Article pubs.acs.org/JAFC
Cite This: J. Agric. Food Chem. XXXX, XXX, XXX-XXX
Elucidating the Mechanisms of the Tomato ovate Mutation in Regulating Fruit Quality Using Proteomics Analysis Juhua Liu,† Jing Zhang,† Hongxia Miao,† Caihong Jia,† Jingyi Wang,† Biyu Xu,*,† and Zhiqiang Jin*,†,‡ †
Key Laboratory of Tropical Crop Biotechnology, Ministry of Agriculture, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, 4 Xueyuan Road, Haikou 571101, China ‡ Key Laboratory of Genetic Improvement of Bananas, Chinese Academy of Tropical Agricultural Sciences, Haikou Experimental Station, Haikou, Hainan Province 570102, China S Supporting Information *
ABSTRACT: The ovate mutation has frequently been used to study changes in fruit shape but not fruit quality. A deterioration in fruit quality associated with the ovate mutation was discovered in this study. To elucidate how ovate influences the quality of fruit, we performed a proteomics analysis of the fruits of the ovate mutant (LA3543) and wild-type (“Ailsa Craig”, LA2838A) using tandem mass tag analysis. The results indicated that the ovate mutation significantly influences fruit quality in a number of ways, including by reducing the expression of 1-aminocyclopropane-1-carboxylic acid oxidase 3 (ACO3) in ethylene biosynthesis, improving firmness by reducing the amount of pectinesterase and polygalacturonase, reducing sugar accumulation by downregulating the abundance of mannan endo-1,4-β-mannosidase 4, β-galactosidase, and β-amylase, and reducing the malic acid content by downregulating the accumulation of malic enzymes and malate synthase. These findings could inform future improvements in fruit quality. KEYWORDS: tomato (Solanum lycopersicum), ovate mutation, fruit quality regulation
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INTRODUCTION
and ripening process of the tomato ovate mutant, including soluble solids, sugars, and organic acids, had declined relative to the wild-type (WT). No mechanistic explanation for this is currently available. As a powerful means for assessing protein profiles, proteomics has previously been used to explore fruit ripening.17,18 Using proteomics analysis, the synthesis of compounds related to aroma and fruit ripening ubiquitin processes were determined to be regulated by the Rin gene.17,18 To compare the differentially expressed protein profiles between the ovate mutant and WT, we used tandem mass tag (TMT) labeling and integrated the resultant proteomic data into a network containing metabolic or regulatory pathways associated with ethylene synthesis, softening, and nutrition synthesis in the ovate mutant fruit. Our aim was to elucidate how the ovate gene regulates physiological and metabolic pathways, specifically those associated with improved fruit quality in tomatoes.
Tomatoes (Solanum lycopersicum) possess numerous characteristics that make them an appropriate model for assessing the mechanics of fruit ripening. These characteristics include a clear genetic background, several well-characterized single gene mutants, a fully sequenced genome, and easy transformation.1,2 Additionally, numerous studies have assessed the changes in biochemistry associated with fruit softening, nutrition and flavor changes, and the regulation of ripening.3,4 From an evolutionary perspective, the natural mutants of a number of genes have remarkably influenced the fruit ripening process in tomatoes, such as Ripening-inhibitor (Rin),5 Colorless nonripening (Cnr),6 and Never-ripe (Nr),7 an unusual phenotype characterized by higher firmness, lower lycopene accumulation, and other traits, displayed by the mutants Green-ripe (Gr)8 and Nonripening (Nor).2 However, the ripening process is complex and is regulated by a variety of transcription factors, and the intricate regulatory network associated with this system and the internal interactions have not been fully elucidated. The OVATE protein, a member of the plant-specific transcription factor family, was initially discovered to be a primary regulator of fruit shape in tomato.9−14 Ovate may influence fruit shape in a variety of ways depending on the associated genetic background, including elongated fruits to pear- or round-shaped fruits.15 The ovate pear-shaped fruit phenotype was complemented both by a genomic DNA fragment covering the ovate gene and by its ectopic overexpression to revert to round-shaped fruits.10 Accordingly, the ovate mutation probably constitutes a loss-of-function mutation of a negative plant growth regulator whose purpose is currently unknown.16 Notably, we discovered that the quality © XXXX American Chemical Society
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MATERIALS AND METHODS
Plant Materials. Tomato ovate mutants (S. lycopersicum L., LA3543) were kindly provided by the Tomato Genetics Resource Center (http://tgrc.ucdavis.edu). The seeds of WT tomato (S. lycopersicum “Ailsa Craig”, LA2838A) and its ovate mutant were germinated and grown together in a greenhouse at 25 °C with 75% relative humidity under a 16 h light/8 h dark regime.4,19 The flowers were tagged 1 day postanthesis (DPA),4 and fruit samples were Received: August 7, 2017 Revised: October 29, 2017 Accepted: November 1, 2017
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DOI: 10.1021/acs.jafc.7b03656 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry collected at the red mature (RM) stage. The pericarps were sampled immediately postharvesting, snap-frozen in liquid nitrogen, and stored at −80 °C until use. Measurements of Fruit Quality-Related Physiological Indexes. Of the marked fruits, three per treatment were sampled upon harvesting for the physiological measurements. Pollinated flowers were tagged to assess the developmental stages of the fruit. Taste and nutritional properties were assessed based on the first ripe fruit harvested from the first truss of each tagged plant. After removal of the seeds and skin, the fruit was cut and blended, and a hand-held ATAGO-P32 temperature-compensated refractometer (ATAGO Co. Ltd., Tokyo, Japan) was used to directly read the % soluble solids (as o Brix) of the blended fruit at room temperature.19,20 The sugar (fructose, glucose, and sucrose) and organic acid (citric acid, malic acid, ascorbic acid, and quinic acid) contents were analyzed using highperformance liquid chromatography (HPLC; Waters, Milford, CT, USA).19 Protein Sample Preparation. After being ground in liquid nitrogen, 2 mL of lysis buffer (8 M urea, 2% SDS, 1× Protease Inhibitor Cocktail (Roche Ltd. Basel, Switzerland)) was added to the samples, which were then sonicated on ice and centrifuged at 13,000 rpm for 10 min at 4 °C. The supernatant was collected in a new tube. The proteins from each sample were precipitated with ice-cold acetone at −20 °C overnight, and the precipitates were washed three times with 50% ethanol and 50% acetone. Protein Digestion and TMT Labeling. Urea (8 M) in 0.1 M Tris-HCl (pH 8.0) was used to dilute 50 μg of protein to 100 μL; then, 11 μL of 1 M DTT was added, and the samples were incubated at 37 °C for 1 h. The samples were transferred to 10 kDa ultrafiltration tubes (Millipore, MA, USA) and centrifuged at 14,000g for 15 min. Then, 100 μL of 55 mM iodoacetamide was added to the ultrafiltration tube, and the tube was incubated for 20 min in the dark at room temperature. Following this, 50 mM triethylammonium bicarbonate (TEAB) was used as the exchange buffer. The proteins were then tryptic digested with sequence-grade modified trypsin (Promega, WI, USA), and the resultant peptide mixture was labeled using chemicals from the TMT reagent kit (Pierce Biotechnology, IL, USA).21 The proteins were assigned to the TMT labels as follows: 126 127 128 were labeled WT, 129 130 131 were labeled M. The samples were then combined and dried in vacuo. High pH Reverse-Phase Separation. The peptide mixture was resuspended in buffer A (buffer A: 20 mM ammonium formate in water, pH 10.0, adjusted with ammonium hydroxide) and then fractionated by high pH separation on an Ultimate 3000 system (ThermoFisher Scientific, MA, USA) connected to a reverse-phase column (XBridge C18 column, 4.6 mm × 250 mm, 5 μm; Waters Corporation, MA, USA). High pH separation was achieved using a linear gradient from 5% B to 45% B over 40 min (B: 20 mM ammonium formate in 80% ACN, pH 10.0, adjusted with ammonium hydroxide).21 Re-equilibration of the column was achieved at initial conditions for 15 min. The column flow rate was 1 mL/min, and the column temperature was set at 30 °C. Twelve fractions were collected, and each fraction was dried in a vacuum concentrator in preparation for the following step. Low pH Nano-HPLC−MS/MS Analysis. The fractions were resuspended with 30 μL of solvents C and D, respectively (C: water with 0.1% formic acid; D: ACN with 0.1% formic acid), separated by nanoLC, and analyzed by online electrospray tandem mass spectrometry. An Easy-nLC 1000 system (Thermo Fisher Scientific, MA, USA) connected to an Orbitrap Fusion Tribrid mass spectrometer (Thermo Fisher Scientific, MA, USA) equipped with an online nanoelectrospray ion source was used for the experiments. Ten μL of peptide sample was loaded onto the trap column (Thermo Scientific Acclaim PepMap C18, 100 μm × 2 cm) at a flow of 10 μL/ min for 3 min and subsequently separated on an analytical column (Acclaim PepMap C18, 75 μm × 15 cm) with a linear gradient from 3% D to 32% D over 120 min. The column was re-equilibrated at initial conditions for 10 min. The column flow rate was maintained at 300 nL/min. An electrospray voltage of 2 kV versus the inlet of the mass spectrometer was used. The fusion mass spectrometer was
operated in data-dependent mode to switch automatically between MS and MS/MS acquisition. Survey full-scan MS spectra (m/z 350−1550) were acquired with a mass resolution of 120 K followed by sequential high-energy collisional dissociation (HCD) MS/MS scans with a resolution of 30 K.21 The isolation window was set as 1.6 Da. The AGC target was set as 400,000. The MS/MS fixed first mass was set at 110. In all cases, one microscan was recorded using a dynamic exclusion of 45 s. Database Searches. Tandem mass spectra were extracted and charge-state-deconvoluted and deisotoped by Mascot Distiller version 2.6. All MS/MS samples were analyzed using Mascot (Matrix Science, London, UK; version 2.5.1). Mascot was set up to search the Uniprot_Tomato_20160816 database (201608, 33952 entries) assuming the digestion enzyme as trypsin. Mascot was searched with a fragment ion mass tolerance of 0.020 Da and a parent ion tolerance of 7.0 PPM. Carbamidomethyl of cysteine and TMT 6 plex of lysine and the N-terminus were specified in Mascot as fixed modifications. Oxidation of methionine and acetyl of the N-terminus were specified in Mascot as variable modifications.22 Criteria for Protein Identification. Scaffold (version Scaffold_4.7.1, Proteome Software Inc., Portland, OR) was used to validate the MS/MS-based peptide and protein identifications.22 Peptide identifications were accepted if they achieved a false discovery rate (FDR) less than 1.0% by the Scaffold Local FDR algorithm. Protein identifications were accepted if they contained at least two identified peptides. Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony. Quantitative Data Analysis. Scaffold Q+ (version Scaffold_4.7.1, Proteome Software Inc., Portland, OR) was used to quantitate peptide and protein identifications. Normalization was performed iteratively (across samples and spectra) on intensities, as described in Statistical Analysis of Relative Labeled Mass Spectrometry Data f rom Complex Samples Using ANOVA.23 Medians were used for averaging. Spectral data were log-transformed, pruned of those matched to multiple proteins and those missing a reference value, and weighted by an adaptive intensity-weighting algorithm. Of the 122,666 spectra in the experiment at the given thresholds, 105,929 (86%) were included in the quantitation. Differentially expressed proteins were determined by applying the Mann−Whitney Test significance level of P < 0.02337 by Benjamini Hochberg correction and fold-change greater than 1.5. Western Blotting. For Western blotting, the fruit proteins were extracted in extraction buffer (25 mM Tris-HCl, pH 8.6, 50 mM NaCl, 6 mM NH4Cl, 10 mM MgCl2·6H2O, and 5% [v/v] Triton X-100). The concentrations were quantified using a 2-D Quantkit (GE Healthcare, USA). Protein separation was performed on 12% SDSPAGE, and then the proteins were transferred onto a BioTrace polyvinylidene difluoride membrane (Bio-Rad Laboratories). The membrane for fruit proteins was immunoreacted with RbcL, Lhcb1, and Organelle Detection Western Blot Cocktail antibodies (Abcam, Cambridge, UK), and the membrane for chloroplast proteins was immunoreacted with the Organelle Detection Western Blot Cocktail antibodies and the Lhcb1, PSAA, RbcL, and D1 antibodies.24 Enhanced chemiluminescence was used to develop the signals, and Quantity One software (Bio-Rad Laboratories, Inc., USA) was used to quantify the signal intensity. RNA Extraction and Quantitative Real-Time (qRT)-PCR Analysis. An RNeasy MiniKit (QIAGEN, Germany) was used to extract total RNA from the fruit pericarps. Polysaccharides and polyphenols were excluded from the samples based on the manufacturer’s instructions. The one-step reverse-transcription system (Trans-Gen Biotech, China) was used to reverse-transcribe the RNA into cDNA as the manufacturer’s protocol. qRT-PCR was performed on a Stratagene Mx3000P Real-Time PCR system using SYBR Premix Ex Taq (TaKaRa, Japan). The PCR amplification conditions used for all reactions were implemented as follows: 10 min at 95 °C, followed by 40 cycles of 10 s at 95 °C, 15 s at 50 °C, and 30 s at 72 °C. The 2−△△Ct method25 was used to calculate the relative expression levels of the targeted genes, and expression values were normalized using the 18S gene and then normalized against WT. The primers used in this B
DOI: 10.1021/acs.jafc.7b03656 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
Figure 1. Phenotype and nutritional contents of fruit at the red mature (RM) stage for the transcriptional and proteomic study. (a) Phenotype of WT fruit at the RM stage, (b) phenotype of ovate fruit at the RM stage, (c) fruit development stage, (d) fruit firmness, (e) fruit soluble solids contents, (f) fruit sugar contents, (g) fruit organic contents. WT, wild type; M, ovate mutant. Panels a, b, and d−f were partially cited from Liu et al.19 study are listed in Table S4. Each biological sample was analyzed in triplicate.
pooled data from three biological replicates resulted in a total of 466,684 spectra. Mascot identified a total of 121,833 spectra that could be matched to known spectra, which were ultimately matched to 7,210 proteins with an FDR of less than 1% (Table S1). The spectra identification rate reached 26%. The distribution of the peptide lengths is provided in Figure 2a. Partial least-squares-discriminant analysis (PLS-DA) indicated that the principal component values were close to each other in the same treatment, which suggested that the sample was repeatable (Figure 2b). A protein species between the mutant and WT was considered to be significantly differentially expressed if associated with a fold-change >1.50 or
