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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References
Fernie AR, Geigenberger P, Stitt M (2005) Flux an important, but neglected, component of functional genomics. Curr Opin Plant Biol 8:174–182
Batista Silva W, Daloso DM, Fernie AR et al (2016) Can stable isotope mass spectrometry replace radiolabelled approaches in metabolic studies? Plant Sci 249:59–69
Salon C, Avice J-C, Colombié S et al (2017) Fluxomics links cellular functional analyses to whole-plant phenotyping. J Exp Bot 68:2083–2098
António C, Päpke C, Rocha M et al (2016) Regulation of primary metabolism in response to low oxygen availability as revealed by carbon and nitrogen isotope redistribution. Plant Physiol 170:43–56
Centeno DC, Osorio S, Nunes-Nesi A et al (2011) Malate plays a crucial role in starch metabolism, ripening, and soluble solid content of tomato fruit and affects postharvest softening. Plant Cell 23:162–184
Araújo WL, Nunes-Nesi A, Trenkamp S et al (2008) Inhibition of 2-oxoglutarate dehydrogenase in potato tuber suggests the enzyme is limiting for respiration and confirms its importance in nitrogen assimilation. Plant Physiol 148:1782–1796
Schwender J, Shachar-Hill Y, Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus. J Biol Chem 281:34040–34047
Sriram G, Fulton DB, Shanks JV (2007) Flux quantification in central carbon metabolism of Catharanthus roseus hairy roots by 13C labeling and comprehensive bondomer balancing. Phytochemistry 68:2243–2257
Masakapalli SK, Bryant FM, Kruger NJ, Ratcliffe RG (2014) 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. Plant J 78:964–977
Alonso AP, Val DL, Shachar-Hill Y (2011) Central metabolic fluxes in the endosperm of developing maize seeds and their implications for metabolic engineering. Metab Eng 13:96–107
Daloso DM, Antunes WC, Pinheiro DP et al (2015) Tobacco guard cells fix CO2 by both Rubisco and PEPcase while sucrose acts as a substrate during light-induced stomatal opening. Plant Cell Environ 38:2353–2371
Daloso DM, Williams TCR, Antunes WC et al (2016) Guard cell-specific upregulation of sucrose synthase 3 reveals that the role of sucrose in stomatal function is primarily energetic. New Phytol 209:1470–1483
Daloso DM, Müller K, Obata T et al (2015) Thioredoxin, a master regulator of the tricarboxylic acid cycle in plant mitochondria. Proc Natl Acad Sci U S A 112:E1392–E1400
Tcherkez G, Mahe A, Gauthier P et al (2009) In folio respiratory fluxomics revealed by 13C isotopic labeling and H/D isotope effects highlight the noncyclic nature of the tricarboxylic acid “cycle” in illuminated leaves. Plant Physiol 151:620–630
Nargund S, Misra A, Zhang X et al (2014) Flux and reflux: metabolite reflux in plant suspension cells and its implications for isotope-assisted metabolic flux analysis. Mol BioSyst 10:1496–1508
Lonien J, Schwender J (2009) Analysis of metabolic flux phenotypes for two Arabidopsis mutants with severe impairment in seed storage lipid synthesis. Plant Physiol 151:1617–1634
Allen DK, Ohlrogge JB, Shachar-Hill Y (2009) The role of light in soybean seed filling metabolism. Plant J 58:220–234
Ma F, Jazmin LJ, Young JD, Allen DK (2014) Isotopically nonstationary 13C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation. Proc Natl Acad Sci U S A 111:16967–16972
Szecowka M, Heise R, Tohge T et al (2013) Metabolic fluxes in an illuminated Arabidopsis rosette. Plant Cell 25:694–714
Arrivault S, Obata T, Szecówka M et al (2017) Metabolite pools and carbon flow during C4 photosynthesis in maize: 13CO 2 labeling kinetics and cell type fractionation. J Exp Bot 68:283–298
Ishihara H, Obata T, Sulpice R et al (2015) Quantifying protein synthesis and degradation in arabidopsis by dynamic 13CO2 labeling and analysis of enrichment in individual amino acids in their free pools and in protein. Plant Physiol 168:74–293
Antoniewicz MR (2015) Methods and advances in metabolic flux analysis: a mini-review. J Ind Microbiol Biotechnol 42:317–325
Schwender J (2009) Isotopic steady-state flux analysis. In: Plant Metab. Networks, pp 1–331
Kruger NJ, Le Lay P, Ratcliffe RG (2007) Vacuolar compartmentation complicates the steady-state analysis of glucose metabolism and forces reappraisal of sucrose cycling in plants. Phytochemistry 68:2189–2196
Sweetlove LJLJ, Fernie AR (2005) Regulation of metabolic networks:understanding metabolic complexity in the systems biology era. New Phytol 168:9–23
Ratcliffe RG, Shachar-Hill Y (2006) Measuring multiple fluxes through plant metabolic networks. Plant J 45:490–511
Luedemann A, Strassburg K, Erban A, Kopka J (2008) TagFinder for the quantitative analysis of gas chromatography-mass spectrometry (GC-MS)-based metabolite profiling experiments. Bioinformatics 24:732–737
Weindl D, Wegner A, Hiller K (2016) MIA: Non-targeted mass isotopolome analysis. Bioinformatics 32:2875–2876
Huang X, Chen Y-J, Cho K et al (2014) X13CMS: Global tracking of isotopic labels in untargeted metabolomics. Anal Chem 86:1632–1639
Lisec J, Schauer N, Kopka J et al (2006) Gas chromatography mass spectrometry–based metabolite profiling in plants. Nat Protoc 1:387–396
Zamboni N, Fendt S-M, Rühl M, Sauer U (2009) 13C-based metabolic flux analysis. Nat Protoc 4:878–892
Heise R, Arrivault S, Szecowka M et al (2014) Flux profiling of photosynthetic carbon metabolism in intact plants. Nat Protoc 9:1803–1824
Huege J, Goetze J, Dethloff F et al (2014) Quantification of stable isotope label in metabolites via mass spectrometry. In: Hicks GR, Robert S (eds) Plant Chem. Genomics Methods Protoc, Methods Mol. Biol, vol 1056. Humana Press, Totowa, NJ, pp 11–17
Fernie AR, Morgan JA (2013) Analysis of metabolic flux using dynamic labelling and metabolic modelling. Plant Cell Environ 36:1738–1750
Shachar-hill Y, Morgan JA, Grady JO (2012) Metabolic cartography: experimental quantification of metabolic fluxes from isotopic labelling studies. J Exp Bot 63:2293–2308
Kruger NJ, Ratcliffe RG (2009) Insights into plant metabolic networks from steady-state metabolic flux analysis. Biochimie 91:697–702
Schwender J, Ohlrogge J, Shachar-Hill Y (2004) Understanding flux in plant metabolic networks. Curr Opin Plant Biol 7:309–317
Shachar-Hill Y (2013) Metabolic network flux analysis for engineering plant systems. Curr Opin Biotechnol 24:247–255
Williams TCR, Miguet L, Masakapalli SK et al (2008) Metabolic network fluxes in heterotrophic Arabidopsis cells: stability of the flux distribution under different oxygenation conditions. Plant Physiol 148:704–718
Williams TCR, Poolman MG, Howden AJM et al (2010) A genome-scale metabolic model accurately predicts fluxes in central carbon metabolism under stress conditions. Plant Physiol 154:311–323
Cheung CYM, Poolman MG, Fell DA et al (2014) A diel flux balance model captures interactions between light and dark metabolism during day-night cycles in C3 and Crassulacean acid metabolism leaves. Plant Physiol 165:917–929
Nikoloski Z, Perez-Storey R, Sweetlove LJ (2015) Inference and prediction of metabolic network fluxes. Plant Physiol 169:1443–1455
Sajitz-Hermstein M, Töpfer N, Kleessen S et al (2016) IReMet-flux: Constraint-based approach for integrating relative metabolite levels into a stoichiometric metabolic models. Bioinformatics 32:i755–i762
Shi H, Schwender J (2016) Mathematical models of plant metabolism. Curr Opin Biotechnol 37:143–152
Nargund S, Sriram G (2014) Mathematical modeling of isotope labeling experiments for metabolic flux analysis, Plant Metab Methods Protoc Methods Mol Biol, pp 85–108
Van Winden WA, Wittmann C, Heinzle E, Heijnen JJ (2002) Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol Bioeng 80:477–479
Jungreuthmayer C, Neubauer S, Mairinger T et al (2015) ICT: Isotope correction toolbox. Bioinformatics 32:154–156
Millard P, Letisse F, Sokol S, Portais JC (2012) IsoCor: Correcting MS data in isotope labeling experiments. Bioinformatics 28:1294–1296
Huege J, Sulpice R, Gibon Y et al (2007) GC-EI-TOF-MS analysis of in vivo carbon-partitioning into soluble metabolite pools of higher plants by monitoring isotope dilution after 13CO2 labelling. Phytochemistry 68:2258–2272
Acknowledgments
Scholarships granted by the Coordination for the Improvement of Higher Level Personnel (CAPES) to V.F.L. and the National Council for Scientific and Technological Development (CNPq-Brazil) to L.P.S. are gratefully acknowledged. The Foundation for Support of Scientific and Technological Development of Ceará (FUNCAP) grant number AEP-0128-00092.01.00/17 to D.M.D. is gratefully acknowledged.
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Lima, V.F., de Souza, L.P., Williams, T.C.R., Fernie, A.R., Daloso, D.M. (2018). Gas Chromatography–Mass Spectrometry-Based 13C-Labeling Studies in Plant Metabolomics. In: António, C. (eds) Plant Metabolomics. Methods in Molecular Biology, vol 1778. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7819-9_4
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DOI: https://doi.org/10.1007/978-1-4939-7819-9_4
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