High-Resolution Magic-Angle-Spinning NMR and Magnetic

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jafc.7b04340. ... PDF. jf7b04340_si_001.pdf...
6 downloads 5 Views 3MB Size
Download PDF
Article Cite This: J. Agric. Food Chem. 2018, 66, 2580−2588

pubs.acs.org/JAFC

High-Resolution Magic-Angle-Spinning NMR and Magnetic Resonance Imaging Spectroscopies Distinguish Metabolome and Structural Properties of Maize Seeds from Plants Treated with Different Fertilizers and Arbuscular mycorrhizal fungi Pierluigi Mazzei,*,† Vincenza Cozzolino,‡ and Alessandro Piccolo*,†,‡ †

Centro Interdipartimentale per la Risonanza Magnetica Nucleare per l’Ambiente, l’Agro-Alimentare ed i Nuovi Materiali (CERMANU) and ‡Dipartimento di Agraria, Università di Napoli Federico II, Via Università 100, 80055 Portici, Italy S Supporting Information *

ABSTRACT: Both high-resolution magic-angle-spinning (HRMAS) and magnetic resonance imaging (MRI) NMR spectroscopies were applied here to identify the changes of metabolome, morphology, and structural properties induced in seeds (caryopses) of maize plants grown at field level under either mineral or compost fertilization in combination with the inoculation by arbuscular mycorrhizal fungi (AMF). The metabolome of intact caryopses was examined by HRMAS-NMR, while the morphological aspects, endosperm properties and seed water distribution were investigated by MRI. Principal component analysis (PCA) was applied to evaluate 1H CPMG (Carr-Purcel-Meiboom-Gill) HRMAS spectra as well as several MRI-derived parameters (T1, T2, and self-diffusion coefficients) of intact maize caryopses. PCA score-plots from spectral results indicated that both seeds metabolome and structural properties depended on the specific field treatment undergone by maize plants. Our findings show that a combination of multivariate statistical analyses with advanced and nondestructive NMR techniques, such as HRMAS and MRI, enables the evaluation of the effects induced on maize caryopses by different fertilization and management practices at field level. The spectroscopic approach adopted here may become useful for the objective appraisal of the quality of seeds produced under a sustainable agriculture. KEYWORDS: HRMAS, MRI, metabolomics, maize caryopses, fertilization, compost, arbuscular mycorrhizal fungi

■

INTRODUCTION The identification of efficient and sustainable strategies to promote plants growth is a major challenge in the agrofood sector, especially for the most important food crops such as maize, wheat and rice.1 A traditional practice is the amendment to soils of mineral fertilizers containing the essential macronutrients, whose scarcity may otherwise represent a growth limiting-factor for plants.2 Large if not excessive amount of mineral fertilizers are commonly applied to maintain high crop yields, and compensate both the progressive P immobilization3 in soils and the consumption due to microbial activity.4 However, this leads to costly and environmentally negative conditions.5 An alternative to traditional fertilizers is the amendment of nutrients in their organic form6 such as in compost that is a biochemically stable organic material rich in organic P and N forms.7−10 An increase in plant nutrient uptake is promoted by soil inoculation with beneficial microorganisms, such as arbuscular mycorrhizal fungi (AMF), which enhance the degree of sustainability in industrial agriculture.11 AMF are widespread in most terrestrial ecosystems where they form symbiotic associations with the majority of plants. AMF protect plants against pathogens and facilitate nutrients uptake through several mechanisms including the formation of an extensive extraradical mycelium, the stimulation of roots elongation, and the induced solubilization of poorly bioavailable nutrients.12 In fact, AMF are regarded as a means to reduce the excessive © 2018 American Chemical Society

supply of fertilizers, thus enhancing, directly and indirectly, the natural soil fertility in agricultural ecosystems.13 Despite the attempts to introduce sustainable practices in agriculture, an exhaustive knowledge is still lacking on the molecular mechanisms that make the alternative practices effective and how they influence plants metabolic responses and their products. We believe that the use of advanced molecular analytical techniques such as NMR spectroscopy may contribute to identify and understand the changes occurring in plants due to field treatments with innovative sustainable practices. In particular, HRMAS (high resolution magic angle spinning) and MRI (magnetic resonance imaging) represent nondestructive NMR techniques that may provide direct molecular and structural information on plant fresh samples.14−16 HRMAS retains the advantages of both traditional solid- and liquid-state NMR techniques and allows the direct examination of whole fresh samples without the need of preliminary extractions.17,18 Moreover, HRMAS 1D spectra were proved useful for the metabolomics analysis of biological samples and the dynamic evaluation of treatment-dependent metabolic processes occurring in plants.16,19−22 With regard to maize plants, NMR-based metabolomics was employed to study Received: Revised: Accepted: Published: 2580

September 21, 2017 November 24, 2017 January 11, 2018 January 11, 2018 DOI: 10.1021/acs.jafc.7b04340 J. Agric. Food Chem. 2018, 66, 2580−2588

Article

Journal of Agricultural and Food Chemistry genetically modified samples23−25 and to monitor the influence exerted by stress conditions such as excess salts26 or nitrogen deficiency.27 As a complementary NMR technique, MRI enables acquisition of morphological and anatomical images of intact samples at a μm level and permits to extrapolate structural information based on mobility and compartmentalization of constitutive water.28 Currently, MRI is mainly used on mammalians within medical, diagnostic, and pharmaceutical applications. In fact, MRI is a consolidated analytical method for the rapid noninvasive evaluation of changes in tissues morphology and occurrence of specific diseases such as cancers development.28,29 Despite its specific large potential, MRI is still underutilized in the research on plants and food.30,31 Only few works have so far reported on MRI applications for maize plants ad seeds. For example, the effects of steeping processes on maize caryopses were followed by 2D images and MRI moisture profile,32 while 1 H MRI was applied to investigate the cell water balance of maize plants during osmotic stress.33 MRI images and relaxation times were used to examine changes in the physical state of water of maize seeds when dried at subzero temperatures.34 MRI was applied to design a physical model of heat and mass transfer in maize caryopses to assess the dehydration degree and quality degradation of seeds during fluidized-bed drying.35 The aim of this work was thus to apply HRMAS and MRI spectroscopies to evaluate the effects on maize caryopses of field amendments with mineral or compost fertilization and of inoculation with a selected AMF consortium.

■

located in the center of each plot. A sufficient number (>100) of caryopses were gently removed from cobs of each treatment and stored at −80 °C until NMR analysis. Maize caryopses for MRI analysis were directly loaded into a 10 mm MRI tube after a 30 min of defrosting time. Maize samples for HRMAS analysis were prepared by cutting longitudinally the pericarp and aleurone outer layers of each caryopsis and collecting about 15 mg of fresh material with a spongy consistency. In particular, the latter was prevalently composed by the endosperm that typically represents the 69−83% of maize caryopsis dry weight.36 Each HRMAS analytical replicate corresponded to material isolated from a single seed. The material was then packed into a 4 mm zirconia HRMAS rotor, fitted with a perforated Teflon insert, soaked with approximately 15 μL of D2O solution (99.8% D2O/H2O, Armar Chemicals), and sealed with a Kel-F cap (Rototech-Spintech GmbH). A spin rate of 5000 Hz ± 1 was adopted to rotate samples. Four replicates for each field parcel were analyzed, thus resulting in 12 total replicates for each plant treatment. HRMAS NMR Experiments. All HRMAS NMR experiments were conducted at 298 ± 1 K on a 400 MHz Bruker Avance magnet (Bruker Biospin, Rheinstetten, Germany), equipped with a Bruker 1H−13C HRMAS probe working at a 1H frequency of 400.13 MHz. A CarrPurcel-Meiboom-Gill (CPMG) NMR pulse sequence was used to acquire 1H spectra of maize caryopses. This sequence was preferred to a conventional 1H acquisition since it allowed application of a T2-filter to enable a selective suppression of overlapping signals due to compounds with short spin−spin (T2) relaxation time. The experiments were acquired by setting 2 s of recycle delay, a 90° pulse length ranging within 6.5 and 8.6 μs, 16 384 points, a spectral width of 16 ppm (6410.3 Hz), and 256 scans. In particular, the CPMG pulse sequence, that is based on a spin−echo method, was performed with a total spin−spin relaxation delay (2nτ) of 320 ms, including single optimal echo times (τ) of 2 ms. The signal of residual water was suppressed by an on-resonance presaturation during thermal equilibrium delay. Structural identification of maize seeds metabolites was assessed by 2D NMR experiments, consisting in homonuclear 1 H−1H COSY (correlation spectroscopy), TOCSY (total correlationspectroscopy), and J-RES as well as heteronuclear 1H−13C HSQC (heteronuclear single-quantum correlation) and HMBC (heteronuclear multiple bond correlation). All 2D experiments had a spectral width of 16 (6410.3 Hz) and 300 (30186.8 Hz) ppm for 1H and 13C nuclei, respectively, and a time domain of 2048 points (F2) and 256 experiments (F1). In particular, all homonuclear 2D spectra consisted in 16 dummy scans and 64 total transients and, in case of TOCSY experiment, a mixing time of 80 ms and a trim pulse length of 2500 ms. HSQC and HMBC heteronuclear experiments were acquired with 16 dummy scans, 80 total transients, and 0.5 μs of trim pulse length. The optimization of these heteronuclear experiments was conducted by taking into account 145 and 6.5 Hz as optimal 1H−13C short and long-range J-couplings, respectively. A phase and baseline correction was applied to all mono- and bidimensional spectra. 1H 1D spectra were Fourier transformed without any apodization and by applying a two-fold zero-filling. NMR data were processed by using both Bruker Topspin Software (v 2.1, BrukerBiospin, Rheinstetten, Germany) and MNOVA Software (v.9.0, Mestrelab Research, Santiago de Compostela, Spain). Magnetic Resonance Imaging (MRI) Experiments. All MRI experiments were performed at 298 ± 1K on a 300 MHz Bruker Avance wide-bore magnet (BrukerBiospin, Rheinstetten, Germany) and equipped with a 10 mm μ-imaging MICRO 5 probe working at a 1 H frequency of 300.13 MHz. T2 experiments were performed by applying an echo-train MSME (multi-slice-multi-echo) pulse sequence, setting 3 s of recycle delay, 10 scans, and acquiring 16 experiments with an increasing number of spin−echoes (total spin−echo time ranging within 10.57 and 169.12 ms). Spin density measurements were performed by considering the images obtained at the shortest echodelay (10.57 ms) in MSME experiments, whereas T2-weighted images were achieved by selecting a total echo-delay of 42.3 ms. T1 measurements were acquired by RARE (rapid acquisition with relaxation enhancement) experiments, which consisted of 10 scans, a rare-factor of 2, and increasing repetition times ranging within 0.188

MATERIALS AND METHODS

Field Experiment. Caryopses were collected from maize plants (Zea mays L. cv 3321 Limagrain) of field experiments conducted at the Experimental Station of University of Naples Federico II, near Castel Volturno (CE), Campania, Italy. The site is governed by a Mediterranean climate, with moist cool winters and warm dry summers. The soil was classified as Typic Vertic Xerofluvent, with a clayey texture (22% sand, 28% silt, and 50% clay). The field experiment consisted in 5 × 8 m2 plots, which received the following treatments: (i) control (M−), (ii) 15 t ha−1 of compost made with organic urban wastes (COM), (iii) a mineral fertilizer (MIN) (N250P150K160) composed by 250 kg ha−1 of N (as urea), 150 kg ha−1 of P2O5 (as Ca(H2PO4)2), and 160 kg ha−1 of K (as K2SO4). Moreover, soils were also treated with AMF inoculation (+) (arbuscular mycorrhizal fungi, as a commercial fungal inoculum), either (iv) without (M+) or (v) with mineral fertilizer (MIN+) or (vi) compost (COM+). The commercial inoculum contained 50 AMF infective propagules g−1 of product (information provided by the supplier) and consisted of a mixture of 50% Rhizophagus irregularis and 50% Funneliformis mosseae (previously named Glomus intraradices and Glomus mosseae, respectively) (AEGIS, Italpollina, Rivoli Veronese, Italy). This microbial mix was defined on the basis of preliminary field trial-tests (data not shown), which selected the combination with the greatest adaptability and performance. Each treatment was replicated three times, resulting in 18 total experimental plots, which were randomly distributed (complete randomized design). Mineral fertilizer and compost were manually broadcast and incorporated in soil. The compost was broadcast 3 weeks before sowing, while the inocula (20 kg ha−1) were applied during sowing by a seed-drill microgranulator. Maize seeds were linearly sowed at 10 cm distance, while the distance among rows was 75 cm. The plant density corresponded to 7 plants per m2. Caryopses Collection and Sample Preparation. A representative number of cobs per plot were harvested during the milky ripeness stage of maize seeds (80 days after sowing) by sampling only plants 2581

DOI: 10.1021/acs.jafc.7b04340 J. Agric. Food Chem. 2018, 66, 2580−2588

Article

Journal of Agricultural and Food Chemistry

Figure 1. 1H HRMAS CPMG NMR spectrum of maize seed (M− sample). The proton spectral regions confined within the two gray rectangles (1 and 2) have been magnified on top sides of the figure. The labels indicate assignment of the most intense signals detected in all spectra. (F, fructose; G, glucose; LA, lactic acid; S, sucrose; UMP, uridinmonophosphate; UDP, uridindiphosphate). MRI-based PCAs, which was composed of 6 variables × 36 observations (6 replicates per treatment). In all cases, the variables mostly involved in the differentiation among treatments were identified on the basis of PCA loading-plots, while their significance (Tukey Test, confidence level >95%) was assessed separately by ANOVA (analysis of variance) test. Statistical elaborations were carried out by the XLStat software (v. 2012, Addinsoft, Paris, France).

and 7.5 s in eight experiments. Diffusion measurements were performed by using a pulse field gradient (PFG) sequence integrated with stimulated echoes. This experiment was set up with 3 s of recycle delay, 5 scans, δ and Δ diffusion delays of 4 and 13 ms, respectively, and applying gradients at increasing strengths (0, 4.5, 112.0, 362.9, 757.3, 1295.0, and 2168.8 s mm−2) in seven experiments. Since no significant differences in diffusivity were observed by applying gradient pulses in longitudinal (z) or transverse (y) direction, it was assumed an isotropic apparent diffusion in seeds. Consequently, the gradients for PFG experiments have been applied only in the z direction in all cases. Diffusion-weighted images were acquired by selecting the gradient strength of 362.9 s mm−2. In all cases, the images consisted of a 256 × 256 matrix produced by acquiring six interlaced coronal (and sagittal, in some cases) slices with a width of 1 mm, a field of view of 1.33 × 1.0 mm2, and 1.07 mm of slice-interdistance. The 3D experiments (rare 3D pulse sequence, 128 × 128 × 128 matrix, field of view 13 × 13 × 13 mm, rare factor of 8, 24 scans, 3 s of recycle delay, and 3.075 ms of echo time) were performed only for several representative samples as well as relaxation and diffusion experiments were repeated by using also axial slices. ParaVision 5.1 Bruker software was used to process MRI data, attain all of the images, calculate T1 and T2 relaxation times as well as the apparent diffusion coefficients. Multivariate Data Analyses. The spectral region ranging from 0.1 to 9.22 ppm in 1H CPMG HRMAS NMR spectra was equally divided into 228 segments (each single bucket width corresponded to 0.04 ppm). All these segments were integrated, except the region of the baseline distortion resulting from water suppression (4.9−4.66 ppm). The spectral integration produced a data matrix composed by 228 variables × 72 observations (12 replicates for 6 treatments). Data were normalized, by dividing each segment area by the sum of all signals areas, and Pareto-scaled prior to perform principal component analysis (PCA).37,38 Also MRI parametric data (apparent diffusion coefficients, T1 and T2 relaxation times) were calculated and evaluated by PCA. In detail, they were selected one large (5 cm2) and two small (1 cm2) sized regions of interest (ROIs) for both vitreous and floury endosperm. For each MRI parameter and endospermic compartment, it was calculated the average value among the three above-mentioned ROIs. The resulting averaged values were then included in the data matrix for

■

RESULTS AND DISCUSSION HRMAS. A 1H HRMAS NMR spectrum of a representative maize caryopsis (M−) (Figure 1) was obtained by a CPMG NMR pulse sequence to selectively suppress broad signals, which are typically due to relatively large lipid and protein molecules such as zein, albumin, and glutelin.36 Elimination of broad signals improved the proton spectral resolution, thus resulting in easier compound assignment and reproducible quantitative elaboration. Identification of principal signals (Figure 1) was conducted on the basis of previous literature assignments23,26,39 and supported by the homo- and heteronuclear 2D NMR spectra of this study (data not shown). Primary metabolites, such as carbohydrates, amino acids, alcohols, and several organic acids, were identified in spectra of fresh caryopses (Figure 1). The most intense proton signals were ascribed to carbohydrates and consisted in overlapped multiplets ranging from 5.5 to 3.5 ppm. This was expected since the analyzed seed part was mostly represented by the endosperm that is prevalently composed by carbohydrates and starch.40 The multiplets detected in the spectral region between 2.35 and 2.01 ppm were assigned to proline \glutamate, as superimposition of proton signals belonging to both glutamate (βCH2 and γCH2) and proline (β′CH2 and βCH) amino acids.23 While no specific molecular markers were identified to enable a distinction among treatments, the quantitative evaluation of the relative concentration of several metabolites was found to vary according with plant treatments, thus indicating an induced modulation of the maize metabolism. 2582

DOI: 10.1021/acs.jafc.7b04340 J. Agric. Food Chem. 2018, 66, 2580−2588

Article

Journal of Agricultural and Food Chemistry This became evident by processing the 1H-HRMAS NMR spectra by principal component analysis (PCA). PCA is an unsupervised pattern-recognition technique to evaluate the intrinsic variation within different classes of samples. In fact, this multivariate elaboration calculates linear combinations of a starting set of variables on the basis of their maximum variance and reduces the dimensionality of the original data matrix, while retaining the maximum amount of variability, as well as most of the original information contained in the data set.37,38 Moreover, PCA offers the practical advantage of exploring, in a single output, referred to as score-plot, the molecular response induced in numerous samples on the basis of a large number of variables.38,41 The PCA facilitated the direct comparison among the HRMAS spectral data set of this study, which consisted of a relatively dense matrix composed of 228 variables (buckets) and 72 observations (12 replicates × 6 treatments). Three PCA score-plots related to samples deriving from MIN (Figure 2A), COM (Figure 2B), and M+ (Figure 2C) field treatments indicated significant differences (Tukey Test in ANOVA, confidence level >95%) as compared to M− samples. Each score-plot shows the direction assumed by the most relevant loading vectors (variables) that are responsible for the differentiation among treatments (Figures S1A−C of the Supporting Information, respectively). The almost neat separation among samples of different treatments suggests that field treatments systematically influenced the metabolome of maize caryopses. Concomitantly, the closeness of replicates deriving from the same treatment indicates a good reproducibility of HRMAS technique (Figure 2). Remarkably, the statistical reliability of our results is supported by the fact that the 12 replicates for each treatment were collected from three different subplots (4 field-replicates for each specific parcel). The score-plot of M− versus MIN samples (Figure 2A) results from the combination of PC1 and PC3, accounting for 50.6% of the total explained variance. According to the direction of the most relevant loading-vectors (Figure S1A of the Supporting Information), MIN samples were characterized by a larger amount of alanine, proline\glutamate, and tryptophan amino acids than for M− (Figure 2A). This abundance of amino acids may be related to a more efficient nitrogen plant uptake, resulting from a larger availability of readily soluble N in soils amended with the mineral fertilizer.42 The relationship between M− and COM samples was shown by the PCA score-plot that was obtained by combining PC3 with PC11 (Figure 2B). Despite the relatively lower explained variance, this score-plot showed the differences occurring between M− and COM samples and revealed that COM samples contained a larger amount of isoleucine but a lower concentration of alanine, proline\glutamate, leucine, and citric acid than for M− (Figure S1B of the Supporting Information). This result may be again related to the immediate availability of nitrogen42 that, in the case of compost, should be first mineralized from its organic forms, thus leading to a nitrogen plant uptake capacity even lower than for M− (Figure 2B).43 The PCA score-plot of Figure 2C highlighted that AMF inoculation significantly influenced the metabolome of maize caryopses. In fact, M+ samples exhibited a larger concentration of sucrose and glucose, accompanied by a lower amount of citric acid, succinate, alanine, and proline\glutamate (Figure S1C of the Supporting Information). Assuming that also the plant roots of M− treatment were likely associated with autochthonous mycorrhizal fungi, the addition of a commercial

Figure 2. (A−C) PCA score-plots of data obtained from 1H CPMG HRMAS spectra of maize seeds deriving from different treatments (M−, no fertilization; MIN, mineral fertilization, 250 kg ha−1 of N as urea, 150 kg ha−1 of P2O5 as Ca(H2PO4)2, and 160 kg ha−1 of K as K2SO4; COM, 15 t ha−1 compost fertilization; +, AFM inoculation, mix of R. irregularis and F. mosseae). Each score-plot includes the name and the indicative direction assumed (Figure S1 in Supporting Information) by the most significant (ANOVA Tukey test, confidence level >95%) loading vectors involved in the differentiation among treatments. 2583

DOI: 10.1021/acs.jafc.7b04340 J. Agric. Food Chem. 2018, 66, 2580−2588

Article

Journal of Agricultural and Food Chemistry inoculum to M+ plants must have produced a more pronounced variation in the caryopsis metabolome. In particular, the larger abundance of glucose and sucrose observed in M+ suggests a more efficient production and translocation of carbohydrates to seeds. In fact, mycorrizal association elicits the expansion of surface, volume, and roots number, with a consequent enhancement of plant uptake of water and nutrients,5,12 and improvement of plant productivity. This explanation agrees with the relatively lower levels of glucose and sucrose in seeds from AMF inoculated plants, which were accompanied by a larger amount of metabolites related to aerobic glycolysis, such as succinate and citrate. In addition, the larger abundance of several amino acids in M− caryopses also suggests an increased biosynthesis of glycolytic enzymes associated with an increase in respiration and due to a larger availability of nitrogen in M− treatment.42−44 The effects of the synergy of compost with AFM inoculation (COM+) are worth noting due to its environmental relevance. We report in Figure 3 three PCA score-plots that differentiate the metabolome of the COM+ treatment from those of COM (Figure 3A), M− (Figure 3B), and M+ (Figure 3C). Each score-plot shows the direction assumed by the most relevant loading vectors (variables), which are responsible for the differentiation among treatments (Figures S2A−C of the Supporting Information, respectively).The PCA score-plot in Figure 3A was built on the combination of PC3 and PC4 (16.9% of total explained variance) and revealed that the addition of compost with or without AMF inoculation brought to a different metabolomic response in maize caryopses. In fact, except for the two COM samples associated with negative values of PC3 and PC4 (placed in the third quadrant), the differentiation occurred prevalently along the PC3 and was due to a lower amount of glucose in COM, accompanied by a larger amount of phenylalanine (Figure S2A of the Supporting Information). The abundance of glucose in seeds may be related to a more efficient photosynthetic activity in plants under the COM+ treatment. This agrees with previous works that showed that compost may support and promote AMF action, that, in turn, favors plant photosynthesis.45,46 The comparison between COM+ and M− treatments is shown in the PCA score-plot of Figure 3B. In this case, only the abundance of citric acid (associated with positive PC3) enabled to significantly differentiate the metabolome of COM+ caryopses from that of control (Figure S2B of the Supporting Information). The excess of citric acid in M− samples, as already shown to be responsible for the differentiation between M− and COM (Figure 2B), may be accounted to an enhanced glycolytic process. Figure 3C reports the PCA score-plot of caryopses collected from maize plants that were subjected to AMF inoculation either with (COM+) or without (M+) compost fertilization. The combination of PC2 versus PC4 (20.8% of total explained variance) distinguished the two treatments along the direction intersecting the second and fourth quadrant of the score-plot. In particular, COM+ caryopses were differentiated due to a larger content of citric acid, proline/glutamate, alanine, and leucine, and a smaller concentration of sucrose, than for M+ (Figure S2C of the Supporting Information). Contrary to the observation that sucrose and glucose were more abundant in M+ than in M− samples (Figure 2C), no significant difference in glucose content was found between M+ and COM+ caryopses (Figure 3C), although sucrose was very abundant in M+ seeds. On the other hand, the excess of several amino acids in COM+ samples

Figure 3. (A−C) PCA score-plots of data obtained from 1H CPMG HRMAS spectra of maize seeds deriving from different treatments (M−, no fertilization; COM, 15 t ha−1 compost fertilization; +, AFM inoculation, mix of R. irregularis and F. mosseae). Each score-plot includes the name and the indicative direction assumed (Figure S2 in Supporting Information) by the most significant (ANOVA Tukey test, confidence level >95%) loading vectors involved in the differentiation among treatments.

(Figure 3C) can be explained by a larger nitrogen availability due to compost amendment, which served not only as N source, but also promoted a beneficial AMF action. 2584

DOI: 10.1021/acs.jafc.7b04340 J. Agric. Food Chem. 2018, 66, 2580−2588

Article

Journal of Agricultural and Food Chemistry

the homogeneous region of EV (Figure 4C). Moreover, the internal structure of maize caryopses are reported in two video clips, which display the 3D projection of seed (Video Clip 1 of the Supporting Information) and the bottom-up sequence of axial slices (Video Clip 2 of the Supporting Information). A coronal and central slice of a control caryopses is shown in Figure 5A, from which it can be excluded the superimposition

A PCA was also performed on HRMAS spectral data of seeds from maize plants, which had been amended with the mineral fertilizer either with (MIN+) or without (MIN) AMF inoculation (Figure S3 of the Supporting Information). In this case, neither the score-plot resulting from the combination of PC1 and PC2 (Figure S3 of the Supporting Information, 49% total variance explained) nor other possible score-plots exploiting the remaining PCs (data not shown) led to a neat differentiation between MIN and MIN+ caryopses. This suggests that the effect exerted on seeds metabolome by the mineral fertilizer was predominant, thus limiting significantly the AMF inoculation. Magnetic Resonance Imaging. MRI is a noninvasive NMR spectroscopy technique capable to provide morphological and anatomical details of intact maize caryopses and indirectly reveal possible effects of field treatments on plant and seed metabolism.47 Figure 4 reports three MRI images of a

Figure 5. (A, B) Coronal MRI images of an integer M− maize caryopsis obtained by using the pulse sequence MSME and (C) diffusion sequence integrated with stimulated echoes (gradient strength of 362.9 s mm−2). MSME experiments were set with two total spin−echo times: 10.57 ms (A, No T2-weighted) and 42.3 ms (B, T2- weighted).

of the embryo region, thereby making both EF and EV regions more clearly visible. Interestingly, the intrinsic properties of this maize caryopses enabled the systematic isolation of EF and EV regions by acquiring T2-weighted (total spin−echo delay of 42.3 ms) (Figure 5B) and diffusion-weighted (gradient strength of 362.95 s mm−2) (Figure 5C) images, respectively. In fact, EF and EV showed a neat difference in both T2 relaxation times and diffusivity, thus suggesting that the detection of specific anatomical characteristics for each endosperm region may lead to a more precise spin-density evaluation. In fact, we compared both conventional (no weighted) and T2-weighted images to identify possible peculiar properties induced in maize seeds by the applied field treatments. Although several differences in morphology were observed in some maize seeds, we estimated that the variations could not be related to treatments but rather to the natural variability in maize seeds. Nevertheless, several other NMR parameters, such as spin− lattice (T1), and spin−spin (T2) relaxation times, and the apparent diffusion coefficients (Diff), were shown to reveal the spatial distribution of the physical status of water in different seed compartments, thus providing detailed and quantifiable information on seeds molecular arrangement.30,33,50 While relatively long T1 and T2 relaxation times are attributed to an intrinsic large molecular and structural flexibility in tissues, short relaxation times are due to smaller tumbling rates of water molecules interacting with either macromolecules or solid surfaces. On the other hand, Diff coefficients estimate the apparent translational self-diffusion (conventionally referred to as “diffusion”) of water molecules into tissue compartments, thus indirectly indicating the extent of free diffusion within the tissue matrix. Consequently, Diff coefficients may be decreased if water molecules experience barriers to diffusion, such as rigid

Figure 4. (A) Sagittal and (B, C) axial MRI images of an integer M− maize caryopsis obtained by using the pulse sequence MSME at a total spin−echo time of 10.57 ms. The axial figures refer to the slices indicated by (A) rectangles and highlight the (B) floury and (C) vitreous endosperm regions.

intact M− maize caryopsis acquired by applying the MSME pulse sequence at a minimal spin−echo time (10.57 ms, no T2weighted). The sagittal slice positioned in the center of the seed allowed a neat differentiation among the main regions composing the internal structure of the caryopses, such as the protective pericarp, the embryo region (including the embryonic radicle, the plumule, and scutellum) and the endosperm (Figure 4A). The endosperm surrounded by the aleurone layer covers most of the seed volume and is divided into two compartments, referred to as vitreous endosperm (EV) and floury endosperm (EF), which have different composition, density, and consistency. Typically, EV is rich in lipids and proteins (including zein), whereas starch, mainly composed by amylose and amylopectine, is predominant in EF.48 However, the properties and extent of separation of these two endosperm compartments depend strictly on the specific maize cultivar and its quality.49 For example, in the case of the cultivar used here, EV and EF appeared neatly separated from each other (Figure 4A) since EV is concentrated in the seed’s lower part near the embryo region, whereas EF occupies most of upper seed volume and appears structurally more heterogeneous.49 Two axial slices acquired at different positions of the maize seed (as indicated in Figure 4A) show the core of EF (Figure 4B) and 2585

DOI: 10.1021/acs.jafc.7b04340 J. Agric. Food Chem. 2018, 66, 2580−2588

Article

Journal of Agricultural and Food Chemistry tissue structures, interact with cell membranes, or diffuse within small-sized cells. Alternatively, Diff values may be increased if water molecules move more freely into a less compact endosperm (longer free diffusion distance). On these bases, differences in relaxation times and diffusion coefficients measured by MRI are likely to reflect different composition, structure, and homogeneity of endosperm samples. In turn, these properties are a function of multiple treatment-dependent factors such as water/nutrients availability during seed development, extent of seed maturation, compounds partition in the endosperm, distribution of starch, and protein reserves for germination. The measurements of relaxation times and diffusion coefficients were conducted in 1 and 5 cm2 sized regions of interest (ROIs) selected in endosperms of maize caryopses (Figure S4 of the Supporting Information). In all cases, three ROIs were used for both vitreous (V1, V2, and V10) and floury (F1, F2, and F10) endosperms. The inclusion of one large ROI (V10 and F10, respectively) for each endosperm compartment had the rationale to minimize possible site-specific artifacts resulting from local nonhomogeneities in smaller ROIs. The PCA score-plot built up on MRI spectral measurements for the caryopses from the M−, M+, MIN, and COM treatments (Figure 6A) was obtained by combining the first and the third principal components (49.3 and 14.8% of explained variance, respectively). A neat differentiation among M−, COM, and M+ samples was observed from positive to negative values along the PC1, which corresponded to the progressive decrease of TE1‑F, T2-EF, and Diff-EF values (Figure S5A of the Supporting Information). While the caryopses from the MIN treatment could not be differentiated from those of M− along the PC1, they resulted sufficiently separated along the PC3 due to larger and smaller Diff-EV and T1-EV values than for the M− treatment. The fact that the floury endosperm of M + samples exhibited the shortest T1, T2, and smallest Diff values suggests a slower mobility of water molecules in EF, which may be ascribed to a more rigid starchy structure than in caryopses of other treatments. Conversely, although the MRI spectral measurements for the floury endosperm in MIN samples were similar to those for the M− treatment, the vitreous endosperm of maize seeds from the treatment with mineral fertilization provided larger Diff-EV and smaller T1-EV values than for the M− caryopses. This finding related to the MIN treatment may be then explained with a larger molecular rigidity of EV (short T1) compartment and a larger presence of water molecules (high Diff) than for the M− treatment. The PCA score-plot related to maize seeds from composttreated plants is reported in Figure 6B, as based on PC1 and PC2 (39.7 and 22.9% of variance, respectively). This score-plot revealed a neat horizontal differentiation between COM, COM +, and M− seeds along the PC1 especially due to the characteristics of vitreous endosperm. Moreover, while both COM and COM+ samples provided larger values of Diff-Ev and T1-EV and T2-EV than for M−, the relaxation times and diffusion coefficients were even larger for the caryopses from maize plants, which received the combined addition of compost and AMF (COM+) (Figure S5B of the Supporting Information). Conversely, M− seeds revealed the largest diffusion coefficients in the floury endosperm, in line with what is shown in Figure 6A. Also a general separation between COM and COM+ along the PC2 was due to differences in T1‑EF values. The MRI spectral measurements thus indicate that field treatments with compost had a significant effect not

Figure 6. (A−C) PCA score-plots based on MRI parameters (T1, T2, Diff) calculated for vitreous (EV) and floury (EF) endosperm of intact maize caryopses deriving from different treatments (M−, no fertilization; MIN, Mineral fertilization, 250 kg ha−1 of N as urea, 150 kg ha−1 of P2O5 as Ca(H2PO4)2, and 160 kg ha−1 of K as K2SO4; COM, 15 t ha−1 compost fertilization; +, AFM inoculation, mix of R. irregularis and F. mosseae). Each score-plot includes the name and the indicative direction assumed (Figure S5 in Supporting Information) by the of most significant (ANOVA Tukey test, confidence level >95%) loading vectors involved in the differentiation among treatments. 2586

DOI: 10.1021/acs.jafc.7b04340 J. Agric. Food Chem. 2018, 66, 2580−2588

Journal of Agricultural and Food Chemistry

■

only on the composition (Figure 3), but also on the morphological structure of caryopses, and this was magnified by the mycorrizal inoculation. The PCA score-plot for the comparison of MRI data between MIN and MIN+ field treatments and those of M− control is shown in Figure 6C. The difference between the two MIN treatments and control was evident along PC1 (33.38% of explained variance), although no differentiation was possible between MIN+ and MIN samples, as already noted from HRMAS spectral results (Figure S3 of the Supporting Information). In line with a previous score-plot (Figure 6A), the difference in caryopses from plants treated with mineral fertilizers from those of control was represented by both larger Diff-Ev and smaller T1-EV values for MIN treatments (Figure S5C of the Supporting Information). Interestingly, on the basis of HRMAS results, which differentiated MIN from M− samples because of a larger amount of several free amino acids (Figure 2), such a different response in MIN and MIN+ samples may be ascribed to a different proteins/amino acids ratio in vitreous endosperm, that is likely dependent on the different Navailability. In this work, we showed that both HRMAS-NMR and MRI spectroscopies enabled the differentiation, respectively, of the molecular composition and morphological structure of caryopses from maize plants, which were treated with either mineral or compost fertilization, as well as with the inoculation by mycorrhizal fungi. 1 H HRMAS spectra provided the metabolomic profile of caryopses, whose spectral features enabled the elaboration of PCA and the identification of the metabolite related to the specific field treatments. Concomitantly, the adopted pulse techniques of MRI spectroscopy revealed the morphological and anatomical images of intact maize caryopses. Although no significant differences were found in seeds morphology, the relaxation times (T1, T2) and the diffusion coefficients (Diff) measured by MRI suggested that the physical status of water in the endosperm compartments of seeds were systematically related to the field treatments undergone by the corresponding maize plants. The spectral information on maize obtained here by both HRMAS and MRI spectroscopies was particularly relevant since it relied on samples from a statistically significant experimental design at field level. Our results indicate that the applied NMR techniques can be used to evaluate the molecular composition and structural properties of seeds from maize plants that are subjected to different field management practices. This may be of importance in the increasing quest for food security that requires an objective assessment of the quality of products of sustainable agricultural practices.

■

Article

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. Phone: 39-081-2539448. *E-mail: [email protected]. Phone: 39-081-2539160. ORCID

Pierluigi Mazzei: 0000-0002-5312-4969 Vincenza Cozzolino: 0000-0002-5618-254X Funding

This work was supported by a project within the 2010 “FARO” program of the University of Naples Federico II. Notes

The authors declare no competing financial interest.

■

REFERENCES

(1) Khan, N.; Yu, P.; Ali, M.; Cone, J. W.; Hendriks, W. H. Nutritive value of maize silage in relation to dairy cow performance and milk quality. J. Sci. Food Agric. 2015, 95, 238−252. (2) Messias, R. S.; Galli, V.; Silva, S. D. D. A. E.; Schirmer, M. A.; Rombaldi, C. V. Micronutrient and functional compounds biofortification of maize grains. Crit. Rev. Food Sci. Nutr. 2015, 55, 123−139. (3) Walker, V.; Couillerot, O.; Von Felten, A.; Bellvert, F.; Jansa, J.; Maurhofer, M.; Bally, R.; Moënne-Loccoz, Y.; Comte, G. Variation of secondary metabolite levels in maize seedling roots induced by inoculation with azospirillum, pseudomonas and glomus consortium under field conditions. Plant Soil 2012, 356, 151−163. (4) Narsian, V.; Patel, H. H. Aspergillus aculeatus as a rock phosphate solubilizer. Soil Biol. Biochem. 2000, 32, 559−565. (5) Vitousek, P. M.; Aber, J.; Howarth, R. W.; Likens, G. E.; Matson, P. A.; Schindler, D. W.; Schlesinger, W. H.; Tilman, D. G. Human alteration of the global nitrogen cycle: sources and consequences. Ecol. Appl. 1997, 7, 737−750. (6) Kowaljow, E.; Mazzarino, M. J. Soil restoration in semiarid Patagonia: Chemical and biological response to different compost quality. Soil Biol. Biochem. 2007, 39, 1580−1588. (7) Spaccini, R.; Piccolo, A. Molecular characterization of compost at increasing stages of maturity. 1. Chemical fractionation and infrared spectroscopy. J. Agric. Food Chem. 2007, 55, 2293−2302. (8) Spaccini, R.; Piccolo, A. Molecular characteristics of humic acids extracted from compost at increasing maturity stages. Soil Biol. Biochem. 2009, 41, 1164−1172. (9) Martinez-Balmori, D.; Spaccini, R.; Aguiar, N. O.; Novotny, E. H.; Olivares, F. L.; Canellas, L. P. Molecular Characteristics of Humic Acids Isolated from Vermicomposts and Their Relationship to Bioactivity. J. Agric. Food Chem. 2014, 62, 11412−11419. (10) Rohlig, R. M.; Engel, K. H. Influence of the Input System (Conventional versus Organic Farming) on Metabolite Profiles of Maize (Zea mays) Kernels. J. Agric. Food Chem. 2010, 58, 3022−3030. (11) Covacevich, F.; Echeverrıa, H. E.; Aguirrezabal, L. A. N. Soil available phosphorus status determines indigenous mycorrhizal colonization of field and glasshouse-grown spring wheat from Argentina. Appl. Soil Ecol. 2007, 35, 1−9. (12) Smith, S. E.; Read, D. J. Mycorrhizal Symbiosis, 3rd ed.; Elsevier: London, 2008. (13) Cozzolino, V.; Di Meo, V.; Piccolo, A. Impact of arbuscular mycorrhizal fungi applications on maize production and soil phosphorus availability. J. Geochem. Explor. 2013, 129, 40−44. (14) Mazzei, P.; Piccolo, A.; Valentini, M.; Webb, G. A. Intact Food Analysis by Means of HRMAS-NMR Spectroscopy. Modern Magnetic Resonance 2017, 1−16. (15) Doty, F. D.; Entzminger, G.; Yang, A. Y. Magnetism in highresolution NMR probe design. II: HR MAS. Concepts Magn. Reson. 1998, 10, 239−260. (16) Mazzei, P.; Piccolo, A. HRMAS NMR spectroscopy applications in agriculture. Chem. Biol. Technol. Agric. 2017, 4, 1−11. (17) Mazzei, P.; Piccolo, A.; Nugnes, L.; Mascolo, M.; De Rosa, G.; Staibano, S. Metabolic profile of uterine leiomyomas intact tissue using

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jafc.7b04340. Supplementary PCA score-plot evaluating MIN vs MIN+ treatments; most significant loading vectors associated with PCA score-plots shown in Figures 2, 3, and 6; representative location of MRI ROIs (PDF) 3D projection of intact M− maize caryopsis rotating around z-axis (AVI) Bottom-up sequence of axial slices of intact M− maize caryopsis (AVI) 2587

DOI: 10.1021/acs.jafc.7b04340 J. Agric. Food Chem. 2018, 66, 2580−2588

Article

Journal of Agricultural and Food Chemistry high resolution magic-angle Spinning 1H NMR spectroscopy. NMR Biomed. 2010, 23, 1137−1145. (18) Mazzei, P.; Piccolo, A. 1H HRMAS-NMR metabolomic to assess quality and traceability of mozzarella cheese from Campania buffalo milk. Food Chem. 2012, 132, 1620−1627. (19) Mazzei, P.; Vinale, F.; Woo, S. L.; Pascale, A.; Lorito, M.; Piccolo, A. Metabolomics by Proton High-resolution magic-anglespinning nuclear magnetic resonance of tomato plants treated with two secondary metabolites isolated from trichoderma. J. Agric. Food Chem. 2016, 64, 3538−3545. (20) Kruger, N. J.; Troncoso-Ponce, M. A.; Ratcliffe, R. G. 1H NMR metabolite fingerprinting and metabolomic analysis of perchloric acid extracts from plant tissues. Nat. Protoc. 2008, 3, 1001−1012. (21) Schripsema, J. Application of NMR in plant metabolomics: techniques, problems and prospects. Phytochem. Anal. 2010, 21, 14− 21. (22) Wu, X.; Li, N.; Li, H.; Tang, H. An optimized method for NMRbased plant seed metabolomic analysis with maximized polar metabolite extraction efficiency, signal-to-noise ratio, and chemical shift consistency. Analyst 2014, 139, 1769−1778. (23) Manetti, C.; Bianchetti, C.; Casciani, L.; Castro, C.; Di Cocco, M. E.; Miccheli, A.; Motto, M.; Conti, F. A. A metabonomic study of transgenic maize (Zea mays) seeds revealed variations in osmolytes and branched amino acids. J. Exp. Bot. 2006, 57, 2613−2625. (24) Broyart, C.; Fontaine, J. X.; Molinie, R.; Cailleu, D.; TerceLaforgue, T.; Dubois, F.; Hirel, B.; Mesnard, F. Metabolic profiling of maize mutants deficient for two glutamine synthetase isoenzymes using 1H-NMR-based metabolomics. Phytochem. Anal. 2010, 21, 102− 109. (25) Barros, E.; Lezar, S.; Anttonen, M. J.; van Dijk, J. P.; Rohlig, R. M.; Kok, E. J.; Engel, K. H. Comparison of two GM maize varieties with a near isogenic non-GM variety using transcriptomics, proteomics and metabolomics. Plant Biotechnol. J. 2010, 8, 436−451. (26) Gavaghan, C. L.; Li, J. V.; Hadfield, S. T.; Hole, S.; Nicholson, J. K.; Wilson, I. D.; Howe, P. W. A.; Stanley, P. D.; Holmes, E. Application of NMR-based metabolomics to the investigation of salt stress in maize (Zea mays). Phytochem. Anal. 2011, 22, 214−224. (27) Kusano, M.; Fukushima, A.; Redestig, H.; Saito, K. Metabolomic approaches toward understanding nitrogen metabolism in plants. J. Exp. Bot. 2011, 62, 1439−1453. (28) Shenton, M. E.; Dickey, C. C.; Frumin, M.; McCarley, R. W. A review of MRI findings in schizophrenia. Schizophr. res. 2001, 49, 1− 52. (29) Bollineni, V. R.; Kramer, G.; Liu, Y.; Melidis, C.; de Souza, N. M. A literature review of the association between diffusion-weighted MRI derived apparent diffusion coefficient and tumour aggressiveness in pelvic cancer. Cancer Treat. Rev. 2015, 41, 496−502. (30) Schmidt, S. J.; Sun, X.; Litchfield, J. B.; Eads, T. M. Applications of magnetic resonance imaging in food science. Crit. Rev. Food Sci. Nutr. 1996, 36, 357−85. (31) Van As, H.; Scheenen, T.; Vergeldt, F. J. MRI of intact plants. Photosynth. Res. 2009, 102, 213−222. (32) Ruan, R.; Litchfield, J. B.; Eckhoff, S. V. Simultaneous and nondestructive measurements of transient moisture profiles and structural changes in corn kernels during steeping using microscopic nuclear magnetic resonance imaging. Cereal Chem. 1996, 69, 600−606. (33) Van Der Weerd, L.; Claessens, M. M. A. E.; Efdè, C.; Van As, H. Nuclear magnetic resonance imaging of membrane permeability changes in plants during osmotic stress. Plant, Cell Environ. 2002, 25, 1539−1549. (34) Borompichaichartkul, C.; Moran, G.; Srzednicki, G. S.; Driscoll, R. H. Studies of physical state of water in maize from Northeast China (cv. Huangmo 417) during drying at subzero temperatures. Drying Technol. 2004, 22, 295−305. (35) Janas, S.; Boutry, S.; Malumba, P.; Vander Elst, L.; Bera, F. Modelling dehydration and quality degradation of maize during fluidized-bed drying. J. Food Eng. 2010, 100, 527−534.

(36) Zilic, S.; Milasinovic, M.; Terzic, D.; Barac, M.; Ignjatovic-Micic, D. Grain characteristics and composition of maize specialty hybrids. Span. J. Agric. Res. 2011, 9, 230−241. (37) Todeschini, R. Introduzione alla Chemiometria; EdiSES s.r.l.: Naples, Italy, 1998. (38) Brereton, R. G. Pattern recognition. In Chemometrics: Data Analysis for the Laboratory and Chemical Plant; Wiley: England, 2003; pp 183−249. (39) Piccioni, F.; Capitani, D.; Zolla, L.; Mannina, L. NMR Metabolic profiling of transgenic maize with the Cry1A(b) Gene. J. Agric. Food Chem. 2009, 57, 6041−6049. (40) Alonso, P.; Val, D. L.; Shachar-Hill, Y. Central metabolic fluxes in the endosperm of developing maize seeds and their implications for metabolic engineering. Metab. Eng. 2011, 13, 96−107. (41) Mazzei, P.; Spaccini, R.; Francesca, N.; Moschetti, G.; Piccolo, A. Metabolomic by 1H NMR spectroscopy differentiates “Fiano di Avellino” white wines obtained with different yeast strains. J. Agric. Food Chem. 2013, 61, 10816−10822. (42) Amiour, N.; Imbaud, S.; Clement, G.; Agier, N.; Zivy, M.; Valot, B.; Balliau, T.; Armengaud, P.; Quillere, I.; Canas, R.; Tercet-Laforgue, T.; Hirel, B. The use of metabolomics integrated with transcriptomic and proteomic studies for identifying key steps involved in the control of nitrogen metabolism in crops such as maize. J. Exp. Bot. 2012, 63, 5017−5033. (43) Vaccaro, S.; Muscolo, A.; Pizzeghello, D.; Spaccini, R.; Piccolo, A.; Nardi, S. Effect of a Compost and Its Water-Soluble Fractions on Key Enzymes of Nitrogen Metabolism in Maize Seedlings. J. Agric. Food Chem. 2009, 57, 11267−11276. (44) Stitt, M.; von Schaewen, A.; Willmitzer, L. ‘Sink’ regulation of photosynthetic metabolism in transgenic tobacco plants expressing yeast invertase in their cell wall involves a decrease of the Calvin-cycle enzymes and an increase of glycolytic enzymes. Planta 1991, 183, 40− 50. (45) Joner, E. J. The effect of long-term fertilization with organic or inorganic fertilizers on mycorrhiza-mediated phosphorus uptake in subterranean clover. Biol. Fertil. Soils 2000, 32, 435−440. (46) Gosling, P.; Hodge, A.; Goodlass, G.; Bending, G. D. Arbuscular mycorrhizal fungi and organic farming. Agric., Ecosyst. Environ. 2006, 113, 17−35. (47) Borisjuk, L.; Rolletschek, H.; Fuchs, J.; Melkus, G.; Neuberger, T. Low and high field magnetic resonance for in vivo analysis of seeds. Materials 2011, 4, 1426−1439. (48) Gayral, M.; Bakan, B.; Dalgalarrondo, M.; Elmorjani, K.; Delluc, K.; Brunet, S.; Linossier, L.; Morel, M. H.; Marion, D. Lipid partitioning in maize (Zea mays L.) endosperm highlights relationships among starch lipids, amylose, and vitreousness. J. Agric. Food Chem. 2015, 63, 3551−3558. (49) Nuss, E. T.; Tanumihardjo, S. A. Maize: A paramount staple crop in the context of global nutrition. Compr. Rev. Food Sci. Food Saf. 2010, 9, 417−436. (50) Sibgatullin, T. A.; Vergeldt, F. J.; Gerkema, E.; Van As, H. Quantitative permeability imaging of plant tissues. Eur. Biophys. J. 2010, 39, 699−710.

2588

DOI: 10.1021/acs.jafc.7b04340 J. Agric. Food Chem. 2018, 66, 2580−2588