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Plant Physiol. 2008 Dec; 148(4): 1809–1829.
PMCID: PMC2593673

Novel Proteins, Putative Membrane Transporters, and an Integrated Metabolic Network Are Revealed by Quantitative Proteomic Analysis of Arabidopsis Cell Culture Peroxisomes1,[W][OA]


Peroxisomes play key roles in energy metabolism, cell signaling, and plant development. A better understanding of these important functions will be achieved with a more complete definition of the peroxisome proteome. The isolation of peroxisomes and their separation from mitochondria and other major membrane systems have been significant challenges in the Arabidopsis (Arabidopsis thaliana) model system. In this study, we present new data on the Arabidopsis peroxisome proteome obtained using two new technical advances that have not previously been applied to studies of plant peroxisomes. First, we followed density gradient centrifugation with free-flow electrophoresis to improve the separation of peroxisomes from mitochondria. Second, we used quantitative proteomics to identify proteins enriched in the peroxisome fractions relative to mitochondrial fractions. We provide evidence for peroxisomal localization of 89 proteins, 36 of which have not previously been identified in other analyses of Arabidopsis peroxisomes. Chimeric green fluorescent protein constructs of 35 proteins have been used to confirm their localization in peroxisomes or to identify endoplasmic reticulum contaminants. The distribution of many of these peroxisomal proteins between soluble, membrane-associated, and integral membrane locations has also been determined. This core peroxisomal proteome from nonphotosynthetic cultured cells contains a proportion of proteins that cannot be predicted to be peroxisomal due to the lack of recognizable peroxisomal targeting sequence 1 (PTS1) or PTS2 signals. Proteins identified are likely to be components in peroxisome biogenesis, β-oxidation for fatty acid degradation and hormone biosynthesis, photorespiration, and metabolite transport. A considerable number of the proteins found in peroxisomes have no known function, and potential roles of these proteins in peroxisomal metabolism are discussed. This is aided by a metabolic network analysis that reveals a tight integration of functions and highlights specific metabolite nodes that most probably represent entry and exit metabolites that could require transport across the peroxisomal membrane.

Within the plant cell, energy metabolism is mainly distributed among three distinct organelles: plastids, mitochondria, and peroxisomes. Although the proteomes of both plastids and mitochondria have been investigated extensively, comparatively little systematic analysis of the protein content of plant peroxisomes has been undertaken. The main obstacle for proteomics of plant peroxisomes is the availability of purified organelles from model plants that are also amenable to mass spectrometry (MS)-based identification by matching to protein sequence data. Whereas the preparation of peroxisomes in sufficient amounts and purity from spinach (Spinacia oleracea), cucumber (Cucumis sativus), pea (Pisum sativum), and soybean (Glycine max) for proteomic purposes is possible (Schwitzguebel and Siegenthaler, 1984; Corpas et al., 1994; Lopez-Huertas et al., 1999; Arai et al., 2008), the purification of peroxisomes from Arabidopsis (Arabidopsis thaliana) has proved to be extremely difficult due to the low yield of intact organelles and contamination with other cell organelles. This complicates data analysis and compromises confidence in the subcellular localization of the identified proteins. So far, three studies in Arabidopsis have been reported, using greening (Fukao et al., 2002) or etiolated (Fukao et al., 2003) cotyledons or mature plant leaves (Reumann et al., 2007), each using different purification methods. In these studies, 42 putatively peroxisomal proteins were identified from cotyledons and 78 from leaves, but the overlap between the sets from both tissues was only 11 proteins.

The protein composition of peroxisomes from different tissues is likely to vary significantly as the function of these organelles changes. Therefore, a full understanding of peroxisomal function requires experimental analysis of these organelles from a variety of plant organs during different developmental stages. Peroxisomes in seedlings of oilseed plants such as Arabidopsis are mainly involved in the breakdown of fatty acids derived from storage triacylglycerols via β-oxidation during germination prior to the initiation of photosynthesis (Graham and Eastmond, 2002). Most of the acetyl-CoA generated by fatty acid β-oxidation is fed into the glyoxylate cycle to produce succinate, which may then be exported out of the organelles or used as a precursor for other metabolites and processes such as gluconeogenesis (Eastmond and Graham, 2001). Leaf peroxisomes too perform β-oxidation; however, this usually happens at a lower rate and is also involved in the production of signaling compounds and hormones such as jasmonic acid (JA) and in the conversion of indole-3-butyric acid (IBA) into indole-3-acetic acid. A major role of peroxisomes in leaf tissue is in photorespiration by oxidation of glycolate derived from the oxygenase reaction of Rubisco to make substrates for mitochondria and the reduction of Ser to glycerate for the return of carbon intermediates to the Calvin cycle (Raghavendra et al., 1998). Peroxisomes in senescing tissue are multifunctional organelles involved in the degradation of cellular constituents, including fatty acids and the remobilization of nitrogen into ureides (Vicentini and Matile, 1993). The transition from one form to another is mediated by a change in the protein content of existing organelles rather than by a degradation and de novo synthesis of organelles (Hayashi et al., 2000). Apart from the above-mentioned functions, plant peroxisomes are also involved in nitrogen metabolism in root nodule cells, amino acid and ureide metabolism, and the degradation of hydrogen peroxide produced during a number of their catalytic functions (Hayashi and Nishimura, 2006).

The size of the peroxisomal proteome is unknown, but it is probably substantially smaller than the thousands of proteins found in the endosymbiont-derived mitochondria and chloroplasts. Peroxisomes lack genetic material and therefore do not require proteins involved in genome replication, transcription, maturation of transcripts, or translation. However, due to the diversity of the plant-specific roles of these organelles, the proteome of the plant peroxisome may well be larger than that of its mammalian or fungal counterparts (Emanuelsson et al., 2003). All peroxisomal proteins are imported posttranslationally into the organelle and therefore require some form of targeting recognition sequence or secondary structure.

Matrix proteins can be directed to the peroxisomes by one of two types of peroxisomal targeting signals (PTSs). PTS1 signals consist of three amino acids at the C terminus of a peroxisomal protein. Although a considerable amount of variation in the PTS1 sequence exists, it usually consists of a small amino acid residue, followed by a basic one, and then a hydrophobic residue, and it is not cleaved off after import. SKL is a typical PTS1 sequence. PTS2 sequences are composed of nine amino acids located at the N terminus of peroxisomal proteins and are removed after import into the organelle. RLx5HL and RIx5HL are typical PTS2 sequences. Searches for peroxisome targeting signals within the protein-coding regions of the Arabidopsis genome have identified 256 to 280 proteins containing putative PTS signals (Kamada et al., 2003; Reumann et al., 2004). However, not all matrix proteins found experimentally in peroxisomes contain these known PTS signals. Recently, the presence of a novel PTS1 in an enoyl-CoA hydratase involved in the β-oxidation of cis-unsaturated fatty acids was described (Ser-Ser-Leu; Goepfert et al., 2006), which was recently confirmed by a study of the leaf peroxisomal proteome (Reumann et al., 2007). Other peroxisomal proteins seem to lack conventional PTS sequences at the N or C terminus but possess internal sequences serving as targeting signals. The most prominent example is catalase, which possesses an internal, PTS1-like targeting sequence (Kamigaki et al., 2003) but is not recognized for import by the normal PTS1 mechanism (Oshima et al., 2008).

Peroxisomal membrane proteins (PMPs) do not possess PTS1 or PTS2 sequences. Instead, they contain a stretch of positively charged amino acids that is usually flanked by transmembrane domains. Sometimes, this sequence is referred to as a membrane PTS (mPTS). However, it is not as conserved as conventional PTS1 and PTS2 sequences, and the definition of a consensus sequence for membrane targeting of peroxisomal proteins is difficult (Trelease, 2002). In general, two import pathways for proteins destined for the peroxisomal membrane are discussed. In the first model, proteins are synthesized in the cytosol and subsequently directly inserted into the peroxisomal membrane and are usually said to have a mPTS type 1 (mPTS1). Alternatively, proteins can be synthesized on rough endoplasmic reticulum (ER) and inserted cotranslationally into the ER membrane. Vesicles containing these proteins then bud from the ER and fuse with the peroxisomal membrane. In addition to the mPTS1 sequence, these proteins also contain an ER sorting signal, and the combination of both the mPTS1 and the ER signal is referred to as mPTS2. The finding that peroxisomal membrane proteins such as ascorbate peroxidase (APX) and the peroxins PEX10 and PEX16 are transferred to the peroxisomes via the ER led to the formulation of the “ER semiautonomous peroxisome maturation and replication” model (for review, see Mullen and Trelease, 2006). It uses the largely contradictory models of autonomous organelles and purely ER-derived peroxisomes and combines them. According to the semiautonomous maturation model, peroxisomes can be derived by budding from the ER but also by fission of existing organelles.

In a bid to better experimentally define the soluble and membrane proteome of peroxisomes in Arabidopsis, we have combined conventional centrifugation-based organelle isolation techniques with free-flow electrophoresis (FFE), which has already been successfully applied to the isolation of other organelles in plants (Bardy et al., 1998; Eubel et al., 2007) and peroxisomes in mammals (Volkl et al., 1997). As this technique employs surface charge rather than the size or density of particles as a separating parameter, it represents a true additional dimension in the purification process and can lead to organellar fractions of greater purity. Peroxisomal proteins were analyzed by MS and nonperoxisomal proteins were excluded by quantitative comparison between highly purified peroxisomal samples and other cellular fractions. Where needed, organellar localization was also confirmed by chimeric fluorescent protein visualization. A metabolic mapping approach was adopted to gauge the completeness of this peroxisomal proteome and, therefore, our understanding of the biochemical processes taking place within it and the biogenesis of this organelle.


FFE Separation of Organelles to Purify Arabidopsis Peroxisomes

An organellar fraction consisting mainly of mitochondria and peroxisomes was obtained from disrupted Arabidopsis protoplasts using differential centrifugation and density gradient purification. FFE was then employed to separate peroxisomes from the bulk of mitochondrial material. We have demonstrated previously that FFE is able to increase the purity of mitochondrial isolates by separating them from plastids and peroxisomes according to differences in the surface charge of each organelle, yielding mitochondria that have seven times less contamination (Eubel et al., 2007). Under the conditions applied, mitochondria, peroxisomes, and other cellular material migrated close together in FFE, but with different degrees of overlap (Eubel et al., 2007). The electrophoretic mobility of peroxisomes was lower than that of mitochondria at 600 V (Fig. 1A). In order to optimize FFE for the isolation of Arabidopsis peroxisomes, a higher voltage (800 V) was applied to increase the separation between the mitochondrial and peroxisomal fraction peaks (Fig. 1B). The distribution of mitochondria and peroxisomes was monitored using immunodetection of marker proteins. At 600 V, the mitochondrial fraction marker protein, HSP70, peaked in fraction 44, while the peroxisomal marker, KAT2, peaked in fraction 48, but the distributions were overlapping. By expanding the distributions at 800 V, both mitochondrial and peroxisomal signals moved further toward anodic fractions, revealing two mitochondrial subpopulations with different electrophoretic mobilities peaking between fractions 21 to 23 and fractions 29 to 31. Meanwhile, the peak fractions enriched in peroxisomes were nearly 10 fractions away, in fractions 39 to 45, and devoid of visible mitochondrial contamination. While this higher voltage did tend to lead to greater losses of KAT2 signal into the anodic mitochondrial fractions than was apparent at 600 V (Fig. 1A), the displacement of the bulk of mitochondria from peroxisomes was optimal for the preparation of peroxisomes. Using this approach, peroxisomal and mitochondrial samples with only minimal amounts of contamination were obtained by selecting the central three fractions of each distribution at 800 V to ensure the best compromise between yield and purity. In order to produce a highly enriched mitochondrial sample for comparative functional assays against the peroxisomal fraction, the mitochondria were then subjected to another round of FFE at 600 V (i.e. repeating the separation in Fig. 1A) to separate them from contaminating plastids, which migrated into the left border of the separation chamber and therefore were not resolved well from the mitochondria at 800 V (data not shown).

Figure 1.
Quantification of protein content from 1D SDS-PAGE and immunoblots of every second of the central 30 fractions collected after FFE separation at 600 V (A) and 800 V (B). Relative protein quantity is displayed as the percentage of the fraction with the ...

Measurement of catalase activity as a marker for peroxisomes gave an oxygen production rate of 60 μmol min−1 in pre-FFE organelle pellets (Supplemental Table S1A), which was approximately 20% of total cellular extract activity. Total catalase activity was approximately 15 μmol min−1 in the FFE-purified peroxisome fraction, which is approximately 23% of the activity in pre-FFE organelle pellets and approximately 4% of total cellular extract activity. This degree of recovery is similar to that shown in preparations of leaf peroxisomes from Arabidopsis when following hydroxypyruvate reductase activity (Reumann et al., 2007). To quantify the difference between mitochondrial and peroxisome fractions, catalase and succinate dehydrogenase activities were measured as marker enzymes (Supplemental Table S1A). The specific activity of catalase was much higher in the putative peroxisomal fraction than in the pre-FFE or mitochondrial sample, indicating clear enrichment of peroxisomes in this fraction. At the same time, the specific activity of succinate dehydrogenase in the putative peroxisomal fraction was only approximately 8% of that measured in the mitochondrial sample.

Coomassie Brilliant Blue-stained SDS gel lanes of a pre-FFE organellar sample compared with post-FFE samples of pooled peroxisomes and mitochondria fractions are shown in Figure 1C. While the banding pattern of the pre-FFE sample was very similar to that of the mitochondrial fraction, the putative peroxisomes displayed a distinct pattern with very little resemblance to the other two samples. Therefore, we concluded that the pre-FFE fraction contained mostly mitochondria and only a limited proportion of other organelles, whereas the putative peroxisomal fraction was largely free of mitochondrial proteins. Abundant protein bands present in the mitochondrial and peroxisomal samples were excised from one-dimensional (1D) gels for identification by MS (Fig. 1C, annotations on gel lanes). The primary protein identification for each spot is summarized in Supplemental Table S1B, supporting these as purified mitochondrial and peroxisomal fractions derived from FFE. Subsequent quantitative proteomic analysis (see below) allowed the quantification of a series of classical peroxisomal and mitochondrial markers between the two fractions. This shows an average ratio of 0.14 for mitochondrial proteins in the peroxisomal compared with the mitochondrial samples and approximately 70-fold enrichment for peroxisomal proteins in the peroxisomal compared with mitochondrial samples (Fig. 1D). In general agreement, the succinate dehydrogenase specific activity in the peroxisomes was one-twelfth of that in the mitochondrial sample (18 ± 1 versus 231 ± 45 nmol O2 min−1 mg−1 protein), and the catalase specific activity was approximately 30-fold higher in the peroxisome sample (13.7 ± 1.7 versus 513 ± 181 nmol O2 min−1 mg−1 protein; Supplemental Table S1A). Based on these specific activity measurements and protein ratios, we estimated the approximate peroxisome purity as 85% to 90%. This is based on mitochondria being the largest contaminant in the peroxisome preparations and this mitochondrial contamination being 8% to 14% (based on Fig. 1D and Supplemental Table S1A). Also, the catalase specific activity in the mitochondrial fraction is only 3% of that in the peroxisome fraction, so the at least approximately 30-fold increase in catalase and other peroxisome markers indicates that approximately 90% of the protein in the peroxisome fraction should be of peroxisomal origin.

Whole Peroxisome Protein Profiling

An in-depth analysis of the proteins in each fraction was obtained by two-dimensional differential in gel electrophoresis isoelectric focusing (DIGE 2D IEF/SDS-PAGE) using three independent peroxisomes and mitochondria preparations. Figure 2 shows the false-colored spot intensity maps for both organelle fractions (top) as well as a superimposition of the two spot maps for one of the three gel sets. The amount of overlap between the two samples is low, and two clearly distinct patterns can be observed. While the mitochondrial pattern is focused around pI values between 5 and 8 and resembles that of a previously published study using the same material (Millar et al., 2001), the distribution of the peroxisomal pattern is heavily skewed toward the basic side of the pI spectrum. This shift to basic pI can also be observed on 2D gels of leaf peroxisome proteins (Reumann et al., 2007). Many peroxisome protein spots of high abundance have very high pI values, and a considerable number did not even reach their pI on the pH 3 to 10 nonlinear immobilized pH gradient strips but migrated right to the cathode. The basic nature of many peroxisome proteins may be related to the typically alkaline nature (pH 8–8.5) of the peroxisome lumen (van Roermund et al., 2004). Quantification of mitochondrial and peroxisomal spot intensities from all three gel sets was performed using the DeCyder software package (GE Healthcare). In total, 1,019 matched spots were found consistently across the three sets. Spots with P ≤ 0.05 and an average ratio of 2 or greater (mitochondria-peroxisomes) were designated as mitochondrial, and those with an average ratio of 2 or greater (peroxisomes-mitochondria) were designated as peroxisomal. On average, the peroxisome-mitochondria ratio was approximately 37 for selected putative peroxisomal protein spots, while the average mitochondria-peroxisome ratio was approximately 5 for selected putative mitochondrial protein spots. Spots from a preparative gel were matched with those on the DIGE gels. Prominent peroxisomal and mitochondrial spots matched to the DIGE gels (Supplemental Fig. S1) were excised for tandem mass spectrometry (MS/MS) identification. In total, 136 unique proteins were identified from this gel (Supplemental Table S2).

Figure 2.
DIGE 2D IEF/SDS-PAGE of peroxisomal (labeled with Cy5; shown in green) and mitochondrial (labeled with Cy3; shown in red) protein composition. Top, Gel images as derived from the Typhoon Trio (GE Healthcare) fluorescence scanner, analyzed with the DeCyder ...

As a complement to the gel-based approaches, reverse-phase HPLC separation coupled with MS/MS was used to gain additional depth in the whole peroxisome proteome. Four 60-min Intelligent Data-Dependent Acquisition (IDDA) runs of the same sample were conducted in series, with peptides identified in each run subsequently excluded from MS/MS acquisition in the next run. This analysis was performed on the same peroxisomal sample used for the 2D gels containing 8% to 10% mitochondria (high purity) and also on a second sample containing twice the amount of mitochondrial contamination (21%; low purity) as deduced from the respiratory assays. In cases in which a protein was identified in both samples, the comparison of (1) the emPAI values (which is the exponentially modified ratio of the observed peptides over the number of peptides that can theoretically be observed) and (2) the difference in a protein's MOWSE score between the samples was taken as a semiquantitative indicator for localization of a protein. Proteins with a higher emPAI value or a higher MOWSE score in the high-purity sample are putative peroxisomal proteins, and those that produced higher values in the low-purity sample are putative contaminants. In cases in which a protein was identified in only the high-purity sample, this has been considered to be an indication of a higher abundance of the protein in that sample. A total of 135 proteins were identified in the high-purity sample and 209 in the low-purity sample, with an overlap of 93 between both fractions (Supplemental Table S4). DIGE and the MS-derived quantitative data (emPAI and MOWSE difference measures) form an important part of our final assessment of the peroxisomal proteome (see below). Sequence information for proteins identified by only a single but significant peptide is given in Supplemental Data Set S2.

Peroxisomal Membrane Protein Profiling

Three suborganellar fractions were prepared from whole peroxisomes by repeated freeze/thaw cycles, followed by centrifugation in order to separate soluble and membrane proteins. Isolation of integral membrane proteins was achieved by sodium bicarbonate stripping of an aliquot of the membrane proteins. A total of 40 μg of protein from the soluble and complete membrane fractions was separated by 1D SDS-PAGE, whereas only 5 μg could be loaded from the integral membrane fraction due to the limited amount of material available. The gel reveals distinct differences in the protein banding patterns between the peroxisomal subfractions (Fig. 3). Based on the protein quantitation (data not shown), we estimate that the integral proteins account for about 5% of the whole membrane fraction protein content. Spots from the bands indicated in Figure 3 were excised, digested, and analyzed by liquid chromatography (LC)-MS/MS. From 65 gel bands, a total of 94 unique proteins were identified using this approach (Supplemental Table S3A). Double SDS-PAGE (dSDS-PAGE) separation of 50 μg of the membrane fraction and 5 μg of the integral membrane fraction was also performed (Supplemental Fig. S2). The dSDS gel system has an increased resolution compared with conventional SDS-PAGE because proteins are separated not only by size but also, to a limited extent, by their hydrophobicity (Meyer et al., 2008). Therefore, it is well suited for the separation of membrane proteins. A set of 49 spots from both gels were cut out, and the identities of 68 proteins were derived from tandem MS analysis (Supplemental Table S3B). Unfortunately, a DIGE approach was not feasible for quantification of the membrane proteins in these two approaches. This is due to the limited resolution inherent to SDS-PAGE gels compared with IEF/SDS-PAGE, which often leads to the identification of more than one protein in a band. Therefore, even if the quantitative analysis of a 1D DIGE gel could indicate a difference in protein abundance, it would be impossible to determine the protein responsible for the change. To complement the 1D and 2D SDS gels, a carbonate-stripped membrane sample of the high-purity peroxisomal fraction was also analyzed by IDDA-MS/MS for the detection of further integral membrane proteins. This analysis resulted in the identification of 89 proteins (Supplemental Table S5). We also used a phosphopeptide enrichment strategy from organelle peptide preparations to identify phosphopeptides from peroxisome proteins; the one significant match was a Ser phosphopeptide for one of the membrane proteins, PMP38 (At2g39970), at Ser-155 (Supplemental Data Set S3).

Figure 3.
SDS-PAGE separation of 40 μg of peroxisomal membrane protein (A), 5 μg of integral membrane protein (B), and 40 μg of soluble protein (C) fractions. Molecular masses in kD are shown at left of each lane, and band numbers extracted ...

Confirmation of Localization by GFP-Targeting Experiments

Several hundred unique proteins were identified in the analyses noted above. While the quantitative proteomics data provided evidence to validate or invalidate peroxisomal location in many cases, a selection of proteins for which this analysis was not clear was further verified in vivo on the basis of the transient expression of fluorescent fusion proteins. For this purpose, proteins carrying a GFP5 insertion 10 to 13 amino acids from their C terminus, to allow targeting by N- and C-terminal sequences and the influence of the mature protein sequence on targeting (Tian et al., 2004), were compared with red fluorescent protein (RFP) fused to the 10 C-terminal amino acids of the PTS1-containing pumpkin (Cucurbita maxima) malate synthase. Four proteins (At1g54340, At3g12800, At4g05530, and At4g14430) were used as controls. These were found by our MS analysis and had each previously been documented to be in leaf peroxisomes by GFP and MS (Reumann et al., 2007; Table I). As our GFP data were completely convergent with these localizations, a range of additional proteins were selected for analysis (Supplemental Data Set S1). This list does not include all of the proteins with ambiguous localization data; rather, it merely focuses on those for which clarification, in our view, would be most beneficial.

Table I.
Nonredundant list of proteins found in peroxisomes after removal of contaminants based on quantification

For four of these proteins (At5g11520, At1g65520, At1g49670, and At5g27520), the GFP localization confirmed peroxisomal location, and no previous GFP data have been reported, to our knowledge. Three of them have recognizable PTS1 and PTS2 sequences, while At5g27520 lacks a recognizable PTS and appears to be a six-transmembrane domain carrier family protein (Fig. 4A). Accordingly, the fluorescence of the At5g27520-GFP construct appears ring like, surrounding the matrix-targeted RFP-SRL.

Figure 4.
Fluorescence images of subcellular localization of selected proteins found in peroxisome preparations by transient expression of internal GFP fusions. A, Localization of membrane carrier protein At5g27520 in an Arabidopsis cultured cell. B, Localization ...

Five targets had been previously reported to localize GFP to other cell compartments (At3g02360, cytosol [Reumann et al., 2007]; At5g42020, ER [Kim et al., 2001]; At4g29130, mitochondria [Damari-Weissler et al., 2007]; At5g58070, vacuole [Jaquinod et al., 2007]; and At4g16210, unclear [Cutler et al., 2000]). However, these earlier reports had used terminal GFP fusions, which frequently localize differentially depending on the terminus to which GFP is fused (Simpson et al., 2001). For example, At3g02360 is localized solely to the cytosol when the whole protein is fused to the C terminus of enhanced yellow fluorescent protein (Reumann et al., 2007) but is found to be present in peroxisomes by internal GFP fusion of the whole protein (Fig. 4B). The other reported locations were confirmed, except for At5g58070, which did not allow for a confident positive assignment of location based on the internal fusion (data not shown).

A set of 14 other proteins analyzed by internal GFP fusion to supplement quantitative proteomic data (At1g02930, At1g07920, At1g44575, At1g44820, At2g16060, At1g77120, At2g17265, At3g52190, At4g00390, At4g29130, At5g19760, At5g43190, At5g43940, and At5g46710) could not be assigned to peroxisomes by GFP and are most likely mitochondrial, cytosolic, plastidic, nuclear, or vacuolar contaminants (Supplemental Data Set S1).

Identification of ER Proteins

Within our list of identified proteins, 14 appeared to be major ER proteins (Table II). These proteins were considered to be of special interest, as connections between the ER and the peroxisomes in relation to peroxisomal protein import have been reported previously (Elgersma et al., 1997; Flynn et al., 2005; Karnik and Trelease, 2005). One of the proteins detected was calreticulin. The distribution of calreticulin across the 800-V separations used for peroxisomal purification reveals enrichment of the antibody signal in the same lanes as the peroxisomes (Fig. 5A), indicating either the comigration of ER components with peroxisomes during FFE or the presence of calreticulin in these organelles. Analysis of the DIGE 2D IEF/SDS-PAGE data revealed that many of the ER proteins reported in Table II, including three isoforms of calreticulin, were enriched in the peroxisome sample relative to the mitochondrial sample (Fig. 5B), consistent with the enrichment in peroxisomal fractions seen with the calreticulin antibodies (Fig. 5A).

Table II.
Nonredundant list of probable ER proteins found in peroxisomal samples but removed on the basis of our GFP data (Supplemental Data Set S1) and previous proteomics reports on ER samples
Figure 5.
Enrichment of ER proteins in peroxisome fractions in vitro, and fluorescence-based evidence for association of ER and peroxisomes in planta. A, Immunoblots of every second of the central 30 fractions collected after FFE separation at 800 V showing distribution ...

Eleven of the 14 proteins suspected to be ER proteins (At1g08450, At1g09210, At1g21750, At1g56340, At2g47470, At4g15955, At4g24190, At5g28540, At5g42020, At5g60640, and At5g61790) were analyzed by internal GFP fusions. Besides their obvious ER location, none of them could be positively localized to peroxisomes (Table II; Supplemental Data Set S1). However, it became apparent from the analysis of the fluorescent images that some sort of interaction between the ER and the peroxisomes might exist. Frequently, peroxisomes appear to be heavily embedded in the ER, with the fluorescence intensity peaking at the ER-peroxisome border (e.g. calreticulin, BIP, and protein disulfide isomerase; Fig. 5C), but so far it is unclear whether this is a result of a higher ER density in this area or a higher concentration of the fusion protein.

Assembling the Data to Define a Peroxisomal Proteome

To ensure maximum depth in protein analysis, multiple strategies employing gel and nongel separation of proteins and peptides were used in our analysis. Quantitative or semiquantitative measurement of the abundance of proteins was obtained using DIGE fluorescence measurements from highly purified peroxisome versus purified mitochondrial samples and the ratio of MOWSE scores, or emPAI (Ishihama et al., 2005), in the nongel LC-MS/MS experiments of high-purity peroxisomal versus low-purity peroxisomal samples. These provided data to discriminate peroxisomal proteins from potential contaminants. Altogether, 250 unique proteins were identified in the course of this study. All of them were assessed by a series of factors to define the final proteome set. These include the quantitative data generated in this study, our and other GFP data, as well as previous reports of subcellular localization from other proteome studies. Additionally, all proteins identified from gels and the liquid phase analysis were examined for the presence or absence of known PTS1 and PTS2 sequences according to the AraPerox database (Reumann et al., 2004). In light of these data, we have classified 89 of these proteins as of peroxisomal origin (Table I) and 14 as ER proteins that copurify with peroxisomes (Table II). Subfractionation of the organelles to soluble, peripheral membrane and integral membrane fractions provided suborganelle location information.

Hydrophobic proteins are notoriously underrepresented in proteome studies using 2D IEF-SDS approaches. To determine our success rate in the identification of hydrophobic proteins, we used the ARAMEMNON database (Schwacke et al., 2003; release 5.0) to predict transmembrane domains in the set of 89 peroxisomal proteins; 16 proteins were predicted to have one or two transmembrane domains, two proteins most probably had three to four transmembrane domains, and four proteins had more than four transmembrane domains. The latter group (At2g39970, At4g04470, At4g39850, and At5g27520) mainly consisted of the proteins listed as transporters or integral membrane proteins in Table I.

Developing a Model of Peroxisome Metabolism

In order to test if our proteins form an integrated set of functions and to predict if many peroxisomal enzymes are missing from our list, we created a metabolic network using data from the AraCyc database and visualized it with the Cytoscape software package (Version 2.6.0). This was based on the Enzyme Commission (EC) number of all identified proteins as annotated in AraCyc, which links Arabidopsis Genome Initiative (AGI) numbers with EC reactions. A total of 44 of the proteins in our peroxisome set from Table I were assigned EC numbers, making a nonredundant set of 28 enzyme nodes and 64 metabolites. Focusing on the metabolites that represent the substrates, reactants, and products of the network enables us to see points of contact between the different functional categories of proteins and also to predict the need for transporters in the peroxisomal membrane by analysis of the metabolite end points of the network. In the network, colored nodes (rounded squares) represent enzymes in different functional categories, metabolites are shown as small gray circles, while the reaction is shown as connecting lines between the enzymes and metabolite nodes (Fig. 6).

Figure 6.
Visualization of peroxisome metabolic functions based on the proteins identified in this study. Colored nodes (rounded squares) represent enzymes in different functional categories as shown in the key, metabolites are shown as small gray circles, and ...

The result is a structure derived from our proteome discovery strategy that appears as a well-connected single metabolic entity, showing that the different metabolic pathways within this peroxisome proteome are interlinked and that there are no large gaps created by lack of identification of critical enzymes in a sequence. About one-third of the metabolites do not represent starting or end points of a pathway but are considered to be intermediates of peroxisome metabolism by this network. The terminal metabolite nodes of the network are potential substrates to be transported in or out across the peroxisomal membrane via transporters or pores. Many of these metabolites have been reported to be transported, to diffuse freely across peroxisomal membranes, or to be incapable of crossing the peroxisomal membrane, and these are highlighted in Figure 6.

The network shows key features of established peroxisome biochemistry. It shows citrate synthase and malate dehydrogenase as key points of contact between β-oxidation and organic acid/amino acid metabolism through CoA/acetyl-CoA and NAD/NADH pools. It also shows that antioxidant defense enzymes operate to detoxify hydrogen peroxide produced by a series of oxidases. The metabolites oxygen, hydrogen peroxide, water, and CoA are the most heavily connected nodes, but removal of these “currency metabolites” (Huss and Holme, 2007) does not break the highly interconnected structure of this metabolic network.


Of the 89 peroxisomal proteins identified here, 54 have been identified previously by the peroxisome proteome studies of other tissue types by Fukao et al. (2002, 2003) and Reumann et al. (2007). These proteins participate in all of the classical peroxisomal pathways, such as fatty acid and JA β-oxidation, reactive oxygen species detoxification, carbon and nitrogen metabolism, and organelle biogenesis (Table I). Interestingly, all of the proteins involved in the peroxisomal steps of the photorespiratory pathway have been identified here in cell cultures, even though they are not green and were grown in the dark for 7 d prior to peroxisome preparation. A total of 35 proteins are reported here in peroxisomes, to our knowledge, for the first time (Table I). These include a series of isoforms of proteins participating in well-characterized peroxisomal pathways that are predicted to possess different substrate specificities. Interestingly, these isoforms are often more hydrophobic than their counterparts previously characterized by MS, based on comparison of their predicted number of transmembrane domains (Table I). Examples are a member of the 4-coumarate-CoA ligase (4CL)-like proteins (At1g20480), PEX11c, and PEX11e, indicating that the broadness of the experimental approach helps to identify such proteins. This is also supported by the identification of several proteins with unknown function that are reported here, to our knowledge, for the first time and that include a number of putative membrane carrier proteins with four or more transmembrane domains.

In the following paragraphs, we discuss different classes of this newly identified set of 35 proteins; we also discuss classes of reported peroxisome proteins not found here, the close association of peroxisomes with the ER, and the challenge of defining the wider peroxisome proteome in plants.

Acyl-Activating Enzymes and Acyl-CoA Oxidases

Our data reveal a variety of acyl-activating enzymes (AAEs) in cell culture peroxisomes that provide the point of entry for many substrates into the β-oxidation pathway. These proteins are known to possess a certain degree of substrate specificity. In addition to the two 4CL family proteins identified by Reumann et al. (2007; At1g20510 and At4g05160), an additional member of this protein family has been identified (At1g20480), which may not be expressed in leaves (Koo et al., 2006). In our study, this protein was identified by five different approaches (Table I), strongly suggesting a significant abundance of this protein. At1g20510 and At4g05160 are expected to participate in JA biosynthesis, as At1g20510 preferentially activates OPC 8:0 (Koo et al., 2006) while At4g05160 prefers OPC 6:0. They are also reported to accept medium- to long-chain fatty acids as substrates. These results have been confirmed in a comparison of substrate specificity of 4CL-like proteins (Kienow et al., 2008). None of the tested substrates seemed to suit At1g20480, whose function in the context of substrate activation for β-oxidation still remains unclear. Other new AAEs include At5g16340, which shares 92% sequence identity with the previously found At5g16370, AAE17 (At5g23050), At1g20560, and LACS6 (At3g05970), a long-chain fatty acid CoA ligase (Shockey et al., 2002) targeted to peroxisomes (Fulda et al., 2002). For some of these enzymes, no substrate has been identified and their predicted functions have only been deduced by amino acid sequence comparisons. Many of these enzymes with known functions have partially overlapping substrate specificities, according to the literature (Kienow et al., 2008).

Acyl-CoA oxidases (ACXs) perform the next step in β-oxidation after acyl activation, and four of the six known isoforms of this enzyme in Arabidopsis have been identified in this study (At4g16760, ACX1; At1g06290, ACX3; At3g51840, ACX4; and At2g35690, ACX5). Only one of these was found by MS in published reports (Table I). Although these enzymes partly overlap in their substrate specificity, they appear to prefer different types of substrates, which they feed into the β-oxidation process. ACX1 preferentially uses medium- to long-chain fatty acids and seems to be the most important ACX for JA synthesis (Schilmiller et al., 2007). ACX3 and ACX4 prefer medium- or short-chain FAs. All three are reported to be involved in the β-oxidation of IBA (Adham et al., 2005), although to differing degrees. Using the GENEVESTIGATOR database (Zimmermann et al., 2004), the expression profiles of all six ACXs were compared in different plant organs. ACX6 is expressed most strongly in root tip, ACX1 in sepal, ACX5 in stamen, and ACX2 and ACX3 in endosperm but also strongly in seed, imbibed seed, and embryo, which is consistent with their role in metabolizing lipids in energy metabolism in oilseeds. The transcript for ACX4 is lowly expressed in most tissues, but we have detected the protein by five different approaches, and it has also been found in leaf peroxisomes (Reumann et al., 2007). Interestingly, ACX4 is the most divergent protein within the ACX family, as it is missing an oxidase domain (Adham et al., 2005). Expression patterns of ACX2, ACX3, and ACX4 were found to cluster during development as well as in their distribution between plant organs in our analysis of GENEVESTIGATOR data (Zimmermann et al., 2004). ACX2 and ACX6 (which may be a pseudogene, as no transcripts have been reported) were not found in this study. In ACX2 knockout line seeds, long-chain fatty acids accumulate (Pinfield-Wells et al., 2005), indicating together with its expression pattern that this protein is mainly involved in the breakdown of storage lipids. Why ACX2 appears to be absent or in low abundance in cell culture, while ACX3 is present, is currently unclear.

In contrast to the AAEs and ACXs, the overlap in identification of all other core enzymes involved in β-oxidation is much higher between studies reporting peroxisome proteomes from different plant tissues. This may indicate that AAEs and ACXs regulate substrate flow into the more generic β-oxidation pathway. A comparison of protein abundance of these enzymes from different plant organs or different developmental stages will probably shed more light on the different functions they fulfill in priming substrates for β-oxidation.

Transporters and Integral Membrane Proteins

Four proteins have been identified that fit clearly into the category of integral membrane proteins: At2g39970 (PMP38), At5g27520, At4g39850 (CTS/PXA/PED3), and At4g04470 (PMP22). All four proteins were found only in the peroxisomal membrane fractions, are predicted to possess three or more transmembrane domains, and lack known PTS1 and PTS2 sequences for targeting.

PMP38 (At2g39970) contains functional domains similar to those found in the mitochondrial carrier family (MCF). A homolog of PMP38 in pumpkin has been localized in the peroxisomal membrane by immunohistochemistry (Fukao et al., 2001); but in Arabidopsis, PMP38 has been, most likely erroneously, detected in the vacuole (Jaquinod et al., 2007). PMP38 is a clear homolog of the yeast peroxisomal PMP47 that was shown many years ago to be a peroxisomal member of the yeast MCF (McCammon et al., 1990). The substrate for PMP38 in plants is currently not clear, but possible candidates are ADP/ATP, 2-oxoglutarate/malate, phosphate, or tricarboxylates. The yeast equivalent is clearly an ADP/ATP transporter but may also function in ΔpH formation (Lasorsa et al., 2004). The closest Arabidopsis homolog to PMP38 is annotated as a plastidic folate transporter (At5g66380) discovered by complementation of folate-deficient hamster cells and bacteria. However, knockout of At5g66380 in Arabidopsis did not change folate concentration in the plastids, suggesting either a different function in plant cells or the presence of alternative folate transporters in plastids (Bedhomme et al., 2005). The phosphorylation of PMP38 at Ser-155 (Supplemental Data Set S3) may indicate that it could be regulated by a phosphorylation/dephosphorylation event. Phosphoproteomics of yeast mitochondria identified phosphorylation of the main ATP/ADP transporter (AAC1) at Ser-155/Thr-156 or Ser-157. Alignment of the two proteins revealed broad but low-level sequence similarity, as both are MCF members, but the phosphorylation sites are in nearly identical locations within the hydrophilic loop between the third and fourth transmembrane domains of both proteins (Supplemental Data Set S3).

The product of At5g27520 is an unknown function member of the MCF and is most closely related in sequence to mitochondrial ADP/ATP transporters and the peroxisomal ADP/ATP transporter identified in yeast. The designation of this carrier as a peroxisomal carrier is strengthened by its identification here in three separate experiments (Table I) and the absence of its identification in our focused work to identify mitochondrial carriers of this type from mitochondria isolated from this same cell culture material (Millar and Heazlewood, 2003). We also tested At5g27520 for peroxisomal localization using transient expression of a GFP fusion protein, confirming its peroxisomal location in vivo (Fig. 4A).

At4g39850 (CTS/PXA/PED3) possesses an ATP-binding cassette domain and is considered a full ATP-binding cassette transporter, containing 12 transmembrane domains and acting as a monomer. There is still some controversy as to its exact mechanistic function and its corequirement for acyl-CoA synthetases compared with the more clear-cut evidence for half-ATP transporters in acyl-CoA entry to peroxisomes in yeast (Visser et al., 2007). However, it appears from a range of genetic studies that CTS has a role in the entry of a broad range of fatty acid substrates into plant peroxisomes. CTS knockout mutants are resistant to IBA or 4-(2,4-dichlorophenoxy)butyric acid, indicating that the transport of both compounds is facilitated into peroxisomes by this protein (Theodoulou et al., 2005). Seed lipid metabolism also seemed to be affected by the knockout of this protein, suggesting a potential role of CTS in the import of fatty acids into peroxisomes (Footitt et al., 2002). Additionally, CTS mutants are JA-deficient and therefore most likely have a reduced import rate of 12-oxo-phytodienoic acid, a plastid-derived JA precursor molecule. However, CTS does not seem to be the only route by which 12-oxo-phytodienoic acid is transferred into the organelle; alternative routes via different, unidentified transporters or diffusion pathways might exist (Theodoulou et al., 2005).

At4g04470 (PMP22) is an integral membrane protein that possesses similarities to known mammalian and yeast peroxisomal proteins (Tugal et al., 1999). But despite a series of reports showing that its loss of function is detrimental in mouse and yeast (Zwacka et al., 1994; Trott and Morano, 2004), relatively little is known about its biological function. The most likely roles proposed are as a nonselective membrane channel and/or as a reactive oxygen species forming protein in the peroxisome membrane (Visser et al., 2007).

There has been a report recently of the molecular identification and cloning of the peroxisomal channel protein in the grass Bromus inermis (Wu et al., 2005). Such a channel has been predicted in a range of species to allow free movement of compounds of less than 300 D across the membrane, but it has not previously been identified in any species (Visser et al., 2007). The Arabidopsis homolog of this protein is an OEP16-like protein, At4g16160, but we found no evidence for this protein in the membranes of our peroxisomes. Recently, GFP localization of this OEP16 homolog in Arabidopsis indicated that it localizes to the plastid (Murcha et al., 2007), further discounting the likelihood that it is a peroxisomal membrane channel.

Overall, if these identified transporters represent the bulk of the transport functions on mature peroxisomes, then the metabolite pools and needs for exchange (Fig. 6) could be understood by the following scenario. Mature peroxisomes may have a static population of cofactors such as CoA and pyridine nucleotides such as NAD+ and NADP+, which explains their impermeability to these reagents. Import of fatty acids would be mediated by CTS, while the two MCF-type carriers could provide a broad entry for organic and amino acids, ATP/ADP, and inorganic phosphate, and some small molecules may diffuse. This would be consistent with the known properties/substrates of other MCFs and the CTS and might provide for many of the known transport properties of plant peroxisomes.

PEX Proteins

Four of the five PEX11 family proteins that have a predicted role in peroxisome proliferation (Orth et al., 2007) in Arabidopsis have been found in this study (PEX11a, -c, -d, and -e). Three of these peroxins (PEX11c, -d, and -e) form a distinct group within the Arabidopsis PEX11 genes, while PEX11a and PEX11b each represent a group on their own. While overexpression of PEX11a and PEX11b resulted merely in elongation of peroxisomes, the overexpression of PEX11c, -d, and -e led to the induction of a complete division process. PEX11c, -d, and -e were also the only peroxins able to complement the yeast pex11 knockout mutant (Orth et al., 2007). Only PEX11d was found by MS in the previous proteome study by Reumann et al. (2007) in leaf peroxisomes. As cell culture is a rapidly dividing tissue, peroxisomal biogenesis and proliferation may be enhanced, which might explain the relative abundance of the PEX11, PEX7, and PEX14 proteins observed here. PEX11b, which has not been detected by us, was recently shown to be involved in light-dependent regulation of peroxisome proliferation (Desai and Hu, 2008) during seedling morphogenesis and therefore is most likely of low abundance in dark-grown cell culture. Controversy persists about the precise molecular role of PEX11, because despite genetic evidence for roles in biogenesis and organelle proliferation (Orth et al., 2007), specific isoforms of these membrane proteins have also been implicated in metabolic functions upstream of β-oxidation, most likely in fatty acid activation or fatty acid transport in yeast (Hettema and Tabak, 2000; van Roermund et al., 2000).

Nucleotide Pools and Redox Shuttling in Peroxisomes

The relative importance of putative organic acid/amino acid shuttles to move reductant in or out of the peroxisome versus an internal balance of reducing and oxidizing reactions remains unclear. This is in large part due to the lack of information about the composition of peroxisomes and their reductive and oxidative catalytic activities. A series of known NAD(H)- or NADP(H)-dependent peroxisomal enzymes were found (Table I) and are clustered in Figure 6 based on their common use of these peroxisomal nucleotide pools. The NAD+ cluster surrounds malate dehydrogenase, and the NADP+ cluster surrounds isocitrate dehydrogenase. In addition to the enzymes of known substrate and products shown in Figure 6, a series of reductases were found in Table I that likely link to these pools. For example, we found dienoyl-CoA reductase proteins. In yeast, this is known to be an NADPH-dependent enzyme and has been convincingly shown to be supplied with NADPH by isocitrate dehydrogenase through genetic studies (van Roermund et al., 1998). Other reductases thought to be involved in the β-oxidation of unsaturated substrates (Table I) were also found in leaf peroxisomes (Reumann et al., 2007), but their specificities for nucleotides are unknown. We also found three putative quinone reductases grouped in the reducing metabolism section of Table I, and one of these was also found in leaf peroxisomes (Reumann et al., 2007). All three have PTS1 signals (Table I) and may link soluble nucleotide redox pools with membrane redox pools of quinone or other unknown reductants. These identifications broaden the possibilities for redox pool regulation in peroxisomes from the classical malate/oxaloacetate and malate/Asp shuttles proposed, based on metabolic models of peroxisome function (Visser et al., 2007).

Proteins Previously Identified in Peroxisomes That Are Missing in This Study

Interestingly, of the seven proteins associated with protection against pathogen attack and herbivores found in leaf peroxisomes (Reumann et al., 2007), none was found in our analysis. The lack of these proteins in the cell culture peroxisomes is striking, as in all other areas of peroxisomal metabolism, including photorespiration, a large overlap could be observed. Leaf-specific expression of the corresponding genes is not evident in GENEVESTIGATOR microarray data (Zimmermann et al., 2004). One of the putative defense proteins (OZI1; At4g00860) has previously been found in the analysis of the mitochondrial proteome (Heazlewood et al., 2004) and on blue-native/SDS gels of Arabidopsis mitochondrial membranes. The latter data suggest an association of OZI1 with the cytochrome c oxidase complex (complex IV) of the plant respiratory chain (Millar et al., 2004); subsequently, the protein was named COX-X2. This protein does not possess a PTS, and targeting prediction programs do not suggest a peroxisomal location, so in our view the data point toward it being a mitochondrial protein. The other six putatively defense-related proteins claimed as peroxisomal (Reumann et al., 2007) have previously been identified in an analysis of the leaf vacuole proteome (Carter et al., 2004), and most are predicted to have secretory signals or ER signal peptides. Another notable absence from the peroxisomes analyzed here are the glyoxylate cycle enzymes isocitrate lyase and malate synthase. This clearly shows that these cell culture organelles cannot be considered to be catalyzing a glyoxylate cycle.

Apparently Nonperoxisomal Proteins in Peroxisome Preparations

The vast majority of proteins that apparently are nonperoxisomal in our preparations have a mitochondrial origin. Given that mitochondria are probably the most abundant organelles present in dark-grown cells, that they migrate very close to the peroxisomes during FFE, and that they are widely considered the major contaminant in yeast and mammalian peroxisome proteome analyses (Kikuchi et al., 2004; Marelli et al., 2004; Saleem et al., 2006), this is not surprising. Our ongoing investigation of the Arabidopsis mitochondrial proteome (Millar et al., 2005), facilitated by technical advances in MS and the increase in the purity of mitochondrial isolations by FFE (Eubel et al., 2007), enables a very precise assignment of mitochondrial proteins in our overall nonredundant protein list. The subtraction of mitochondrial proteins is supported in the vast majority of cases by the quantitative data generated in the course of this study, namely through DIGE and comparative LC-MS/MS. Contaminations by cellular compartments other than mitochondria are significantly harder to confidently exclude. This is especially true in the case of the ER proteins identified here, such as calreticulin, calnexin, HSP90, SEC12p, and the lumenal chaperones BIP1 and BIP2. While it is beyond doubt that these proteins are primarily found in the ER, it is harder to tell whether this group also represents bona fide proteins in peroxisomal preparations or if they are merely contaminating proteins due to a copurification of ER vesicles with the peroxisomes. Similar dilemmas have been presented a number of times in the literature about separation of the ER and peroxisome proteomes in other species (Saleem et al., 2006, and references therein). The resolution to these questions may be tightly linked to peroxisomal biogenesis and the import of peroxisomal proteins, especially those inserted into the membrane of these organelles. An involvement of the ER in the import of proteins into peroxisomes has been proposed for PEX15 in yeast (Elgersma et al., 1997) and for PEX10 and PEX16 in Arabidopsis cell suspension cultures (Flynn et al., 2005; Karnik and Trelease, 2005), although PEX10 has also been reported to be targeted to peroxisomes without a passage through the ER (Sparkes et al., 2005). BIP has been found in the same gradient fraction as APX in pumpkin (Nito et al., 2001). The involvement of the ER with peroxisomal biogenesis and protein import has been reviewed (Mullen and Trelease, 2006), and ricinosomes emerging from the ER were found to contain BiP and PDI protein (Schmid et al., 2001). Our own GFP localization studies did not support the presence of the analyzed ER proteins inside peroxisomes in vivo (Table II; Fig. 4; Supplemental Data Set S1). The presence of these proteins in the peroxisomal samples might be explained by the close interaction of these two compartments observed in our GFP images (Fig. 5; Supplemental Data Set S1) and the potential for isolating peroxisomes tethered to ER vesicles.

On balance, the data are more in favor of contamination of the peroxisomes with a small amount of ER material, either due to comigration in FFE (Fig. 5A) or due to physical association between ER fragments and peroxisomes (Fig. 5C), but probably not due to the presence of ER proteins within the peroxisome membrane or lumen.

The Complexity of Defining the Full Peroxisomal Proteome

Despite substantial efforts of three separate groups working on different Arabidopsis tissue types (Fukao et al., 2002, 2003; Reumann et al., 2007; Table I), less than 20% of the proteins with predicted PTS sequences (Reumann et al., 2004) have been experimentally confirmed in peroxisomal preparations. In the process, each group has found a range of proteins that lack PTS signals, suggesting that bioinformatics predictions will be of limited help. The task of experimentally confirming the complete peroxisomal proteome in Arabidopsis may still be some way off. While 11 proteins (photorespiratory enzymes, catalases, and malate dehydrogenases) have been found in two or three studies (Table I), significant discrepancies exist between the lists of peroxisomal proteins from our analysis and those from other Arabidopsis tissues. Reumann et al. (2007) claimed 29 proteins as peroxisomal that were not confirmed in our study; only four have recognizable PTS sequences (At1g06460, At1g21770, At1g60550, and At5g48880; Supplemental Table S6). Fukao et al. (2002, 2003) claim an entirely separate set of 29 proteins that were not confirmed in this study (Supplemental Table S6); only one has a recognizable PTS, malate synthase (At5g03860), and most of the others have currently unclear functions in peroxisomes. This study claims 35 proteins not found in any of the other studies of leaf or cotyledon peroxisomes (Table I); 21 contain PTS1 or PTS2, and most are involved in fatty acid oxidation. In addition, six are transmembrane proteins that would not have a clear PTS. More quantitative data and assessment of targeting are necessary to resolve if each of these proteins lacking independent confirmation are peroxisomal in a range of plant tissue types. Further advances in peroxisome purification are required so that 10 to 100 mg of peroxisomes can be isolated from Arabidopsis tissues to allow suborganelle fractionation, so effective for improving protein identification in other organelles. However, many proteins have now been found in two or three independent studies (Table I). This gives a solid foundation for detailed analysis of peroxisomal function in plants, as it is likely that many of the major metabolic pathways can now be reconstructed (Fig. 6).


Cell Culture Maintenance

An Arabidopsis (Arabidopsis thaliana) suspension cell culture has been maintained and subcultured as stated elsewhere (Millar et al., 2001). Briefly, 20 mL of a 7-d-old cell culture grown in the light was transferred into 100 mL of fresh medium. Starting material for the peroxisome preparation was grown in the dark for 7 d, whereas material used for the maintenance of the culture was incubated in the light for the same period of time.

Organelle Preparation

The preparation of the organelles was based on Eubel et al. (2007), with some modifications. Approximately 200 g of cells was used for each preparation. After enzymatic digestion of the cell wall, the resulting protoplasts were disrupted by four strokes in a Potter-Elvehjem homogenizer. The homogenization medium contained bovine serum albumin and EDTA as general protease inhibitors; in addition, Complete (Roche Applied Science) protease inhibitor cocktail was used according to the manufacturer's instructions to inhibit Ser, Cys, and metalloproteases. The homogenate was centrifuged at 3,000g for 5 min to remove cell debris. The supernatant was spun at 24,000g for 10 min to concentrate the organelles. However, in order to avoid pelleting of the organelles, the supernatant of the low-speed spin was layered on top of 5 mL of a Percoll cushion (60% [v/v] Percoll, 10 mm MOPS-KOH, pH 7.2). The organelle-containing interphase was taken and diluted 1:1 with wash buffer and loaded onto discontinuous Percoll density gradients consisting of 5 mL of 50% (v/v) Percoll and 25 mL of 25% (v/v) Percoll (bottom to top) in wash buffer. After centrifugation, the mitochondrial/peroxisomal band was found between the 50% (v/v) and the 25% (v/v) Percoll phases. This band was extracted, and the Percoll was removed by three repeated washes in FFE separation buffer. The first two washes were performed using a 60% (v/v) Suc cushion (60% [v/v] Suc, 10 mm MOPS-KOH, pH 7.2) at the bottom of the tubes, again to prevent pelleting of the organelles. The third wash was performed without any cushion, and the organelles were pelleted. After resuspension in a small volume of FFE separation buffer (2 mL), the organelle suspension was slowly homogenized in a Potter-Elvehjem homogenizer in preparation for FFE.

FFE buffer composition and conditions were similar to those described previously (Eubel et al., 2007) with the exception of the use of either 800 V or 600 V in experiments as indicated. Using the higher voltage, mitochondria and plastids were deflected to such an extent that the plastids were running into the anode stabilization medium, whereas the mitochondria just stayed within the borders of the separation medium. Although a certain amount of mixing between those two organelles occurred, the distance between the mitochondria and the peroxisomes increased, which led to a higher level of purity of the peroxisomal fraction. After visual inspection of the 96-well plate, mitochondrial fractions (contaminated with plastids) and peroxisomal fractions were pooled separately. The mitochondria were then subjected to a second round of FFE at 600 V in order to obtain purer material for the subsequent measurements.

Oxygen Electrode Measurements

Catalase activity was measured using a Clark-type oxygen electrode (Hansatech) as outlined previously (Eubel et al., 2007). Succinate dehydrogenase measurements were performed using a Clark-type oxygen electrode in the presence of 10 mm succinate, 500 nmol of ADP, and 100 nmol of ATP. Fifty micrograms of protein was used for each assay.

1D SDS-PAGE, 2D IEF/SDS-PAGE, DIGE, and Immunoblotting

These techniques were performed according to Eubel et al. (2007). For the preparative 2D gels, 300 μg of protein was used. Primary antibodies to calreticulin (1:1,000; Agrisera), HSP70 (1:2,000; PM003 from Dr. Tom Elton), and KAT2 (1:5,000; Germain et al., 2001) were visualized with horseradish peroxidase-conjugated secondary antibodies (1:10,000) and chemiluminescent detection of the signal.


Aliquots of membrane and integral membrane proteins extracted from peroxisome samples were separated according to Meyer et al. (2008) on 10% (w/v) Tricine-SDS-PAGE containing 6 m urea. After the migration, gel strips corresponding to each sample were cut and incubated in acidic solution (100 mm Tris, 150 mm HCl, pH < 2). The strips were then loaded on top of a 16% (w/v) Tricine-SDS-polyacrylamide gel. The gap between the strip and the gel was filled with a 10% (w/v) acrylamide mixture. After electrophoresis, the gels were stained with colloidal Coomassie Brilliant Blue.

Phosphopeptide Isolation

The procedure essentially follows the method outlined by Bodenmiller et al. (2007). A 1-mg organellar protein pellet was solubilized in 100 μL of 8 m urea, 3 mm EDTA, and 20 mm Tris-HCl, pH 8.0. The sample was reduced with 25 mm DTT for 1 h at room temperature followed by alkylation of thiols with 50 mm iodoacetamide for 1 h at room temperature. The solution was diluted to approximately 1 m urea with 20 mm Tris-HCl, pH 8.0, used to hydrate 25 μg of trypsin (Invitrogen), and incubated at 37°C overnight. Peptides were desalted on Bio-Select reverse-phase C18 extraction columns (Grace Vydac) and dried in a vacuum concentrator. Peptides were reconstituted in 400 μL of solution containing 50% (v/v) acetonitrile, 2.5% (v/v) trifluoroacetic acid (TFA), and 20 mg mL−1 2,5-dihydroxybenzoic acid. This solution was added to 5 mg of Titanosphere TiO 5 μm (GL Science) equilibrated with 50% (v/v) acetonitrile, 2.5% (v/v) TFA, and 20 mg mL−1 2,5-dihydroxybenzoic acid. The slurry was rotated for 30 min at room temperature in a mobicol spin column (MoBiTec), then washed twice with the 50% (v/v) acetonitrile, 2.5% (v/v) TFA, and 20 mg mL−1 2,5-dihydroxybenzoic acid solution, twice with 50% (v/v) acetonitrile and 0.1% (v/v) TFA, and twice with a 0.1% (v/v) TFA solution. Phosphopeptides were eluted from the Titanosphere chromatographic material using a freshly prepared 0.3 m NH4OH solution. Eluted phosphopeptides were dried in a vacuum desiccator and resuspended in 5% (v/v) acetonitrile and 0.1% (v/v) formic acid prior to analysis. Phosphopeptides were identified in peptide mixture analysis by 6510 Q-TOF LC-MS/MS (Agilent Technologies) as outlined below.

MS Analysis of Peptides

Colloidal Coomassie Brilliant Blue-stained protein spots where cut from gels and destained twice in 10 mm Na2HCO3 with 50% (v/v) acetonitrile. Samples were dried at 50°C before being rehydrated with 15 μL of digestion solution (10 mm NH4CO3 with 12.5 μg mL−1 trypsin [Invitrogen] and 0.01% [v/v] TFA) and incubated overnight at 37°C. Peptides produced from trypsination were twice extracted from gel plugs using 15 μL of acetonitrile. The supernatant was then collected, and plugs were washed twice with 15 μL of 50% (v/v) acetonitrile and 5% (v/v) TFA and combined with the initial supernatant. The pooled extracts were dried by vacuum centrifugation and stored at 4°C before being analyzed by MS using an Agilent XCT Ultra IonTrap (Agilent Technologies) mass spectrometer. The mass spectrometer was fitted with an electrospray ionization (ESI) source equipped with a low-flow nebulizer in positive mode and controlled by Chemstation (Rev B.01.03; Agilent Technologies) and MSD Trap Control software Version 6.1 (Bruker Daltonik). Peptides were eluted from a self-packed Microsorb (Varian) C18 (5 μm, 100 Å) reverse-phase column (0.5 × 50 mm) using an Agilent Technologies 1100 series capillary liquid chromatography system at 10 μL min−1 using a 9-min acetonitrile gradient (5%−60%, v/v) in 0.1% (v/v) formic acid at a regulated temperature of 50°C. The method used for initial ion detection utilized a mass range of 200 to 1,400 mass-to-charge ratio (m/z) with scan mode set to standard (8,100 m/z s−1), ion charge control conditions set at 250,000, and three averages taken per scan. Smart mode parameter settings were employed using a target of 800 m/z, a compound stability factor of 90%, a trap drive level of 80%, and optimize set to normal. Ions were selected for MS/MS after reaching an intensity of 25,000 cps, and two precursor ions were selected from the initial MS scan. MS/MS conditions employed SmartFrag for ion fragmentation, a scan range of 70 to 2,200 m/z using an average of three scans, the exclusion of singly charged ions option, and ion charge control conditions set to 200,000 in ultra scan mode (26,000 m/z s−1). Resulting MS/MS spectra were exported from the DataAnalysis for LC/MSD Trap Version 3.3 (Build 149) software package (Bruker Daltonik) using default parameters and 1,000 compound maxima for AutoMS(n) and compound export. The .mgf files generated were then analyzed as outlined below.

Protein samples were also analyzed with a nongel approach, using peptide mixture LC-MS/MS analysis. The protein extracts were digested overnight at 37°C with trypsin (10:1), and insoluble components were removed by centrifugation at 20,000g for 5 min. The supernatant was then dried by vacuum centrifugation and stored at 4°C before being analyzed by MS. Samples were analyzed on an Agilent 6510 Q-TOF mass spectrometer (Agilent Technologies) with an HPLC Chip Cube source. The chip consisted of a 40-nL enrichment column (Zorbax 300SB-C18 5 u) and a 150-mm separation column (Zorbax 300SB-C18 5 u) 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 resuspended in 5% (v/v) acetonitrile and 0.1% (v/v) formic acid and loaded onto the trapping column at 4 μL min−1 in 5% (v/v) acetonitrile and 0.1% (v/v) formic acid with the chip switched to enrichment and using the capillary pump. After the sample volume passed through the enrichment column five times, the chip was then switched to separation and peptides were eluted from the enrichment column and run through the separation column during a 1-h gradient (15% to 60% [v/v] acetonitrile) directly into the mass spectrometer. The mass spectrometer was run in positive ion mode, and MS scans were run over a range of m/z 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 a maximum of three precursors per cycle, and active exclusion set at two spectra and released after 1 min. Precursor charge-state selection and preference were 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, 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.xml files and searched as outlined below.

Data Analysis

Output files were analyzed against an in-house Arabidopsis database comprising ATH1.pep (release 7) from The Arabidopsis Information Resource and the mitochondrial and plastid protein sets (The Arabidopsis Information Resource). This sequence database contained a total of 30,700 protein sequences (12,656,682 residues). Searches from ion trap data were conducted using the Mascot search engine Version 2.1.04 (Matrix Science) utilizing error tolerances of ±1.2 D for MS and ±0.6 D for MS/MS, Max Missed Cleavages set to 1, the Oxidation (M) and Carboxymethyl (C) variable modifications, and the Instrument set to ESI-TRAP and Peptide charge set at 2+ and 3+. Results were filtered using standard scoring, maximum number of hits set to 20, significance threshold at P < 0.05, and ion score cutoff at 0. Searches from Q-TOF data were conducted using the Mascot search engine Version 2.1.04 (Matrix Science) utilizing error tolerances of ±100 ppm for MS and ±0.5 D for MS/MS, Max Missed Cleavages set to 1, the Oxidation (M) and Carboxymethyl (C) variable modifications, and the Instrument set to ESI-Q-TOF and Peptide charge set at 2+ and 3+. Results were filtered using MUDPIT scoring, maximum number of hits set to 20, significance threshold at P < 0.05, and ion score cutoff at 0. Protein matches were only claimed if at least two distinct peptides were detected per protein, resulting in MOWSE scores typically higher than 70 (P < 0.05 significance level is score > 37).


Following an initial run as outlined above in peptide mixture analysis, the resulting mzdata.xml files were searched as outlined in “Data Analysis.” The resulting matches were then filtered by an Ion Score setting of 37, and all peptides with ion scores of 37 or greater were exported from MASCOT along with their respective peptide charge into a .csv file. This file was then used to construct an exclusion list, based on peptide (m/z) and charge (z). Isolation width was set to medium approximately 4 m/z, precursor type was set to Exclude, retention time was set to 0, and Δm/z was set to 100 ppm. This table was then loaded into the MassHunter Workstation Data Acquisition for Q-TOF (Version B.01.02, Build 65.4, Patches 1,2,3,4; Agilent Technologies) software, and then the next sample was run. Following the second run, the new list of excluded peptides was added to the previous list and the new list was loaded for the third run. This process was repeated for the fourth run also. Following acquisition of data from all four runs, the resulting mzdata.xml files were concatenated into a single mzdata.xml file using mzdataCombinator Version 1.0.4 (University of Western Australia Centre of Excellence for Computational Systems Biology; http://www.ce4csb.org/software.shtml). The resulting files were then used to search an in-house Arabidopsis database as outlined above.

GFP Localization Studies

GFP fusions were constructed according to a modification of the fluorescent tagging of full-length proteins (FTFLP) method (Tian et al., 2004). FTFLP introduces GFP into genomic clones (including native promoters and terminators) in a stretch of hydrophilic amino acids in a position corresponding to approximately 10 amino acids from the C terminus. In its original context, FTFLP is claimed to represent a good first pass for spatial and temporal localization of proteins for which no other information is available (Tian et al., 2004; Tzafrir et al., 2004) and is suggested to be a good alternative to constructing both N- and C-terminal fusions (Goodin et al., 2007). Tian et al. (2004) present proof of principle for marker proteins targeted to numerous organelles, including MFP2, which was directed to peroxisomes. A number of studies have specifically used FTFLP to preserve the N-terminal targeting signal and the C-terminal retention motifs (Chen et al., 2005; Li et al., 2005; Drakakaki et al., 2006; Anand et al., 2007; Goh et al., 2007; Blakeslee et al., 2008; Gallavotti et al., 2008). We adapted the method for high-throughput analysis of full-length proteins via a transient expression assay. For many of the proteins examined here, there were either no clear predicted targeting signals or potentially conflicting N- and C-terminal signals. Thus, GFP was still inserted 10 to 13 amino acids from the C terminus, but this was done using coding sequence alone and driven by the 35S promoter for transient expression in onion (Allium cepa) cell epidermal peel and Arabidopsis cell culture. The position of 10 amino acids from the C terminus largely avoids structural and functional protein domains and preserves both N- and C-terminal targeting sequences in full-length proteins (Tian et al., 2004). The aim of this approach was to avoid masking potential N- or C-terminal targeting signals with GFP and to reduce the chance that blocking the biologically relevant signal might allow cryptic, physiologically meaningless signals to take precedence (Simpson et al., 2001; Tian et al., 2004; Goodin et al., 2007; Pottosin and Schonknecht, 2007). GFP5 was amplified including adapters as described (Tian et al., 2004). The portion of the gene corresponding to the N terminus of the protein was amplified using appropriate primers (primers P1 and P2). Templates for amplification were cloned cDNAs if available (ordered from the Arabidopsis Biological Resource Center if available) or total cDNA. Oligonucleotides P3 and P4, corresponding to the C-terminal 10 to 13 amino acids plus the stop codon of the protein (i.e. 33–42 nucleotides), were synthesized to constitute a template for direct inclusion in a second round of PCR. Primers P1 and P4 included adapters that partially overlapped with attB Gateway cloning sequences, while primers P2 and P3 had adapters that overlapped with those bounding the GFP fragment; the adapters were as described by Tian et al. (2004). Three-template PCR thus included three overlapping templates (the P1-P2 PCR fragment, GFP, and the P3-P4 oligonucleotides). Three-template PCR products were cloned into Gateway vector pDONR207 and sequenced to check PCR accuracy. The GFP constructs were then introduced into a pGREEN vector modified for Gateway. We used pGREEN0179 containing cauliflower mosaic virus 2× 35S promoter and cauliflower mosaic virus terminator with the Gateway A cassette inserted between them in the SmaI site of the pGREEN multiple cloning site. For colocalization studies, pGREEN0049-RFP-SRL (Pracharoenwattana et al., 2005) was used as a peroxisomal marker. Plasmids were precipitated onto 1-μm gold particles and biolistically transformed into Arabidopsis cultured cells or onion epidermal peel as described by Thirkettle-Watts et al. (2003). Fluorescence images were obtained using an Olympus BX61 epifluorescence microscope with HQ GFP (U-MGFPHQ) and RFP (U-MRFPHQ) filters and CellR software. Alternatively, a Leica TCS SP2 AOBS multiphoton confocal microscope was used with laser excitation of GFP at 488 nm and RFP at 561 nm. Emission collection was in the ranges of 500 to 550 nm and 570 to 700 nm, respectively. Confocal images were captured using Leica confocal software.

Network Analysis and Visualization

AraCyc (www.arabidopsis.org/biocyc/; Zhang et al., 2005) is a database of biochemical pathways for Arabidopsis. Over 90% of the pathways in the current release of AraCyc (4.5) have been manually curated with experimental data. Proteins identified in this study were associated with biochemical reactions in AraCyc release 4.5 by downloading from the Plant Metabolic Network FTP server (ftp://ftp.plantcyc.org/Pathways/) the tab-delimited text files “aracyc_compounds.20080611” and “aracyc_dump.20080611.” For each AGI code in Table I, pathway names, EC numbers, and enzyme names that have been associated by AraCyc with that AGI code were extracted from the “aracyc_dump” file. Biochemical reactions and their compounds were extracted from the lines in the “aracyc_compounds” file, which contained both the pathway name and the EC number associated with each AGI code. A total of 44 of the AGI numbers in our peroxisome set shown in Table I were assigned EC numbers in this manner, making a nonredundant set of 28 enzyme nodes and 64 metabolites. It should be noted that multiple distinct reactions, corresponding to differing substrates, can be assigned to a single EC number in AraCyc. These often occur when an EC number occurs in the context of separate biochemical pathways. Therefore, we extracted only those biochemical reactions for which both the EC number and the pathway name matched those associated with an AGI code, to avoid incorporating metabolites that may only be involved in pathways outside of the peroxisome.

After the recovery of these data, the set of unique EC numbers and biochemical reactions was parsed to generate a Simple Interaction Format file to represent a metabolic network. The Simple Interaction Format file and other data, such as AGI codes associated with EC numbers, enzyme names, and node types (enzyme or metabolite), were inputted into the Cytoscape software (Version 2.6.0; Shannon et al., 2003) for network visualization and analysis. Network images were exported from Cytoscape as .svg files, imported into Adobe Illustrator, and modified visually for presentation purposes.

Supplemental Data

The following materials are available in the online version of this article.

  • Supplemental Figure S1. 2D IEF/SDS-PAGE gels and spots annotated that were analyzed by MS.
  • Supplemental Figure S2. dSDS-PAGE gels and spots annotated that were analyzed by MS.
  • Supplemental Table S1. A, Catalase and succinate dehydrogenase activity assays. B, Gel spot identifications by MS of protein bands from Figure 1C.
  • Supplemental Table S2. Gel spot identifications by MS of gel spots from Supplemental Figure S1 and the corresponding DIGE ratios from Figure 2.
  • Supplemental Table S3. A, Gel band identifications by MS for Figure 3. B, Gel spot identifications by MS for Supplemental Figure S2 (dSDS).
  • Supplemental Table S4. Complex peptide mixture MS analysis by IDDA of digested whole peroxisomes of two different purities.
  • Supplemental Table S5. Complex peptide mixture MS analysis by IDDA of peroxisome membrane sample.
  • Supplemental Table S6. Proteins reported in peroxisomes by Reumann et al. (2007) and Fukao et al. (2002, 2003) but not found in Table I.
  • Supplemental Data Set S1. Images of fluorescent tagging of full-length proteins, supporting Table I and Table II GFP claims.
  • Supplemental Data Set S2. Single peptide mass spectral analysis supporting the data in Table I.
  • Supplemental Data Set S3. Phosphopeptide analysis of PMP38.

Supplementary Material

[Supplemental Data]


1This work was supported by grants from the Australian Research Council (ARC) through the Centres of Excellence Program (grant no. CE0561495), by the Western Australian State Government via its Centres of Excellence program, and by a University of Western Australia Research Grant to J.D.B. H.E., N.L.T., and J.L.H. are supported as ARC Australian Postdoctoral Fellows, A.H.M. as an ARC Australian Professorial Fellow, and S.M.S. as an ARC Federation Fellow.

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 (ua.ude.awu.enellyc@rallimh).

[W]The online version of this article contains Web-only data.

[OA]Open Access articles can be viewed online without a subscription.



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