Abstract
Plant growth is an important process in physiological as well as ecological respect and a number of metabolic parameters (elemental ratios as well as steady-state levels of individual metabolites) have been demonstrated to reflect this process on the whole plant level. Since plant growth is highly localized and is the result of a complex interplay of metabolic activities in sink and source organs, we propose that ratios in metabolite levels of sink and source organs are particularly well suited to characterize this process. To demonstrate such a connection, we studied organ-specific metabolite ratios from Lotus japonicus treated with mineral nutrients, salt stress or arbuscular mycorrhizal fungi. The plants were displaying a wide range of biomass and of flower/biomass ratios. In the analysis of our data we looked for correlations between shifts in sink/source metabolite ratios and plant productivity (biomass accumulated at the time of harvest). In addition we correlated shifts in metabolite ratios comparing competing generative and vegetative sink organs with shifts in productivity of the two organs (changes in flower/biomass ratios). In our analyses we observed clear shifts of carbohydrates and of compounds connected to nitrogen metabolism in favour of sink organs of particularly high productivity. These shifts were in agreement with general differences in metabolite steady-state levels when comparing sink and source organs. Our findings suggest that differentiation of sink and source organs during sampling for metabolomic experiments substantially increases the amount of information obtained from such experiments.
Similar content being viewed by others
References
Ayre BG (2011) Membrane-transport systems for sucrose in relation to whole-plant carbon partitioning. Mol Plant 4:377–394
Carles CC, Fletcher JC (2003) Shoot apical meristem maintenance: the art of a dynamic balance. Trends Plant Sci 8:394–401
Desbrosses GG, Kopka J, Udvardi MK (2005) Lotus japonicus metabolic profiling. Development of gas chromatography–mass spectrometry resources for the study of plant–microbe interactions. Plant Physiol 137:1302–1318
Elser JJ, Fagan WF, Kerkhoff AJ, Swenson NG, Enquist BJ (2010) Biological stoichiometry of plant production: metabolism, scaling and ecological response to global change. New Phytol 186:593–608
Fester T, Fetzer I, Bucher S, Lucas R, Rillig MC, Härtig C (2011) Towards a systemic metabolic signature of the arbuscular mycorrhizal interaction. Oecologia 167:913–924
Hollander M, Wolfe DA (1973) Nonparametric statistical methods. Wiley, New York
Inokuchi R, Kuma K-I, Miyata T, Okada M (2002) Nitrogen-assimilating enzymes in land plants and algae: phylogenic and physiological perspectives. Physiol Plant 116:1–11
Iqbal N, Nazar R, Khan MIR, Masood A, Khan NA (2011) Role of gibberellins in regulation of source–sink relations under optimal and limiting environmental conditions. Curr Sci 100:998–1007
Jeong MJ, Jiang H, Chen HS, Tsai CJ, Harding SA (2004) Metabolic profiling of the sink-to-source transition in developing leaves of Quaking Aspen. Plant Physiol 136:3364–3375
Katahira R, Ashihara H (2006) Profiles of purine biosynthesis, salvage and degradation in disks of potato (Solanum tuberosum L.) tubers. Planta 225:115–126
Kopka J, Schauer N, Krueger S, Birkemeyer C, Usadel B, Bergmüller E, Dörmann P, Weckwerth W, Gibon Y, Stitt M, Willmitzer L, Fernie AR, Steinhauser D (2005) GMD@CSB.DB: the Golm Metabolome Database. Bioinformatics 21:1635–1638
Kuhn M, Wing J, Weston S, Williams A, Keefer C, Engelhardt A (2012) caret: classification and regression training. R package version 5.15-023. http://CRAN.R-project.org/package=caret
Kusano M, Fukushima A, Redestig H, Saito K (2011) Metabolomic approaches toward understanding nitrogen metabolism in plants. J Exp Bot 62:1439–1453
Lalonde S, Tegeder M, Throne-Holst M, Frommer WB, Patrick JW (2003) Phloem loading and unloading of sugars and amino acids. Plant Cell Environ 26:37–56
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
Mardia KV, Kent JT, Bibby JM (1979) Multivariate analysis. Academic Press, London
Martens H, Naes T (1989) Multivariate calibration. Wiley, New York
Matsuda F, Hirai MY, Sasaki E, Akiyama K, Yonekura-Sakakibara K, Provart NJ, Sakurai T, Shimada Y, Saito K (2010) AtMetExpress development: a phytochemical atlas of Arabidopsis development. Plant Physiol 152:566–578
Matzek V, Vitousek PM (2009) N:P stoichiometry and protein : RNA ratios in vascular plants: an evaluation of the growth-rate hypothesis. Ecol Lett 12:765–771
Morgenthal K, Wienkoop S, Scholz M, Selbig J, Weckwerth W (2005) Correlative GC-TOF-MS-based metabolite profiling and LC-MS-based protein profiling reveal time-related systemic regulation of metabolite–protein networks and improve pattern recognition for multiple biomarker selection. Metabolomics 1:109–121
Naes T, Mevik BH (2001) Understanding the collinearity problem in regression and discriminant analysis. J Chemom 15:413–426
Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H (2012). vegan: community ecology package. R package version 2.0-4. http://CRAN.R-project.org/package=vegan
R development core team (2012) R: A language and environment for statistical computing. http://www.R-project.org
Rivas-Ubach A, Sardans J, Pérez-Trujillo M, Estiarte M, Peñuelas J (2012) Strong relationship between elemental stoichiometry and metabolome in plants. PNAS 109:4181–4186
Sadras VO, Denison RF (2009) Do plant parts compete for resources? An evolutionary viewpoint. New Phytol 183:565–574
Sanchez DH, Lippold F, Redestig H, Hannah MA, Erban A, Krämer U, Kopka J, Udvardi MK (2008) Integrative functional genomics of salt acclimatization in the model legume Lotus japonicus. Plant J 53:973–987
Sardans J, Penuelas J, Rivas-Ubach A (2011) Ecological metabolomics: overview of current developments and future challenges. Chemoecology 21:191–225
Schauer N, Steinhauser D, Strelkov S, Schomburg D, Allison G, Moritz T, Lundgren K, Roessner-Tunali U, Forbes MG, Willmitzer L, Fernie AR, Kopka J (2005) GC–MS libraries for the rapid identification of metabolites in complex biological samples. FEBS Lett 579:1332–1337
Schmitz G, Theres K (2005) Shoot and inflorescence branching. Curr Opin Plant Biol 8:506–511
Schurr U, Walter A, Rascher U (2006) Functional dynamics of plant growth and photosynthesis—from steady-state to dynamics—from homogeneity to heterogeneity. Plant Cell Environ 29:340–352
Slewinski TL, Braun DM (2010) Current perspectives on the regulation of whole-plant carbohydrate partitioning. Plant Sci 178:341–349
Szabados L, Savouré A (2010) Proline: a multifunctional amino acid. Trends Plant Sci 15:89–97
Tarpley L, Duran AL, Kebro TH, Sumner LW (2005) Biomarker metabolites capturing the metabolite variance present in a rice plant developmental period. BMC Plant Biol 5:8
Tegeder M, Rentsch D (2010) Uptake and partitioning of amino acids and peptides. Mol Plant 3:997–1011
Tikunov Y, Lommen A, de Vos CHR, Verhoeven HA, Bino RJ, Hall RD, Lindhout P, Bovy AG (2005) A novel approach for non-targeted data analysis for metabolomics: large-scale profiling of tomato fruit volatiles. Plant Physiol 139:1125–1137
Urbanczyk-Wochniak E, Baxter C, Kolbe A, Kopka J, Sweetlove LJ, Fernie AR (2005) Profiling of diurnal patterns of metabolite and transcript abundance in potato (Solanum tuberosum) leaves. Planta 221:891–903
Wind J, Smeekens S, Hanson J (2010) Sucrose: metabolite and signaling molecule. Phytochemistry 71:1610–1614
Wold S, Sjöström M, Eriksson L (2001) PLS-regression: a basic tool of chemometrics. Chemom Intell Lab Syst 58:109–130
Zrenner R, Riegler H, Cathleen R, Marquard CR, Lange PR, Geserick C, Bartosz CE, Celine T, Chen CT, Slocum RD (2009) A functional analysis of the pyrimidine catabolic pathway in Arabidopsis. New Phytol 183:117–132
Acknowledgments
The authors thank Elke Häusler and Angelika Wichmann for excellent technical assistance and our colleagues from the “Versuchstation Bad Lauchstädt” for plant cultivation.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Fig. S1 PCAs of sink/source- and flower/source metabolite ratios from experiment I, II and III. Fertilized plants are separated from all other plants along the first component. The remaining treatments (control, salt stress, mycorrhization) are separated from each other in varying order and to varying degree along the second component. The amount of variation explained by each PC is given in brackets in axes’ labels. Corresponding PLS-DAs are given in Fig. 4.
Fig. S2 Metabolite partitioning between competing sink organs. PCA of flower/sink metabolite ratios in experiment I (orange), II (blue), and III (green). The position of the mean of each group is indicated by a filled symbol. Filled stars represent the location of the mean of all samples belonging to a particular experiment. The amount of variation explained by each PC is given in brackets in axes’ labels. A corresponding PLS-DA is given in Fig. 6.
Rights and permissions
About this article
Cite this article
Fester, T., Fetzer, I. & Härtig, C. A core set of metabolite sink/source ratios indicative for plant organ productivity in Lotus japonicus . Planta 237, 145–160 (2013). https://doi.org/10.1007/s00425-012-1759-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00425-012-1759-y