Integrating High‐Resolution and Solid‐State Magic Angle Spinning NMR Spectroscopy and a Transcriptomic Analysis of Soybean Tissues in Response to Water Deficiency Isabel D. Coutinho, a * Tiago Bueno Moraes, a Liliane Marcia Mertz‐Henning, b Alexandre Lima Nepomuceno, b Willian Giordani, c Juliana Marcolino‐Gomes, b Silvia Santagneli d and Luiz Alberto Colnago b ABSTRACT: 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 1 H HR‐MAS and CP‐MAS 13 C{ 1 H} 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 1 H HR‐MAS. Conclusions – The integration of the 1 H 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. Additional Supporting Information may be found online in the supporting information tab for this article. Keywords: soybean; metabolic fingerprinting; HR‐MAS; SSNMR; transcriptomic Introduction Nuclear magnetic resonance (NMR) spectroscopy has been widely used to obtain qualitative, quantitative and structural information about organic molecules (Laghi et al., 2014). As an analytical technique, NMR allows the structures of unknown metabolites to be elucidated in a non‐destructive way (i.e. the analyte can be reused), and the analyses do not rely on analyte volatility, polarity, molecular weight, size, chemical structure or the sample matrix (Ramanlingam et al., 2015). NMR and chromatography methods combined with mass spectrometry (MS) are the most important analytical techniques employed for metabolomics screening. Although MS produces a greater number of detectable metabolites and is more sensitive than NMR, NMR has the advantages of high reproducibility, the lack of a requirement for prior chromatographic separation, and most importantly, it requires minimal sample preparation (Emvas et al., 2013). Direct analysis by NMR is ideally suited to high‐throughput metabolite profiling applications and has the advantage of detecting a wide range of metabolites in an inherently quantitative and unbiased manner. Of the magic angle spinning (MAS) techniques, 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 (Foston, 2014). Cross polarisation and magic angle spinning (CP‐MAS) techniques have been extensively used to investigate the cell wall and protective tissues (Dick‐Perez et al., 2011; Serra et al., 2012). In a complementary fashion, high‐ resolution magic angle spinning (HR‐MAS) has been successfully applied to analyse the soluble metabolites in intact cells and * Correspondence to: Isabel D. Coutinho, Embrapa Instrumentação, XV de Novembro, 1452, Centro, CEP 13560‐970, São Carlos, São Carlos, Brazil. Email: isadcoutinho@hotmail.com a Embrapa Instrumentação, XV de Novembro, 1452, Centro, 13560‐970, São Carlos, São Carlos, Brazil b Embrapa Soja, Rodovia Carlos João Strass, Distrito de Warta, 86001‐970, Londrina, Paraná, Brazil c Londrina State University, Rodovia Celso Garcia Cid, Km 380, 86051‐900, Londrina, Paraná, Brazil d Institute of Chemistry, University of São Paulo State, Rua Prof. Francisco Degni, 55, 14800‐060, Araraquara, São Paulo, Brazil Phytochem. Anal. 2017, 28, 529–540 Copyright © 2017 John Wiley & Sons, Ltd. Research Article Received: 27 December 2016, Revised: 18 May 2017, Accepted: 18 May 2017 Published online in Wiley Online Library: 19 July 2017 (wileyonlinelibrary.com) DOI 10.1002/pca.2702 529