Changes in the 2-DE protein profile during zygotic embryogenesis in the Brazilian Pine (Araucaria angustifolia).

Abstract

Araucaria angustifolia is the only native conifer of economic importance in the Brazilian Atlantic Rainforest. Due to a clear-cutting form of exploitation this species has received the status of vulnerable. The aim of this work was to investigate and characterize changes in protein expression profile during seed development of this endangered species. For this, the proteome of developing seeds was characterized by 2-DE and LC-MS/MS. Ninety six proteins were confidently identified and classified according to their biological function and expression profile. Overaccumulated proteins in early seed development indicated a higher control on oxidative stress metabolism during this phase. In contrast, highly expressed proteins in late stages revealed an active metabolism, leading to carbon assimilation metabolism leading to storage compounds accumulation. Comprehensive protein expression profiles and identification of overaccumulated proteins provide new insights into the process of embryogenesis in this recalcitrant species. Considerations on the improvement and control of somatic embryogenesis through medium manipulation and protein markers screening using data generated are also discussed.

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Changes in the 2-DE protein profile during zygotic
embryogenesis in the Brazilian Pine (Araucaria angustifolia)
Tiago S. Balbuenaa,⁎, Vanildo Silveirab, Magno Junqueirac, Leonardo L.C. Diasa,
Claudete Santa-Catarinad, Andrej Shevchenkoc, Eny I.S. Floha
aPlant Cell Biology Laboratory, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
bBiotechnology Laboratory, State University of North Fluminense, Rio de Janeiro, Brazil
cMax Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
dCellular and Tissue Research Laboratory, State University of North Fluminense, Rio de Janeiro, Brazil
A R T I C L E D A T A A B S T R A C T
Article history:
Received 10 November 2008
Accepted 6 January 2009
Araucaria angustifolia is the only native conifer of economic importance in the Brazilian
Atlantic Rainforest. Due to a clear-cutting form of exploitation this species has received the
status of vulnerable. The aim of this work was to investigate and characterize changes in
protein expression profile during seed development of this endangered species. For this, the
proteome of developing seeds was characterized by 2-DE and LC-MS/MS. Ninety six proteins
were confidently identified and classified according to their biological function and
expression profile. Overaccumulated proteins in early seed development indicated a
higher control on oxidative stress metabolism during this phase. In contrast, highly
expressed proteins in late stages revealed an active metabolism, leading to carbon
assimilation and storage compounds accumulation. Comprehensive protein expression
profiles and identification of overaccumulated proteins provide new insights into the
process of embryogenesis in this recalcitrant species. Considerations on the improvement
and control of somatic embryogenesis through medium manipulation and protein markers
screening using data generated are also discussed.
© 2009 Elsevier B.V. All rights reserved.
Keywords:
LC-MS/MS
MS BLAST
Plant proteomics
Seed development
Somatic embryogenesis
1.Introduction
Araucaria angustifolia (Bert) O. Ktze is the only native conifer
of economic importance in the Brazilian Atlantic Rainforest.
Originally, the forests of A. angustifolia covered an area of
20 million hectares in Brazil [1,2]. A clear-cutting form of
exploitation and the spread of agriculture reduced their
original area to 1–2% and drove this species to the status of
vulnerable [2]. Seeds of A. angustifolia are recalcitrant, desicca-
tion-sensitive, and non-dormant which currently hampers
their storage and utilization in large-scale conservation
programs [3,4].
Seed development is one the major subjects in plant
physiological research. Increasing numbers of data are now
retrievable from large-scale analyses of gene expression during
this process. In the context of proteomics, however, most of
available information is derived from studies of model or grain
species, which presents a desiccation phase at the end of seed
filling and a quiescent state at maturation [5–7]. The only
attempt to study seed proteome in a recalcitrant tree species
was carried out in Fagus sylvatica, a Fagaceae species, during
dormancy breaking [8].
To date there have been few studies concerning to proteome
analysis in conifers. Costa et al. [9] and Gion et al. [10] carried out
J O U R N A L O F P R O T E O M I C S 7 2 ( 2 0 0 9 ) 3 3 7 – 3 5 2
⁎ Corresponding author. Universidade de São Paulo, Instituto de Biociências, Rua do Matão 277, Cidade Universitária, CP11461, 05422-970,
São Paulo, SP, Brazil. Tel.: +55 11 30917556; fax: +55 11 30917547.
E-mail address: tsbalbuena@usp.br (T.S. Balbuena).
1874-3919/$ – see front matter © 2009 Elsevier B.V. All rights reserved.
doi:10.1016/j.jprot.2009.01.011
available at www.sciencedirect.com
www.elsevier.com/locate/jprot

Page 2

comparative analyses in wood forming tissue. Lippert et al. [11]
and Wang et al. [12] studied plant host interactions in Picea
sitchensis and Pinus nigra, while Fernando [13] and Wagner et al.
[14]identifiedseveralproteinsrelatedtoconifersexualreproduc-
tionaspects.Dongetal.[15],studyingthesomaticembryogenesis
ofPiceaglauca,reportedtheappearanceofseveralnewproteinsin
responsetoremovalofphytohormonesfromtheculturemedium
prior to abscisic acid stimulation during the maturation process
in somatic embryos.
The only attempts to understand the changes in protein
expression during the zygotic embryogenesis in conifer
specieswere carried out in P. glauca[16], Cupressus sempervirens
[17] and A. angustifolia, in which protein expression between
the early and late stages of embryogenesis using 2-DE and PMF
for protein identification was carried out [18] and patterns of
chitinases and arabinogalactan proteins expression during
seed development were also investigated [19]. As for protein
changes on the whole level, there are no reports.
In the present study we conducted a proteomic analysis of
A. angustifolia seed development and aimed to investigate and
characterize changes in the protein expression patterns
throughout the process studied. Protein expression profiling
provided new insights into the process of embryogenesis in
this and other recalcitrant seeds, and a background for future
improvement and control of somatic embryogenesis for in
vitro scale up propagation, through medium manipulation
and protein markers screening.
2.Materials and methods
2.1. Plant material
Seeds of A. angustifolia were harvested in the Santa Catarina
State, Brazil (27°47′S, 49°29′W), from December 2006 to May
2007 and embryos at the stages of proembryo (1), globular
(2), torpedo (3), early-cotyledonary (4), late-cotyledonary (5)
and mature (6) were morphologically determined according
to Astarita et al. [20]. Due to the small size and the low
protein recovery of proembryo, globular and torpedo
embryos, these were together extracted with megagameto-
phyte tissues. Megagametophytes and the zygotic embryos
from stages 4, 5 and 6 were individualized under a dissecting
microscope (Fig. 1). All materials were stored at −80 °C prior
to analysis.
2.2.Protein extraction
Protein extracts were prepared in biological triplicates for each
time point. Due to the changes in seed tissues fresh weight
(FW) throughout seed development (Table 1S), each biological
sample was prepared from a bulk of, at least, 15 seeds and
grounded to a fine powder under liquid nitrogen. For protein
extraction 300 mg of each grounded and mixed sample
powders were transferred into clear 2 mL microtubes contain-
ing 1.5 mL of extraction buffer (7 M urea, 2 M thiourea, 1% DTT,
2% triton X-100, 0.5% pharmalyte (GE Healthcare, Freiburg,
Germany), 1 mM PMSF, 5 µM pepstatin). All extracts were
briefly vortexed and kept in the extraction buffer, standing on
ice,for30minfollowedbycentrifugationat12,000gfor5minat
4 °C. The supernatants were transferred to clear microtubes
and proteins were precipitated in ice, for 30 min, in trichlor-
oacetic acid (10%) and washed three times with cold acetone.
Finally, proteins were re-suspended and concentrated in
0.5 mL of the same extraction buffer, with addition of 0.5%
immobilized pH gradient (IPG) buffer (pH 4–7) (GE Healthcare)
instead of pharmalyte. Protein concentration was estimated by
2-DQuantKit(GEHealthcare)andsampleswerestoredat−20°C
until 2-DE.
2.3.Two dimensional gel electrophoresis
Two 2D gels were performed to each biological sample. Sample
aliquots containing 180 µg of proteins were used to 2-DE. Prior to
this assay protein extracts were separated across a broad-range
pH 3–10 IPG strip and resulted in low resolution gels, especially
those from early seed development stages (Fig. 1S), containing
spots preferentially distributed in the range of pH 4–7. Aiming a
better 2-DE spot resolution for comparative analysis and gel
excision for mass spectrometer analysis the use of IPGs with a
linear separation range of pH 4–7 was chosen. Prior to loading in
18 cm IPG strips, small volumes of rehydration buffer (7 M urea,
2 M thiourea, 2% CHAPS, 0.5% IPGbuffer (pH4–7),1%DTT,0.002%
Fig. 1 – The development of Araucaria angustifolia tissues
during zygotic embryogenesis. Proembryo (A), globular (B),
torpedo (C), early-cotyledonary (D, E), late-cotyledonary (F, G)
and mature (H, I) stages. Bars: 0.7 cm.
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bromophenol blue)wereadded tothesamplealiquotsinorderto
achieve a final volume of 375 µL. After 12 h in gel rehydration,
isoelectric focusing was performed on an IPGphor II apparatus
(GE Healthcare) for a total of 35 kVh at 20 °C. IPG strips were then
subjected to reduction, alkylation by 2×15 min incubations with
buffer (50 mM Tris–HCl, 6 M urea, 30% glycerol, 2% SDS, 0.002%
bromophenol blue) containing 125 mM DTT for the first incuba-
tionand125mMiodoacetamideforthesecond.Then,stripswere
appliedtothetopofa12%polyacrylamidegel.Seconddimension
electrophoresis was carried out at 25 mA per gel in a Protean II
apparatus (Bio-Rad, Hercules, US) and gels were silver-stained,
according to Shevchenko et al. [21].
2.4. Spot matching
Duplicated silver-stained 2D gels from each of the three
biological samples were analyzed using the Image Master
Platinum v. 6 software (GE Healthcare). The spot detection
parameters were optimized by checking different protein
spots in certain regions of the gel and then automatically
detected, followed by visual inspection for removal or addition
of undetected spots. For 2-DE characterization representative
in silico images were obtained, containing only spots that
were detected in all six repetitions. For this, the processed gels
were automatically matched in order to attribute a common
spot identity for the same spot derived from different gels and
visually inspected for improper spot matches. In silico images
were then used for all 2-DE gels characterization.
2.5.In gel digestion of proteins
In-gel protein digestion was performed as described in Shev-
chenko et al. [22]. Individual protein spots were excised from a
gel slab using a clean scalpel, cut into ca. 1×1 mm pieces and
placed into 600 µL microtubes. Gel pieces were dehydrated in
500µLacetonitrilefor10minand then reducedin50µLofa DTT
solution (10 mM DTT in 100 mM ammonium bicarbonate) for
30minat56°C,followedbyadehydrationstepinacetonitrilefor
10min.For alkylation,50µL of 55mMiodoacetamide in100mM
ammonium bicarbonate was added and gel pieces incubated at
room temperature in the dark. Prior to addition of sequencing
gradeporcinetrypsin(Promega,Madison,USA)at16ngµL−1,gel
pieces were dehydrated by acetonitrile. After 120 min, samples
were placed into an air circulation thermostat and incubated
overnight at 37 °C. Upon in-gel digestion, gel pieces were
saturated with 100 µL of extraction buffer 5% formic acid (FA):
acetonitrile(1:2,v/v)andincubatedfor15minat37°Cinshaker.
Supernatants were then collected , pooled together and ... dried
down in a vacuum centrifuge. For LC-MS/MS analyses 0.05%
trifluoroacetic acid (TFA) (10 µL) was added into the dried tubes,
incubated for 2 min and vortexed for 10 min at 7 g.
2.6. LC-MS/MS
LC-MS/MS was performed on an Ultimate 3000 nanoLC system
(Dionex, Sunnyvale, USA), which was interfaced to a LTQ
Orbitrap hybrid mass spectrometer (Thermo Fisher Scientific,
Bremen, Germany) via a robotic nanoflow ion source TriVersa
(Advion BioSciences, NY, USA). Ionization voltage was set to
1.7 kV and the capillary transfer temperature was set at 180 °C.
For each round of analysis 4 µL of the tryptic peptides were
loaded onto 5 mm×300 µm id trapping column packed with
C18 PepMAP100 5 µm particles (Dionex) in 0.05% TFA at the
flow rate of 20 µL min−1. After 6 min peptides were eluted into
15 cm×75 µm id nanocolumn packed with C18 PepMAP100
3 µm particles (Dionex) at the flow rate of 200 nL min−1and
separated using the following mobile phase gradient: from 5 to
20% of solvent B in 20 min, 20 to 50% B in 16 min, 50 to 100% B
in 5 min, 100% B during 10 min, and back to 5% B in 10 min.
Solvent A was 95:5 water:acetonitrile (v/v) containing 0.1% FA;
solvent B was 20:80 water:acetonitrile (v/v) containing 0.1% FA.
MS data were acquired in data-dependent acquisition (DDA)
mode controlled by Xcalibur 2.0 software (Thermo Fisher
Scientific). The automated gain control (AGC) was set to 5×105
charges for survey scan on the Orbitrap and 5×104charges for
MS/MS on the ion trap analyzers. Typical data-dependent
acquisition (DDA) cycle consisted of a survey scan within m/z
300 to 1600 performed at the Orbitrap analyzer under the
target mass resolution of 60,000 (FWHM, full width at half
maximum) followed by MS/MS fragmentation of the four most
abundant precursor ions under the normalized collision
energy of 35% in the linear trap. Singly charged ions were
excluded from MS/MS experiments, and m/z of fragmented
precursor ions were dynamically excluded for further 90 s. MS/
MS spectra were exported as .dta files, using BioWorks 3.1
software (Thermo Fisher Scientific).
2.7.MS data analysis
MS/MS spectra queries were filtered against a library of more
than 15,000 non-annotated background spectra using Eagle-
Eye software as described in Junqueira et al. [23]. Background
spectra recognized by EagleEye were removed, while the
remaining genuine spectra were merged into a single .mgf
(MASCOT generic format) file and searched against a MSDB
database (2.344.227 sequence entries; updated April, 2006) by
MASCOT v. 2.1 software (Matrix Science Ltd., London, UK)
installed on a local 2 CPU server. Tolerances for precursor and
Fig. 2 – Protein content from zygotic embryogenesis of
Araucaria angustifolia at different developmental stages.
Stageofdevelopment: 1=proembryo, 2=globular,3=torpedo,
4=early-cotyledonary, 5=late-cotyledonary, 6=mature.
Crossed boxes indicate intact megagametophyte containing
embryo, the dashed and blank boxes indicate isolated
embryo and megagametophyte tissues, respectively.
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fragment masses were set at 10 parts per million (ppm) and
0.6 Da, respectively. Up to 2 missed cleavages were allowed
and the following parameters were used for database
searches: instrument profile: ESI-Trap; fixed modification:
carbamidomethyl (cysteine); variable modification: oxidation
(methionine) and acetylation of the N-terminal peptide of
protein sequence entry were set as variable modifications.
MASCOTidentifications of proteinswere considered confident
if hits were produced by matching of at least three MS/MS
spectra with peptide ions scores above 20. For hits matched by
one or two spectra it was required that at least one spectrum
should be matched with score of 50 or better [24].
In parallel to stringent database search, de novo sequen-
cing was performed as described by Waridel et al. [25]. After
EagleEye spectra filtering the remaining MS/MS spectra
(represented by .dta files) obtained in each LC-MS/MS experi-
ment were interpreted de novo by a modified version of
PepNovo software [26]. For each spectrum, PepNovo reported
the expected confidence of produced sequence candidates by
assigning a quality score, which stands for the expected
number of confidently called amino acid residues. Unless
specified otherwise, in de novo sequencing experiments, we
only considered sequence candidates having the score of 6.0
or above [27]. For MS BLAST searches, all selected peptide
sequence candidates obtained by PepNovo sequencing of all
peptide precursors, were merged into a single MS BLAST query
string and searches were performed against nr database at the
web-accessible server at http://genetics.bwh.harvard.edu/
msblast, applying LC-MS/MS presets as described by Junqueira
et al. [28].
2.8.Protein expression profiling
To access information on similarities among protein expres-
sion profiles, we used the hierarchical clustering software
EPCLUST, available at URL: http://www.bioinf.ebc.ee/EP/EP/
EPCLUST/. For this, normalized spot volumes from represen-
tative in silico images from the same protein accession within
Fig. 3 – In silico 2-DE images of proteins extracted during Araucaria angustifolia seed development. Images represent the
expression of protein profiles in proembryo (A), globular (B), torpedo (C), early-cotyledonary (D, E), late-cotyledonary (F, G),
mature (H, I) stages. The pH gradient and position of Mr are indicated at the top and sides of gel images, respectively.
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and between embryo and megagametophyte tissues were
summed and converted to log2 transformed data. The
Euclidian distances and UPGMA algorithm were used for the
analysis.
3.Results and discussion
3.1.
characterization
Protein content and two-dimensional gels
Measurements of extracted protein content during A. angusti-
folia seed development revealed an increase of almost 17-fold
in protein content (Fig. 2). The highest amount of protein was
detected during seed filling, when embryos reached the late-
cotyledonary stage (19 µg mg−1FW). Although this species
produce starchy seeds, Panza et al. [3] demonstrated the
presence of protein storage vacuoles in A. angustifolia mature
cotyledons and embryo axis, suggesting that embryos accu-
mulatestorageproteins.Due to thisfeatureand the absenceof
a quiescence stage in this species [4] a plateau in protein
content was expected after seed filling; however, protein
profile showed a decrease in protein levels in mature seeds,
indicating that the protein burst observed in late-cotyledonary
stage may be mostly due to an increase in translational
processes, and possible of metabolic activity, that takes place
during seed filling. In accordance with this result, total protein
spot detection analysis of representative in silico images
(Fig. 3) showed that spot number increased almost three folds
between torpedo tissues (353 spots) and early-cotyledonary
stage embryo (955 spots) gels (Table 1).
3.2.
MS BLAST searches
Protein identification using combined MASCOT and
To ensure a good overview, in terms of pH and molecular
weight, and to assess changes in metabolic protein profiles
during A. angustifolia seed development, the 155 most abun-
dant spots from globular and mature 2-DE gels were excised
and in gel digested using trypsin (Fig. 4). For protein
identification, MASCOT stringent database search and
MS BLAST driven sequence similarity database search were
used in a combined approach [28]. This combined strategy of
peptide sequence analysis resulted in the identification of 56
spots in globular stage and 81 mature stage gels, from which
15 and 40 spots were exclusively detected in globular and
mature gel stages, respectively (Table 2). This represents a
Fig. 4 – Reference 2-DE maps for globular (embryo+megagametophyte) and mature (embryo) tissues of Araucaria angustifolia
seed development (pH 4–7 linear gradient). Proteins that were identified are marked with arrows and numbered in following
Table 2.
Table 1 – Number of common spots detected in different
stage gels during zygotic embryogenesis in Araucaria
angustifolia.
Stage of developmenta, b, c
Common spotsb
EM EM
Early embryogenesis
1 (EM: 426)–2 (EM: 425)
2 (EM: 425)–3 (EM: 353)
203
179
–
–
–
–
Late embryogenesis
4 (E: 955, M: 545)–5 (E: 773, M: 473)
5 (E: 773, M: 473)–6 (E: 496, M: 427)
–
–
414
235
167
175
Spots presented in each in silico images were detected in all six gels
repetitions.
a1=proembryo, 2=globular, 3=torpedo, 4=early-cotyledonary,
5=late-cotyledonary, 6=mature.
bNumber of detected spots in each in silico image is presented in
parenthesis.
cEM = embryo and megagametophyte, E = embryo,
M = megagametophyte.
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Table 2 – List of identified proteins during seed development in Araucaria angustifolia via combined MASCOT stringent search and MS BLAST sequence-similarity search.
Spota
Stageb
MASCOT search MS BLAST searchMW (kDa)pI
Protein name Accession
numberc
OrganismScored
Unique
peptidese
Coveragef
(%)
Protein nameAccession
numberc
OrganismMatched
queriesg
Coverageh
(%)
Theory Observation Theoretical Experimental
Protein fate
16 G, M Heat shock protein
17.0
Chloroplast
chaperonin 21
Peptidyl-prolyl cis–trans
isomerase
Q40851 P. glauca94211 Heat shock
protein 17.0
Putative
chaperonin 21
Peptidyl-prolyl
cis–trans
isomerase CYP20-2
OSJNBa0020P07.3
protein
Putative disulfide-
isomerase
RuBisCO large
subunit-binding
protein subunit
alpha
RuBisCO large
subunit-binding
protein subunit
alpha
Heat shock
protein 70
Heat shock
protein 70
Heat shock
protein 60
Heat shock
protein 83
Q40851 P. glauca323 1717 5.85.7
36M
Q6B4V3 V. vinifera701 11Q6Y679 P. vittata117 13274.6 5.84
37MP21568S. lycopersicum 7418
Q9ASS6A. thaliana31518298.85.8
63MPutative elongation
factor 2
Protein disulfide
isomerase
Putative rubisco
subunit binding-
protein alpha
subunit
Putative rubisco
subunit binding-
protein alpha
subunit
Hsc70
Q6H4L2 O. sativa16433Q7XTK1O. sativa46 94415.9 5.5
75M Q5EUD6Z. mays14634Q75M08O. sativa 3940476.35.6
88G, M
Q8L5U4A. thaliana 23647
P21238A. thaliana101962635.14.7
89G, M
Q8L5U4A. thaliana39159
P21238 A. thaliana21 43 6261 5.14.7
91G, M Q40151L. esculentum454820 Q40693O. sativa6 11 7270 5.25.0
92G, MHsc70Q40151L. esculentum318614Q40693O. sativa487270 5.24.9
93G, MHeat shock
protein 60
Molecular
chaperone
Hsp90-1
Heat shock
protein
Protein disulfide
isomerase
Q8H6U4P. dulcis485713Q8H6U4P. dulcis163358615.35.6
95G, M
Q6UJX6N. benthamiana9752022P51819I. nil193080804.94.9
96G, M Q71EE1H. brasiliensis9131819Heat shock
protein 81-1
Probable protein
disulfide-
isomerase
Leucine
aminopeptidase 1
Heat shock protein 60
Putative TCP-1
OSJNBa0020P07.3
protein
70 kDa peptidyl-
prolyl isomerase
40S ribosomal
protein S12
Heat shock
protein 17.0
Chloroplast
chaperonin 21
60S acidic
ribosomal protein P0
60S acidic
ribosomal protein
P0
Translational
elongation
factor Tu
Q0J4P2O. sativa 193080805.04.9
115GQ5EUD6Z. mays6526
P38661 M. sativa38 4052 6.35.6
133G, M Leucine
aminopeptidase 1
Heat shock protein 60
Putative TCP-1
Putative elongation
factor 2
NI
P30184A. thaliana 2455 10P30184 A. thaliana92055565.75.3
134
137
159
G
G, M
G, M
Q8H6U4
Q6AV23
Q6H4L2
P. dulcis
O. sativa
O. sativa
116
432
164
3
8
3
4
17
3
Q8H6U4
Q6AV23
Q7XTK1
P. dulcis
O. sativa
O. sativa
5
16
4
10
34
6
58
58
94
70
61
38
5.3
5.6
5.9
5.4
5.7
5.3
161G–––––Q38931A. thaliana35 62825.25.2
188MNI–––––Q9XHS0H. vulgare54115165.45.1
189M Heat shock
protein 17.0
20 kDa chaperonin
Q40851P. glauca1223 15 Q40851P. glauca432 1717 5.8 4.8
192M O65282A. thaliana11036 Q6B4V4V. vinifera8 36 27268.95.1
195G, MPutative 60S acidic
ribosomal protein P0
Putative 60S acidic
ribosomal
protein P0
Translational
elongation
factor Tu
Q8LNX8Z. elegans241536P50345L. luteus123922399.64.9
196G, M
Q8LNX8Z. elegans 255638
O24573Z. mays124422399.65.2
210G, M
Q851Y8O. sativa503922
Q8W2C4O. sativa122748416.06.5
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Metabolism
47 G, MPutative
uncharacterized
protein
Cysteine synthase
Glutamine synthetase
O04428C. paradisi 2915 17 Putative
uncharacterized
protein
Cysteine synthase
Glutamine
synthetase
GDP-mannose 3,
5-epimerase
GDP-mannose-3,
5-epimerase
Adenosylhomocysteinase
Granule-bound glycogen
(Starch) synthase
Granule-bound starch
synthase 1
Phosphoglucomutase
O04428 C. paradisi 10 3433345.54.8
60
64
G, M
M
P32260
Q9AXD8
S. oleracea
A. marina
131
498
4
10
8
17
Q9XEA6
Q9AXD8
O. sativa
A. marina
7
12
7
36
41
39
38
44
6.8
6.2
5.9
5.4
72MGDP-mannose-3,
5-epimerase
GDP-mannose-3,
5-epimerase
Adenosylhomocysteinase
Granule-bound glycogen
(Starch) synthase
Granule-bound starch
synthase 1
Cytosolic
phosphoglucomutase
Type IIIa membrane
protein cp-wap13
Type IIIa membrane
protein cp-wap13
Type IIIa membrane
protein cp-wap13
Q93VR3A. thaliana 14337Q93VR3 A. thaliana1443 475.9 5.9
73MQ93VR3A. thaliana 395720Q93VR3A. thaliana41443475.95.8
77
83
G, M
M
Q4H1G1
Q9ZSQ5
B. vulgaris
A.
membranaceus
S. tuberosum
211
213
5
4
13
6
P93253
Q9ZSQ5
M. crystallinum
A.
membranaceus
P. sativum
3
8
6
16
54
67
55
58
5.8
7.6
5.9
5.3
84MQ007756013Q430922467 586.95.2
94G, MQ6S3D6P. tomentosa 4596 14P93804 Z. mays15 2763 66 5.55.5
112G O24548V. unguiculata 12438 Type IIIa membrane
protein cp-wap13
Type IIIa membrane
protein cp-wap13
Putative reversibly
glycosylatable
polypeptide
Adenosylhomocysteinase 1 O23255
Betaine-aldehyde
dehydrogenase
Putative alpha-
xylosidase
Alpha-glucosidase 1
Alpha-glucosidase 1
Cobalamin-independent
methionine synthase
Putative adenosine kinase
O24548V. unguiculata3 1039 46 6.25.9
113G O24548V. unguiculata 3588 30O24548 V. unguiculata4143946 6.25.7
114GO24548V. unguiculata323828
Q9SR90A. thaliana
310 39 466.25.6
123
138
G, M
G, M
Adenosylhomocysteinase
Betaine-aldehyde
dehydrogenase
NI
Q4H1G1
Q6DQ92
B. vulgaris
M. acuminata
508
66
11
1
18
5
A. thaliana
M. acuminata
8
6
16
26
54
29
55
59
5.8
6.3
5.7
5.6Q6DQ92
140G–––––Q8VWV9P. pinaster2311011046.35.6
141
142
143
G
G
G, M
Alpha-glucosidase 1
Alpha glucosidase 1
Cobalamin-independent
methionine synthase
Putative adenosine
kinase
S-adenosylmethionine
synthetase
O22444
O22444
Q6KCR0
A. thaliana
A. thaliana
A. thaliana
59
54
131
1
1
2
1
1
3
O22444
O22444
Q6KCR0
A. thaliana
A. thaliana
A. thaliana
1
2
2
1
2
3
101
101
91
105
106
76
5.6
5.6
8.2
5.7
5.8
5.9
199 G, MQ6SV73P. tremula612923Q6SV73P. alba83825 426.05.1
201G, M Q9FVG7P. contorta 8021139S-adenosylmethionine
synthetase
Q9FVG7P. contorta 14 4343475.6 5.4
Energy
41MTriosephosphate
isomerase
Triosephosphate
isomerase
Malate dehydrogenase
Nodule-enhanced
malate dehydrogenase
NADP specific isocitrate
dehydrogenase
NADP specific isocitrate
dehydrogenase
Enolase
UTP-glucose-1-phosphate
uridylyltransferase
UDP-glucose
pyrophosphorylase
ATP synthase subunit beta
ATP synthase subunit beta
Enolase
Enolase
P48496S. oleracea293313Triosephosphate
isomerase
Triosephosphate
isomerase
Malate dehydrogenase
Nodule-enhanced malate
dehydrogenase
NADP specific isocitrate
dehydrogenase
NADP specific isocitrate
dehydrogenase
Enolase 1
UTP-glucose-1-phosphate
uridylyltransferase
UDP-glucose
pyrphosphorylase
ATP synthase subunit beta
ATP synthase subunit beta
Enolase
Enolase
P48496S. oleraceae1242 34286.55.5
43MP48496S. oleracea 10614P46225S. cereale2834 29 6.55.3
58
59
G, M
G, M
Q5QLS8
O81278
O. sativa
G. max
50
440
1
7
3
19
Q42972
O81278
O. sativa
G. max
1
10
3
23
42
44
39
40
7.6
6.9
7.8
5.8
69MQ9ZWI1D. carota6461023 Q9ZWI1D. carota10 2846476.5 6.2
70M
Q9ZWI1 D. carota440818Q9ZWI1D. carota 113046476.56.1
78
79
G, M
G, M
Q42971
Q43772
O. sativa
H. vulgare
88
257
2
6
8
15
Q9LEJ0
Q9SDX3
H. brasiliensis
M. acuminata
2
9
6
21
48
52
53
56
5.4
5.2
5.7
5.6
81 G, MQ8W557A. fructicosa18237Q8W557A. fructicosa4952566.15.4
85
87
111
122
G, M
G, M
G
G, M
Q01859
Q01859
Q6WB92
Q42971
O. sativa
O. sativa
G. barbadense
O. sativa
259
370
86
252
5
6
2
4
13
17
5
12
P29685
P19023
Q43130
Q42971
H. brasiliensis
Z. mays
M. crystallinum
O. sativa
7
8
2
3
14
17
6
10
59
59
48
48
56
56
45
53
5.9
5.9
6.2
5.4
5.2
5.1
6.1
5.8
(continued on next page)
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Page 8

Table 2 (continued)
Spota
Stageb
MASCOT searchMS BLAST searchMW (kDa) pI
Protein nameAccession
numberc
OrganismScored
Unique
peptidese
Coveragef
(%)
Protein nameAccession
numberc
OrganismMatched
queriesg
Coverageh
(%)
Theory Observation Theoretical Experimental
Energy
144G, M2,3-bisphosphoglycerate-
independent phosphoglycerate
mutase
ATP synthase gamma chain
P35493 R. communis 9735 Phosphoglycerate mutase Q9XE59 S. tuberrosum2461 635.5 5.9
193G, MQ59I53 I. nil 15238 ATP synthase subunit
gamma
Fructose-bisphosphate
aldolase
P26360 I. batatas3 1036 349.0 4.2
198M Fructose-bisphosphate
aldolase
Q9LLD7 O. sativa 13238Q53P96 O. sativa2642 389.05.6
Storage process
1
3
4
5
6
7
M
M
M
M
M
M
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
NI
High molecular weight
glutenin subunit 1By15
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
NI
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
–
Q4JHY1
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
–
T. aestivum
587
998
552
518
–
111
10
18
8
9
–
2
20
22
17
18
–
2
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
High molecular weight
glutenin y-subunit
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Vicilin-like storage protein
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q7Y0S9
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
T. elongatum
9
9
8
10
2
1
23
24
20
26
4
2
53
53
53
53
53
78
13
13
12
13
14
14
7.7
7.7
7.7
7.7
7.7
8.6
4.6
4.8
4.9
5.0
4.9
4.9
8
9
18
19
27
31
35
38
39
40
42
44
45
61
M
M
M
M
M
M
M
M
M
M
M
M
M
G, M
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
–
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
–
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
508
433
1035
1100
905
–
175
566
244
277
218
167
304
727
10
8
22
24
21
–
4
10
7
7
5
5
6
13
18
15
36
35
32
–
8
23
23
15
12
12
12
27
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q40844
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
Q8LKI7
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
P. glauca
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
A. angustifolia
6
8
13
11
9
3
6
11
10
9
10
1
5
7
14
20
31
27
24
7
13
18
26
23
26
2
11
15
53
53
53
53
53
51
53
53
53
53
53
53
53
53
15
15
22
22
22
24
27
28
29
29
29
30
29
41
7.7
7.7
7.7
7.7
7.7
7.9
7.7
7.7
7.7
7.7
7.7
7.7
7.7
7.7
4.8
4.6
6.5
6.8
6.4
5.5
6.0
5.7
5.6
5.6
5.4
6.1
6.2
6.9
Stress response and detoxification
13 G, M
62M
Peroxiredoxin
Putative aldose reductase
Q8S3L0
Q65WW3 O. sativa
P. tremula 116
107
3
3
16
5
Peroxiredoxin
Putative aldose reductase
Q8S3L0
Q8GXW0
P. tremula
A. thaliana
6
6
40
22
17
36
19
42
5.6
6.3
5.0
5.7
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Page 9

80G, MPutative mitochondrial
aldehyde dehydrogenase
ALDH2a
Cytosolic ascorbate
peroxidase 2
Ascorbate peroxidase
Q6YWQ9 O. sativa 5713Mitochondrial aldehyde
dehydrogenase
Q8LST5S. bicolor12 46 565.95.5
98GQ76LA6 G. max 5517 Cytosolic ascorbate
peroxidase
Ascorbate peroxidase
Q8H1K7R. raetam16 2728 5.7 4.8
104G Q6RY58P. pinaster218417Q6RY58 P. pinaster419 27305.45.5
Cellular signaling
99
102
211
212
G, M
G
G, M
G, M
14-3-3-like protein GF14 iota
14-3-3-like protein GF14 iota
14-3-3 protein
14-3-3-like protein GF14 iota
Q8LEN1
Q8LEN1
Q6PWL7
Q8LEN1
A. thaliana
A. thaliana
S. chacoense
A. thaliana
166
113
306
161
3
2
6
3
13
10
22
13
14-3-3-like protein D
14-3-3 protein
14-3-3-like protein
14-3-3 protein
Q96453
Q944P2
Q9SP07
Q944P2
G. max
F. cirrhosa
L. longiflorum
F. cirrhosa
2
2
4
3
8
12
19
17
29
29
29
29
34
34
32
33
4.9
4.9
4.7
4.9
4.7
4.8
4.7
4.7
Cellular transport
163
164
G
G
NI
NI
–
–
–
–
–
–
–
–
–
–
Patellin-3
Patellin-3
Q56Z59
Q56Z59
A. thaliana
A. thaliana
2
2
5
5
56
56
113
113
5.2
5.2
4.7
4.7
Cell cycle and DNA processing
194G, MProliferating cell
nuclear antigen
P17070O. sativa 3769 37Proliferating cell nuclear
antigen large form
Q00265D. carota 174929 36 4.6 4.3
Structure
68
197
G, M
M
Actin
Tubulin beta-2 chain
Q9SP17
P18026
P. rubens
Z. mays
1288
291
23
5
62
12
Actin
Tubulin beta-4 chain
P93485
Q41782
P. sativum
Z. mays
18
3
55
7
83
50
46
37
6.0
4.8
5.2
5.4
Unclassified
65
191
M
M
NI
GTP-binding protein,
ras-like
–
Q9FJH0
–
A. thaliana
–
368
–
7
–
31
F13E7.34 protein
GTP-binding protein,
ras-like
Q9M8R4
Q9FJH0
A. thaliana
A. thaliana
4
7
11
34
42
24
44
26
5.2
5.7
5.6
5.1
NI: non-identified protein.
aSpot numbers correspond to the numbers indicated in Fig. 4.
bStage of development in which the corresponding spot was detected.
cAccession number in Swiss-Prot/TrEMBL.
dProbability based MOWSE score of MASCOT software for the hit.
eNumber of unique peptide sequences identified via MASCOT.
fPercentage of predicted protein sequence covered by matched peptides via MASCOT.
gNumber of unique peptide sequences identified via MSBLAST that had a significant sequence-alignment score superior or equal to 55.
hPercentage of predicted protein sequence covered by matched query sequence via MSBLAST according to [Σpositive queries (aa)×100]/predicted protein (aa).
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Page 10

very successful result considering that A. angustifolia genome
has not been sequenced and, currently, only sequences of 6
unique proteins are available in NCBI database.
Stringent database searches enable precise protein identi-
fication relying upon a few fragmented peptide precursors.
However, any peptide sequence discrepancy precludes strin-
gent matching and, consequently, makes protein identifica-
tion impossible. In A. angustifolia seed development,
automated de novo sequencing and MS BLAST search protocol
has proven its efficiency. This strategy confirmed all A.
angustifolia cross species MASCOT identifications. Addition-
ally, it enabled the identification of eight proteins (Table 2:
spots 6, 31, 65, 140, 161, 163, 164 and 188) that were not
identified by MASCOT.
From the 96 identified proteins, 38 appeared as double or
triple spots. Multiple vicilin-like protein (acc. number Q8LKI7)
spots were identified in mature stage gels (Table 2). Similarly
high spot redundancy was recently found in other conifer
species, such as in Pinus pinaster [10] and P. sitchensis [11].
Multiple spots for a given protein mostly originate from post-
translational modifications, but can also be attributed to
differentially spliced forms or allelic variants [11].
3.3.Functional classification of proteins
Biological processes, in which the 96 identified proteins are
involved, were defined according to the Gene Ontology
Annotation database (http://www.ebi.ac.uk/GOA/). Since no
functional classification has been defined in conifers, it was
based on the comprehensive catalogue proposed by Ruepp
et al. [29] and available at http://mips.gsf.de/projects/funcat.
To assess differences in the protein profile during
A. angustifolia seed development, proteins were classified
into nine and eight categories in globular and mature stages,
respectively (Fig. 5). The most representative classes of
proteins observed in globular and mature stages were protein
fate (folding, modification and protein destination), metabo-
lism, energy and storage proteins (Fig. 5).
Protein fate class, which includes proteins related to the
folding, assembly and modification processes, constitutes 17
and 21 spots in globular and mature stages, respectively.
Within this group, HSPs are the most abundant as 6 spots were
identified in both globular and mature stages. Second most
representative proteins during seed development were the
proteins involved in basic metabolic processes, as they
accounted for 26 and 17% of identified proteins in globular
and mature stage gels, respectively. Energy protein class
constitutes of proteins related to the glycolysis, tricarboxylic
acid-pathway and energy conversion and although sixteen
spots were detected and classified within this group, it
comprises only ten unique identifications. Another group
containing high levels of redundant identifications was the
storage protein class. They showed major percentage of
variation between globular and mature stages, representing
the most abundant class of proteins identified in mature
stage. In globular tissues, this group represented only 2% of
total identified proteins, however in mature stage 19 spots
matched its sequence with vicilin-like storage proteins,
representing 25% of total identified spots.
3.4.Protein expression profiling during seed development
It is well known that a single gene can manifest itself as
multiple protein spots on a 2-D gel due to alternative splicing
or posttranslational modifications [5]. Although it is possible
to detect isoforms in 2-D gels, A. angustifolia is a species with
unknown genome and protein identification mostly relies on
limited sequence coverage. Both of these features hamper
revealing the molecular and biological function of different
isoforms. Thus, for the analysis of changes in the metabolic
processes that take place during seed development, we have
only considered changes in protein accessions from all the 96
spots identified.
The 66 unique proteins were clustered within 4 groups
(Fig. 6). Cluster A contained 7 unique proteins, most of which
highly accumulated throughout seed development, such as
actin (Q9SPI7) and the rubisco binding protein (RBP) (Q8L5U4).
Cluster B contained 26 proteins showing low accumulation
throughoutseeddevelopment.ClusterCcontained25proteins
overaccumulated in late stages, whereas cluster D contained
proteins overaccumulated in early seed development. Aiming
a better understanding in changes of the proteome and
activation of different metabolic pathways throughout seed
development, in the following paragraphs we will discuss
somecharacteristicoveraccumulatedproteinsinearlyandlate
stagesandtheirpossiblefunctionintheprocessstudied.These
Fig. 5 – Functional distribution of the identified spot during Araucaria angustifolia seed development. A: globular stage;
B: mature stage.
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Page 11

proteins may give insights into specific or preferentially
metabolic pathways during the studied process and may also
be potential candidates for markers of this process.
3.4.1.
Many biological events result in cellular oxidative stress,
which is mainly associated with accumulation of reactive
Overaccumulated proteins in early stages
Fig. 6 – Hierarchical clustering analysis of the 66 unique proteins identified during Araucaria angustifolia seed development.
Dataset clustering was carried out through the sum of all normalized spot volumes from the same protein accession within and
between embryo and megagametophyte tissues.
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Page 12

oxygen species (ROS) and/or a ROS-scavenging system, like
peroxidases. Ascorbate peroxidase (APX) is one of the most
important enzymes involved in the oxidative defense system,
controlling and modulating hydrogen peroxide (H2O2) cellular
levels [30]. Although H2O2has a harmful effect on cells at high
concentrations; it is an important molecule at the end of seed
development and early germination due to its protecting effect
against invasion by parasitic organisms and, although not yet
described in Gymnosperms, by oxidizing germination inhibitors
presented in the pericarp of Angyosperms [31,32]. Few works
have been developed relating the ROS production during seed
development, specially in recalcitrant seeds. Contrarily, several
studies have documented the production of ROS during seed
storage in the dry state [33,34]. Although only one APX accession
(Q76LA6)wasclusteredwithinclusterD,theothershowedhigher
expressioninearlystagesofseeddevelopmentand,aspredicted,
was not found in mature stage (Fig. 6). Theidentification ofAPXs
overaccumulated in proembryo, globular and torpedo stages
indicates a higher oxidative stress metabolism in early stages of
seed development and the consequent higher accumulation of
cytosolicAPXforcontrollingandmaintenanceofoxidativestress
generated by a high ROS activity, which is inagreement with the
higher number of identified proteins classified into the stress
response class during early seed development (Fig. 5). Over-
accumulation of peroxiredoxin in early seed development
contributes to this hypothesis (Table 2S), as in dormant seeds
and orthodox seeds it shows to play a part in inhibition of
germination under unfavorable conditions [35].
In early stages of conifer zygotic embryogenesis, the zygote
undergoes several rounds of nuclear duplication without
cytokinesis, followed by a cellularization phase, where high
rates of cell divisions are then achieved [36]. Plant cells
partition their cytoplasm during cytokinesis by building a
cell plate structure from the inside out between the two sets of
daughter chromosomes, which is dominated by membrane-
trafficking events [37]. Patellin (spots 163, 164), which was low
expressed and identified especially in globular stage (Fig. 6), is
a carrier protein that is recruited from the cytoplasm to the
expanding and maturing cell plate. High levels of patellin in
globular and torpedo stages also indicate a decrease in the
mitotic activity during seed filling and maturation. This is in
accordance with the absence of morphological transitions in
zygotic embryos from torpedo to mature stage, as observed by
Astarita et al. [20], and may also indicate a decrease in cell
differentiation and lost of cell competency from torpedo/early
cotyledonary stages. To our knowledge, this is the first report
on patellin accumulation during seed development.
Proliferating cell nuclear antigen (PCNA) plays an important
role in DNA duplication and repair [38]. Despite the recalcitrant
behavior of A. angustifolia seeds, PCNA levels decreased in late
embryogenesis, as observed in maize mature seeds [38]. This
suggests the necessity of de novo synthesis of this protein
during late germination and early seedling development
independently of the recalcitrant nature of seeds.
Biological processes with high rates of cell division should
also require the expression of cell wall degradation, loosening
and biosynthesis proteins, such as alpha-xylosidase (spot 140)
and type IIIa membrane protein cp-wap13 (spots 112, 113 and
114)[39–41],whichareessentialforgrowthandtissueexpansion
in fast growth phases, usually observed in young tissues.
As expected few proteins related to carbon and storage
metabolism were detected in early embryogenesis, such as
alpha-glucosidase type I (spots 141, 142), which hydrolyzes
preferentially heterogeneous substrates, like sucrose [40]. It
is interesting to notice that alpha-glucosidase levels de-
crease during seed development, whereas starch synthase
enzyme levels (spots 83, 84) increase in late stages of seed
development (Table 2S, Fig. 6), probably indicating that in
early stages sucrose is hydrolyzed by alpha-glucosidase I,
releasing alpha-D-glucose that is used as substrate for starch
synthesis, the major storage compound in A. angustifolia
mature seeds [42].
3.4.2.
Chaperonins did not present a preferential accumulation
throughout seed developmental stages. However, the 20 kDa
accessions (O65282, Q6B4V3) were only identified in late
embryogenesis. Chaperonins are proteins that play a vital
role in protein folding in eukaryotic and prokariotic cells. They
are generally divided into two groups, according to the cellular
localization: (a) group I chaperonins are localized in the
stroma of chloroplasts, the matrix of mitochondria and
eubacteria, and (b) group II chaperonins are found in
eukaryotic cytosol and archaebacteria [43]. One of the
differences between these groups is that group I work together
with co-chaperonins, whereas group II work alone [43].
The chaperonin cpn60 and co-chaperonin cpn10 have been
characterized in detail in Escherichia coli [44]. An homologue of
co-chaperonin cpn 10 was identified in both pea and spinach
as being twice the size of the classic mammalian cpn10 and
sequence analysis showed that the protein was composed of
two linked cpn10 homologs [45,46]. In vitro studies showed
that this cpn20 is capable of assisting chloroplast cpn60 in
refolding denatured rubisco [45,47]. Interestingly, in A. angu-
stifolia seed development, although RBP(Q8L5U4)was detected
in early and late stages, the co-chaperonin cpn20 was not
identified in early stages (Fig. 6). During Daucus carota somatic
embryogenesis the expression of photosynthesis-associated
mRNAs and differentiation of photosynthetic embryos was
observed in late torpedo-shaped embryos [48]. In A. angustifolia
seed development, cpn20/21 expression was only observed
from torpedo stages indicating that photosynthetic apparatus
differentiation may start from this stage on (Fig. 6).
In early stages, due to low levels of O2, mainly converted to
superoxide, embryos are ATP limited, responding mainly by
fermentation, and during further photosynthetic apparatus
differentiation and expression of glycolytic and tricarboxylic
acid (TCA) enzymes, ATP levels increase [49]. Although
enolase was identified in all stages of seed development
and, consequently, clustered within clusters B, C and D, other
enzymes involved in the glycolytic and TCA pathway were
only identified in late embryogenesis: triosephosphate iso-
merase, fructose-bisphosphate aldolase and isocitrate dehy-
drogenase. High expression of these enzymes in late
developmental stages indicates a shift in the stress related
metabolism, as discussed above, resulting in availability of the
molecule O2as a final hydrogen acceptor and, thus, increasing
respiratory levels in mature seed. D-glucose is the other
substrate involved in the respiratory chain and is probably
found in abundance during late embryogenesis due to sucrose
Overaccumulated proteins in late stages
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hydrolyzation by alpha-glucosidase I activity in early stages.
Another evidence of high D-glucoselevels in late stagesof seed
development is the abundant expression of granule-bound
starch synthase (Table 2S, Fig. 6), which utilizes D-glucose for
starch synthesis.
Final seed development is usually marked by increase in
storage compounds and onset of related enzymes, like starch
synthase in starchy seeds. Although A. angustifolia is one of
these seeds, vicilin-like proteins were identified in large
amounts in late seed development. Also, multiple spots were
correlated to this identification and are probably due to post-
translational modifications or different splice forms derived
from single gene or the existence of allelic variants [11].
Alternatively, as a storage protein, it could also correspond to
fragments released by specific proteolysis even before germi-
nation starts, as also observed in Arabidopsis seeds [50] and,
thus, seems to be unrelated to desiccation responses.
Although very little is known about N metabolism in
embryogenic tissues of conifers, a balanced N supply and
metabolism seem to be critical for plant embryogenesis [51]. A
major metabolic event during seed maturation is the accu-
mulation of reserves at late embryogenesis. According to
previous works, the major amino acid residues of seed storage
proteins in Pinus taeda and P. pinaster are arginine, glutamine
and glutamate [51,52]. In the present study the enzyme
glutamine synthase (GS) expression was overaccumulated in
early-cotyledonary stage (Table 2S, Fig. 6). Changes in GS
expression during the maturation process indicate that the
biosynthesis and interconversion of glutamine/glutamic acid
is active during conifer maturation. Astarita et al. [20]
observed that glutamic acid is the major free amino acid
accumulated in mature seeds. Moreover, amino acid composi-
tion of A. angustifolia vicilin storage protein (Q8LKI7) indicates
that more than 10% of its sequence is composed by glutamic
acid. Thus, the time-specific expression of GS may be critical
for obtaining fully mature embryos and may be considered
another important protein marker of embryo maturation in
this species.
3.5.Proteomics approach in somatic embryogenesis
Despite the attempts to develop a protocol for inducing
somatic embryogenesis in A. angustifolia, only somatic
embryos in early developmental stages were obtained [53,54].
Seed development studies have been useful to better
understand the molecular and physiological basis of embry-
ogenesis and system manipulation for in vitro multiplication
via somatic embryogenesis [18].
Basically, A. angustifolia seed development can be divided
into two distinct phases according to its protein expression
profile: early and late embryogenesis. The metabolic arrange-
ment that takes place during cotyledon formation seems to be
crucial as the protein content and 2-DE maps presented a
significant change during cotyledon differentiation and
growth. In conifers somatic embryogenesis, immature
embryos have been extensively used for embryogenic culture
initiation, with the developmental explant stage affecting the
induction rates [55–57].
In the somatic embryogenesis of A. angustifolia, the choice
of the correct developmental stage of zygotic embryos is a
critical factor in the induction of embryogenic cultures, with
the best results when pre-cotyledonary zygotic embryos are
used as explants [58,59]. This strict requirement of juvenile
explants is common in conifer species and indicates that re-
direction of developmental programs in this plant group is
difficult to achieve in culture [60]. Taking into account the
results obtained in the present work, it can be inferred that the
successful conversion rates of embryogenic cultures when
using torpedo/early-cotyledonary zygotic embryos may be
mostly due to a boom in the gene expression levels and
activation of different biochemical pathways, which lead to
the detection of a great number of 2-DE spots and marks the
transition from a growth and cell division phase to a highly
determined and differentiated phase, the maturation.
Proteins involved in energetic, metabolic and protein fate
processes are essential across A. angustifolia seed development.
As predicted, metabolic proteins were the most abundant
during early seed development as this stage is marked by
intensive cell division and growth. In the Araucaria genus, both
recalcitrant and orthodox seed species may be found. Due to its
elevated moisture content and little desiccation tolerance, A.
angustifolia is considered as a recalcitrant species [3]. The high
number of energy and metabolic related spots in late zygotic
embryogenesis of A. angustifolia indicates an active metabolic
state during the late stages of seed development. Contrary to
orthodox,therecalcitrantseedsareshedat highwatercontents
and are also metabolically active at shedding [61]. Although dos
Santos et al. [19] observed some similarities of protein electro-
phoretic pattern with orthodox seeds, the high number of
identified metabolic and energy proteins in the maturation
phase of seed development is in accordance with its recalci-
trant nature and indicates a strategy of continuous develop-
ment without the interposition of a dry and quiescent state, as
suggested by Panza et al. [3]. These observations may be of a
great value for the establishment of somatic embryogenesis
protocols, as little is known about protein patterns during the
maturationphaseofrecalcitrantconiferousspeciesandmostof
the somatic embryogenesis protocols, including those for
A. angustifolia [1,54] are based on the metabolic pattern changes
in orthodox type seeds.
Furthermore, in the present work a similar expression
profile,especially concerned to the highest abundant proteins,
between mature embryos and megagametophyte was
observed. This may reflect the mutual conversion of proteins
and the signaling events taking place between the embryo and
the surrounding tissue. Analysis of late-cotyledonary and
mature seeds indicates that storage proteins, which are
further used for plantlet growth, are accumulated in both
embryo and megagametophyte tissues. Thus, the addition of
maturation agents that induce protein expression in the
culture medium are expected for successful somatic embryo
maturation. Here we also suggest the addition of glutamic acid
in maturation culture medium, as amino acid composition of
vicilin storage protein indicates a preferential use of this
amino acid in its primary structure. Additionally, vicilin-like
proteins were far the most abundant identification during
embryomaturation,reflectingtheir importancein latestageof
A. angustifolia zygotic embryogenesis and potential use as
protein markers for embryo maturation, attending on the
development of somatic embryo protocols that may utilize
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these and the other suggested spot markers for establishing a
correct quality control and maximal plant conversion rates
from somatic embryos.
4.Concluding remarks
The present work illustrates the robustness of the proteomic
approach based on the use of 2-DE gels followed by protein
identification via MS/MS analyses for a comprehensive
investigation on the metabolic changes during A. angustifolia
seed development. Further studies addressing temporal and
spatial transcription of vicilin genes are being carried out and
constitute a potential target for functional genomics studies.
Furthermore, specific identified proteins may be used as
markers for embryo maturation through in vivo imaging
using fluorescent protein fusions. Therefore, the identified
protein list presented in this work gives the foundation for
future studies on the genetic, physiology and metabolism of
the developmental embryo process in this and other conifer-
ous species. Additionally, the coordination of this knowledge
may give insight in future studies addressing the optimization
of the somatic embryogenesis protocols for mass propagation
and conservation strategies applied to A. angustifolia.
Acknowledgements
This research was carried out with financial support from the
State of São Paulo Research Foundation (FAPESP) and the
National Council for Scientific and Technological Develop-
ment (CNPq) to E.I.S.F. This research was supported by the
doctoral and postdoctoral FAPESP scholarships to T.S.B. and
V.S., respectively, and by a short-term travel grant by the
Deutscher Akademischer Austauschdienst (DAAD) to T.S.B.
Work in Shevchenko lab was, in part, supported by
1R01GM070986-01A1 grant from NIH NIGMS. The authors
thank Prof. Dr. Miguel P. Guerra and M.Sc. Neusa Steiner for
kindly providing A. angustifolia seeds.
The authors have declared no conflicts of interest.
Appendix A. Supplementary data
Supplementary data associated with this article can be found,
in the online version, at doi:10.1016/j.jprot.2009.01.011.
R E F E R E N C E S
[1] Guerra MP, Silveira V, Santos ALW, Astarita LV, Nodari RO.
Somatic embryogenesis in Araucaria angustifolia (Bert)
O. Kuntze. In: Jain SM, Gupta PK, R.J. Newton, editors. Somatic
embryogenesis in woody plants. Dordrecht: Kluwer Academic
Publishers; 2000. p. 457–78.
[2] Guerra MP, Silveira V, Reis MS, Schneider L. Exploração,
manejo e conservação da Araucária (Araucaria angustifolia).
In: Simões LL, Lino CF, editors. Sustentável Mata Atlântica: a
exploração de seus recursos florestais. São Paulo: Editora
SENAC; 2002. p. 85–101.
[3] Panza V, Lainez V, Maroder H, Prego I, Maldonado S. Storage
reserves and cellular water in mature seeds of Araucaria
angustifolia. Bot J Linn Soc 2002;140:273–81.
[4] Salmen–Espindola L, Noin M, Corbineau F, Côme D. Cellular
and metabolic damage induced by desiccation in recalcitrant
Araucaria angustifolia embryos. Seed Sci Res 1994;4:193–201.
[5] Agrawal GK, Hajduch M, Graham K, Thelen JJ. In-depth
investigation of the soybean seed-filling proteome and
comparision with a parallel study of rapessed. Plant Physiol
2008;148:504–18.
[6] Finnie C, Malchior S, Roepstorff P, Svensson B. Proteome
analysis of grain filling and seed maturation in barley. Plant
Physiol 2002;129:1308–19.
[7] Gallardo K, le Signor C, Vandekerckhove J, Thompson RD,
Burstin J. Proteomics of Medicago truncatula seed development
establishes the time frame of diverse metabolic processes
related to reserve accumulation. Plant Physiol
2003;133:664–82.
[8] Pawlowski TA. Proteomics of European beech (Fagus
sylvatica L.) seed dormancy breaking: influence of abscisic and
giberellic acids. Proteomics 2007;7:2246–57.
[9] Costa P, Pionneau C, Bauw G, Dubos C, Bahrmann N, Kremer A,
etal. Separationand characterizationofneedleand xylempine
proteins. Electrophoresis 1999;20:1098–108.
[10] Gion JM, Lalanne C, le Provost G, Ferry-Dumazet H, Paiva J,
Chaumeil P, et al. The proteome of marine pine wood forming
tissue. Proteomics 2005;5:3731–51.
[11] Lippert D, Chowrira S, Ralph SG, Zhuang J, Aeschliman D,
Ritland C, et al. Conifer defense against insects: proteome
analysis of sitka spruce (Picea sitchensis) bark induced by
mechanical wounding or feeding by white pine weevils
(Pissodes strobi). Proteomics 2007;7:248–70.
[12] Wang D, Eyles A, Mandich D, Bonello P. Systemic aspects
of host–pathogen interactions in Austrian pine
(Pinus nigra): a proteomics approach. Physiol Mol
Plant P 2006;68:149–57.
[13] Fernando DD. Characterization of pollen tube development in
Pinus strobus (Eastern white pine) through proteomic analysis
of differentially expressed proteins. Proteomics
2005;5:4917–26.
[14] Wagner RE, Mugnaini S, Sniezko R, Hardie D, Poulis B, Nepi M,
et al. Proteomics evaluation of gymnosperm pollination drop
proteins indicates highly conserved and complex biological
functions. Sex Plant Reprod 2007;20:181–9.
[15] Dong J-Z, Bock CA, Dunstan DI. Influences of altered
phytohormone use on endogenous ABA and mRNA
populations during white spruce (Picea glauca) somatic
embryo culture. Tree Physiol 1997;17:53–7.
[16] Flinn BS, Roberts DR, Webb DT, Sutton BCS. Storage protein
changes during zygotic embryogenesis in interior spruce.
Tree Physiol 1991;8:71–81.
[17] Sallandrouze A, Faurobert M, el Maataoui M. Characterization
of the developmental stages of cypress zygotic embryos by
two-dimensional electrophoresis and by cytochemistry.
Physiol Plant 2002;114:608–18.
[18] Silveira V, Santa-Catarina C, Balbuena TS, Moraes FMS,
Ricart CAO, Sousa MV, et al. Endogenous abscisic acid and
protein contents during seed development of Araucaria
angustifolia. Biol Plantarum 2008;52:101–4.
[19] dos Santos ALW, Wiethölter N, Gueddari NE, Moerschbacher
BM. Protein expresssion during seed development in
Araucaria angustifolia: transient accumulation of class IV
chitinases and arabinogalactan proteins. Physiol Plant
2006;127:138–48.
[20] Astarita LV, Floh EIS, Handro W. Free amino acid, protein and
water changes associated with seed development in Araucaria
angustifolia. Biol Plantarum 2003;47:53–9.
350
J O U R N A L O F P R O T E O M I C S 7 2 ( 2 0 0 9 ) 3 3 7 – 3 5 2

Page 15

[21] Shevchenko A, Wilm M, Vorm O, Mann M. Mass spectrometric
sequencing of proteins silver-stained polyacrylamide gels.
Anal Chem 1996;68:850–8.
[22] Shevchenko A, Thomas H, Havlis J, Olsen JV, Mann M. In-gel
digestion for mass spectrometric characterization of proteins
and proteomes. Nat Protoc 2007;1:2856–60.
[23] Junqueira M, Spirin V, Balbuena TS, Waridel P, Surendranath V,
Kryukov G, et al. Separating the wheat from the chaff: unbiased
filtering of background tandem mass spectra improves protein
identification. J Proteome Res 2008;7:3382–95.
[24] Charneau S, Junqueira M, Costa CM, Pires DL, Fernandes ES,
Bussacos AC, et al. The saliva proteome of the blood-feeding
insectTriatomainfestansisrichinplatelet-aggregationinhibitors.
Int J Mass Spectrom 2007;268:265–76.
[25] Warindel P, Frank A, Thomas H, Surendranath V, Sunyaev S,
Pevzner P, et al. Sequence similarity-driven proteomics
in organisms with unknown genomes by LC MS/MS
and automated de novo sequencing. Proteomics
2007;7:2318–29.
[26] Frank A, Pevzner P. PepNovo: de novo peptide sequencing via
probabilistic network modeling. Anal Chem 2005;77:964–73.
[27] Wielsch N, Thomas H, Surendranath V, Waridel P, Frank A,
Pevzner P, et al. Rapid validation of protein identifications
with the borderline statistical confidence via de novo
sequencing and MS BLAST searches. J Proteome Res
2006;5:2448–56.
[28] Junqueira M, Spirin V, Balbuena TS, Thomas H, Adzhubei I,
Sunyaev, et al. Protein identification pipeline for
the homology-driven proteomics. J Proteomics
2008;71:346–56.
[29] Ruepp A, Zollner A, Maier D, Albermann K, Hani J, Mokrejs M,
et al. The FunCat, a functional annotation scheme for
systematic classification of proteins from whole genomes.
Nucl Acids Res 2004;32:5539–45.
[30] Ishikawa T, Shigeoka S. Recent advances in ascorbate
biosynthesis and the physiological significance of ascorbate
peroxidase in photosynthesizing organisms. Biosci Bio-
technol Biochem 2008;72:1143–54.
[31] Ogawa K, Iwabuchi M. A mechanism for promoting the
germination of Zinnia elegans seeds by hydrogen peroxide.
Plant Cell Physiol 2001;42:286–91.
[32] Schopfer P, Plachy C, Frahry G. Release of reactive oxygen
intermediates (superoxide radicals, hydrogen peroxide, and
hydroxyl radicals) and peroxidase in germinating radish
seeds controlled by light, gibberellin, and abscisic acid. Plant
Physiol 2001;125:1591–602.
[33] McDonald MB. Seed deterioration: physiology, repair and
assessment. Seed Sci Technol 1999;27:177–237.
[34] Pukacka S, Ratajczak E. Production and scavenging of reactive
oxygen species in Fagus sylvatica seeds during storage at
varied temperature and humidity. J Plant Physiol
2005;162:873–85.
[35] Haslekas C, Viken MK, Grini PE, Nygaard V, Nordgard SH,
Meza TJ, et al. Seed 1-cysteine peroxiredoxin antioxidants
are not involved in dormancy, but contribute to inhibition
of germination during stress. Plant Physiol
2003;133:1148–57.
[36] Cairney J, Pullman G. The cellular and molecular biology of
conifer embryogenesis. New Phytol 2007;176:511–36.
[37] Bednarek SY, Falbel TG. Membrane trafficking during plant
cytokinesis. Traffic 2002;3:621–9.
[38] Herrera I, SánchezMP, Molina J, Plasencia J, Vázquez-Ramos JM.
Proliferating cell nuclear antigen expression in maize seed
development and germination: regulation by phytohormones
and its association with putative cell cycle proteins. Physiol
Plant 2000;110:127–34.
[39] Wald FA, Kissen R, du Jardin P, Moreno S. Characterization of
UDP-glucose: protein transglucosylase genes from potato.
Plant Mol Biol 2003;52:705–14.
[40] Nakai H, Tanizawa S, Ito T, Kamiya K, Kim YM, Yamamoto T,
et al. Function-unknown glycoside hydrolase family 31
proteins, mRNAs of which were expressed in rice ripening
and germinating stages, are α-glucosidase and α -xylosidase.
J Biochem 2007;142:491–500.
[41] Sánchez M, Gianzo C, Sampedro J, Revilla G, Zarra I. Changes
in α -xylosidase during intact and auxin-induced growth of
pine hypocotyls. Plant Cell Physiol 2003;44:132–8.
[42] Cordenunsi BR, de Menezes EW, Genovese MI, Colli C,
do Souza AGA, Lajolo FM. Chemical composition and
glycemicindexofBrazilianpine(Araucariaangustifolia)seeds.
J Agric Food Chem 2004;52:3412–6.
[43] Kuomoto Y, Shimada T, Kondo M, Hara-Nishimura I,
Nishimura M. Chloroplasts have a novel cpn10 in addition to
cpn20 as co-chaperonins in Arabidopsis thaliana. J Biol Chem
2001;276:29688–94.
[44] Bonshtien AL, Weiss C, Vitlin A, Niv A, Lorimer GH, Azem A.
Significance of the n-terminal domain for the function of
chloroplast cpn20 chaperonin. J Biol Chem 2007;282:4463–9.
[45] Bertsch U, Soll J, Seetharam R, Viitanen PV. Identification,
characterization, and DNA-sequence of a functional double
groes-like chaperonin from chloroplasts of higher-plants.
Proc Natl Acad Sci U S A 1992;89:8696–700.
[46] Dickson R, Weiss C, Howard RJ. Reconstitution of higher plant
chloroplast chaperonin 60 tetradecamers active in protein
folding. J Biol Chem 2000;275:11829–35.
[47] Viitanen PV, Schmidt M, Buchner J, Suzuki T, Vierling E,
Dickson R, et al. Functional-characterization of the
higher-plant chloroplast chaperonins. J Biol Chem
1995;270:18158–64.
[48] Sato-Nara K, Demura T, Fukuda H. Expression of
photosynthesis-related genes and their regulation by
light during somatic embryogenesis in Daucus carota.
Planta 2004;219:23–31.
[49] Rolletschek H, Weber H, Borisjuk L. Energy status and its
control on embryogenesis of legumes. Embryo photosynthesis
contributes to oxygen supply and is coupled to biosynthetic
fluxes. Plant Physiol 2003;132:1196–206.
[50] Gallardo K, Job C, Groot SPC, Puype M, Demol H,
Vandekerckhove J, et al. Proteomic analysis of Arabidopsis
seed germination and priming. Plant Physiol
2001;126:835–48.
[51] Rodríguez MJP, Suárez MF, Heredia R, Ávila C, Breton D,
Trontin JF, et al. Expression patterns of two glutamine
synthetase genes in zygotic and somatic pine embryos
support specific roles in nitrogen metabolism during
embryogenesis. New Phytol 2006;169:35–44.
[52] Allona I, Casado R, Aragoncillo C. Seed storage proteins from
Pinus pinaster Ait.: homology of major components with 11S
proteins from angiosperms. Plant Sci 1992;87:9–18.
[53] Silveira V, Santa-Catarina C, Tun NN, Scherer GFE, Handro
W, Guerra MP, et al. Polyamine effects on the endogenous
polyamine contents, nitric oxide release, growth and
differentiation of embryogenic suspension cultures of
Araucaria angustifolia (Bert.) O. Ktze. Plant Sci 2006;171:91–8.
[54] Steiner N, Santa-Catarina C, Silveira V, Floh EIS, Guerra MP.
Polyamine effects on growth and endogenous hormones
levels in Araucaria angustifolia embryogenic cultures. Plant
Cell Tissue Organ Cult 2007;99:52–62.
[55] ParkYS, Pond SE, BongaJM. Initiationofsomaticembryogenesis
in white spruce (Picea glauca): genetic control, culture treatment
effects, and implications for tree breeding. Theor Appl Genet
1993;86:427–36.
[56] Salajova T, Salaj J, Kormutak A. Initiation of embryogenic
tissues and plantlet regeneration from somatic embryos of
Pinus nigra Arn. Plant Sci 1999;145:33–40.
[57] Li XY, Huang FH. Induction of somatic embryogenesis in
loblolly pine (Pinus taeda L.). In Vitro Cell Dev Biol Plant
1996;32:129–35.
351
J O U R N A L O F P R O T E O M I C S 7 2 ( 2 0 0 9 ) 3 3 7 – 3 5 2