Original Paper
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Acta Biochim Biophys
Sin 2008, 40: 2737
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)dimethylammonio]-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.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? 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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