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A novel method for single-grain-based metabolic profiling of Arabidopsis seed

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In plant metabolomics, metabolite contents are often normalized by sample weight. However, accurate weighing of very small samples, such as individual Arabidopsis thaliana seeds (approximately 20 µg), is difficult, which may lead to irreproducible results.


We aimed to establish alternative normalization methods for seed-grain-based comparative metabolomics of A. thaliana.


Arabidopsis thaliana seeds were assumed to have a prolate spheroid shape. Using a microscope image of each seed, the lengths of major and minor axes were measured by fitting a projected 2-dimensional shape of each seed as an ellipse. Metabolic profiles of individual diploid or tetraploid A. thaliana seeds were measured by our highly sensitive protocol (“widely targeted metabolomics”) that uses liquid chromatography coupled with tandem quadrupole mass spectrometry. Mass spectrometric analysis of 1 µL of solution extract identified more than 100 metabolites. The data were normalized by various seed-size measures, including seed volume (single-grain-based analysis). For comparison, metabolites were extracted from 4 mg of diploid and tetraploid A. thaliana seeds and their metabolic profiles were analyzed by normalization of weight (weight-based analysis).


A small number of metabolites showed statistically significant differences in the single-grain-based analysis compared to weight-based analysis. A total of 17 metabolites showed statistically different accumulation between ploidy types with similar fold changes in both analyses.


Seed-size measures obtained by microscopic imaging were useful for data normalization. Single-grain-based analysis enables evaluation of metabolism of each seed and elucidates the metabolic profiles of precious bioresources by using small amounts of samples.

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We thank Ms. Akane Sakata and Mr. Yutaka Yamada for sample preparation and information technology support, respectively. This work was supported by the Japan Society for the Promotion of Science (Grants-in-Aid for Creative Scientific Research and Scientific Research A), Ministry of Education, Culture, Sports, Science and Technology, Japan (Scientific Research on Priority Areas and Scientific Research on Innovative Areas), and Mitsubishi Foundation.

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Correspondence to Masami Yokota Hirai.

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All the authors declare that they have no conflict of interest.

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This article does not contain any studies with human participants performed by any of the authors.

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Yuji Sawada, Hirokazu Tsukaya and Kensuke Kawade have contributed equally to this work.

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Supplementary Figure 1—Schematic diagram of data pre-processing (PDF 195 KB)


Supplementary Figure 2—Boxplot for z-scores of log2-transformed data. Differences in the median values and distribution of metabolomic data between diploid (DP) and autotetraploid (TP) A. thaliana seeds were analyzed in single-grain-based and weight-based analyses to compare methods of normalization (PDF 79 KB)


Supplementary Figure 3—Volcano plot based on weight-based data. The weight-normalized autotetraploid data were divided by those of diploid data and transformed into log2 values. The metabolites exhibiting statistically significant differences between diploid and autotetraploid seeds (Welch’s t test, p < 0.05) are shown as red dots with metabolite annotations. The other metabolites are shown as gray dots (PDF 293 KB)


Supplementary Figure 4—Betaine and sucrose contents per grain and per weight. Sample No. corresponds to that in Supplementary Table S1. Experimental groups are indicated by color. Black, diploid and single-grain-based; red, tetraploid and single-grain-based; green, diploid and weight-based; blue, tetraploid and weight-based (PDF 8 KB)

Supplementary material 5 (XLSX 570 KB)

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Sawada, Y., Tsukaya, H., Li, Y. et al. A novel method for single-grain-based metabolic profiling of Arabidopsis seed. Metabolomics 13, 75 (2017).

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