Integrating High-Resolution and Solid-State Magic Angle Spinning NMR Spectroscopy and a Transcriptomic Analysis of Soybean Tissues in Response to Water Deficiency

• Autor(a) principal: Coutinho, Isabel D.
• Data de Publicação: 2017
• Outros Autores: Moraes, Tiago Bueno, Mertz-Henning, Liliane Marcia, Nepomuceno, Alexandre Lima, Giordani, Willian, Marcolino-Gomes, Juliana, Santagneli, Silvia, Colnago, Luiz Alberto
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1002/pca.2702; http://hdl.handle.net/11449/220882
• topic: HR-MAS; metabolic fingerprinting; soybean; SSNMR; transcriptomic

Introduction: Solid-state NMR (SSNMR) spectroscopy methods provide chemical environment and ultrastructural details that are not easily accessible by other non-destructive, high-resolution spectral techniques. High-resolution magic angle spinning (HR-MAS) has been widely used to obtain the metabolic profile of a heterogeneous sample, combining the resolution enhancement provided by MAS in SSNMR with the shimming and locking procedures in liquid-state NMR. Objective: In this work, we explored the feasibility of using the HR-MAS and SSNMR techniques to identify metabolic changes in soybean leaves subjected to water-deficient conditions. Methodology: Control and water-deficient soybean leaves were analysed using one-dimensional (1D) HR-MAS and SSNMR. Total RNA was extracted from the leaves for the transcriptomic analysis. Results: The 1H HR-MAS and CP-MAS 13C{1H} spectra of soybean leaves grown with and without water deficiency stress revealed striking differences in metabolites. A total of 30 metabolites were identified, and the impact of water deficiency on the metabolite profile of soybean leaves was to induce amino acid synthesis. High expression levels of genes required for amino acid biosynthesis were highly correlated with the compounds identified by 1H HR-MAS. Conclusions: The integration of the 1H HR-MAS and SSNMR spectra with the transcriptomic data provided a complete picture of the major changes in the metabolic profile of soybeans in response to water deficiency. Copyright © 2017 John Wiley & Sons, Ltd.