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Metabolites 2017, 7(1), 4; doi:10.3390/metabo7010004

NMR-Based Metabolic Profiling of Field-Grown Leaves from Sugar Beet Plants Harbouring Different Levels of Resistance to Cercospora Leaf Spot Disease

Food Research Institute, National Agriculture and Food Research Organization (NARO), Tsukuba 305-8642, Japan
RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Yokohama 235-0045, Japan
Hokkaido Agricultural Research Center, NARO 9-4 Shinsei-minami, Memuro 082-0081, Japan
Graduate School of Medical Life Sciences, Yokohama City University, Yokohama 230-0045, Japan
Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya 464-8601, Japan
Author to whom correspondence should be addressed.
Academic Editor: Peter Meikle
Received: 31 August 2016 / Revised: 17 January 2017 / Accepted: 23 January 2017 / Published: 26 January 2017
(This article belongs to the Special Issue Challenging Biochemical Complexities by NMR)
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Cercospora leaf spot (CLS) is one of the most serious leaf diseases for sugar beet (Beta vulgaris L.) worldwide. The breeding of sugar beet cultivars with both high CLS resistance and high yield is a major challenge for breeders. In this study, we report the nuclear magnetic resonance (NMR)-based metabolic profiling of field-grown leaves for a subset of sugar beet genotypes harbouring different levels of CLS resistance. Leaves were collected from 12 sugar beet genotypes at four time points: seedling, early growth, root enlargement, and disease development stages. 1H-NMR spectra of foliar metabolites soluble in a deuterium-oxide (D2O)-based buffer were acquired and subjected to multivariate analyses. A principal component analysis (PCA) of the NMR data from the sugar beet leaves shows clear differences among the growth stages. At the later time points, the sugar and glycine betaine contents were increased, whereas the choline content was decreased. The relationship between the foliar metabolite profiles and resistance level to CLS was examined by combining partial least squares projection to latent structure (PLS) or orthogonal PLS (OPLS) analysis and univariate analyses. It was difficult to build a robust model for predicting precisely the disease severity indices (DSIs) of each genotype; however, GABA and Gln differentiated susceptible genotypes (genotypes with weak resistance) from resistant genotypes (genotypes with resistance greater than a moderate level) before inoculation tests. The results suggested that breeders might exclude susceptible genotypes from breeding programs based on foliar metabolites profiled without inoculation tests, which require an enormous amount of time and effort. View Full-Text
Keywords: NMR; metabolomics; sugar beet (Beta vulgaris L.); Cercospora leaf spot disease NMR; metabolomics; sugar beet (Beta vulgaris L.); Cercospora leaf spot disease

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Sekiyama, Y.; Okazaki, K.; Kikuchi, J.; Ikeda, S. NMR-Based Metabolic Profiling of Field-Grown Leaves from Sugar Beet Plants Harbouring Different Levels of Resistance to Cercospora Leaf Spot Disease. Metabolites 2017, 7, 4.

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