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Original Paper
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Acta Biochim Biophys
Sin 2008, 40: 27�37 |
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doi:10.1111/j.1745-7270.2008.00367.x |
Comparative proteomics
analysis of light responses in cryptochrome1-304 and Columbia wild-type 4 of Arabidopsis
thaliana
Yuejun Yang1,2, Yan Li1, Xu Li1, Xinhong Guo1, Xiaojuan Xiao1, Dongying Tang1, and Xuanming Liu1*
1 College of Life Science and Biotechnology, Hunan
University, Changsha 410082, China
2 College of Medicine, Hunan Normal University,
Changsha 410081, China
Received: July 18,
2007�������
Accepted: September
15, 2007
This work was
supported by the grants from the �985� Program of China (No. 200501), the
Department of Education of Hunan Province Fund (No. 04C328), and the National
Natural Science Foundation of China (No. 30770200)
*Corresponding
author: Tel/Fax, 86-731-8821721; E-mail, [email protected]
The blue light
photoreceptor mutant cryptochrome1-304 (cry1-304) and Columbia wild-type 4
(col-4) of Arabidopsis thaliana were grown under white light and blue
light, and in the dark. To study the difference in protein expression levels
between cry1-304 and col-4, a proteomic approach was applied� based on 2-D gel
electrophoresis. Twenty-one different protein� spots were identified by
matrix-assisted laser desorption/ionization�-time of flight/time of flight mass
spectrometry. The expression of four genes corresponding to four protein spots
was analyzed by semiquantitative reverse transcription�-polymerase chain
reaction. We applied analytical procedures to study cry1-304 and col-4, and
found that the differentially expressed proteins formed six clusters reflecting
co-regulation. This assessment was consistent with the known physiological
responses of plants to light.
Keywords������� Arabidopsis thaliana; cryptochrome1-304; proteomics;
cluster analysis
Most aspects of plant development are affected by light. Plants respond to their surrounding solar radiation and adjust their growth and development accordingly [1-5]. Phytochromes, phototropins, and cryptochromes are the three main kinds of photoreceptor proteins in Arabidopsis thaliana [6]. The phytochromes recognize light in the red portion of the spectrum, whereas phototropins and cryptochromes perceive blue and ultraviolet A light [7]. In A. thaliana, cryptochromes are nuclear proteins that mediate� light control of hypocotyl elongation, leaf expansion, photoperiodic flowering, and the circadian clock. Cryptochromes could interact with phytochromes, constitutive photomorphogenesis 1 (COP1), clock proteins, chromatin, and DNA. Recent studies suggested that cryptochromes undergo a blue light-dependent phosphorylation that affects the conformation, intermolecular interactions, physiological activities, and protein abundance of the photoreceptors [8,9]. In general, differential expression techniques were used in the mRNA-based screening in previous studies [10]. However, these techniques are not necessarily comprehensive in the context of gene expression at the protein level due to post-transcriptional control and post-translational modifications. An alternative approach is direct screening of the protein profiles, or proteome, of a sample using 2-D gel electrophoresis (2-DE) and mass spectrometry (MS). 2-DE of high resolution� is a powerful tool for separating complex protein mixtures [11], and has been used to analyze proteins in response to environmental changes [12]. Proteomic analysis of Arabidopsis seedlings, treated with various stresses such as gravity and high light, has been carried out [13-15].
The hypocotyls of cryptochrome1-304 (cry1-304) were clearly longer than those of Columbia wild-type 4 (col-4) grown under white light, but both were the same length when grown in the dark. In this study, the proteins extracted from 7 d seedlings of cry1-304 and col-4, which were grown under white light, blue light, and in the dark, were separated by 2-DE, and the gels were stained by silver nitrate. Forty-four protein spots were differently expressed between cry1-304 and col-4 and were analyzed using MS and searched in an online database. Among the 44 different protein spots, 21 spots were identified successfully by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF)/TOF-MS analysis. We filtered the altered proteins related to the response of cry1-304 to light using a proteomic approach, and extracted proteomic profiles that provided information on the changes occurring to specific light.
Materials and Methods
Plant growth conditions
The cry1-304 and col-4 of A. thaliana analyzed in this study were of the Columbia ecotype. Seeds of cry1-304 and col-4 were gifts from Dr. Chentao LIN (University of California, Los Angeles, USA). They were plated on solid Murashige and Skoog salt, stratified at 4 �C in the dark for 4 d, then transferred to a temperature-controlled room under continuous white light or blue light with light intensities of 802 mmol photons/(m2∙s) at 23-25 �C, or they were continuously grown under dark. Broadband blue light was obtained by filtering output from Interelectric (Warren, USA) Biliblue 20 W F20T12/BBY fluorescent tubes through blue Plexiglas No. 2424 (Commercial Plastics, San Diego, USA). White light was provided by Philips cool white 20 W F20T12/CW tubes (Philips, New York, USA). All light measurements were made by an LI-189 quantum radiometer (Li-Cor, Lincoln, USA).
Extract preparation
The 7-day seedlings were harvested, grinded in liquid nitrogen, and suspended in acetone containing 10% trichloroacetic acid and 0.3% dithiothreitol (DTT). The homogenates were kept for 24 h at 20 �C, then centrifuged at 34,900 g, at 4 �C for 1 h. The precipitates were washed with acetone containing 0.07% mercaptoethanol, and lyophilized. The samples were stored at 80 �C. The cry1-304 and col-4 protein samples (450 mg each) were suspended in lysis buffer containing 8 M urea, 4% 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate, 40 mM Tris, and 2 mM phenylmethylsulphonyl fluoride. After 30 min, two volumes of extraction buffer containing 8 M urea, 4% 3-[(3-cholamidopropyl)dimethy�lammonio]-1-propanesulfonate, 2% Pharmalyte 310, and 1% DTT was added to the samples. The samples were then stirred, followed by centrifugation at 18,900 g for 10 min. The dialyzed proteins were quantified using the Bradford assay [16]. All samples were stored at -80 �C prior to electrophoresis.
2-DE
The 2-DE was carried out
essentially as previously described [17]. Isoelectric focusing and immobilized
strip gels (pH 3-10, 24 cm; Amersham
Biosciences, Uppsala, Sweden) were used to separate the protein lysate (450 mg) and they were carried out at 20 �C with
immobilized pH gradient (Amersham Biosciences). The procedure was modified for
full and steady-state focusing. Briefly, the strip gel was rehydrated for 13 h
at 30 V and the proteins were separated using the following step-wise increases
in voltage and running times: 500 V for 1 h; 1000 V for 1 h; and 8000 V for 8.5
h (a total of 69,890 V∙h. Focused strip gels were incubated for 15 min at
room temperature with equilibration buffer I [50 mM Tris-HCl, pH 8.8, 6 M urea,
30% glycerol, 2% sodium dodecyl sulfate (SDS), and 1% DTT] then transferred to
equilibration buffer II (50 mM Tris-HCl, pH 8.8, 6 M urea, 30% glycerol, 2%
SDS, and 2.5% iodoacetamide). After equilibration, the strip gels were placed
on 10% denaturing acrylamide gels and sealed with a 3% agarose solution.
SDS-polyacrylamide gel electrophoresis was then were placed at 2.5 W for 30 min
followed by 15 W for 5 h with Ettan DALT-six electrophoresis units (Amersham
Biosciences). The SDS marker for relative
molecular mass calibration was added. Gels were stained with silver nitrate
according to a modified procedure of Blum et al [18].
Image acquisition and data
analysis
The silver-stained gels were scanned using an Amersham image scanner at an optical resolution of 300 dpi in transmission model. Image analysis was carried out with PDQuest software version 7.1 (Bio-Rad Laboratories, Hercules, USA). After spot detection and background subtraction (mode:average on boundary), 2-D gels were aligned and matched, and the quantitative determination of the spot volumes was carried out (mode:total spot volume normalization). For each analysis, statistical data showed a high level of reproducibility between normalized spot volumes of gels produced in triplicate from the two independent protein extractions. On average, 986 and 967 protein spots were detected in the gels of cry1-304 and col-4, respectively.
The significance of the difference in protein expression between cry1-304 and col-4 was estimated by Student's-test (P<0.05 was considered as significant), and was carried out using PDQuest software. The qualitative comparisons were also carried out using PDQuest software, followed by the confirmation of manual and whole-mount gels checking.
In situ digestion of proteins
The silver-stained protein spots were excised from preparative gels using a punch and placed into 500 ml Eppendorf tubes. The proteins were digested in-gel with trypsin as previously described [19-21]. Briefly, the spots were washed three times with double-distilled water. A fresh solution containing 15 mM K3Fe(CN)6 and 50 mM Na2S2O3 was used to decolor. The cysteine reduction and alkylation steps consisted of incubation in 10 mM DTT/100 mM NH4HCO3 for 1 h at 57 �C, and then in the same volume of freshly prepared 55 mM iodoacetamide/100 mM NH4HCO3 solution for 30 min at room temperature in the dark. The gel pieces were dried again and rehydrated in 10 ml of 40 mM NH4HCO3 containing 10% acetonitrile and 0.02 g/L trypsin for 45 min at 0 �C. The excess liquid was removed and the pieces of gel were immersed in 40 mM NH4HCO3 containing 10% acetonitrile at 37 �C overnight. The digests were desalted with ZipTip (Millipore, Bedford, USA) according to the manufacturer抯 instructions and subjected to analysis using MALDI-TOF/TOF-MS.
MALDI-TOF/TOF identification
of peptide mixtures
The tryptic-mixed peptides from 2-DE were loaded onto an AnchorChip target plate as previously described [21]. Molecular weight information of peptides was obtained using a MALDI-TOF/TOF mass spectrometer (UltroFlex I; Bruker Daltonics, Billerica, USA) equipped with a nitrogen laser (337 nm) and operated in reflector/delay extraction mode for MALDI-TOF peptide mass fingerprint (PMF) or laser-induced forward transfer (LIFT) mode for MALDI-TOF/TOF with a fully automated mode using FlexControl software. An accelerating voltage of 25 kV was used for PMF. Calibration of the instrument was carried out externally with [M+H]+ ions of angiotensin I, angiotensin II, substance P, bombesin, and adrenocorticotropic hormones (clips 1-17 and clips 18-39). Each spectrum was produced by accumulating data from 100 consecutive laser shots and the spectra were interpreted with the aid of Mascot software (Matrix Science, London, UK). The peaks with signal to noise (S/N)=5, resolution=2500 were selected and used for LIFT from the same target. A maximum of five precursor ions per sample were chosen for MS/MS analysis. In the TOF1 stage, all ions were accelerated to 8 kV under conditions promoting metastable fragmentation. After selection of a jointly migrating parent and fragment ions in a timed ion gate, the ions were lifted by 19 kV to a high potential energy in LIFT cells. After further acceleration of the fragment ions in the second ion source, their masses could simultaneously be analyzed in the reflector with high sensitivity. LIFT spectra were interpreted by Mascot software. PMF and LIFT datasets were combined using BioTools version 2.2 software (Bruker Daltonics) and used for protein identification. The parameters were: mass tolerance in PMF of 50 ppm; MS/MS tolerance of 1.0 Da and one missing cleavage site; and cysteines modified by carbamidomethylation. The protein identifications were considered to be confident when the protein score of the hit exceeded the threshold significance score of 58 (P<0.05). When there were several hits, the first hit was selected.
Database searches
The peptide masses were input in Peptident software (http://www.expasy.ch). The databases used for all searches were SWISS-PROT and TrEMBL (http://www.expasy.ch/sprot/). The database searches were carried out using the following values: Arabidopsis species; protein molecular weight range; isoelectric point range; trypsin digest (two missed cleavage sites allowed); cysteines modified by carbamidomethylation; and mass tolerance 50 ppm using internal calibration. The identification was based on four matching peptides and 15% coverage. Tryptic autolytic fragments and contamination were removed from the set of data used for database search.
RNA analysis
Genes corresponding to spots of interest were selected for reverse transcription-polymerase chain reaction (RT-PCR) analysis. Total RNA was isolated using Puprep RNAeasy mini kit (Spin Column; Ambiogen Life Science Technology Ltd, Shanghai, China). DNA-free RNA was obtained by RQ1 DNase I treatment according to the manufacturer's instructions (Promega, Madison, USA). The amount of mRNA was analyzed by RT-PCR [23]. cDNA was prepared from 2.0 mg total RNA using Moloney murine leukemia virus reverse transcriptase according to the manufacturer'snstructions (Promega). The cDNA was diluted 5-fold, and 0.5 ml diluted cDNA was used in a 20 ml reaction volume. The PCR primers were shown in Table 1. The thermal cycling parameters were 94 �C for 5 min, one cycle of 95 �C for 30 s, 60-61 �C for 30 s, 72 �C for 50 s then ACT2, at5g54770, at5g13450, at5g15090, and at5g19510 followed by 26, 33, 30, 33, and 27 cycles, respectively. The 18 ml PCR products were separated by 1.5% agarose gel electrophoresis. The ACT2 gene was used as an internal control for RT-PCR.
Cluster analysis
The data matrix of protein abundances was clustered by the clustergram function in Matlab 2006 [24] with default options. The quanitities of the protein spots of white light-grown, blue light-grown, or dark-grown cry1-304 seedling samples were compared with those of the respective protein spots of wild-type seedling samples. To minimize systematic errors, values of protein abundance were normalized among samples, as in Equation 1:
Eq. 1
The K-means clustering was analyzed by the statistics toolbox of Matlab 2006 [24].
Similarity analysis of protein
profiles
Protein profiles were classified by the K-means clustering function in the statistics toolbox in Matlab 2006. The distance between two protein profiles was determined by Euclidean distance (D) using Equation 2:
Eq. 2
The results were drawn by the plot function in Matlab 2006 [24].
Results
2-DE and analysis of gel
images
To seperate proteins efficiently, 2-DE was carried out with a 10% separation gel in the second dimension. To effectively identify as many different proteins as possible, we loaded 450 mg of protein and stained gels with silver nitrate. At the same experimental conditions, six gels, three for cry1-304 and three for col-4 in white light, blue light, and darkness, were analyzed by PDQuest software. In the 2-DE maps of cry1-304 and col-4, 44 spots were found to be significantly altered (P<0.05) and 21 of them were identified successfully. Typical 2-DE proteome spot patterns of the seedlings of cry1-304 and col-4 grown under white light, blue light, and in the dark are shown in Fig. 1.
Alteration of cry1-304
compared with col-4 grown under white light and blue light, and in the
dark, and cluster analysis
The 21 protein spots altered in different ways in white light, blue light and darkness, which belong to six MPs in col-4 or cry1-304 respectively (Table 2).
Identity of proteins that were
differentially regulated by various lights
The molecular identities of the 21 proteins were determined by PMF and LIFT, followed by a search of the NCBInr database (http://www.ncbi.nlm.nih.gov/). The identified proteins listed in Table 3 were differently expressed between cry1-304 and col-4. Some were annotated as unclassified proteins, and the rest were categorized into several functional groups including metabolism, energy, defense, transcription, protein synthesis, RNA processing, protein fate, and cellular transport and transport mechanisms. The category for their expected functions was predicted by http://www.arabidopsis.org/.
RT-PCR analysis
To investigate whether the change observed at the protein level also occurs at the RNA level, semiquantitative RT-PCR analysis was carried out on four selected protein genes. The gene expression variations between col-4 and cry1-304 treated with white light, blue light, and darkness were shown to be consistent with those in the 2-DE images (Fig. 2). For spot 9 (putative elongation factor 1B alpha-subunit), there was a significant increase both at the mRNA and protein levels under white light and blue light in cry1-304. Consistently, the mRNA expression levels of spots 12, 14, and 15 were detected. However, in some instances, the level of mRNA and the level of the related protein were inconsistent. For example, the mRNA expression of spot 14 did not change, but the protein level was up-regulated in cry1-304 under white light and blue light (Fig. 2). The degrees of the changes were also not consistent in some instances due to the differential turnover rates or the different stabilities of RNA and protein. This difference could also be affected by post-translational modifications, such as phosphorylation that changes the isoelectric point of proteins.
Clustering analysis
Clustering analysis was carried out on the 21 protein spots that had been identified. It was found that they are regulated differentially. We carried out a K-means clustering analysis based on the relative abundances of these proteins under different treatement conditions, and generated three distinct nodes. Using these nodes, we carried out K-means clustering, definitively classifying the 21 protein spots into six clusters. The resulting clusters are shown graphically in Fig. 3(B1,B2). We defined these protein clusters as molecular phenotypes (MPs), representing characteristic proteomic responses to specific environments [Fig. 3(C1,C2)]. The term MP was used instead of morphological or physiological phenotypes that are used routinely to characterize the light responses of wild-type plants or genetic mutants. The result showed that the six K-means clusters (or MPs) represent distinct protein expression patterns for different light responses. The following statistically significant differences in regulation were identified: in col-4, under blue light, 1MP2 and 1MP4 were up-regulated, and 1MP5 and 1MP6 were down-regulated; under white light, 1MP2 and 1MP3 were down-regulated; and in the dark, 1MP2 and 1MP4 were down-regulated [Fig. 3(C1)]; in cry1-304, under blue light, 2MP1, 2MP5, and 2MP6 were up-regulated; in white light, 2MP5 and 2MP6 were down-regulated; and in the dark, 2MP3 and 2MP5 were up-regulated and down-regulated, respectively. In addition, significantly different regulation was observed between white and blue light treatments for 2MP2, 2MP5, and 2MP6, and between darkness and blue light treatments for 2MP3 and 2MP4.
The blue light and dark responses were more closely related than the white light response in cry1-304 mutants. The blue light and white light responses were more closely related than the dark response in col-4.
Discussion
We attempted to seek the responses of plants to a specific light condition in a proteomic landscape, and applied the procedure to analyze the light responses of the cry1-304 mutant. We used two-dimensional gel electrophoresis to study the seedlings which grown under blue light with light intensities of 100 mmol photons/(m2∙s) at 23-25 �C [15], and the results were different. We found that the seedlings grown under light with light intensities of 80 mmol photons/(m2∙s) that we used this experiment had the quite reproducible 2-DE proteomic profiles, and the results were more reasonable. Between independent electrophoresis and quantification procedures we were able to quantitatively carry out protein pattern comparisons with a high correlation coefficient value.
The alteration of the protein spots 8, 9, 12, 14, 16, 18, 19, 33, and 42 were similar in white and blue light, however, these protein levels were unchanged in dark conditions comparing cry1-304 with col-4. The results showed that these proteins might be regulated by blue light. They belong to 2MP1, 2MP2, 2MP4, and 2MP5 in the clustering analysis.
Under different conditions, some similar changing trends were observed in cry1-304, such as spots 17, 28, 32, and 43. The alteration of these proteins is independent of light conditions, and the expression changes of the corresponding genes were caused by the loss of cry1-304 (Table 2). The identified proteins showed that the cry1-related blue light signal elicits the down- or up-regulation of different kinds of functional proteins in accord with recent microarray studies and eventually confers an altered morphology [25,26].
As many of the down- and up-regulated proteins were found to be involved in metabolism and energy, it seems likely that cry1 is the photoreceptor responsible for mediating the blue light effect on gene expression. These data indicate that light controls Arabidopsis development through coordinately regulating metabolism [26].
The protein spots involved in metabolism such as spots 17, 23, 28, and 33 had the tendency for increasing expression in cry1-304 grown under white light and blue light. There were three proteins involved in energy synthesis. Protein spot 18 corresponds to ribulose1, 5-bisphosphate carboxylase/oxygenase large chain, and protein spot 19 contains enolase (2-phospho-D-glycerate hydroxylase). Their expression levels in cry1-304 grown under white and blue light were decreased, but did not change in the dark. Protein spot 12, ATP synthase delta chain oligomycin sensitivity conferral protein, had decreased expression levels in cry1-304 but had no change in darkness. The results indicated that energetic metabolism is involved cry1-related blue light signaling regulation.�
It is also noteworthy that a disease resistance protein catalase (spot 24), involved in circadian clock regulation [27], was up-regulated (Table 3), also previously identified by microarray and Northern blot analysis [7]. It confirms that the blue light signal is related to disease resistance gene expression. The disease resistance protein glutathione S-transferase (spot 25) was down-regulated in cry1-304 when grown under white light. The gene expression of glutathione S-transferase is induced by auxin, salicylic acid, and HO, implicating this gene is involved in plant stress/defense responses [28]. It is confirmed that cry1 affects the expression of many genes, of which suppresses stem growth by repressing auxin levels and/or sensitivity [10].
We identified some transcription proteins, including protein spots
3, 10, and 42. Spot 3 (protein T2E6.8) and spot 10 (mRNA capping enzyme-like
protein) were down-regulated in cry1-304. The germin-like protein (spot 42) was
up-regulated in cry1-304. These proteins are regulated by blue light through
cry1, and it is shown that cry1
involves the expression of transcription proteins [10,29]. Therefore, many
transcription proteins are involved in the morphological changes that occur in
the cry1 mutant, such as hypocotyl elongation and cotyledon expansion
[10,29]. The next goal of our research is to find out the mechanism behind how
these transcription proteins are regulated by cry1 in blue light.
Voltage-dependent anion-selective channel protein hsr2 (spot 14) is decreased significantly during stress treatments [30]. However, its expression level was up-regulated in cry1-304 under white light and blue light, but did not change in the dark in our results. This indicates that this protein might be responsive to blue light. According to previous research [31], blue light affected plasma membrane depolarization, anion channel activity, and growth inhibition kinetics. It was proposed that cryptochromes activate anion channel activity, resulting in plasma membrane depolarization and the inhibition of cell elongation. Research has also shown that the early signaling process of cry1 was involved in the opening or closing of anion channels [32-34].
Spot 43, similarity to 30s ribosomal protein s10, has some mutual changing trends in three different conditions, and this protein is independent of light. It is reported that thiazole biosynthetic enzyme, responsive to DNA damage stimulus, is involved in the thiamin biosynthetic process and is also responsive to light [35].
The RNA processing protein (spot 4), the RNA-binding protein RNP-7 precursor, was changed in white light, blue light, and in the dark. These results might support the theory that plant cryptochromes relate to mediating light regulation of development by direct interactions with DNA or DNA-binding proteins [36].
We additionally identified a heat shock protein cognate 70-1 (spot 16) that prevents protein misfolding and aggregation in cells [37]. The heat shock protein cognate 70-1 has a role for cry1 in circadian temperature as well as light regulation [38].
We showed that protein expression profiles could be used to investigate the relatedness of light response mutants under different conditions. The light response of A. thaliana has been well defined both genetically and physiologically, and served as a useful model to quantify the degree of correlation between physiological and proteomic responses. In the present study, we attempted to use the proteomic profiles to analyze the responses to various light conditions. The MP from protein profiles of cry1-304 mutants was determined by clustering analysis. The proteomic information obtained in this study also served as the molecular markers for the responses to various conditions. Furthermore, the results by clustering analysis were consistent with the known physiological responses of plant to light.
Our observations could suggest that protein expression is significantly influenced by inactivation of the gene cry1, and blue light acting through cry1 regulates the expression of many proteins. Our study provides a useful overview of how cryptochromes affect patterns of protein expression, and could be the basis for further proteomic analysis of seedlings of cry1-304 and col-4.
Acknowledgements
We are grateful to Prof.
Songping LIANG (College of Life Science, Hunan Normal University; Changsha,
China) for his technical help in mass spectrometry, and Dr. Chentao LIN
(University of California, Los Angeles, USA) for his guidance in the work.
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