Download Experimental Analysis of the Rice Mitochondrial

Experimental Analysis of the Rice Mitochondrial
Proteome, Its Biogenesis, and Heterogeneity1[W][OA]
Shaobai Huang, Nicolas L. Taylor, Reena Narsai, Holger Eubel, James Whelan, and A. Harvey Millar*
Australian Research Council Centre of Excellence in Plant Energy Biology, M316, University of Western
Australia, Crawley, 6009 Western Australia, Australia
Mitochondria in rice (Oryza sativa) are vital in expanding our understanding of the cellular response to reoxygenation of tissues
after anaerobiosis, the crossroads of carbon and nitrogen metabolism, and the role of respiratory energy generation in
cytoplasmic male sterility. We have combined density gradient and surface charge purification techniques with proteomics to
provide an in-depth proteome of rice shoot mitochondria covering both soluble and integral membrane proteins. Quantitative
comparisons of mitochondria purified by density gradients and after further surface charge purification have been used to
ensure that the proteins identified copurify with mitochondria and to remove contaminants from the analysis. This rigorous
approach to defining a subcellular proteome has yielded 322 nonredundant rice proteins and highlighted contaminants in
previously reported rice mitochondrial proteomes. Comparative analysis with the Arabidopsis (Arabidopsis thaliana) mitochondrial proteome reveals conservation of a broad range of known and unknown function proteins in plant mitochondria,
with only approximately 20% not having a clear homolog in the Arabidopsis mitochondrial proteome. As in Arabidopsis, only
approximately 60% of the rice mitochondrial proteome is predictable using current organelle-targeting prediction tools. Use of
the rice protein data set to explore rice transcript data provided insights into rice mitochondrial biogenesis during seed
germination, leaf development, and heterogeneity in the expression of nucleus-encoded mitochondrial components in different
rice tissues. Highlights include the identification of components involved in thiamine synthesis, evidence for coexpressed and
unregulated expression of specific components of protein complexes, a selective anther-enhanced subclass of the decarboxylating segment of the tricarboxylic acid cycle, the differential expression of DNA and RNA replication components, and
enhanced expression of specific metabolic components in photosynthetic tissues.
As rice (Oryza sativa) is the one of the major food
supplies for the expanding world population, especially in developing countries, exploiting a molecular
understanding of rice biology has the potential to aid
humanity in a profound way, as has been seen in the
development and use of vitamin A-enhanced cv
Golden Rice (Paine et al., 2005). Mitochondria are
essential for all plant species as the energy production
factory for ATP production via respiratory oxidation
of organic acids and the transfer of electrons to O2. But
the role and nature of mitochondria in rice take on
special significance due to their early growth habitat in
1
This work was supported by the Australian Research Council
(ARC) through the Discovery Programme (grant no. DP0664692 to
A.H.M. and J.W.). N.L.T. and H.E. are supported as ARC Australian
Postdoctoral Fellows (grant nos. DP0772155 and DP0773152), and
A.H.M. is an ARC Australian Professorial Fellow (grant no.
DP0771156).
* Corresponding author; e-mail [email protected].
The author responsible for distribution of materials integral to the
findings presented in this article in accordance with the policy
described in the Instructions for Authors (www.plantphysiol.org) is:
A. Harvey Millar ([email protected]).
[W]
The online version of this article contains Web-only data.
[OA]
Open Access articles can be viewed online without a subscription.
www.plantphysiol.org/cgi/doi/10.1104/pp.108.131300
hypoxic or even anaerobic environments (Perata and
Voesenek, 2007) and the need for mitochondrial biogenesis during the reoxygenation phase (Millar et al.,
2004a; Howell et al., 2007). Rice seed embryos contain
highly reduced protomitochondrial structures that
mature to fully functional mitochondria through a
complex biogenesis process involving induction of the
general import pathway (Howell et al., 2006) and
oxygen signaling of transcription (Howell et al.,
2007). Furthermore, the farming practice of using
hybrid rice production to boost crop yields relies on
cytoplasmic male-sterile lines that have dysfunctional
mitochondria in their pollen and restorer lines that
recover mitochondrial function and thus fertility to the
hybrid (Eckardt, 2006; Wang et al., 2006). Mitochondria
in dicots are known to play critical roles in the synthesis of vitamins and cofactors important for human
nutrition, including vitamin C (Bartoli et al., 2000;
Millar et al., 2003), folate (Ravanel et al., 2001), biotin
(Picciocchi et al., 2003), and lipoic acid (Yasuno and
Wada, 2002), but there is little research in rice to
confirm these roles or investigate these processes at the
molecular level. Photorespiration in C3 plants like rice
depends on the prevailing CO2 concentrations and
involves a critical role of mitochondria in carbon
recycling. But despite attempts to engineer C4 metabolism in rice and thus eliminate photorespiration
(Ku et al., 1999), there has been little analysis of the
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Huang et al.
photorespiratory machinery and related metabolism
as integral components in rice mitochondrial function.
The coordination of biochemical processes to perform the functions of mitochondria requires many
hundreds of different proteins working together in
protein complexes, in two membrane systems, and in
several aqueous spaces. The majority of mitochondrial
proteins are encoded in the nucleus and transported
into mitochondria as cytosolic precursor proteins by
the mitochondrial protein import machinery. Prediction tools based on N-terminal portions of protein
sequences are unable to predict localization to a high
fidelity (Heazlewood et al., 2005), so the best option is
direct experimental analysis of the rice mitochondrial
proteome. We have previously reported rice mitochondrial isolation and analysis, using Percoll gradient purification, two-dimensional isoelectric focusing
(IEF)/SDS-PAGE, blue native (BN)-PAGE, and liquid
chromatography-tandem mass spectrometry (LC-MS/
MS), and the identification of 122 nonredundant rice
mitochondrial proteins (Heazlewood et al., 2003).
Subsequently, a separate set of 112 nonredundant
rice mitochondrial proteins was identified and listed
in the rice proteome database (Komatsu, 2005) using
mitochondria isolated by Suc gradient centrifugation
and gel-based spot analysis. However, there is less
than 20% overlap between the protein lists reported in
these two studies.
The removal of contaminants is essential for accurate curation of subcellular organelle proteomes.
While dual targeting of some proteins to multiple
compartments occurs in plants (Peeters and Small,
2001), the question of contamination between compartments needs to be resolved in a quantitative
fashion before such a claim can be considered. Isolation of mitochondria using the traditional differential
and gradient centrifugation methods based on size
and density has been applied to mitochondrial proteomic analysis in a variety of plant species (Kruft
et al., 2001; Millar et al., 2001; Bardel et al., 2002;
Heazlewood et al., 2003, 2004). However, a range of
contaminants have been found when data obtained by
these methods are compared with proteins identified
in other cellular organelles by mass spectrometry and/
or independent experiments (Heazlewood et al., 2005).
Free-flow electrophoresis in zone electrophoresis
mode (ZE-FFE) has been used to purify yeast mitochondria to an increased homogeneity based on the
surface charge of the organelles (Zischka et al., 2006).
Recent separation of plant organelles using ZE-FFE
has allowed a deeper and more comprehensive analysis
of Arabidopsis (Arabidopsis thaliana) organellar proteomes and highlighted that some proteins reported as
dual targeted can be explained as contaminants
through quantitative analysis (Eubel et al., 2007).
In this study, traditional differential and gradient
centrifugation were combined with FFE separation to
isolate rice mitochondria. Through the direct analysis
of trypsin-digested mitochondrial peptides by LCMS/MS and gel-based analysis of rice mitochondrial
proteins and the removal of contaminants by quantitative comparison of mitochondria prior to FFE separation, a refined rice mitochondrial data set of 322
proteins is presented. The expanded rice mitochondrial data set is comparable in size and complexity to
the previously published Arabidopsis data set
(Heazlewood et al., 2004). Analysis revealed that rice
and Arabidopsis mitochondria share conserved energy production and metabolism proteins. Interestingly, a significant proportion of the set of proteins
with unknown function identified have clear homologs in Arabidopsis mitochondria. This indicates that a
range of conserved functions exist that are carried out
by unknown function proteins in plant mitochondria
that deserve future investigation. The use of this
protein data set to explore rice transcript data has
given several insights into rice mitochondrial biogenesis during seed germination and heterogeneity between rice tissues. Highlights include evidence for
coexpressed and unregulated expression of specific
components of protein complexes, a selective antherenhanced version of the decarboxylating segment of
the tricarboxylic acid (TCA) cycle, the differential
expression of DNA and RNA replication components,
and enhanced expression of specific mitochondrial
metabolism in photosynthetic tissues.
RESULTS
Purification of Isolated Rice Mitochondria Using FFE
The integrity of the mitochondrial proteome is
largely dependent on the purification of the isolated
organelles away from other cellular contaminants. A
two-Percoll gradient density separation technique to
isolate mitochondria from dark-grown Arabidopsis
cells (Millar et al., 2001; Heazlewood et al., 2004) works
efficiently in dark-grown rice shoots and yield extracts
largely free of contamination by cytosol, peroxisomes,
plastids, and other membranes (Heazlewood et al.,
2003). To further purify these organelles, washed and
Percoll-free organelles were then injected into the
separation chamber of the FFE instrument. The visible
turbidity pattern in the separation chamber was similar to that observed in the separation of Arabidopsis
organelles with two main streams and two minor
streams (Eubel et al., 2007), and these streams were
reflected in the pattern of the 280-nm absorbance of
collected fractions on 96-well plates (Supplemental
Fig. S1). Based on comparison with the separation
pattern in Arabidopsis (Eubel et al., 2007), the major
peak 2 (fractions 25–36) would likely contain enriched
mitochondria, and the peaks 1 (fractions 16–22) and 3
(fractions 38–44) would contain plastids and peroxisomes, respectively.
To confirm the distribution of organelles in different
FFE fractions, an aliquot of every third fraction was
separated by one-dimensional SDS-PAGE (Fig. 1A).
Western blotting was applied for analysis using anti-
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Rice Mitochondrial Proteome
Figure 1. A, Coomassie Brilliant Blue-stained one-dimensional SDS-PAGE and immunoblots of every third of the 45 fractions
collected after FFE. The gels were loaded on a volume basis to monitor the distribution of three marker proteins for mitochondria
(mtHSP70), plastids (RbcS), and peroxisomes (KAT2). The numbers at right represent molecular mass in kilodaltons. B,
Coomassie Brilliant Blue-stained one-dimensional SDS-PAGE of pooled fractions 16 to 21 and 27 to 30 collected after FFE. The
bands denoted with numbers were analyzed by MS/MS for protein identification, and identified proteins are presented in Table I.
The numbers at right represent molecular mass in kilodaltons.
bodies raised against protein markers for mitochondria (mtHSP70), plastids (small subunit of Rubisco;
RbcS), and peroxisomes (3-ketoacyl-CoA thiolase;
KAT2; Fig. 1A). The mtHSP70 was present in fractions
27 to 36, which also contained the bulk of the protein
content visible in colloidal Coomassie Brilliant Bluestained gel lanes and in 280-nm absorbance measurements (Fig. 1A; Supplemental Fig. S1), indicating that
those fractions constitute the mitochondrial portion of
sample. The plastidic RbcS was mainly present in the
fractions around 18, indicating that plastids were
enriched in those fractions after FFE. The minor RbcS
peak that copurified with mitochondrial fractions is
most likely due to RbcS from ruptured plastids that
adhere to the mitochondrial membrane, but it could
be due to a very small proportion of chloroplast
having the same surface charge as mitochondria. A
similar bimodal distribution of RbcS is seen in Arabidopsis mitochondria purified by FFE (Eubel et al.,
2007). The peroxisomal KAT2 marker was enriched in
the fractions 33 to 45, deflecting to the right (cathodic)
side of the mitochondrial fractions. Mitochondriaenriched fractions (27–30) and the suspected plastidic
fractions (16–21) were collected after FFE for onedimensional SDS-PAGE separation and showed different protein patterns after Coomassie Brilliant Blue
staining (Fig. 1B). In the mitochondria-enriched fraction, classical mitochondrial proteins were found, such
as HSP70 (Os02g53420), ATP/ADP carrier protein
(Os02g48720), and MnSOD (Os05g25850; Fig. 1B; Table
I). In the plastid-enriched fraction, typical plastidic
proteins were identified, such as TIC110 (Os10g35010),
chaperone clpB1 (Os10g35010), and transaldolases
(Os01g70170 and Os08g05830; Fig. 1B; Table I). Based
on the results obtained above, fractions 27 to 31 were
selected as FFE-purified mitochondrial organelles for
further analysis.
The FFE-purified mitochondrial samples were compared with Percoll gradient-prepared mitochondria
samples before FFE purification using differential twodimensional IEF/SDS-PAGE by labeling proteins with
fluorescent Cydyes (Fig. 2). The overall spot patterns
were consistent with the rice mitochondrial profiles
published previously (Heazlewood et al., 2003). Spots
with the decreased abundance after FFE (indicated by
arrows in Fig. 2) were selected for protein identification using LC-MS/MS. The proteins identified as
putative contaminants are listed in Table I. Most of
them are plastidic, peroxisomal, or cytosolic proteins
but also include bovine serum albumin that was
added in the mitochondrial extraction buffer.
Gel-Based Analysis of FFE-Purified Rice
Mitochondrial Proteins
To identify the proteins in FFE-purified rice mitochondria, preparative IEF/SDS-PAGE gels were run
and analyzed. A set of 291 abundant spots from these
gels (Supplemental Fig. S2) were excised and subjected
to in-gel digestion followed by MS/MS-based analysis
of the resultant peptides. Comparison of spot locations
with the quantitative data in Figure 2 ensured that
these spots were not decreased during the FFE process, indicating that they were retained or enriched by
the mitochondrial purification. This analysis led to
identification of a set of 146 nonredundant proteins
from rice. We also reanalyzed a set of 89 spots excised
from BN/SDS-PAGE gels to separate rice mitochon-
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Huang et al.
Table I. Selected protein bands identified from enriched fractions containing mitochondria and chloroplasts (Fig. 1), and selected protein spots
identified from DIGE two-dimensional gels that decreased in abundance after FFE purification of mitochondria (Fig. 2)
Proteins were identified by MS/MS. The predicted molecular mass in kilodaltons (MM) and pI of the match are shown along with the MOWSE
score (P , 0.05 when score . 37), number of peptides matched to tandem mass spectra, and the percentage coverage of the matched sequence. The
localization of the identified proteins is listed based on their description. The average DIGE ratio represents the decrease of spot abundance after FFE
purification (Fig. 2).
MS/MS
Spot
Gene Identifier
One-dimensional gel
1
Os02g53420
2
Os02g48720
Os05g11780
Os12g13380
3
Os05g25850
Os06g43850
Osm1g00590
4
Os10g35010
5
Os03g31300
6
Os04g32560
7
Os01g70170
8
Os08g05830
9
Os06g09679
DIGE gel
1
Os05g23740
2, 3 Os06g04270
4, 5
6
Os03g57220
Os07g05820
7
Os01g02880
8
Os02g52940
9
Os09g36450
Description
MOWSE
Score
Peptides
Coverage
Location
Heat shock 70 kD
72.9/5.5
ADP, ATP carrier
41.5/9.8
2-Oxoglutarate/malate carrier
32.8/9.6
Adenylate kinase A
26.4/8.5
Superoxide dismutase
25.0/6.5
ATP synthase delta subunit
25.1/9.4
NADH dehydrogenase subunit 9 (NAD9)
22.6/7.8
Chloroplast envelope translocase (TIC110) 110.7/5.5
Chaperone clpB 1
108.9/6.3
ATP-dependent Clp protease subunit
101.7/6.1
Transaldolase 2
46.4/6.1
Transaldolase
43.0/5.2
Chloroplast chaperonin
26.3/7.7
131
51
64
46
79
77
43
110
48
91
213
74
55
13
5
1
1
2
7
1
8
5
8
10
4
4
16%
8%
4%
3%
6%
26%
5%
9%
4%
7%
23%
8%
16%
Mitochondrion
Mitochondrion
Mitochondrion
Mitochondrion
Mitochondrion
Mitochondrion
Mitochondrion
Plastid
Plastid
Plastid
Plastid
Plastid
Plastid
Stromal 70-kD heat shock-related protein
Transketolase
Albumin BSA
Hydroxyacid oxidase 1
Hydroxyacid oxidase 1
Chloroplast Fru-bisP aldolase
Inorganic pyrophosphatase
Chloroplast triosephosphate isomerase
105
41
199
68
67
116
106
79
3
1
6
3
4
2
3
3
6%
2%
10%
8%
9%
7%
11%
7%
Plastid
Plastid
drial protein complexes as described by Heazlewood
et al. (2003); this allowed identification of these proteins against the latest set of predicted rice protein
sequences (Osa5). There were a set of 88 nonredundant
protein sequences identified from BN-PAGE-separated
proteins; 57 were unique protein sequences not identified
by the IEF/SDS-PAGE because most were membrane
protein subunits of the respiratory chain complexes,
which do not enter IEF gels. Taken together, a set of 203
nonredundant proteins were identified based on the
gel separations.
Non-Gel-Based Analysis of FFE-Purified Rice
Mitochondrial Proteins Using Complex
Mixture LC-MS/MS
Non-gel-based LC-MS/MS of rice mitochondrial
peptides allowed us to identify the highly hydrophobic, basic, and small or large molecular mass proteins
excluded from polyacrylamide gel-based analysis. The
whole mitochondrial samples before and after FFE
purification were analyzed with three independent
biological samples using LC-MS/MS. This analysis
allowed us to quantitatively compare the ratio of
peptide numbers found for each protein before and
after FFE purification, which provided additional criteria to remove contaminants. There were a total of 357
nonredundant proteins found by LC-MS/MS from the
MM/pI
73.5/5.1
80.0/6.1
69.2/5.8
40.4/8.5
40.2/8.5
42.0/8.8
31.8/5.8
32.4/7.0
Peroxisome
Peroxisome
Plastid
Plastid
Plastid
DIGE Ratio
1.74
1.92–1.96
1.48–1.66
1.93
1.43
1.70
2.30
samples before and after FFE purification (Fig. 3). A set
of 56 proteins were only found in the samples before
FFE purification, and most of these proteins were
contaminants from the plastids, cytosol, and peroxisomes (Supplemental Table S2A). For example, 17, 11,
and 10 peptides were found for peroxisomal hydroxyacid oxidase 1 (Os07g05820), cytosolic Ala aminotransferase 2 (Os07g01760), and plastidic ATP
synthase CF1 b-chain (Osp1g00410), respectively
(Supplemental Table S2A). There were 262 proteins
for which peptides were found in samples both before
and after FFE purification. Nearly 71% of proteins
were enriched (ratio of peptide number identified,
#1.0) after FFE purification (Fig. 3). A large proportion
of proteins with peptide ratios greater than 1.6 could
be confidently classified as contaminants (Fig. 3; Supplemental Table S2A). These data were consistent with
the results from differential in-gel electrophoresis
(DIGE) experiments (Fig. 2; Table I) but provide a
much deeper assessment of low-level contaminants
and low-abundance mitochondrial proteins. The possible contaminants were removed based on peptide
ratios before and after FFE purification and DIGE data
as described above. For the 52 proteins only found in
FFE-purified samples, MS spectral quality, peptide
number, and protein coverage were also used as
additional criteria to distinguish contaminants from
mitochondrial proteins (Supplemental Table S2B).
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Rice Mitochondrial Proteome
Figure 2. DIGE on two-dimensional IEF/SDS-PAGE
gels. Samples before FFE treatment (2FFE; labeled
with Cy3, shown in red) and after FFE treatment
(+FFE; labeled with Cy5, shown in green) were
compared. The top panels are gel images of each
fluorescence signal, and the bottom panel is a combined fluorescence image electronically overlaid using ImageQuant TL software (GE Healthcare). Yellow
spots represent proteins of equal abundance before
and after FFE purification. Spots that are more abundant in samples before FFE purification are red, and
those more abundant in samples after FFE purification
are green. The numbered arrows indicate proteins
with statistically significantly decreased abundance
after FFE purification (n = 3, P , 0.05), which were
selected for MS/MS-based identification.
Broad Analysis of Mitochondrial Functions Identified
in Rice
Combining the gel-based and non-gel-based approaches and after removal of contaminants, a nonredundant set of 322 proteins can be conservatively
defined as rice mitochondrial proteins (Supplemental
Table S3). In this set of rice mitochondrial proteins, 168
proteins were found using the gel-based method and
307 proteins were found using LC-based methods
(Supplemental Table S3). Seventy-eight of the 122
nonredundant rice mitochondrial proteins reported
previously using Percoll gradient centrifugation purification methods (Heazlewood et al., 2003) were confirmed in this study (Supplemental Table S3). Half of
the unconfirmed proteins (21 of 43) from Heazlewood
et al. (2003) were proteins predicted from retrotransposon sequences and unknown function proteins.
Surprisingly, only six proteins were confirmed from
a set of 112 nonredundant proteins listed as mitochondrial in the rice proteome database (Komatsu, 2005;
http://gene64.dna.affrc.go.jp/RPD/), apparently due
to the heavy contamination of the rice mitochondrial
samples used to generate these identifications.
Each rice mitochondrial protein was assigned to one
of 17 functional categories (Fig. 4; Supplemental Table
S3). In this data set, known function proteins were
highly represented by those involved in energy production (complexes I–V, 22%) and metabolism (TCA
and general metabolism, 28%; Fig. 4), while the proteins with unknown function represented 17% of the
mitochondrial protein set (Fig. 4). The numbers of
proteins involved in energy production and metabolism are very similar in the rice and Arabidopsis
mitochondrial data sets (Fig. 4). There are fewer proteins identified to be involved in electron transport
chain assembly and signaling, stress defense, carriers
and transporters, protein import/fate, and unknown
Figure 3. Distribution of the ratios of the number of peptides from a
given protein identified before FFE purification to those identified after
FFE purification by LC-MS/MS. Three biological samples, each consisting of pre-FFE and post-FFE samples, were analyzed. The area of
each bar highlighted in gray represents the contaminants based on their
functional classification and our manual analysis (listed in Supplemental Table S2A), while the white areas of each bar indicate mitochondrial
proteins in each ratio class.
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Huang et al.
Figure 4. Functional distribution of the 322 rice mitochondrial proteins (white bars) alongside 416 Arabidopsis mitochondrial
proteins (gray bars) from Heazlewood et al. (2004). Rice mitochondrial protein data were extracted from Supplemental Table S3.
proteins in the rice compared with the Arabidopsis
mitochondrial data sets (Fig. 4).
Prediction of Rice Mitochondrial Proteins
This experimentally determined rice mitochondrial
protein set provides an opportunity to test the sensitivity of different organelle-targeting prediction programs in rice. When our set of 313 nucleus-encoded
rice mitochondrial proteins were analyzed, the accuracy of mitochondrial prediction by four leading targeting prediction programs ranged from 61% to 66%
(Table II), which was higher than the 40% to 50%
prediction rate observed for the Arabidopsis mitochondrial protein set (Heazlewood et al., 2004). The
high accuracy of prediction by the four programs in
this study may be due to the higher purity of the FFEpurified mitochondrial sample and the removal of
proteins during FFE that only bind to the surface of the
mitochondrial outer membrane but are not imported.
Proteins most often predicted by these programs
belonged to electron transport chain assembly, DNA
and RNA replication, TCA cycle, and complex III (Fig.
5; Supplemental Table S3). On the other hand, the
proteins from the functional groups of carriers, protein
import and fate, complex V, and unknown proteins had
a low proportion of proteins predicted to be mitochondrially localized (Fig. 5; Supplemental Table S3). Some
of these mitochondrial proteins have known internal
targeting sequences rather than classical N-terminal
sequences, and these are not detected by these prediction programs. However, for many proteins, the mechanism of sorting to mitochondria is still unknown.
Global Analysis of Expression Pattern of the Identified
Rice Mitochondrial Proteins
The plant mitochondrial proteome changes during
development of plant organs as well as differing in
various cell and tissue types. We have already shown
in Arabidopsis that 40% of proteins change more than
2-fold in abundance when comparing mitochondrial
proteomes from photosynthetic and nonphotosynthetic tissues (Lee et al., 2008). The combination of
proteome and gene expression data can provide a
more global understanding of gene functions in particular organs and developmental stages and in response to stresses. To analyze the gene expression
pattern, we extracted the available rice microarray
data from the National Center for Biotechnology Information gene expression omnibus (http://www.
ncbi.nlm.nih.gov/geo) of six independent studies
with relevance for mitochondrial function (Walia
et al., 2005, 2007; Jain et al., 2007; Lasanthi-Kudahettige
et al., 2007; Li et al., 2007; Ribot et al., 2008) and our
own rice microarray data during the first 24 h of
germination. From 322 mitochondrial proteins identified, 306 had representative probe set identifiers on the
microarrays. Analysis of the combined microarray
expression data is described in “Materials and
Methods.” The genes were divided into 12 hierarchical
clusters (Fig. 6A) based on differential expression
patterns in different organs or treatments, with seven
major clusters containing more than 16 genes in each
cluster and five minor clusters containing fewer than
10 genes in each cluster. Cluster 1 was defined by high
expression of photorespiratory components in leaf
tissue that were largely absent in most other samples
except young seedlings. Cluster 4 was defined by
expression in anoxically grown 4-d coleoptiles, and
cluster 5 was defined by a set of genes that peak in
expression in mature anthers. Cluster 6 displayed high
expression in suspension cells and 12- and 24-h imbibed seeds and to a lesser extent in developing seeds.
Clusters 8 and 11 were defined by expression in most
of the arrays except 0- to 3-h imbibed seed, while
cluster 10 members were evenly expressed in all rice
tissues. The proportion of each cluster in different
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Rice Mitochondrial Proteome
Table II. Evaluation of mitochondrial prediction programs using
experimental sets of rice and Arabidopsis nucleus-encoded
mitochondrial proteins
Two mitochondrial sets were used in the analysis: a set of 313
nucleus-encoded rice mitochondrial proteins (Supplemental Table S3)
and a set of 405 nucleus-encoded Arabidopsis mitochondrial proteins
from Heazlewood et al. (2004).
Program
Rice
Mitochondrial
Set (313)
Sensitivity
Target P
iPsort
MitoProtII
Predotar
194
205
202
191
62
66
65
61
Arabidopsis
Mitochondrial
Set (405)
Sensitivity
162
202
191
168
40
50
47
41
%
%
functional classes is summarized in Figure 6B. Detailed information is given in Supplemental Figure S3
and Table S5, and highlights are described in the
following sections based on the functional classification of proteins and their expression patterns.
The Respiratory Apparatus and Its Expression
The mitochondrion is an energy factory for ATP
production coupled to the respiratory oxidation of
organic acids and the transfer of electrons to O2. Over
71 proteins of the five electron transport chain complexes and 28 protein subunits of TCA cycle enzymes
have been identified (Fig. 4), representing 31% of the
rice mitochondrial protein set. Most of these proteins
have orthologs in Arabidopsis, and most have also
been experimentally shown to be mitochondrial proteins in Arabidopsis (Supplemental Table S3). This
highlights that rice and Arabidopsis have a very
conserved composition of the respiration chain complexes and the TCA cycle. Six proteins involved in
alternative pathway respiration were also found,
namely cytosol-facing NADH dehydrogenases that
donate electrons to ubiquinone and bypass complex I
and components of the electron-transfer flavoprotein
pathway that reduces ubiquinone and is linked to the
matrix branched-chain amino acid degradation path-
way (Supplemental Table S3; Taylor et al., 2004). No
alternative oxidases that oxidize ubiquinol and consume O2 were found in this rice study, which is
consistent with the very low expression of alternative
oxidases in rice shoots under normal conditions
(Saika et al., 2002) and the very low cyanideinsensitive respiratory rate of isolated rice mitochondria (Heazlewood et al., 2003; Millar et al., 2004a). The
genes encoding the subunits of the oxidative phosphorylation complexes (complexes I–V) were highly
expressed across all tissues (mainly cluster 11 in Fig.
6), confirming the essential function of the respiration
chain for energy production. Comparison of the expression profiles of the genes for the subunits in each
respiratory complex separately revealed in each case a
core of coexpressed subunits and a series of apparently
aberrantly expressed subunits (Supplemental Fig. S3).
A series of genes encoding TCA cycle subunits were
highly expressed in the anther; these were nearly all
components of the pyruvate dehydrogenase complex
(PDH) and the initial steps of the TCA cycle (citrate
synthase, aconitase, and isocitrate dehydrogenase
[ICDH]). In most cases, another isoform was also in
our list of TCA cycle components and had a much
more ubiquitous gene expression pattern (most notably, PDH E1a Os02g50620 versus Os12g08260, PDH
E1b Os09g33500 versus Os08g42410, PDH E2
Os06g01630 versus Os02g01500, aconitase Os03g04410
versus Os08g09200, and ICDH Os04g40310 versus
Os02g38200). In contrast to this, later steps of the TCA
cycle, such as malate dehydrogenase (Os01g46070 and
Os05g49880), were more evenly expressed across tissue
types (Supplemental Fig. S3). Mature anthers might
thus possess a very high metabolic activity for energy
production during pollen formation, and potentially
this is mediated by a specific highly expressed form of
the TCA cycle in pollen.
General Metabolism in Rice Mitochondria
Plant mitochondria are also involved in synthesis of
vitamins, cofactors, and lipids, metabolism of amino
acids, photorespiratory Gly oxidation, and export of
organic acid intermediates for other cellular biosynFigure 5. Proportion of mitochondrial proteins in
different functional categories that were predicted to
be localized in mitochondria using the four major
prediction programs listed in Table II. In each bar, the
white region was not predicted by any program, the
black region was predicted by all four programs,
while increasingly gray bars indicate mitochondrial
prediction by one, two, or three programs. The
functional classifications of a total of 322 proteins
were taken from Supplemental Table S3.
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Figure 6. (Legend appears on following page.)
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Rice Mitochondrial Proteome
thesis. Rice mitochondrial proteins involved in these
processes were also evident in our protein lists. In
total, 64 proteins were identified as being involved in a
range of metabolic pathways (Supplemental Table S3).
Subdivision of this functional classification showed 16
proteins involved in amino acid metabolism, seven
proteins involved in aldehyde/alcohol metabolism,
six proteins involved in lipid synthesis, and six proteins
involved in metabolism of nucleotides. Photorespiratory genes (Gly decarboxylase complex subunits and
Ser hydroxymethyltransferase) were selectively expressed in leaf tissues (cluster 1, Fig. 6A), while
components linked to C1 metabolism (glyoxylate, formate, and tetrahydrofolate metabolism) did not show
leaf enhanced expression profiles (Supplemental Fig.
S3). Two isoforms of the H protein of the Gly decarboxylase complex (Os06g45670 and Os02g07410) did
not show leaf enhanced expression patterns but were
broadly expressed with the C1 metabolism genes
(Supplemental Fig. S3). The role of Gly decarboxylase
in plant mitochondrial C1 metabolism outside of its
photorespiratory role is still largely unexplored in
plants. A 4-methyl-5-thiazole monophosphate biosynthesis protein (Os01g11880) predicted to be involved in
thiamine biosynthesis was enriched after FFE purification (Supplemental Table S3), representing, to our
knowledge, the first component of thiamine synthesis
found in rice mitochondria.
DNA Replication, Transcription, and Translation
There were 19 proteins in the DNA replication
and transcription category (Supplemental Table S3).
Among them, five were DAG-like proteins and eight
were pentatricopeptide repeat (PPR) proteins. Genetic
evidence shows that DAG proteins influence DNA
synthesis and alter chloroplast differentiation (Bisanz
et al., 2003), but while DAG proteins have also been
reported in the Arabidopsis mitochondrial proteome,
the specific function of this class of proteins in mitochondria is still unknown. There are 477 PPRs in the
rice genome and 450 PPRs in Arabidopsis, and most
are predicted to be targeted to mitochondria or plastids (Small and Peeters, 2000; O’Toole et al., 2008). PPR
proteins are associated with both the transcriptional
(Pfalz et al., 2006) and translational (Pusnik et al., 2007)
machinery and are involved in many stages of mRNA
splicing (de Longevialle et al., 2007). In rice, two
mitochondrial PPR proteins were reported to be restorers of cytoplasmic male sterility (Wang et al., 2006).
Here, we have found eight PPRs that complement two
other PPRs found in rice mitochondria by Heazlewood
et al. (2003). Five of the PPRs identified in our study
are orthologs of PPRs previously identified in Arabidopsis mitochondria. For example, OsPPR_02g58300
is an ortholog of the P-class PPR336 protein At1g61870.
PPR336-like proteins are known to be extrinsically
attached to the inner mitochondrial membrane and to
be associated with polysomal RNA (Uyttewaal et al.,
2008). OsPPR_02g02020 is an ortholog of At2g37230,
which was found in the thylakoid membrane of
Arabidopsis (Peltier et al., 2004), even though these
proteins were predicted to be mitochondrial in both
rice and Arabidopsis. To our knowledge, the possibility of orthologous PPRs swapping location between
mitochondria and chloroplasts in different plant species or being dual targeted has not been reported.
OsPPR_04g09530, to our knowledge, is the first DYWtype PPR found by mass spectrometry. This class of
PPRs often has an RNA-editing role and is typically
expressed at very low levels. Further studies are
required to investigate the function of these eight
PPRs in rice mitochondria.
Fourteen proteins are listed in the group of proteins
involved in translation. Six subunits of the putative
mitochondrial ribosome were identified: L1, L27, and
L30 of the 50S complex and S12, S18, and S19 of the 30S
complex. Even with this small number of predicted
subunits of the mitochondrial ribosome, clear differences between Arabidopsis and rice are apparent. The
nucleus-encoded S12 protein in rice (Os12g33930) is
most similar to the mitochondria-encoded S12 in
Arabidopsis (AtMg00980), while the mitochondriaencoded S19 in rice (OsM1g00450) is orthologous to
a nucleus-encoded ribosomal subunit in Arabidopsis
(At5g47320). Extensive studies have been performed
on ribosomal proteins shifting or swapping their
location during recent evolution in plants (Adams
et al., 2000, 2002). The S19 gene has been transferred to
the nucleus in many cereals, with the notable exception of rice, where an intact gene and transcript have
been reported in mitochondria (Fallahi et al., 2005).
Here, we show clear evidence for this S19 protein
accumulating in rice mitochondria. The S12 is mitochondrially encoded and cotranscribed with nad3 in
many dicots and monocots (Perrotta et al., 1996), but
our match here is to a nuclear gene. So it seems that in
rice it has been transferred to the nucleus, which has
also been reported for the dicot Oenothera (Grohmann
et al., 1992). Elongation factors and tRNA synthetases
make up the majority of the other translation components, as they do in the proteome analysis of
Arabidopsis mitochondria. The genes encoding DNA
replication, transcription, and translation factors were
Figure 6. Hierarchical clustering of transcripts for the nucleus-encoded components of the rice mitochondrial proteome (A), and
functional categorization of the transcripts grouped into each cluster (B). Hierarchical clustering was carried out using average
linkage based on Euclidean distance of the 306 mitochondrial genes across all of the Affymetrix rice genome arrays carried out
on various tissue types and conditions. Twelve distinct clusters were colored and numbered (shown in Supplemental Table S5).
The proportion of components from each functional categorization present in each of the 12 clusters is defined in A, and B shows
the number of components in each functional categorization above each column.
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Huang et al.
most highly expressed in suspension cells and in the
imbibed germinating seeds at 12 and 24 h, as shown in
cluster 6 (Fig. 6; Supplemental Fig. S3). This pattern of
expression might be related to the high rate of mitochondrial division and recombination in dividing cells
and the early steps of mitochondrial biogenesis during
germination.
Components of Protein Import and Fate
There were 19 proteins identified involved in protein import and fate (Supplemental Table S3). These
included proteins involved in protein import and
sorting, presequence cleavage, and proteolysis, and
all of them had clear orthologs in the Arabidopsis
mitochondrial proteome. The translocase of the outer
membrane (TOM) was represented by TOM40, TOM20,
and TOM22 subunits, while the only translocase of the
inner membrane (TIM) components found were the
intermembrane space members of the carrier import
pathway, Tim8, Tim9, and Tim13 homologs. Lon,
ClpX, and FtsH homologs were found, representing
the three main classes of mitochondrial proteases in
plants. The expression of genes encoding these proteins was mainly grouped into clusters 6 and 10, with
notable expression in suspension cells, seeds, and
embryos during the early stages of germination (Fig.
6; Supplemental Fig. S3). These results were consistent
with our reports of the substantial mRNA pool in dry
rice seeds for the genes encoding import components
(Howell et al., 2006).
Heat Shock and Stress Response Proteins
There are 15 heat shock proteins and putative or
well known molecular chaperones listed in our current
data set (Supplemental Table S3). These included the
classical 60/10-, 70-, and 80-kD chaperone classes.
While these chaperone and heat shock protein classes
are sometimes components induced by stresses with
roles in stress tolerance (Schöffl et al., 1998), we found
little evidence for this in the transcriptional data from
stress responses (such as drought, salt, and cold).
Instead, the expression of genes encoding these proteins was grouped into clusters 6 and 10, due mainly to
high expression in suspension cells and seeds and
during early germination (Fig. 6; Supplemental Fig.
S3). This suggests primary transcriptional regulation
of these proteins in response to cell division, expansion, and growth rather than stress tolerance.
There were nine proteins with putative roles in
stress response or oxidative stress in our data set
(Supplemental Table S3). Mitochondria are often exposed to self-generated reactive oxygen species, primarily through the ubisemiquinone intermediate,
formed by the NADH:ubiquinone oxidoreductase
(complex I) or ubiquinone:cytochrome c oxidoreductase (complex III) of the electron transport chain,
which can reduce O2 to O22 (Moller, 2001a). Antioxidant systems consisting of MnSOD, components of the
dual-targeted ascorbate/glutathione cycle, and peroxiredoxin and glutaredoxin family proteins were experimentally identified here (Supplemental Table S3).
Most of genes encoding stress-responsive proteins and
antioxidants were highly expressed in the suspension
cells (cluster 6, Fig. 6). Surprisingly, except for a few
selective proteins that were induced (several of the
ascorbate/glutathione cycle components), these components were not a group positively induced in response to the different environmental stresses tested,
including drought, salt, and cold (Fig. 6; Supplemental
Fig. S3).
Proteins of Unknown Function in Rice Mitochondria
A total of 55 proteins were identified as proteins
with unknown functions. Thirty-five of these rice
unknown proteins were predicted as mitochondrially
localized by at least one targeting prediction program,
but only five of these unknown proteins have been
identified in our previous study of the rice mitochondrial proteome (Heazlewood et al., 2004; Supplemental Table S3). Forty-nine of these 55 rice proteins had
clear Arabidopsis orthologs (Supplemental Table
S3), and 22 of them have been identified as Arabidopsis mitochondrial proteins in the SUBA database
(Heazlewood et al., 2005). These results indicate a
substantial conservation of unknown function proteins between mitochondria from different plant species, even though there is great divergence between
unknown function mitochondria proteins from different
eukaryotic lineages (Heazlewood et al., 2004). The identification of these conserved unknown function
mitochondrial proteins provides a focus for the use
of reverse genetics to identify novel mitochondrial
functions in plants.
The overall expression pattern of genes encoding
proteins with unknown function was dispersed
among other mitochondrial components, as shown in
Figure 6, but some gene expression data could be
grouped into different clusters or specific tissues. For
examples, seven unknowns (Os05g08920, Os07g26700,
Os04g41950, Os03g20860, Os05g01300, Os02g01450,
and Os02g07910) are most highly expressed in the
mature anthers (Fig. 6; Supplemental Fig. S3), which
might be related to high mitochondrial metabolism in
the same way as specific isoforms of TCA cycle enzymes show this distribution, as indicated above. Eight
unknown function genes (Os10g40410, Os03g38520,
Os03g48110, Os09g31260, Os05g46450, Os01g68030,
Os06g33920, and Os02g35610) are coexpressed with
genes encoding subunits of mitochondrial respiratory
complexes (Fig. 6A; Supplemental Table S5), indicating that those genes might be involved in energy
production or are associated with or are assembly
factors for these complexes. Another five unknown
function genes (Os06g22070, Os04g54410, Os08g34130,
Os01g50310, and Os11g14990) are coexpressed with
genes encoding proteins for DNA transcription and
replication (Fig. 6A; Supplemental Table S5), indicat-
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Rice Mitochondrial Proteome
ing that those genes might be involved in similar
functions, while Os01g05010 is tightly coexpressed
with several mitochondrial ribosomal components. In
cluster 7, comprising three genes (Fig. 6A; Supplemental Table S5), one unknown function gene (Os05g39390)
was coexpressed with two genes encoding proteins
involved in ubiquinone reduction, suggesting that this
gene might have a related function.
DISCUSSION
In this study, the combination of FFE-based plant
mitochondria separation (Eubel et al., 2007) and traditional differential and gradient centrifugations was
applied to determine the rice mitochondrial proteome.
This was achieved by organellar fraction selection
using marker antibodies as well as differences in spot
abundance in DIGE and peptide number ratios before
and after FFE purification. The final rice mitochondrial
data set provides evidence to confirm most of the
fundamental biological processes in mitochondria previously uncovered in Arabidopsis (Fig. 4; Heazlewood
et al., 2004). For example, the majority of mitochondrial proteins involved in energy production have
highly conserved amino acid sequences between rice
and Arabidopsis (Supplemental Table S3). A notable
exception is the subunits of succinate dehydrogenase
(SDH) or complex II. Differences between complex II
in higher plants and mammals have been known for
some time, most notably in the similarity of sequences
for SDH1 and SDH2 but great divergence in sequences
for the hydrophobic membrane anchor proteins SDH3
and SDH4 (Burger et al., 1996). In dicots, plant mitochondrial complex II appears to have four additional
subunits in BN-PAGE-purified preparations, termed
SDH5, -6, -7, and -8 (Millar et al., 2004b). In rice, we
identified classical SDH1 and SDH2 subunits, but the
SDH3 isoform we identified, Os02g02940, is very
poorly related to SDH3 (At5g09600) in Arabidopsis.
We did not identify the small SDH4 protein in rice, and
the annotated SDH4 gene from rice (Os01g70980) bares
little resemblance at all to the Arabidopsis SDH4. Furthermore, we found conserved homologs for SDH5, -6,
and -7 (Supplemental Table S3) but no evidence for an
SDH8 in rice analogous to the Arabidopsis SDH8. As
BN-PAGE separation of mitochondrial membrane complexes from monocot mitochondria does not resolve
complex II (Eubel et al., 2003; Heazlewood et al., 2003;
Millar et al., 2004b), the potential differences in mitochondrial complex II between monocots and dicots
requires further research.
Evidence for the dual targeting of proteins to both
mitochondria and chloroplasts has increased with the
greater ease in GFP-tagging experiments and the
increased interest in processes common to both organelles. In Arabidopsis, almost all organellar aminoacyltRNA synthetases are dual targeted, as shown by in
vivo GFP and in vitro organelle import (Duchene et al.,
2005). Two aminoacyl-tRNA synthases (Os01g31610,
orthologous to At3g02660, and Os07g07060, orthologous to At5g52520; Supplemental Table S3) found in
this study were also present in the proteome set of
etioplasts (Kleffmann et al., 2007), indicating that both
tRNA synthases could be dual targeted. Antioxidant
enzymes classically found in the chloroplast stroma,
such as ascorbate peroxidase (At4g08390) and monohydroascorbate reductase (At1g63940), have been shown
to be dual targeted to mitochondria in Arabidopsis
(Chew et al., 2003). Similarly, ascorbate peroxidase
(Os12g07820, orthologous to At4g08390) and monohydroascorbate reductase (Os08g05570, orthologous to
At1g63940) are also presented in both our mitochondrial
samples and the rice plastid proteome (Kleffmann et al.,
2007; Supplemental Table S3).
Glycolytic enzymes are traditionally regarded as
cytosol-abundant proteins. Interestingly, 5% to 10% of
the cytosolic isoforms of each glycolytic enzyme, at
least in Arabidopsis, is associated with the outer
membrane surface of the mitochondrion (Giegé et al.,
2003). It appears that glycolytic enzymes are associated dynamically with mitochondria to support respiration and that substrate channeling restricts the use
of intermediates by competing metabolic pathways
(Graham et al., 2007). In plants, hexokinase is associated with the outer mitochondrial membrane (Dry
et al., 1983; da-Silva et al., 2004; Damari-Weissler et al.,
2006; Kim et al., 2006). In this study, three hexokinases
were identified as mitochondrial proteins (Os01g53930,
Os01g71320, and Os05g44760; Supplemental Table S3).
In animal cells, mitochondrially associated hexokinase
play a pivotal role in the regulation of apoptosis
(Downward, 2003; Birnbaum, 2004; Majewski et al.,
2004). In plants such as Nicotiana benthamiana, a similar
function of mitochondrially associated hexokinases
in the control of programmed cell death has been
reported (Kim et al., 2006), suggesting a link between
Glc metabolism and apoptosis in plant cells. Apart
from hexokinases, however, other glycolytic enzymes,
such as Fru-bisP aldolase (Os01g02880), pyruvate
kinase (Os03g20880), D-3-phosphoglycerate dehydrogenase (Os04g55720), and triosephosphate isomerase
(Os09g36450), were only found in rice mitochondrial
samples before, but not after, FFE purification (Supplemental Table S2A). The separation of glycolytic enzymes from Arabidopsis mitochondria by FFE has also
been observed (Eubel et al., 2007), suggesting that the
FFE process allows a removal of peripherally associated cytosolic proteins from the organelle surface.
The relatively low levels of transcript abundance
observed for the majority of genes in mature leaf tissue
(last four columns in Fig. 6A), with the notable exception of genes encoding subunits of Gly decarboxylase,
are in agreement with previous studies on the expression of genes encoding mitochondrial proteins in
monocots. It has been previously shown that subunits
of Gly decarboxylase were only detectable at the
protein level in older regions of wheat (Triticum
aestivum) leaf tissue (Rogers et al., 1991), while transcripts for mitochondria-encoded genes were abun-
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Huang et al.
dant in the first 1 to 2 cm from the basal meristem but
declined sharply afterward (Topping and Leaver,
1990). The relatively low abundance of transcripts
from genes encoding mitochondrial proteins from
17-d-old rice leaf tissue in the Ribot et al. (2008) data
suggests that a similar pattern occurs for nucleuslocated genes in rice and wheat. In contrast, transcript
abundance from genes encoding subunits of Gly decarboxylase peaked in older leaf tissue of both rice and
wheat. Additionally, four other genes for rice mitochondrial components displayed high levels of expression in mature leaf tissue (Os11g24450, general
dicarboxylate/tricarboxylate carrier; Os05g50840,
probable CoA transporter; Os06g39344, branchedchain amino acid catabolism enzyme enoyl-CoA
hydratase; Os05g49880, TCA cycle enzyme malate dehydrogenase), which suggests a role related to photosynthetic metabolism or mitochondria-chloroplast
interaction. We have already noted increased abundance of malate dehydrogenase and branched-chain
amino acid metabolic machinery in dicot leaf mitochondria (Lee et al., 2008), and plant mitochondrial
dicarboxylate-tricarboxylate carriers have been proposed to play important roles in nitrogen assimilation
and export or import of reducing equivalents to mitochondria in leaves (Picault et al., 2002).
A range of proteins identified that are involved in
aldehyde/alcoholic metabolism might be related to
alcoholic metabolism in rice mitochondria. Ethanolic
fermentation is not only observed in anaerobic plant
tissues but also in aerobic tissues such as anthers
(Tadege et al., 1999). The mechanism and regulation of
aerobic ethanolic fermentation in the anther is still
unclear, but it likely involves a new steady state in
which pyruvate is distributed between PDH and an
aerobic TCA cycle in mitochondria and a cytosolic
fermentation pathway involving ADH and PDC. Our
data suggest that metabolism of pyruvate might be
changed in anther mitochondria by differential expression of PDH complexes and early steps of the TCA
cycle that might coexist with aerobic alcoholic fermentation. The PDH complex is the key entry point of
carbon into the TCA cycle and is considered to be a key
point in regulation, as phosphorylation/dephosphorylation controls its activity. It would be particularly
interesting to investigate whether there are any differences in the kinetics of PDH between pollen and other
tissues that allow low-affinity PDC (Km in approximately millimolar range) and higher affinity PDHs (Km
in approximately micromolar range) to simultaneously
utilize a common pyruvate pool. Aldehyde dehydrogenases (ALDHs) have been reported as major mitochondrial proteins in pea (Pisum sativum) leaves and
roots (Bardel et al., 2002), and two ALDHs were also
observed in the Arabidopsis mitochondrial proteome
(Millar et al., 2001; Heazlewood et al., 2004). In this
study, three abundant rice mitochondrial ALDHs
(Os06g15990, Os02g49720, and Os05g45960) were
found. Os06g15990 and Os02g49720 are orthologs of
rf2a and rf2b, respectively, encoding ALDHs in maize
(Zea mays; Liu and Schnable, 2002). In maize, rf2a is
involved in restoring male fertility to Texas cytoplasmic
male-sterile plants (Cui et al., 1996). The mechanism of
restoration of male fertility in maize by rf2 encoding
ALDH is still unclear. One possible role of rf2-encoded
ALDH is the removal of the products of lipid peroxidation that would be expected to accumulate preferentially in T-cytoplasm cells if these cells produce more
reactive oxygen species than normal cytoplasm cells
(Liu et al., 2001; Moller, 2001b). The mitochondrial
ALDH (Os02g49720) can also be induced in rice seedlings by submergence, having a very similar pattern of
expression to classic anaerobic proteins such as ADH1
and PDC1 (Nakazono et al., 2000). These authors
suggested that induction of mitochondrial ALDH in
rice under submergence might protect mitochondrial
damage by diffused acetaldehyde produced by PDC
during aerobic ethanolic fermentation (Nakazono
et al., 2000). Logically, the restoration of maize male
fertility by mitochondrial ALDH might be partially due
to protection of pollen mitochondria from acetaldehyde during aerobic ethanolic fermentation. There
are also four sex-determination TASSELSEED2-like
proteins (Os07g40250, Os07g46840, Os07g46920, and
Os07g46930) found in our proteome set, which encode
short-chain alcohol dehydrogenases based on annotation. Their maize homolog, TASSELSEED2, is required
for stage-specific floral organ abortion (DeLong et al.,
1993) and can reduce a broad range of substrates tested,
including steroids and dicarbonyl and quinone compounds (Wu et al., 2007). The substrate range of these
rice mitochondrial short-chain alcohol dehydrogenaselike proteins and their potential involvement in alcoholic metabolism in specific rice organs deserve further
investigation. Further exploring the expression and
kinetics of the components of rice mitochondrial pyruvate, aldehyde, and alcohol metabolism identified here
may uncover a key mechanistic basis of cytoplasmic
male sterility.
Thiamine (vitamin B1) synthesis in plants was
thought at one time to be plastid specific (Belanger
et al., 1995), while in yeast it is a mitochondrial process
(Eijssen et al., 2008). It is synthesized through the
convergence of two independent biosynthetic pathways, one that synthesizes 2-methyl-4-amino-5hydroxymethylpyrimidine pyrophosphate to form
the pyrimidine moiety and another that synthesizes
4-methyl-5-(hydroxyethyl) thiazole phosphate to form
the thiazole moiety, but the specific number and identity of the enzymes involved in plants are still unclear.
In Arabidopsis, the product of the thiamine biosynthesis gene (THI1), which catalyzes Gly, NAD+, and a
sulfur donor into hydroxyethylthiazole, is dual targeted to chloroplasts and mitochondria (Chabregas
et al., 2001, 2003). A 4-methyl-5-thiazole monophosphate biosynthesis protein (Os01g11880) that is unrelated to THI1 but is a probable THIJ (catalyzing
phosphorylation of hydroxymethylpyrimidine to hydroxymethylpyrimidine monophosphate in thiamine
biosynthesis) was enriched after FFE purification (ra-
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Rice Mitochondrial Proteome
tio = 0.33) and is predicted as a mitochondrial protein
by three different targeting programs (Supplemental
Table S2). This finding provides further experimental
evidence that plant mitochondria are involved in
thiamine synthesis in plants.
The plant mitochondrial proteome is a changing
entity over time and in different cells and tissues. This
is evident by looking at mitochondria from photosynthetic and nonphotosynthetic plant tissues (Bardel
et al., 2002; Lee et al., 2008) and at the mitochondrial
components in the Arabidopsis proteome map generated from different organs, developmental stages, and
undifferentiated culture cells (Baerenfaller et al., 2008).
The combination of proteome and gene expression on
this scale in rice will greatly benefit our global understanding of the functions of genes for mitochondrial
proteins in particular organ and developmental stages.
Future combinations of data sets focusing on mitochondrial function will allow the common patterns of
expression, and thus putative regulators of mitochondrial biogenesis, stress response, and other aspects of
the nucleus-mitochondria interaction in rice, to be
uncovered.
MATERIALS AND METHODS
Growth of Rice Seedlings
Batches of 200 g of rice (Oryza sativa ‘Amaroo’) seeds were washed in 1%
(v/v) bleach for 10 min, rinsed in distilled water, grown in the dark in
vermiculite trays (30 3 40 cm) at a constant 30°C, and watered daily, and the
shoot tissues were harvested at 10 d for mitochondrial isolation.
Rice Mitochondrial Isolation
Rice mitochondrial isolation was performed by differential centrifugation
followed by Percoll gradients as described by Heazlewood et al. (2003). After
0% to 4.4% (v/v) Percoll gradient centrifugation, the enriched mitochondrial
fractions were washed three times with FFE separation medium (10 mM acetic
acid, 10 mM triethanolamine, 1 mM EDTA, and 280 mM Suc, pH 7.4).
FFE
FFE was performed using the BD FFE system (Becton Dickinson) with a
separation chamber height of 0.5 mm. The separation and counterflow
medium (10 mM acetic acid, 10 mM triethanolamine, 1 mM EDTA, and 280
mM Suc; medium inlets 2–6 and counterflow inlets 1–3) as well as electrode
stabilization medium (100 mM acetic acid, 100 mM triethanolamine, 10 mM
EDTA, and 200 mM Suc; medium inlets 1 and 7) were injected into the
separation chamber at a speed of 200 mL h21. Media for anode and cathode
circuits consisted of 100 mM triethanolamine and 10 mM EDTA, respectively. A
voltage of 600 V was applied. Before the FFE run, the sample (approximately
10 mg protein mL21) was subjected to one stroke in a Potter-Elvehjem
homogenizer. Sample injection speed was 3,000 to 3,500 mL h21 depending
on the sample and the level of contamination. Fractions were collected on
2-mL 96-well plates. The separation chamber was cooled to 5°C, and the
sample and 96-well plates were cooled in an ice bath.
One-Dimensional SDS-PAGE and Immunoblotting
Precast gels with 12% (w/v) acrylamide and 1 mM Tris-HCl (Bio-Rad) were
used for analytical purposes and western blotting. Protein assays (Bradford,
1976) were performed on pooled FFE fractions. Proteins were transferred onto
nitrocellulose membranes and probed with a 1:5,000 dilution of the primary
antibodies mtHSP70:PM003 from Dr. Tom Elthon, Kat2 (Germain et al., 2001),
and RbcS, raised against tobacco (Nicotiana benthamiana) Rubisco in rabbits,
supplied by Dr. Spencer Whitney (Australian National University). Horseradish peroxidase-conjugated secondary antibodies at a dilution of 1:10,000
were used for the chemiluminescent detection of the immune signal.
Two-Dimensional Gel Electrophoresis
Mitochondrial protein samples (700 mg) were extracted by addition of cold
acetone (220°C) to a final concentration of 80% (v/v). Samples were stored at
280°C for 4 h and then centrifuged at 20,000g at 4°C for 15 min. The pellets
were resuspended in IEF sample buffer (7 M urea, 2 M thiourea, 4% [w/v]
CHAPS, and 40 mM Tris, pH 8.5). Aliquots of 450 mL were used to reswell
immobilized pH gradient strips pH3-10 NL (24 cm; GE Healthcare) according
to the manufacturer’s instructions. The strips were run for 24 h in Ettan
IPGphor3 (GE Healthcare) according to the manufacturer’s instruction. The
strips were then transferred to an equilibration buffer (50 mM Tris-HCl [pH
6.8], 4 M urea, 2% [w/v] SDS, 0.001% [w/v] bromphenol blue, and 100 mM
b-mecaptoethanol) and incubated for 20 min at room temperature with
rocking. After a brief wash in 13 gel buffer, the strips were transferred to 12%
acrylamide Gly gels and covered with 1.2% (v/w) agarose in gel buffer.
Second-dimensional gels were run at 50 mA per gel for 6 h. Proteins were
visualized by colloidal Coomassie Brilliant Blue (G250) staining.
DIGE Two-Dimensional IEF/SDS-PAGE
Samples (50 mg) of pre- and post-FFE, as well as 50 mg of a 1:1 mixture of
both samples, were acetone precipitated, resolubilized in lysis buffer (7 M urea,
2 M thiourea, 4% [w/v] CHAPS, and 40 mM Tris base, pH 8.5), and individually
labeled with 400 mM of weight- and pI-matched fluorescent dyes Cy2, Cy3,
and Cy5 (GE Healthcare). Samples were then combined and separated on IEF
strips pH3-10NL (24 cm; GE Healthcare) according to the manufacturer’s
instructions. After first dimension running, the strips were then transferred to
an equilibration buffer consisting of 50 mM Tris-HCl (pH 6.8), 4 M urea, 2% (w/v)
SDS, 0.001% (w/v) bromphenol blue, and 100 mM b-mecaptoethanol and
incubated for 20 min at room temperature with rocking. After a brief wash in 13
gel buffer, the strips were transferred to 12% (w/v) acrylamide Gly gels and
covered with 1.2% agarose in gel buffer. Second dimensional gels were run at
50 mA per gel for 6 h. Proteins were visualized on a Typhoon laser scanner
(GE Healthcare), and image comparison was performed using the DECYDER
software package (version 6.5; GE Healthcare). Three independent experiments
were performed, and each of the resulting three gel sets was first analyzed using
differential in-gel analysis mode DECYDER prior to a comprehensive biological variance analysis including all three gel sets. Gel spots were filtered
according to their presence and average abundance ratio. Gel images were
electronically overlaid using ImageQuant TL software (GE Healthcare).
Analysis of Peptides from In-Gel-Digested
Protein Samples
Protein samples to be analyzed were cut from the gels and were in-gel
digested according to the method described by Taylor et al. (2005). Samples
were then dried in a vacuum centrifuge, resuspended in 5% (v/v) acetonitrile
and 0.1% (v/v) formic acid, and analyzed on an Agilent XCT Ultra Ion Trap
mass spectrometer (Agilent Technologies) according to Meyer et al. (2007).
Resulting MS/MS-derived spectra were analyzed against an in-house rice
database (release 5; Rice_osa5) of The Institute for Genomic Research Rice
Pseudomolecules and Genome Annotation and mitochondrial and plastid
protein sets (combined database contained 66,874 sequences and 29,957,714
residues). The database was searched using the Mascot search engine version
2.2.03 and utilizing error tolerances of 61.2 D for MS and 60.6 D for MS/MS,
Max Missed Cleavages set to 1, with variable modification of oxidation (M) and
carbamidomethyl (C), instrument set to ESI-TRAP, and peptide charge set at 2+
and 3+. RICE-ALL.pep is a nonredundant database with systematically named
protein sequences based on rice genome sequencing and annotation. Results
were filtered using standard scoring, maximum number of hits set to AUTO, and
ion score cutoff at 37. The significance threshold P # 0.05 and Require Bold Red
were also set. In order to estimate the false-positive rate of this protein strategy, a
single concatenated file was generated by MASCAT (Agilent Technologies) that
comprised all of the MS/MS output data. The concatenated file was then used to
search against Rice_osa5 (target), reversed (decoy), and randomized (decoy)
databases using the above search strategy. The false-positive rate in target-decoy
searches was found to be 4.7% for peptides with ion scores . 37, which was
calculated using the equation described previously (Elias et al., 2005).
Plant Physiol. Vol. 149, 2009
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Copyright © 2009 American Society of Plant Biologists. All rights reserved.
Huang et al.
Analysis of Peptides from Whole Organelle Digests
Whole organelle protein extracts were digested overnight at 37°C in the
presence of trypsin, and insoluble components were removed by centrifugation at 20,000g for 5 min. Samples were analyzed on an Agilent 6510 Q-TOF
mass spectrometer with an HPLC Chip Cube source (Agilent Technologies).
The chip consisted of a 40-nL enrichment column (Zorbax 300SB-C18; 5-mm
pore size) and a 150-mm separation column (Zorbax 300SB-C18; 5-mm pore
size) driven by the Agilent Technologies 1100 series nano/capillary liquid
chromatography system. Both systems were controlled by MassHunter
Workstation Data Acquisition for Q-TOF (version B.01.02, Build 65.4, Patches
1,2,3,4; Agilent Technologies). Peptides were loaded onto the trapping column
at 4 mL min21 in 5% (v/v) acetonitrile and 0.1% (v/v) formic acid with the chip
switched to enrichment and using the capillary pump. The chip was then
switched to separation, and peptides eluted during a 1-h gradient (5% [v/v]
acetonitrile to 40% [v/v] acetonitrile) directly into the mass spectrometer. The
mass spectrometer was run in positive ion mode, and MS scans were run over
a mass-to-charge ratio range of 275 to 1,500 and at four spectra per second.
Precursor ions were selected for auto MS/MS at an absolute threshold of 500
and a relative threshold of 0.01, with maximum three precursors per cycle, and
active exclusion set at two spectra and released after 1 min. Precursor chargestate selection and preference was set to 2+ and then 3+, and precursors were
selected by charge and then abundance. Resulting MS/MS spectra were
opened in MassHunter Workstation Qualitative Analysis (version B.01.02,
Build 1.2.122.1, Patches 3; Agilent Technologies), and MS/MS compounds
were detected by Find Auto MS/MS using default settings. The resulting
compounds were then exported as mzdata files, which when appropriate
were combined using mzdata Combinator version 1.0.4 (West Australian Centre of Excellence in Computational Systems Biology; http://www.
plantenergy.uwa.edu.au/wacecsb/software.shtml). Searches were conducted
using Mascot Search Engine version 2.2.03 (Matrix Science) with mass error
tolerances of 6100 ppm for MS and 60.5 D for MS/MS, maximum missed
cleavages set to 1, with variable modification of oxidation (M) and carbamidomethyl (C), instrument set to ESI-QUAD-TOF, and peptide charge set at 2+
and 3+. Results were filtered using mudpit scoring, maximum number of hits
set to 400, and ion score cutoff at 20. The significance threshold P # 0.05 and
Require Bold Red were also set. The false-positive peptide identification rate
under the matching criteria described above was estimated at 1.5%. The total
number of times each protein was identified after FFE purification using nongel-based methods in four independent runs is listed in the Supplemental
Table S4, with the removed contaminants listed in Supplemental Table S2B.
GSE7256). All data were MAS5.0 normalized and normalized against average
ubiquitin expression for that array. These normalized array data were then
compiled together, and for each probe set the maximum expression was set to
1.0, with all other data relative to this. This normalization allowed crosscomparison of arrays from all of the different studies at once. The arrays
analyzed included all arrays from this study together with publicly available
rice genome arrays carried out from different tissues/conditions. Hierarchical
clustering across all of the arrays was carried out with average linkage
clustering based on Euclidian distance using Partek Genomics suite software,
version 6.3 (Supplemental Table S5).
Supplemental Data
The following materials are available in the online version of this article.
Supplemental Figure S1. Separation of Percoll-purified mitochondria
from rice shoots by FFE into 96 fractions.
Supplemental Figure S2. Coomassie Brilliant Blue-stained IEF/SDSPAGE separation of rice mitochondrial proteins (pI = 3–10) and number
of protein spots for analysis in Supplemental Table S1.
Supplemental Figure S3. Hierarchical clustering of the expression on
nuclear genes encoding rice mitochondrial proteins based on their
functional classification.
Supplemental Table S1. Identification of proteins from FFE-purified rice
mitochondria using MS/MS after separation of proteins by IEF/SDSPAGE.
Supplemental Table S2. Proteins removed as contaminants in rice mitochondrial preparations.
Supplemental Table S3. Final list of proteins classified as rice mitochondrial proteins.
Supplemental Table S4. Total protein identifications found by four independent non-gel-based LC runs after FFE purification of rice mitochondria
Supplemental Table S5. Hierarchical clustering of all arrays using average
linkage clustering based on Euclidian distance, which was used to
generate Figure 6.
Received October 15, 2008; accepted November 12, 2008; published November
14, 2008.
Rice Germination Microarray Analysis and Comparison
with Public Rice Microarray Data
LITERATURE CITED
Dehulled, sterilized rice seeds were grown under aerobic conditions in the
dark at 30°C as described previously (Howell et al., 2006). RNA isolation,
cDNA synthesis, and quantitative reverse transcription-PCR were conducted
according to methods described previously (Howell et al., 2006). Transcriptomic analysis was performed using Affymetrix GeneChip Rice Genome
Arrays (Affymetrix), and three biological replicates were analyzed for each
time point. Preparation of labeled copy RNA from 2 to 3 mg of total RNA,
target hybridization, as well as washing, staining, and scanning of the arrays
were carried out exactly as described in the Affymetrix GeneChip Expression
Analysis Technical Manual, using the Affymetrix One-Cycle Target Labeling
and Control Reagents, an Affymetrix GeneChip Hybridization Oven 640, an
Affymetrix Fluidics Station 450, and an Affymetrix GeneChip Scanner 3000 7G
at the appropriate steps. Data quality was assessed using GCOS 1.4 (Affymetrix) before CEL files were imported into Avadis 4.3 (Strand Genomics) for
further analysis. Raw intensity data were initially normalized using the MAS5
algorithm allowing probe identifiers called present to be determined. Only
those probe sets that were called present in at least two of three replicates in
at least one time point were included for further analysis. Ambiguous probe
sets and bacterial controls were also removed, resulting in a final data set of
24,150 probe sets. All microarray data have been deposited in the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) under accession
code E-MEXP-1766.
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