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Physiologia Plantarum 142: 390– 406. 2011 Copyright ©Physiologia Plantarum 2011, ISSN 0031-9317
Proteomic analysis of peach endocarp and mesocarp during
early fruit development
Hao Hua,b,c, Yong Liua, Guang-Lu Shib, Yue-Ping Liub, Rui-Jie Wud, Ai-Zhen Yangb, Yi-Ming Wangb,c,
Bao-Guang Huab,c,∗and You-Nian Wangb,∗
aCollege of Forestry, Beijing Forestry University, Beijing 100083, China
bKey Laboratory of Urban Agriculture (North) of Ministry of Agriculture P. R. China, Beijing University of Agriculture, Beijing 102206, China
cProteomics Research Platform, Beijing University of Agriculture, Beijing 102206, China
dCollege of Plant Science and Technology, Beijing University of Agriculture, Beijing 102206, China
Correspondence
*Corresponding authors,
e-mail: huabg@bac.edu.cn;
wyn@bac.edu.cn
Received 27 February 2011
doi:10.1111/j.1399-3054.2011.01479.x
The development of the stone and formation of peach (
Prunus persica
)fruit
were explored in this work using a proteomic approach. Sixty-eight proteins
with different expression patterns were identified in both the endocarp and
mesocarp during early fruit development (from 28 to 59 days after flowering)
and the majority were involved in primary or secondary metabolism. In con-
trast to most proteins associated with primary metabolism in the endocarp,
whose expression is down-regulated, expression of pyruvate dehydrogenase
(PDH) unexpectedly increased exponentially. Moreover, its expression pat-
tern was linearly positively correlated with the exponentially growing lignin
content (R =0.940), which suggests that PDH may play a role in endo-
carp lignification. Our data also revealed different spatiotemporal expressions
of enzymes involved in the lignin and flavonoid pathways that provided
proteome-level evidence to support the hypothesis that these two pathways
are competitive during endocarp development. In addition, we observed
endocarp-specific oxidative stress and propose that it may act as a stimulating
factor in activating lignification and subsequent programmed cell death in
the endocarp.
Introduction
Peach (
Prunus persica
) is the third most economically
important fruit crop in the temperate zone and also one
of the model species in Rosaceae (Shulaev et al. 2008).
After the peach ovule is fertilized, the outermost layer
shapes the protective exocarp, the middle layer forms the
succulent edible mesocarp and the inner layer develops
into the hard, lignified endocarp (Jackson and Edwards
1999). The molecular basis of peach fruit development
Abbreviations – ANR, anthocyanidin reductase; CCoAOMT, caffeoyl-CoA O-methyltransferase; CHI, chalcone isomerase;
CHS, chalcone synthase; β-CAS, β-cyanoalanine synthase; 2D-E, two-dimensional electrophoresis; DAF, days after flowering;
DTT, dithiothreitol; IEF, isoelectric focusing; LDOX, leucoanthocyanidin dioxygenase; LGL, lactoylglutathione lyase; MDAR,
monodehydroascorbatereductase; MALDI-TOF, matrix-assisted laser desorption/ionization time-of-flight; MnSOD, manganese
superoxide dismutase; OMT, O-methyltransferase; PAGE, polyacrylamide gel electrophoresis; PCD, programmed cell death;
PDH, pyruvate dehydrogenase; PDH E1α, pyruvate dehydrogenase E1 component subunit α; PGK, phosphoglycerate kinase;
PRK, phosphoribulokinase; ROS, reactive oxygen species; SAMS, S-adenosylmethionine synthetase; SDS, sodium dodecyl
sulfate; TCA, tricarboxylic acid; UDP-GlcA DCX, UDP-D-glucuronate carboxylyase.
and ripening in the mesocarp and exocarp have been
relatively well researched during recent decades because
of the growing demand for improvements in fruit quality
and nutritional value (Abbott et al. 2009). In contrast,
although lignification (also known as lignin deposition)
in peach endocarp plays important physiological and
evolutional roles in providing waterproof protection
against seed dehydration during maturation, preventing
digestion of the seeds by animals and enhancing seed
dispersal (Rogers and Campbell 2004), it has not received
390 Physiol. Plant. 142, 2011
sufficient scientific attention. Only limited information
was available about the developmental mechanisms
of the peach endocarp, e.g. anatomical observations
(Masia et al. 1992, Ognjanov et al. 1995), biochemical
analyses (Abeles and Biles 1991, Alba et al. 1998,
2000, Hayama et al. 2006, Ryugo 1962, 1964) and
examination of MADS-box transcription factors (Tani
et al. 2007, 2009), until a microarray study on stone
formation very recently elicited a more comprehensive
picture of gene expression dynamics during endocarp
development (Dardick et al. 2010).
Developmental lignification of peach endocarp
involves a strictly co-ordinated process that is simi-
lar to tracheary element differentiation, consisting of
lignin biosynthesis, deposition in the secondary cell wall
and programmed cell death (PCD), that finally shapes
the highly lignified dead cells (Marjamaa et al. 2007).
Although lignin plays an important role in the production
of paper pulp, forage (Baucher et al. 1998) and even bio-
fuel (Chen and Dixon 2007), its biosynthesis is thought to
be an energetically costly process because large amounts
of carbon and energy are invested in this pathway for
producing the unrecoverable structural material (Amthor
2003, Rogers et al. 2005). Taking advantage of a plant
metabolic engineering strategy to enhance fruit quality
by regulating carbon metabolism is an attractive prospect
(Carrari et al. 2006). A report that peach endocarp tends
to accumulate extremely high concentrations of lignin
other than in woody tissues (Dardick et al. 2010) and the
characterization of a stoneless plum cultivar by Callahan
(2009) shed light on the possibility of genetic manipu-
lation of peach fruit lignin metabolism, e.g. breeding
stoneless peach fruit by preventing carbon flux from
entering lignin biosynthesis and improving the sugar and
acid content of the flesh. Consequently, the investigation
of endocarp development and formation mechanisms in
peach fruit highlights not only its scientific but also its
economic importance.
In fact, both fruit development and lignin metabolism
were more complicated than anticipated: there were
many transcriptional and post-translational events affect-
ing the regulation of development and metabolism
(Boerjan et al. 2003, Carrari and Fernie 2006). Com-
pared with approaches based on genomics and tran-
scriptomics, proteomics provides more opportunities to
directly examine the dynamic changes in protein lev-
els and post-translational modifications occurring during
development (Weiss and G ¨org 2007). Among a variety of
proteomics methods, two-dimensional electrophoresis
(2D-E) coupled with mass spectrometry is a powerful
approach for identifying and quantifying proteins that
change during a complex biological process (Aebersold
and Mann 2003). However, only a small number of
reports have been published on the peach fruit proteome
and almost all of them only concerned the post-harvest
field, including physiological disorders (Obenland et al.
2008), heat treatment (Lara et al. 2009), disease defence
(Chan et al. 2007), carbon metabolism changes (Borsani
et al. 2009), oxidative damage (Qin et al. 2009) in har-
vested fruit, mesocarp softening and chilling injury (Nilo
et al. 2010). Proteomic investigation of fruit development
and stone formation has not previously been reported.
In this study, a proteomic approach, based on 2D-E
together with matrix-assisted laser desorption/ionization
time-of-flight (MALDI-TOF) mass spectrometry, was
employed to explore the molecular mechanism of early
peach endocarp development.
Materials and methods
Plant materials and biological measurements
Three neighboring peach trees (
P. persica
cv. Ohkubo)
located in the experimental orchard of Beijing University
of Agriculture (40◦9’ N, 117◦10’ E, Pinggu District, Bei-
jing, China) were the source of fruits and five peaches
were harvested from each tree at 7, 14, 21, 28, 35,
45, 52, 59, 73, 80, 104 and 112 days after flower-
ing (DAF), respectively, for the following observations:
weight and diameter (7–112 DAF), lignin content (7 –73
DAF) and lignin deposition (7–59 DAF). The lignin con-
tent was measured according to the method of Kirk and
Obst (1988) and lignin deposition was detected using
a phloroglucinol–HCl reagent (Abeles and Biles 1991).
Five fruits were picked from each tree at 28, 35, 45, 52
and 59 DAF, respectively, for proteomic analysis. All of
the 15 fruits were randomly divided into three groups
(five fruits per group). The endocarps and mesocarps of
all fruits in the same group were separated, cut into small
pieces, pooled and packaged. Most part of samples were
immediately frozen in liquid nitrogen and then stored
at −80◦C for protein extraction. The remaining fresh
samples were used for evaluating the amounts of water,
according to the following method: fresh tissues were
heated at 110◦C for 1 h and then dried at 85◦C for about
22 h until the dry weight remained constant in a forced
air draft, the amount of water was calculated based on
the ratio of fresh weight to dry weight.
Total protein extraction
Three biological replicates (five fruits per sampling tree)
were subjected to independent protein extraction for
each tissue sample at five developmental stages. Total
protein extraction was performed via the modified phe-
nol–methanol method, as described by Hurkman and
Tanaka (1986) and Deng et al. (2007). In brief, 0.5 g
Physiol. Plant. 142, 2011 391
endocarp or mesocarp tissue was ground into a fine
powder with 0.2% PVPP in liquid nitrogen and then
suspended in 5 ml of sodium dodecyl sulfate (SDS)
extraction buffer [100 m
M
Tris–HCl (pH 8.0), 2%
SDS, 0.5% β-mercaptoethanol, 5 m
M
EGTA, 10 m
M
EDTA and one Complete Mini Protease Inhibitor Tablet
(Roche, Mannheim, Germany)] and incubated at 65◦C
for 10 min. The samples were then centrifuged at 20 000
g
for 20 min. The supernatant was mixed with an equal
volume of ice-cold Tris-buffered phenol (pH 7.8) and
then centrifuged at 20 000
g
for 15 min at 4◦C. The
upper aqueous phase was carefully removed and the
lower phenol phase was re-extracted twice with 50 m
M
Tris–HCl (pH 8.0). Then 5 ml of cold precipitation
solution (0.1
M
ammonium acetate in methanol) was
added; and the mixture was kept at −20◦C overnight to
precipitate the proteins. After centrifugation at 20 000
g
for 20 min at 4◦C, the pellet was washed three
times with 5 ml of precipitation solution and once
with ethanol, then it was dissolved in 450 μl isoelec-
tric focusing (IEF) buffer [7
M
urea, 2
M
thiourea, 3%
3-[(3-cholamidopropyl)dimethylammonio]-1-propane-
sulfonate (CHAPS), 15 m
M
dithiothreitol (DTT) and 0.5%
Bio-Lyte 5/8 Ampholyte (Bio-Rad, Hercules, CA)] and
centrifuged at 20 000
g
for 30 min in order to remove
insoluble debris. Then the protein samples were cleaned
with ReadyPrep 2-D Cleanup Kit (Bio-Rad) and the pro-
tein concentration was assessed with 2-D Quant Kit
(GE Healthcare, Uppsala, Sweden) using bovine serum
albumin as standard, according to the manufacturer’s
instructions. The resolubilized protein samples were
stored at −80◦C prior to use.
Two-dimensional gel electrophoresis
Three gels were run on each extract. In brief, each 800-
μg protein sample dissolved in IEF buffer was loaded
on 24-cm ReadyStrip IPG Strips, pH 5–8 (Bio-Rad),
for 14 h active rehydration at 20◦ConPROTEANIEF
Cell (Bio-Rad). The IEF procedure was programmed
as follows: 500 V for 1 h, 1000 V for 1 h, ramping
increased to 8000 V over 3 h and voltage maintained
at 8000 V up to 65 000 V/h. Focused strips were
equilibrated with equilibration buffer [6
M
urea, 30%
glycerol, 2% SDS, 50 m
M
Tris–HCl (pH 8.0)] first with
0.5% DTT and then with 2% iodoacetamide for 15 min.
The 2D-E was carried out on an Ettan DALTsix (GE
Healthcare) by transferring the strips to 12.5% SDS-
polyacrylamide gel electrophoresic (SDS-PAGE) gels;
proteins were separated for 30 min at 5 W per gel and
then at 17 W per gel until the bromophenol blue dye
front reached the bottom of the gel. The gels were
visualized by Coomassie Brilliant Blue-G250 using the
Bluesilver protocol (Candiano et al. 2004).
Image scanning and data analysis
The stained gels were scanned by a UMAX 2100 XL
Scanner (UMAX Technologies, Dallas, TX) with transmis-
sion mode at 300 DPI. The digitalized images were pro-
cessed with PDQuest Advanced V8.0.1 (Bio-Rad); spot
detection and matching were performed automatically,
followed by manual editing and the local regression
model was used to normalize the experimental variations
across gels. In PDQuest, the term ‘spot quantity’ was used
to define the total intensity of a given spot in a gel image
and it was calculated by using the following formula:
Spot quantity =spot height ×π×σx×σy
where the spot height was the peak of the Gaussian
distribution of the spot in optical density units and σx
and σywere the standard deviations of the Gaussian
distribution in the directions of the x- and y-axes.
For the purpose of minimizing variations in protein
extractability and content during fruit development,
each 800-μg (0.8-mg) protein loading sample was
first converted to its original dry tissue weight by the
following formula:
Original dry tissue weight (g DW)
=0.8 mg protein loading sample
protein content (mg g−1DW)
Then the individual spot quantity value exported from
PDQuest was transformed against the above calculated
original dry tissue weight according to the following
formula:
Spot quantity g−1DW
=exported spot quantity
original dry tissue weight (g DW)
The transformed quantitative data were statistically ana-
lyzed using SigmaPlot Statistics V11.2 (http://www.
sigmaplot.com). Two-way analysis of variance followed
by the Student–Newman –Keuls test was used to deter-
mine whether the spot quantity changes in different
tissues (endocarp and mesocarp) across the five sam-
pling stages were statistically significant. Only spots
with significant variation (
P
<0.05) in spot quantity
and whose presence was detectable in all replicates
were excised manually. Hierarchical clustering was car-
ried out using PermutMatrix V1.9.3 software (Caraux
and Pinloche 2005) by normalizing spot quantity with
a z-score transformation and Pearson’s distances and
Ward’s algorithm were used for this analysis.
In-gel digestion, mass spectrometry-based protein
identification and database searches
The in-gel digestion was performed according to
the protocol of Sommerer et al. (2007) with minor
392 Physiol. Plant. 142, 2011
modification. Briefly, the selected protein spots were
washed twice with ultra-pure water, de-stained twice
with 50% acetonitrile in 100 m
M
ammonium bicar-
bonate until the dyes were fully removed, lyophilized
under vacuum and rehydrated in 2 μl digestion solu-
tion [20 m
M
ammonium bicarbonate, 1 m
M
CaCl2and
0.025 mg ml−1modified trypsin (Roche, Mannheim,
Germany)] for 1 h at 4◦C, then digested at 37◦C
overnight. The peptides were extracted twice with a
solution containing 50% acetonitrile and 0.1% triflu-
oroacetic acid, vacuum-dried to 5 μl and mixed with
α-cyano-4-hydroxycinnamic acid matrix on a target
plate. The mass spectra were obtained by Autoflex II
MALDI-TOF mass spectrometer (BrukerDaltonics, Bre-
men, Germany) according to the manufacturer’s manual.
The raw spectra were manually filtered by
PEAKERAZOR (http://www.protein.sdu.dk/gpmaw/Help/
PeakErazor/peakerazor.html) to detect potential con-
taminants and then were submitted to MASCOT soft-
ware (http://www.matrixscience.com) to search the
NCBInr (version 20100102, 10272453 sequences and
3505279183 residues included) or SwissProt (version
57.12, 513877 sequences and 180750753 residues
included) databases. The search was performed using the
following settings: taxonomy was Viridiplantae (green
plant), fixed modifications of carbamidomethylation,
variable modifications of oxidation, one miscleavage
of trypsin and 0.2-Da mass tolerances for the pep-
tide. Candidate peptides qualified only if the MASCOT
score was above the significance threshold of 95% (in
this circumstance, a score ≥71 for NCBInr and ≥57
for SwissProt), the minimum four predicted peptide
masses matched (at least 10% for sequence cover-
age) and the maximum diversity between theoretical
and experimental molecular weights did not exceed
25%. Spots for which the MASCOT scores were lower
than the significance threshold were resequenced using
MALDI-TOF-TOF mode, followed by the MASCOT MS/MS
ion searching program. The identified proteins were
assigned to KEGG (http://www.genome.jp/kegg), MIPS
funcats (http://www.mips.gsf.de/projects/funcat), or the
literature for functional annotation.
Results
Identification of fruit development and endocarp
lignification
The weights and diameters of growing fruits were
monitored from 7 to 112 DAF. Both parameters were
characterized by four fruit growth stages: S1, S2, S3 and
S4 (Fig. 1A). The inflection points of the different stages
were noted at 35, 59 and 104 DAF and we sampled
between 28 and 59 DAF for proteomic analysis, cover-
ing the end of the S1 stage and the entire S2 stage. Fig. 1B
shows a continued expansion of the endocarp from 7
to 59 DAF, while the mesocarp remained compact.
The lignin deposition dynamics of the endocarp were
observed via phloroglucinol–HCl staining (Fig. 1B). The
phloroglucinol-positive reaction was first detected on
exocarp fuzz at 7 DAF and then bits of vascular bundles
were detected at 14 DAF. The lignified patterns were
clearly visible in relatively large areas starting from 45
DAF and featured a rapid expansion from seed cav-
ity to the peripheral region of the endocarp. However,
the lignin content of the endocarp displayed a sharp
increase starting from 21 DAF and its curve was fitted
to the five-parameter double exponential growth func-
tion (y =−37.008 +18.838e0.034x +7.918e0.034x,R
2=
0.996) (Fig. 1 C).
Evolution of proteome profiles in the endocarp
and mesocarp during fruit development
By applying a modified phenol– methanol protein extrac-
tion protocol, each protein sample collected from the
endocarp and mesocarp at 28, 35, 45, 52 and 59
DAF contained more than 10 mg protein per gram dry
fruit weight (Table 1). To minimize variations in protein
extractability and content during fruit development, the
original spot quantity values exported from PDQuest
were transformed into a corrected spot quantity with
units ‘spot quantity/g DW’, which was employed as
a reliable unit for the following quantitative analysis
procedures.
To investigate the global dynamics of protein expres-
sion during early fruit development, we used 2D-E to
reveal the proteome profiles sampled in the endocarp
and mesocarp at five time points during development.
The comparative proteomic analysis indicated the spot
numbers were higher in the endocarp than the mesocarp
during the sampled days (Fig. 2, Table 1). During the end
of the S1 stage (28–35 DAF), the spot numbers in gels of
the two grouped tissues displayed a dramatic decline of
approximately −20% in the endocarp and −39% in the
mesocarp. During the following S2 stage (35–59 DAF),
the spot numbers of the gels exhibited a similar decrease
of, on average, −21 and −36% in the endocarp and
mesocarp, respectively.
Mass spectrometry protein identification,
hierarchical clustering analysis and functional
distribution
On the basis of the image and statistical analyses, a
total of 115 spots were associated with clear quantity
Physiol. Plant. 142, 2011 393
Fig. 1. Assessment of peach fruit development and the lignin deposition process in the endocarp. (A) The growth curve of peach fruit. The entire fruit
development process was matched to a typical double-sigmoid growth pattern, which featured four stages: S1, S2, S3 and S4. The fruit samples for
proteome analysis were harvested at 28, 35, 45, 52 and 59 DAF. (B) The lignin deposition process in developing peach fruit. The dissected 7– 59 DAF
fruits were stained by phloroglucinol –HCl to detect lignin deposition. S, Seed; En, Endocarp; Me, Mesocarp. Arrows indicate the lignified vascular
bundle. (C) Quantitative determination of lignin content. The solid line indicates the change in lignin content in the endocarp from 7 to 73 DAF and
the dotted line shows the calculated curve (y =−37.008 +18.838e0.034x +7.918e0.034x,R
2=0.996).
Fig. 2. Representative Coomassie Brilliant Blue stained 2D-E gels of peach fruit endocarp and mesocarp from 28 to 59 DAF. Protein samples (800-μg)
were loaded onto 24-cm immobilized strips (pH 5– 8) for IEF, followed by 12.5% SDS-PAGE.
394 Physiol. Plant. 142, 2011
Table 1. The number of valid spots observed on 2D-E gels and their
protein contents from extracts of peach endocarp and mesocarp sampled
at different stages of development. DW, dry fruit weight.
Endocarp Mesocarp
DAF
Number of
valid spots
Protein content
(mg/g DW)
Number of
valid spots
Protein content
(mg/g DW)
28 714 10.420 601 11.175
35 573 18.486 368 13.720
45 543 12.681 334 10.666
52 491 14.859 274 12.508
59 455 17.132 237 13.455
changes both in the endocarp and mesocarp at the five
time-points during development. From the mass spec-
trometric analysis, 90 of the 115 spots were shown to
be peptide signals and, among them, 68 spots were
successfully matched to proteins in either the NCBInr
or SwissProt database by MASCOT software based on
the criteria described in section Materials and meth-
ods, including six spots identified by MALDI-TOF-TOF
(superscript letter ‘a’ in Table 2). Among 68 identified
spots, 57 were actually characterized as unique proteins
(Tables 2, S1 and S2, Supporting information, Fig. 3).
The remaining 11 proteins were represented by multiple
spots with different pI and/or mass weight value, or the
mixture of several proteins with very similar pI and/or
mass weight values (mark of ‘m1’ and ‘m2’ in Table 2).
Sixty-eight identified spots were subjected to hierar-
chical clustering analysis using the PermutMatrix soft-
ware (Fig. 4) and three groups of spots were observed
both in endocarp and mesocarp. Clusters E1 and M1
contained 30 and 29 spots, respectively, which over
Fig. 3. Localization of 68 identified spots on a representative 2D-E gel
of peach fruit endocarp at 28 DAF. The corresponding proteins are listed
in Table 2 with details.
accumulated in the end of S1 stage (28– 35 DAF). Clus-
ters E2 and M2 were composed of 23 and 19 spots,
respectively, whose abundance increased in beginning
and middle of the S2 stage (35–52 DAF). Clusters E3
and M3 comprised 15 and 20 spots, respectively, which
were specifically induced during the end of the S2 stage
(52–59 DAF).
All identified proteins were catalogued by five
functional groups according to the descriptions in KEGG
and MIPS FunCat annotations or the other published
literature. The major proportion of proteins (44%) were
involved in primary metabolism, 17% in secondary
metabolism, 14% in detoxification and stress response,
13% in protein synthesis and degradation and 4% in
cytoskeleton and signaling; the remaining 10% of spots
were assigned to unknown proteins. From the taxonomic
viewpoint, among the 57 unique proteins, eight matched
available peach sequences (
P. persica
), eight belonged
to Rosaceae, five to
Vitis
,threeto
Populus
, six to
Arabidopsis and the remaining 34 were associated with
other green plant species.
Spatiotemporal expression of the proteins
involved in the energy and carbohydrate
metabolism pathways
Our results have shown that the enzymes involved in pri-
mary metabolism were more abundant in the endocarp
than in the mesocarp. Most of glycolysis and gluconeoge-
nesis enzymes (Table 2) gradually decreased in the endo-
carp but slightly induced in the mesocarp from 28 to 59
DAF, while most tricarboxylic acid (TCA) cycle and car-
bohydrate metabolism proteins (Table 2) were repressed
in both the endocarp and mesocarp. Unexpectedly, the
pyruvate dehydrogenase E1 component subunit α(PDH
E1α) displayed an endocarp-specific significant expo-
nential upregulation from 28 to 59 DAF (up to 19.92 −
fold, y =109029.016 +135.088e0.166x,R
2=0.994). In
addition, a cell wall formation associated enzyme,
UDP-D-glucuronatecarboxylyase (UDP-GlcA DCX), was
strongly over-expressed (up to 5.32-fold) from 45 to 59
DAF in the endocarp, but it remained at lower levels in
the mesocarp.
Spatiotemporal expression of the proteins
involved in the lignin, flavonoid and detoxification
metabolism pathways
Among the identified proteins, many are involved in
secondary metabolism, such as the lignin, flavonoid and
detoxification pathways.
The lignin pathway proteins, caffeoyl-CoA-O-methyl-
transferase (CCoAOMT) and S-adenosylmethionine
Physiol. Plant. 142, 2011 395
Table 2. Proteins identified by mass spectrometry. Evolution of identified proteins in the endocarp (dotted line) and the mesocarp (solid line) during
early fruit development is shown by linear graphic representation of ‘spot quantity/g DW’ (y-axis) for the five sampling dates (28, 35, 45, 52 and 59
DAF). Spot quantity is expressed in units of OD ×IU2, where OD is the spot quantity in optical density units and IU (image unit) is the product of the
standard deviations of the Gaussian distributions of the spot in the directions of the y- and x-axes and πand additional computational procedures
were used to eliminate protein extractability and content variation during fruit development (see section on Materials and methods). ‘m1’ and ‘m2’
are the two spots identified as mixtures of different proteins. MW, mass weight. aProteins identified only in MALDI-TOF-TOF mode. More details
about the MASCOT results are shown in ‘Table S2’.
Spot no. Homologous protein Accession no.
Mowse
score
Theoretical
MW (KDa)/pI
Observed MW
(KDa)/pI
Evolution
(28– 59 DAF)
Primary and energy metabolism
Carbohydrate metabolism
24 α-1,4-Glucan-protein
synthase
O04300 71 42.06/5.73 35.71/5.74
30 α-1,4-Glucan-protein
synthase
O04300 73 42.06/5.73 39.66/5.79
38 Phosphoglycerate
kinase
P29409 74 50.11/8.74 41.00/5.98
62 Phosphoribulokinase P09559 62 45.32/5.82 39.41/5.80
59 Rubisco large chain P28450 288 48.73/6.46 53.41/6.37
60 Rubisco large subunit ACB88656 110 48.26/6.21 54.59/6.09
3 Rubisco
subunit-binding
protein subunit β
XP_002523404 78 64.49/5.65 59.59/5.67
42 Soluble inorganic
pyrophosphatase
AAF27918 108 26.20/5.64 27.67/6.51
54 UDP-D-glucuronate
carboxylase
BAB40967 134 39.06/6.68 38.30/7.90
Amino acid metabolism
61 5-Methyltetrahydro-
pteroyltriglutamate-
homocysteine
methyltransferase
XP_002525709 138 84.90/6.09 71.95/6.95
36 S-adenosylmethionine
synthetase 2
Q9AT55 148 43.57/5.50 46.73/5.90
35 S-adenosylmethionine
synthetase 2
Q9AT55 75 43.57/5.50 46.07/5.86
396 Physiol. Plant. 142, 2011
Table 2. Continued.
Spot no. Homologous protein Accession no.
Mowse
score
Theoretical
MW (KDa)/pI
Observed MW
(KDa)/pI
Evolution
(28– 59 DAF)
37 S-adenosylmethionine
synthetase 5
A7Q0V4 137 43.22/5.57 47.03/5.94
67 Serine hydroxymethyl-
transferase
ACJ11726 90 52.38/7.57 68.14/7.45
66 Serine hydroxymethyl-
transferase
ACJ11726 155 52.38/7.57 59.41/7.31
Glycolysis and gluconeogenesis
53 AldolaseaAAG21429 68 38.72/6.93 38.40/7.64
9 Enolase NP_177543 144 51.84/5.79 53.25/5.83
33 Enolase ABW21688 144 47.98/5.49 54.73/5.88
64 Enolase (m1) Q43321 79 47.80/5.41 57.75/5.75
64 Enolase (m1) AAY34909 74 16.02/5.13 57.75/5.75
49 Glyceraldehyde-3-
phosphate
dehydrogenase
Q42671 138 36.57/7.06 37.68/7.43
41 Triosephosphate
isomerase
P21820 59 27.24/5.54 28.22/6.41
TCA cycle
45 NAD+-dependent
malate
dehydrogenase
ACG34976 79 41.39/7.60 35.21/6.97
39 NAD+-dependent
malate
dehydrogenase
AAL11502 177 35.81/6.60 36.94/6.04
44 NAD+-dependent
malate
dehydrogenase
AAL11502 194 35.81/6.60 37.07/6.83
Physiol. Plant. 142, 2011 397
Table 2. Continued.
Spot no. Homologous protein Accession no.
Mowse
score
Theoretical
MW (KDa)/pI
Observed MW
(KDa)/pI
Evolution
(28– 59 DAF)
48 NAD+-dependent
malate
dehydrogenase
AAL11502 178 35.82/6.60 36.80/7.20
52 Pyruvate
dehydrogenase E1
component
subunit α
P52902 59 43.96/8.02 40.04/7.44
29 Succinyl-CoA ligase O82662 69 45.60/6.30 42.10/5.66
Energy generation
4 ATP synthase subunit
β3
Q9C5A9 115 59.99/6.06 54.04/5.62
31 ATP synthase subunit
β
P17614 162 59.93/5.95 53.74/5.65
Secondary metabolism
26 Anthocyanidin
reductasea
AAX12184 79 37.10/5.29 38.85/5.66
8 Anthocyanidin
reductasea
AAX12184 87 37.10/5.29 38.99/5.61
14 Caffeoyl-CoA O-
methyltransferase
BAE48788 108 27.90/5.29 29.61/5.10
15 Chalcone isomeraseaBAC98341 86 78.86/4.97 24.89/5.75
51 Chalcone synthase BAE17124 192 42.99/6.04 39.96/6.59
56 Chalcone synthase BAE17124 147 42.99/6.04 44.19/6.41
22 Coproporphyrinogen
III oxidase
P35055 61 43.58/6.73 35.15/5.98
27 Flavanone
3-hydroxylase (m2)
BAC98346 105 30.44/5.43 40.28/5.72
27 Leucoanthocyanidin
dioxygenase (m2)
ABX89941 173 40.68/5.46 40.28/5.72
398 Physiol. Plant. 142, 2011
Table 2. Continued.
Spot no. Homologous protein Accession no.
Mowse
score
Theoretical
MW (KDa)/pI
Observed MW
(KDa)/pI
Evolution
(28– 59 DAF)
20 Leucoanthocyanidin
dioxygenase
ABX89941 151 40.68/5.46 35.11/5.77
23 Leucoanthocyanidin
dioxygenase
ABX89941 93 40.68/5.46 39.22/5.82
7 Magnesium-chelatase
subunit ch II
O22436 70 46.88/6.64 42.25/5.52
Detoxification and stress response
50 β-cyanoalanine
synthase
AAN86822 84 38.26/6.38 38.81/7.08
65 Dehydrin type II SK2 AAZ83586 112 28.53/5.73 50.80/5.64
68 Dehydrin-like protein CAC00637 108 48.18/6.53 59.55/7.60
13 Ferritin 1 P19976 70 28.20/5.73 27.03/5.65
19 Lactoylglutathione
lyasea
ACJ11750 82 32.61/5.69 32.32/5.64
43 Manganese
superoxide
dismutase 2
CAC19487 62 25.88/7.10 25.13/6.48
55 Monodehydroas-
corbate
reductase
Q40977 106 47.39/5.79 43.93/6.85
32 Polyphenol oxidase
precursor
AAC28935 99 67.43/6.39 63.04/5.89
40 Polyphenol oxidase
precursor
AAC28935 71 67.43/6.39 41.35/6.09
34 Polyphenol oxidase
precursor
AAC28935 107 67.43/6.39 60.00/6.01
Protein synthesis and degradation
17 20S proteasome
subunit α1
ACJ11727 111 27.39/5.92 27.72/5.96
Physiol. Plant. 142, 2011 399
Table 2. Continued.
Spot no. Homologous protein Accession no.
Mowse
score
Theoretical
MW (KDa)/pI
Observed MW
(KDa)/pI
Evolution
(28– 59 DAF)
47 20S proteasome β
subunit 5
AAL26914 135 21.88/6.08 25.61/7.13
6 26S protease
regulatory subunit
6A
O04019 238 46.86/4.90 48.95/5.56
5 26S protease
regulatory subunit
6B
Q9SEI4 125 45.90/5.42 50.75/5.61
63 26S protease
regulatory subunit
6B
Q9SEI4 237 45.90/5.42 43.87/5.84
28 40S ribosomal protein
SA
A5BUU4 81 34.06/5.43 42.39/5.67
1 Disulfide-isomerase
precursor
ACH58420 76 94.79/7.93 64.20/5.40
2 Heat shock cognate
70 kDa protein 1
XP_002284008 172 71.59/5.17 67.98/5.59
16 Proteasome subunit α
type 3
O24362 78 27.55/6.11 28.12/5.92
Cytoskeleton and signaling
64 β-Tubulin (m1) ACI03399 158 50.88/4.79 57.75/5.75
25 Actin 7 P53492 161 41.93/5.31 37.73/5.66
46 Ran3 GTP-binding
protein
ABV57373 174 18.83/9.44 29.19/7.31
Unknown
21 Hypothetical protein XP_002263926 133 41.49/5.66 37.89/5.92
58 Hypothetical protein XP_002271021 112 53.74/6.32 50.82/6.47
11 Predicted proteinaXP_002309064 82 27.10/5.68 28.64/5.61
400 Physiol. Plant. 142, 2011
Table 2. Continued.
Spot no. Homologous protein Accession no.
Mowse
score
Theoretical
MW (KDa)/pI
Observed MW
(KDa)/pI
Evolution
(28– 59 DAF)
57 Predicted protein XP_002308228 84 43.89/6.58 47.94/6.59
10 Unknown proteinaACU21370 57 35.88/8.91 32.38/5.59
12 Unknown protein ABK94952 87 35.47/4.93 30.36/5.66
18 Unknown protein ABK94952 109 35.47/4.93 33.95/5.73
synthetase (SAMS) were identified in our study (Table 2).
CCoAOMT revealed a remarkable over-expression (up
to 139.36-fold) after 45 DAF in the endocarp, but did not
change significantly in the mesocarp; these data are in
agreement with our phloroglucinol –HCl staining results.
On the other hand, SAMS was detected at higher expres-
sion levels (average 3.79-fold) in the endocarp than in
the mesocarp throughout the period.
Various enzymes from the flavonoid pathway
(Table 2), including chalcone isomerase (CHI), antho-
cyanidin reductase (ANR), chalcone synthase (CHS) and
leucoanthocyanidin dioxygenase (LDOX), exhibited sig-
nificant downregulation after 35 DAF in the endocarp
[up to 2.88-fold for CHI (spot 15), 4.19- and 2.14-fold
for ANR (spots 08 and 26), 8.29-fold for CHS (spot 56)
and 5.53-fold for LDOX (spot 23)], while these proteins
were present at lower levels in the mesocarp.
Several reactive oxygen species (ROS) scavenging and
detoxification enzymes from the detoxification pathway
were found (Table 2). Two ROS-scavenging enzymes,
manganese superoxide dismutase 2 (MnSOD2) and
monodehydroascorbatereductase (MDAR), as well as
two detoxification enzymes, lactoylglutathionelyase
(LGL) and β-cyanoalanine synthase (β-CAS), were
obviously down-regulated (up to 4.82-fold for MnSOD2,
7.73-fold for MDAR, 4.09-fold for LGL and 2.02-fold
for β-CAS) after 35 DAF in the endocarp. In contrast,
in the mesocarp we found that MnSOD2 and β-CAS
were up-regulated, LGL was down-regulated and MDAR
remained at low levels. In addition, another ROS-
scavenging enzyme, ferritin 1, was observed to maintain
a steady expression pattern in the endocarp throughout
development, but it was enhanced (up to 2.03-fold) in
themesocarpfrom35to59DAF.
Discussion
Assessment of the lignification process
and proteome dynamics
The peach fruit is a typical stone fruit with a double-
sigmoid growth curve. Of the four stages of fruit
development, it is widely recognized that endocarp
lignification starts in the S2 stage and some papers have
also confirmed that this process rapidly begins to occur
within 10 days of the transition period from the S1 to
the S2 stage (Chalmers and Ende 1975, Lilien-Kipnis and
Lavee 1971, Ryugo 1961), which is consistent with our
experimental results on the survey of growth parameters
and lignin deposition.
On the basis of the analysis of proteome profiles, the
total number of valid protein spots decreased throughout
early fruit development in both the endocarp and meso-
carp. This trend is in agreement with previously pub-
lished results in a study of grape berries (Giribaldi et al.
2007) and tomato (Faurobert et al. 2007), which revealed
higher protein expression and activity in young fruits fol-
lowed by a decline during development. In addition, we
observed that the number of protein spots was much
higher in the endocarp than in the mesocarp through-
out development. These data emphasize that metabolic
activities in the endocarp are more vigorous than in the
mesocarp, i.e. the endocarp may play a predominant
role in the early stage of peach fruit development.
Among the 68 identified protein spots, 25 were
verified to represent 11 unique proteins; hence, it
was suggested that 37% of the identified spots might
be related to post-translational modifications of the
same gene-encoded products or protein isoforms that
originated from a different gene family. The six proteins
Physiol. Plant. 142, 2011 401
Fig. 4. Clustering analysis of the 68 identified spots in endocarp and
mesocarp between 28 and 59 DAF. Dataset clustering was performed
with PermutMatrix software after z-score normalization of the means
of spot quantities. Each colorized cell represents the averaged spot
quantity, according to the color scale at the bottom of the figure.
that remain unclassified may be attributed to the lack
of peach sequence information in current databases
and their functions are expected to be characterized by
upcoming peach genome data.
Alterations of primary metabolism in endocarp
lignification
The primary metabolism in peach is highly linked to
fruit quality (e.g. the formation of sugar and organic acid
content) and mescocarp metabolic activities have been
relatively well characterized in recent years. However,
detailed investigations of the primary metabolism of the
endocarp have rarely been reported. It is well known that
the carbon sources demanded by secondary metabolism
rely on the precursor supply of primary metabolism
(Douglas 1996) and some evidence has indicated that
the manipulation of primary metabolism can affect the
production of secondary metabolites, such as lignin
(Dauwe et al. 2007, Henkes et al. 2001, Rogers et al.
2005). In this study, we attempted to interpret the
underlying relationship between primary metabolism
and lignification.
Our results have shown that the majority of enzymes
involved in primary metabolism, including glycolysis
and the TCA and Calvin cycles, were significantly
decreased in the endocarp after 28 or 35 DAF (Table 2).
A similar finding, documented by Dardick et al. (2010),
was that the genes involved in these pathways were
repressed during lignin and flavonoid induction accord-
ing to ‘regulons’ analysis. Furthermore, unlike previous
investigations on individual proteins or single tissues of
peach fruit, our study for the first time illustrates the
comparative expression patterns of primary metabolism
proteins in both the endocarp and mesocarp and indi-
cates the expression levels of most of primary metabolism
proteins are higher in the endocarp than in the meso-
carp. We suggest that the endocarp may prefer to use
these enzymes as carbon sources for channeling into
biosynthetic pathways during early fruit development.
Interestingly, we found that the expression of PDH
E1α, a well-characterized enzyme complex that links
glycolysis to the TCA cycle (Tovar-M´endez et al. 2003),
was exponentially increased in the endocarp during
the sampled days (Table 2). Moreover, surprisingly,
it was notable that the lignin content was high
positively correlated with the PDH E1αexpression
level (R =0.940). According to the dataset of gene
expression analysis published by Dardick et al. (2010),
the expression of PDH E1β, which is another subunit of
PDH, was found to be up-regulated by approximately
40-fold during development and it was also identified
as a ‘regulon’ that is induced during lignin pathway
induction. Hence, these observations suggest that PDH
may have a potential role in the lignification of the
endocarp and further studies will be needed to determine
the exact role of PDH in affecting stone formation.
The identified carbohydrate-related proteins, phos-
phoribulokinase (PRK) and phosphoglycerate kinase
(PGK), showed a clear decline after 28 and 35 DAF,
respectively, in the endocarp; during the same period
PRK was up-regulated in the mesocarp and the abun-
dance of PGK was higher in mesocarp than endocarp
(Table 2). As essential enzymes in the Calvin cycle, the
different expression patterns of PRK and PGK in the two
tissues suggest the beginning of photosynthetic carbon
assimilation in the mesocarp and the loss of photosyn-
thesis function in the endocarp. This was also supported
by our unpublished electron microscopy observations
of endocarp chloroplast degeneration occurring at 35
DAF. Another carbohydrate-related protein, UDP-GlcA
402 Physiol. Plant. 142, 2011
DCX (also known as UDP-D-xylose synthase), plays an
important role in cell wall formation by converting UDP-
D-glucuronate to UDP-xylose that is used to produce
the structural components (glycoproteins, polysaccha-
rides and hemicelluloses) of the cell wall (Harper and
Bar-Peled 2002). It has been reported that the expression
of a 40-kDa UDP-GlcA DCX protein in tobacco was
found to elevate secondary cell wall formation (Bind-
schedler et al. 2005). Another report on the antisense
UDP-GlcA DCX transgenic tobacco lines also showed
they were associated with reduced xylans in the sec-
ondary cell wall as well as better extractability of the
hemicelluloses (Bindschedler et al. 2007). The 38.3-kDa
UDP-GlcA DCX found in our study is very similar to the
40-kDa one reported above. According to its increased
abundance from 45 to 59 DAF in the endocarp (Table 2),
we suggest that UDP-GlcA DCX may be involved in the
formation of the secondary cell wall in the endocarp.
Different protein expressions in the lignin and
flavonoid pathways during endocarp development
The proper formation of a lignified stone is highly depen-
dent on the accurate regulation of lignin biosynthesis
and deposition that has been integrated into cell devel-
opment and differentiation. In this study, we found
the expression of CCoAOMT, a well-known enzyme
that acts as an O-methyltransferase (OMT) responsible
for catalyzing the transformation of caffeoyl-CoA into
feruluyl-CoA in monolignol biosynthesis (Martz et al.
1998), was significantly up-regulated in the endocarp
from 45 to 59 DAF (Table 2). Meanwhile, SAMS proteins
were detected at higher abundance in the endocarp than
in the mesocarp from 28 to 59 DAF (Table 2). SAMS
catalyzes the formation of
S
-adenosylmethionine (SAM),
the main methyl group donor utilized by OMTs in mono-
lignol biosynthesis (Campbell and Sederoff 1996, Moffatt
and Weretilnyk 2001). Shen et al. (2002) reported that
SAMS genes were intensely expressed in highly ligni-
fied tissues and it was suggested that the lignification
might consume large amounts of SAM. In addition, we
found the proteins linked to the flavonoid pathway,
such as ANR, CHI, CHS and LDOX, were obviously
down-regulated in the endocarp after 35 DAF (Table 2).
Taken together, we observed different spatiotemporal
expressions of the enzymes involved in the lignin and
flavonoid pathways at the proteome level and these
data strongly support a model in which the lignin and
flavonoid pathways are competitive in the endocarp
(Dardick et al. 2010).
On the contrary, we found that the expression of
the flavonoid enzymes (ANR, CHI, CHS and LDOX)
in the mesocarp was markedly repressed during fruit
development (Table 2). This inconsistency could be
interpreted in terms of the assumption of Dardick et al.
(2010), who suggested that different peach cultivars
might have varied flavonoid gene expression patterns. In
our experiments we sampled the young fruit of cultivar
‘Ohkubo’, which was characterized by its green flesh and
skin and it seems that the pigments in its young fruit may
be dominated by chlorophyll rather than anthocyanins.
Endocarp-specific oxidative stress during early
fruit development
It has been shown that PCD can be initiated by ele-
vated ROS levels, such as H2O2and superoxide anion
(Blokhina and Fagerstedt 2010, Gadjev et al. 2008,
Miller et al. 2008). It is noteworthy that H2O2also acts
as a signal in inducing gene expression of lignin biosyn-
thesis enzymes (Desikan et al. 1998, Torres et al. 2010,
Wu et al. 1997). In our study, several ROS-scavenging
enzymes were found to be noticeably down-regulated
in the endocarp after 35 DAF (Table 2). MnSOD is
responsible for eliminating superoxide anions (Bagnoli
et al. 2002) and it may lose catalytic activity or struc-
tural integrity under strong oxidative stress (Qin et al.
2009). Therefore, the decreased MnSOD activity in the
endocarp may reflect enhanced superoxide anion levels
and oxidative stress in the mitochondria. MDAR is a
key enzyme that uses NAD(P)H to regenerate antioxi-
dants such as ascorbic acid, which can detoxify H2O2to
H2O in enzymic and non-enzymic approaches (Mittler
et al. 2004). The sharply down-regulated MDAR in the
endocarp suggests a shrinkage of the antioxidant pool in
the cells and underlying H2O2accumulation. LGL and
β-CAS play roles in eliminating cellular toxicants. LGL
was known as glutathione-based glyoxalase I, which
catalyzes the transformation of highly toxic methylgly-
oxal into lactoylglutathione in the glyoxalase system
(Thornalley 1996). In addition, β-CAS catalyzes the for-
mation of the non-protein amino acid β-cyanoalanine by
using lethal hydrogen cyanide (Blumenthal et al. 1968).
Previous reports have proved that methylglyoxal and
hydrogen cyanide could act as either ROS-generating
compounds or apoptosis inducers (Amicarelli et al.
2003, Chan et al. 2005, Oracz et al. 2009). It is con-
ceivable that the declining expression patterns of these
two enzymes after 35 DAF might, in turn, stimulate the
production of ROS. These data indicate that the endocarp
was undergoing an aggravating oxidative stress after 35
DAF compared with the contemporaneous mesocarp.
Taking into consideration the above results concern-
ing the dramatically increased lignin deposition and
turnover in the lignin and flavonoid pathways in the
endocarp between 35 and 59 DAF, we suggest here that
Physiol. Plant. 142, 2011 403
the ROS enhancement and the resulting oxidative stress
may activate the lignification process and the subsequent
PCD in the endocarp.
In summary, by using a comparative proteomic
approach, we have observed the global proteome
dynamics of the endocarp and mesocarp during
early fruit development. According to our data, we
found repression of the primary metabolic pathway,
competition between the lignin and flavonoid pathways
at the proteome level and endocarp-specific antioxidant
system breakdown at the transition from stage S1 to
stage S2 (35–45 DAF). To our knowledge, this is
the first proteomics investigation focused on peach
fruit development and these results not only provide
new understanding of the endocarp development
mechanism, but also new inspiration for further genetic
manipulation to improve fruit quality.
Acknowledgements –
This work was financially sup-
ported by the National Natural Science Foundation of
China (30872029), the Key Natural Science Founda-
tion of Beijing Municipality (5111001), the Natural Sci-
ence Foundation of Beijing Municipality (6092007), the
Key Foundation of Beijing Municipal Education Com-
mittee (KZ201010020016), Funding Project for Academic
Human Resources Development in Institutions of Higher
Learning Under the Jurisdiction of Beijing Municipal-
ity (PHR20090516, PHR200906134, PXM2007-014207-
044536 and PXM2007-014207-044538), Beijing Municipal
Education Committee and New Star Plan of Science and
Technology of Beijing (2008B22). We thank Dr Jian-Wen
Wang for his advice in statistical analysis.
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Supporting Information
Additional Supporting Information may be found in the
online version of this article:
Table S1. The quantitative data of 68 identified spots.
Spot quantities were determined as described in
section Materials and methods, and the significance
of differences for each protein spot over five sampling
stages in endocarp and mesocarp was evaluated by
the two-way analysis of variance. The mean spot
quantity and standard deviation are presented. The red
letters indicate the significant differences (
P
<0.05) of
spot quantity change in different tissues (endocarp and
mesocarp) across five sampling stages.
Table S2. MASCOT search results. Spot number and
name in Table 2; Their source plant, database, number
of matched peptides and sequence coverage (%) are
provided
Please note: Wiley-Blackwell are not responsible for
the content or functionality of any supporting materials
supplied by the authors. Any queries (other than missing
material) should be directed to the corresponding author
for the article.
Edited by Y. Helariutta
406 Physiol. Plant. 142, 2011
