometric MFA, (13)C metabolic flux analysis, isotopic non-stationary (13)C metabolic flux analysis, dynamic metabolic flux analysis, and (13)C dynamic metabolic flux analysis. For each method, we discuss key advantages and limitations and conclude by highlighting important recent advances in flux analysis approaches.
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Affiliation(s)
- Maciek R Antoniewicz
- Department of Chemical and Biomolecular Engineering, Metabolic Engineering and Systems Biology Laboratory, University of Delaware, 150 Academy St, Newark, DE, 19716, USA,
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Masakapalli SK, Bryant FM, Kruger NJ, Ratcliffe RG. The metabolic flux phenotype of heterotrophic Arabidopsis cells reveals a flexible balance between the cytosolic and plastidic contributions to carbohydrate oxidation in response to phosphate limitation. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2014; 78:964-977. [PMID: 24674596 DOI: 10.1111/tpj.12522] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2014] [Revised: 03/17/2014] [Accepted: 03/24/2014] [Indexed: 05/29/2023]
Abstract
Understanding the mechanisms that allow plants to respond to variable and reduced availability of inorganic phosphate is of increasing agricultural importance because of the continuing depletion of the rock phosphate reserves that are used to combat inadequate phosphate levels in the soil. Changes in gene expression, protein levels, enzyme activities and metabolite levels all point to a reconfiguration of the central metabolic network in response to reduced availability of inorganic phosphate, but the metabolic significance of these changes can only be assessed in terms of the fluxes supported by the network. Steady-state metabolic flux analysis was used to define the metabolic phenotype of a heterotrophic Arabidopsis thaliana cell culture grown on a Murashige and Skoog medium containing 0, 1.25 or 5 mm inorganic phosphate. Fluxes through the central metabolic network were deduced from the redistribution of (13) C into metabolic intermediates and end products when cells were labelled with [1-(13) C], [2-(13) C], or [(13) C6 ]glucose, in combination with (14) C measurements of the rates of biomass accumulation. Analysis of the flux maps showed that reduced levels of phosphate in the growth medium stimulated flux through phosphoenolpyruvate carboxylase and malic enzyme, altered the balance between cytosolic and plastidic carbohydrate oxidation in favour of the plastid, and increased cell maintenance costs. We argue that plant cells respond to phosphate deprivation by reconfiguring the flux distribution through the pathways of carbohydrate oxidation to take advantage of better phosphate homeostasis in the plastid.
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Affiliation(s)
- Shyam K Masakapalli
- Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK
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