Proteomic Analysis of the Oil Palm Fruit Mesocarp Reveals Elevated

Oct 2, 2013 - 43400 Serdang, Selangor, Malaysia. ∥. Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, ...
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Proteomic Analysis of the Oil Palm Fruit Mesocarp Reveals Elevated Oxidative Phosphorylation Activity is Critical for Increased Storage Oil Production Hendrick Loei,† Justin Lim,‡ Melvin Tan,† Teck Kwang Lim,† Qing Song Lin,† Fook Tim Chew,† Harikrishna Kulaveerasingam,§ and Maxey C. M. Chung*,†,∥ †

Department of Biological Sciences, Faculty of Science, National University of Singapore, 14 Science Drive 4, Singapore 117543 AB SCIEX (Distribution), 10 Biopolis Road, #03-06, Chromos, Singapore 138670 § Sime Darby Technology Centre Sdn Bhd, Universiti Putra Malaysia, First Floor, Block B, UPM-MTDC Technology Centre III, 43400 Serdang, Selangor, Malaysia ∥ Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597 ‡

S Supporting Information *

ABSTRACT: Palm oil is a highly versatile commodity with wide applications in the food, cosmetics, and biofuel industries. Storage oil in the oil palm mesocarp can make up a remarkable 80% of its dry mass, making it the oil crop with the richest oil content in the world. As such, there has been an ongoing interest in understanding the mechanism of oil production in oil palm fruits. To identify the proteome changes during oil palm fruit maturation and factors affecting oil yield in oil palm fruits, we examined the proteomic profiles of oil palm mesocarps at four developing stages − 12, 16, 18, and 22 weeks after pollination − by 8-plex iTRAQ labeling coupled to 2D-LC and MALDI-TOF/TOF MS. It was found that proteins from several important metabolic processes, including starch and sucrose metabolism, glycolysis, pentose phosphate shunt, fatty acid biosynthesis, and oxidative phosphorylation, were differentially expressed in a concerted manner. These increases led to an increase in carbon flux and a diversion of resources such as ATP and NADH that are required for lipid biosynthesis. The temporal proteome profiles between the high-oil-yielding (HY) and low-oil-yielding (LY) fruits also showed significant differences in the levels of proteins involved in the regulation of the TCA cycle and oxidative phosphorylation. In particular, the expression level of the β subunit of the ATP synthase complex (complex IV of the electron transport chain) was found to be increased during fruit maturation in HY but decreased in the LY during the fruit maturation. These results suggested that increased energy supply is necessary for augmented oil yield in the HY oil palm trees. KEYWORDS: proteomics, oil palm mesocarp, lipid biosynthesis, iTRAQ, MRM, ATP



INTRODUCTION

Storage oil in the oil palm mesocarp can make up a remarkable 80% of its dry mass, making it the oil crop with the richest oil content in the world. Three recent independent studies have explored the transcriptomes of the oil palm mesocarp with the view to determine the regulatory features within the lipid biosynthetic pathway that have contributed to such outstanding oil yield in oil palm fruits. Both studies derived at similar conclusions, showing increased levels of the transcripts of enzymes involved in fatty acid (FA) biosynthesis during fruit maturation. They were also able to independently show that a transcription factor (WRI1) orthologous to the Arabidopsis

Oil palms (Elaeis guineensis) are oleaginous monocotyledonous plants that originate from the intertropical regions of Africa. Since its import into Southeast Asia about 120 years ago, it has established itself as one of the most important crop plants for commercial agriculture in the region, in particular, Malaysia and Indonesia. Palm oil is a commodity of high economic value because of its versatility and wide areas of use.1 Palm oil is most commonly used as cooking oil and is involved in the processing of various food products. Nonedible applications of palm oil include soap production, cosmetics, additives for leathers and textile, and, increasingly, as a source of biofuel.2−4As such, there has been an ongoing interest in understanding the mechanism of storage oil production in oil palm fruits.5,6 © 2013 American Chemical Society

Special Issue: Agricultural and Environmental Proteomics Received: June 25, 2013 Published: October 2, 2013 5096

dx.doi.org/10.1021/pr400606h | J. Proteome Res. 2013, 12, 5096−5109

Journal of Proteome Research

Article

Figure 1. Overview of the iTRAQ labeling strategy for the temporal analysis of the oil palm mesocarp. Palm fruits were harvested at various time points after pollination and proteins from the mesocarps were extracted, trypsinized, and labeled with the respective iTRAQ labels. The labeled peptides were separated by 2D-LC and analyzed by MALDI-TOF/TOF MS/MS.

(Arabidopsis thaliana) WRINKLED1 transcription factor is associated with the up-regulation of several FA biosynthetic transcripts and increased lipid production in the fruit mesocarp.7−9 Despite the increased understanding of lipid production in oil palm fruits from these two landmark studies, the biosynthetic processes leading to higher oil yield in commercial oil palm plantations have not been investigated. Our group has recently reported the differential metabolite profiles of oil palm mesocarps during fruit development,10,11 and in this study a parallel proteome analysis was performed to profile the global changes at the protein level for this biological process. As a part of this study, we examined the proteomic profiles of oil palm mesocarps at four developing stages: 12, 16, 18, and 22 weeks after pollination (WAP) − by 8-plex iTRAQ coupled to 2D-LC and MALDI-TOF/TOF MS (Figure 1). These time points were chosen because during the fruit maturation period (from 12 WAP to 24 WAP) the rate of oil production in the mesocarp peaks during 16 and 18 WAP.12 As such, proteomic changes during these time points are likely to contribute heavily to lipid production in the oil palm fruits. On the basis of past harvest records, the fruits from oil palm trees selected for this study were classified as either high-oil-yielding or low-oil-yielding fruits. This iTRAQ labeling strategy allowed us to first analyze the temporal and biological changes in the oil palm mesocarp proteomes during fruit maturation and oil production and second perform a comparative analysis between the mesocarps from high- and lowoil-yielders at specific time points during fruit maturation.



randomly selected from each bunch, and the mesocarps were isolated from these fruits, snapped frozen, and ground in a liquidnitrogen-cooled mortar and pestle before storage at −80 °C. Protein Extraction from Oil Palm Mesocarp

The protein extraction method adopted here was modified from a previous study used for pine needles.13 In brief, proteins from 0.6 g of ground mesocarp were extracted with 0.06 g of polyvinylpyrrolidone (PVPP) (Sigma Aldrich, St. Louis, MO) in 6 mL of extraction buffer containing 5% sucrose (Bio-Rad, Hercules, CA), 4% sodium dodecyl sulfate (SDS) (Bio-Rad), and 5% β-mercaptoethanol (Merck, Whitehouse Station, NJ). The extraction mixture was incubated for 10 min at room temperature with gentle agitation, followed by centrifugation at 10 000g for 10 min at 4 °C. The supernatant was collected and heated at 95− 100 °C for 3 min and left to cool to room temperature. Protein precipitation was carried out by the addition of 30 mL of cold acetone (Merck) containing 0.07% (w/v) dithiothreitol (DTT) (Bio-Rad) to the supernatant. The protein was allowed to precipitate at −20 °C for 1 h before centrifugation at 10 000g for 10 min at 4 °C. The supernatant was discarded and the pellet was resuspended in 3 mL of extraction buffer and centrifuged at 10 000g for 10 min at 4 °C. The supernatant was collected and precipitated again with 12 mL of cold acetone/0.07% DTT at −20 °C for 1 h. The mixture was then centrifuged, and the protein pellet was washed with 3 mL of 80% cold acetone/0.07% DTT. The mixture was centrifuged once again, and the resulting pellet was collected, air-dried, and dissolved in an iTRAQ compatible buffer containing 25 mM triethylammonium bicarbonate (TEAB) (Sigma Aldrich), 8 M urea (USB, Cleveland, OH), 2% Triton X-100 (Sigma Aldrich), and 0.1% SDS (Bio-Rad).14 Protein concentrations were determined using the Coomassie Plus Protein Assay (Pierce, Rockford, IL). Absorbances were read at 595 nm in a Tecan Infinite M200 spectrophotometer (Tecan, Männedorf, Switzerland).

MATERIALS AND METHODS

Plant Material

Sixteen oil palm trees, eight trees categorized as high-oil-yielding (HY) and the other eight as low-oil-yielding (LY), were selected for this study. These trees are cultivated in an oil palm plantation in Carey Island, Selangor, Malaysia that is managed by Sime Darby Berhad (Kuala Lumpur, Malaysia). These trees are commercial crosses of Serdang Avenue dura and AVROS pisifera that yielded a hybrid tenera progeny. The HY trees were identified by their relatively high oil yield over the past 7 years. These eight HY trees yielded an average of 78.1 kg of palm oil per palm per year. In contrast, the LY trees yielded an average of only 40.5 kg of palm oil per palm per year.11 Fruit bunches from these 16 trees that were harvested at four different time points − 12, 16, 18, and 22 WAP − were used in this study. Twenty fruitlets were

Sample Pooling for iTRAQ Labeling

A total of 64 individual samples − 32 HY samples and 32 LY samples − representing fruit lysate from each palm tree at the four harvest time points were available for proteome analyses. To accommodate the large sample size, we used pooled samples instead to perform iTRAQ 8-plex analyses. Although this is not ideal, we have taken note that two recent studies have shown that in sample pooling (1) the protein expression in a pool would represent the mean expression of the individual samples that 5097

dx.doi.org/10.1021/pr400606h | J. Proteome Res. 2013, 12, 5096−5109

Journal of Proteome Research

Article

citrate in 70% ACN) at a flow rate of 5.4 μL/min via a 25 nL mixing tee before they were spotted in 28 × 44 spot arrays on 123 × 81 mm Opti-TOF LC/MALDI Inserts (AB Sciex) using a Probot Micro Precision Fraction collector (Dionex), at a frequency of one spot per 5 s.

make up the pool15 and (2) the biological variance between the pools can be reduced compared with between individuals.16 In this experiment, equal amounts of proteins extracted from the oil palm fruits harvested from the 8 HY trees from the same time point were pooled. The same was performed for samples originating from the eight LY trees. As such, there are eight pooled samples representing the following categories: high yield/12 WAP, high yield/16 WAP, high yield/18 WAP, high yield/22 WAP, low yield/12 WAP, low yield/16 WAP, low yield/ 18 WAP, and low yield/22 WAP.

MALDI-MS/MS Analysis

MS and MS/MS analyses were performed on a 4800 MALDITOF/TOF analyzer (AB Sciex) operating in MS-positive reflector mode. Instrument calibration and optimization were performed using calibration mixture 1 from the 4700 proteomics analyzer mass standards kit (AB Sciex). Laser intensity was set to 4000 for MS and 4300 for MS/MS acquisition. Typically 1000 shots were accumulated in each spot and MS spectra were acquired between m/z 920 and 3900. The seven precursor ions with the highest peak intensity of each spot with S/N of at least 50 were automatically selected for MS/MS acquisition. MS/MS was performed using air as the collision gas at collision energy of 2 kV and collision gas pressure of ∼1.4 × 10−6 Torr, with an accumulation of 5000 shots for each spectrum.

iTRAQ 8-plex Labeling

The iTRAQ 8-plex reagents were purchased from AB Sciex (Framingham, MA), and the labeling was carried out following the protocol provided by the manufacturer with minor modifications. Samples were labeled with the respective iTRAQ labels as follows: For HY fruit, the pooled sample representing 12 WAP was labeled with iTRAQ-113, 16 WAP with iTRAQ-114, 18 WAP with iTRAQ-115, and 22 WAP with iTRAQ-116. For the LY fruit, the sample representing 12 WAP was labeled with iTRAQ-117, 16 WAP with iTRAQ-118, 18 WAP with iTRAQ-119, and 22 WAP with iTRAQ-121 (Figure 1). In brief, 50 μg of each sample was reduced in 5 mM tris(2carboxyethyl)phosphine (TCEP) at 60 °C for 1 h, and cysteinyl residues were blocked with 10 mM methyl methanethiosulfonate (MMTS) at room temperature for 10 min. The SDS concentrations in all samples were adjusted to 0.05% (w/v) prior to trypsinization. The samples were trypsinized at 37 °C for 16 h. The protein digests were subsequently dried by vacuum centrifugation and resuspended in 30 μL of 0.5 M TEAB. The iTRAQ reagent was added to each tryptic digest and incubated at room temperature for 2 h. Finally, the labeled peptides were then mixed and subjected to cation-exchange chromatography using a hand-held cation-exchange cartridge system (AB Sciex) to remove interfering substances and excess labels in the sample. The eluate was further desalted using a SEP-PAK column (Waters, Milford, MA), lyophilized, and reconstituted in 50 μL of SCX buffer A, which contained 5 mM KH2PO4 (Merck), pH 3 and 5% acetonitrile (ACN) (Fisher Scientific, Pittsburgh, PA).

Peptide and Protein Identification and iTRAQ Quantitation

Protein identification and relative iTRAQ quantification were performed with the ProteinPilot Software 4.0 (AB Sciex) using the Paragon algorithm as the database search engine. Each MS/ MS spectrum was searched against an in-house palm oil protein database created by Sime Darby. This database contains 586 164 protein sequences, and each protein entry in the oil palm database was annotated to a known protein on Uniprot using an in-house bioinformatics algorithm. The identified proteins were grouped by the ProGroup algorithm in the software to minimize redundancy. In the iTRAQ analysis parameter settings, sample type was indicated as iTRAQ 8plex (Peptide Labeled), MMTS was selected for cysteine alkylation, digestion by trypsin, ID focus was set to biological modifications, and thorough search effort was selected. A decoy database search strategy was adopted to estimate the false discovery rate (FDR) for peptide identification. A corresponding reversed sequence database was generated using the Proteomics System Performance Evaluation Pipeline (PSPEP) feature in the ProteinPilot Software 4.0. 826 proteins were identified with 95% confidence, and the FDR was calculated to be 1.7% based on the global FDR fit (Supplementary Table S1 in the Supporting Information). Bias correction and background correction were applied for iTRAQ Quantitation in ProteinPilot. The results were then exported into Microsoft Excel for manual data interpretation. Only proteins with an “Unused (Conf) Cutoff” of >1.3 (at least 95% confidence) were used for analysis. Proteins that were matched to the decoy database (false positives) were removed. An iTRAQ cutoff threshold of 1.3 was used as it had been determined to be statistically significant in a previous study.17 As such, proteins with iTRAQ ratio of 1.3 in at least two out of three time points were considered to have an “increase in temporal expression”, while those with relative abundance