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A novel method for single-grain-based metabolic profiling of Arabidopsis seed
Authors:Yuji Sawada  Hirokazu Tsukaya  Yimeng Li  Muneo Sato  Kensuke Kawade
Affiliation:1.RIKEN Center for Sustainable Resource Science,Yokohama,Japan;2.Department of Biological Sciences, Graduate School of Science,The University of Tokyo,Tokyo,Japan;3.Okazaki Institute for Integrative Bioscience, National Institutes of Natural Sciences,Okazaki,Japan;4.National Institute for Basic Biology, National Institutes of Natural Sciences,Okazaki,Japan;5.Department of Basic Biology, School of Life Science,Graduate University for Advanced Studies (SOKENDAI),Okazaki,Japan
Abstract:

Introduction

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.

Objectives

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

Methods

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).

Results

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.

Conclusion

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.
Keywords:
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