Chiang Mai J. Sci. 2017; 44(4) : 1379-1391http://epg.science.cmu.ac.th/ejournal/Contributed Paper

Comparative Analysis of Protein Profiles of Toxic and Non-toxic Jatropha curcas LatexLucsame Gruneck [a], Eleni Gentekaki [a], Janthima Jaresitthikunchai [b], Teerawit Waratrujiwong [a], Sittiruk Roytrakul [b] and Siam Popluechai*[a][a] School of Science, Mae Fah Luang University, Chiang Rai, Thailand.[b] Genome Institute, National Center for Genetic Engineering and Biotechnology, National Science and

Technology Development Agency, Pathumthani, Thailand*Author for correspondence; e-mail: siam@mfu.ac.th

Received: 15 July 2016Accepted: 22 September 2016

ABSTRACT Latex proteins have been previously characterized in various plants including their indispensable roles. However, latex protein profiles are not well defined in Jatropha, neither of toxic nor non-toxic varieties. To compare the protein profiles between toxic and non-toxic latex we employed a proteomic approach using one-dimensional gel electrophoresis in conjunction with LC-MS/MS. Proteomic analysis of Jatropha latex revealed 421 proteins, of which 368 were shared between the two varieties. Functional classification showed that the most abundant proteins in both toxic and non-toxic Jatropha latex were related to cellular and metabolic processes, while some were associated with immune system processes. Furthermore, some unique proteins were classified as defense-related highlighting the special role of latex in the defense mechanism of Jatropha. Finally, we identified proteins belonging to the phenylpropanoid, carotenoid and flavonoid biosynthesis pathways. To the extent of our knowledge, this study provides the first comprehensive proteomic data for Jatropha latex.

Keywords: Jatropha curcas, latex, LC-MS/MS, one dimensional gel electrophoresis, proteomic analysis

1. INTRODUCTIONLatex is a milky-like fluid that accumulates

in laticifers, specialized cells that are widely distributed in roots, stems and leaves [1]. The primary role of latex is defensive, as it provides resistance to herbivorous insects due to its toxic nature [2, 3, 4]. Several studies suggest that the diverse secondary metabolites present in latex account for its apparent toxicity. These chemical compounds include terpenoids, alkaloids and phenolics. Nevertheless, the exact protein content of latex and their corresponding roles

remain unknown in the vast majority of latex-producing plants. Recently, proteomics studies of latex from various species of plants including Hevea brasiliensis revealed that several proteins are categorized as defense or pathogenesis related and are expressed under biotic and/or abiotic stress conditions [5, 6].

Jatropha curcas (hereafter referred to Jatropha) is a member of the latex producing plant family Euphorbiaceae. Jatropha has been recognized as a promising non-edible source for biodiesel

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production [7]. Moreover, the plant contains tumor-promoting chemical compounds [8]. Jatropha plants are categorized into toxic and non-toxic varieties based on the level of phorbol esters (PE) present; accessions with PE levels of less than or equal to 0.11mg/g or non-detected are considered non-toxic, while those with levels higher than 0.11mg/g are classified as toxic and [9, 10]. Nonetheless and regardless of level of PE, both varieties successfully utilize latex against herbivores. The interaction between Jatropha latex and herbivorous insects is not well understood. Proteomic studies of latex in various plants have been invaluable in not only uncovering the protein composition of latex but also in pinpointing potential drug targets [11, 12, 13]. However, no such investigation has ever been carried out in Jatropha.

Jatropha genus is unique in that it comprises both toxic and non-toxic latex varieties. It, therefore, provides an excellent study model system to examine comparative composition of latex and its role, if any, in plant defense and response against biotic and abiotic factors. Preliminary comparative studies of the two accessions using three matrices and MALDI-TOF MS analysis showed a clear separation of the peptides between toxic and non-toxic varieties [14, 15].

Several studies of proteomics have been carried out on Jatropha seeds as a source of renewable oil, yet has been conducted in latex [16, 17, 18]. In order to achieve a better understanding of the latex proteome, we employ one-dimensional gel electrophoresis (1DE), liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and bioinformatics analysis to investigate the protein profiles of toxic and non-toxic latex. We provide a comprehensive overview of the latex protein composition between the two accessions. Subsequently, we compare the latex proteomes of the two varieties and their

corresponding protein functions. In total, 421 proteins were identified in the latex of Jatropha.

2. MATERIALS AND METHODS 2.1 Collection of Jatropha Curcas Crude Latex and Protein Extraction

Latex was collected directly from 5-year old non-toxic (Mexico accession) and toxic variety (Chiang Mai accession) from Mae Fah Luang University germplasm, in three 1.5 ml microcentrifuge tubes for each accession. All samples were collected at the same time point and kept at -20 oC for a maximum of 48 hours. Subsequently, the samples were centrifuged at 13,680xg to remove particles. Two hundred μl of latex were obtained from each of the three biological replicates of toxic and nontoxic Jatropha. Then 200 μl of latex from the two accessions were pooled into two separate new 1.5 ml microcentrifuge tubes. At the end, there were two tubes each containing 600 μl of latex with one tube corresponding to each variety. Afterwards the latex samples were precipitated using acetone in a 2:1 ratio. The precipitates were harvested by centrifugation at 13,680xg for 10 min. The supernatant was discarded and the excessive amount of acetone was removed by evaporation. The precipitate was then dissolved in 0.5% SDS and assayed for protein concentration using Lowry’s assay [19].

2.2 Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE)

Sodium Dodecyl Sulfate gel electrophoresis used in this study was the vertical discontinuous slab system according to the modified method of [20]. Extracted latex proteins were re-suspended in SDS-loading buffer (600mM dithiothreitol (DTT), 10% sodium dodecyl sulfate (SDS), 0.4 M Tris-HCl pH 6.8, 0.03% bromophenol blue and 50% glycerol) by boiling for 5 min. Subsequently, samples were loaded on 12% SDS-PAGE gel and were run for 45 min at 100 V. The gel was stained by silver

Chiang Mai J. Sci. 2017; 44(4) 1381

staining method as follows: initially, the gel was fixed with fixing solution (50% methanol, 10% acetic acid and 0.05% formaldehyde) for 30 min. After that, the gel was washed twice with 35% ethanol for 5 min, sensitized with 0.02% sodium thiosulfate for 2 min, washed with milliQ water for 30 sec and stained with 0.2% silver nitrate for 20 min. Subsequently, the gel was immersed into developing solution (6% Na2CO3, 0.05% formalin and 0.0004% Na2S2O3) followed by immersion into stopping solution (25 mM EDTA) for 30 min.

2.3 In-gel Digestion and Peptide Sample Preparation

Protein bands were excised from the silver stained gel following the marker’s size. Each lane was cut into 13 segments (Supplementary Figure 1). The gel plugs were then subjected to

in-gel digestion as previously described [21]: briefly, the gel plugs were placed in 96-well plates and washed with sterile milliQ water and 25 mM ammonium bicarbonate (NH4HCO3). Afterward, the gel plugs were dehydrated with 100% acetonitrile (ACN) and reduced with 10mM DTT in 10 mM NH4HCO3 at room temperature for 1 h. After reduction, the proteins were alkylated with 100 mM iodoacetamide (IAA) in 10 mM NH4HCO3 at room temperature in the dark for 1 h. The gel plugs were then dehydrated with 100% ACN. For in-gel digestion of protein, 10 μl trypsin solution (10 ng/ml trypsin in 50% ACN/10mM ammonium bicarbonate) were added to gels and incubated at room temperature for 20 min followed by overnight incubation at 37oC. The remaining peptides in the plate were extracted with 30 μl of 50% ACN in 0.1% formic acid (FA) and incubated at room temperature on a shaking platform. The extracted peptides were pooled together and dried by vacuum centrifuge. The peptide samples were kept at -80oC for further analysis by LC-MS/MS.

2.4 Liquid Chromatography Coupled with Tandem Mass Spectrometry (LC-MS/MS)

Protein samples were analyzed by LC-MS/MS as described previously [22]. The dried protein samples were dissolved in 10 μL /well of 0.1% FA in LC-MS grade water and transferred to the vial for injection. Nanoscale LC separation of tryptic peptides was performed with an Ultimate 3000 LC System (Dionex, USA) coupled to ESI-Ion Trap MS (HCT Ultra PTM Discovery System, Bruker, Germany) with electrospray at a flow rate of 300 nl/min to a nanocolumn (PepSwift monolithic column 100 mm i.d. x 50 mm). Mobile phase A was 0.1% formic acid in water, and mobile phase B was 80% acetonitrile with 0.1% formic acid. A multistep gradient was used to elute peptides: a linear increase from 10%–70% B for 13 min, 90% B at 13–15 min followed by a decrease

1 2 3 5 6 7M

(kDa)97

66

45

30

20.1

14.1

Band 5

Band 4

Band 3Band 2

Band 1

Figure 1. 12.5 % SDS-PAGE gel stained with silver nitrate. Lanes 1 - 3 are non-toxic latex precipitated by acetone, Lane 4 is the protein standard marker (LMW-SDS Marker Kit, GE Healthcare) and Lanes 5 - 7 are toxic latex also precipitated by acetone.

Chiang Mai J. Sci. 2017; 44(4)1382

to 10% B at 15– 20 min. The mass spectra of the peptide fragments were acquired in data-dependent AutoMS mode with a scan range of 300-1500 m/z, 3 averages, and up to 5 precursor ions selected from the MS scan 50-3000 m/z. Spiked BSA was used as a reference standard for normalization of peptide intensity.

2.5 Protein Quantitation and Initial Identification

The DeCyder MS Differential Analysis software (DeCyderMS, GE Healthcare) was used for protein quantitation [23, 24]. The LC-MS raw data was converted in the appropriate format and the PepDetect module of the DeCyder software was used for automated peptide detection, charge state assignments, and quantitation based on the peptide ions signal intensities in MS mode. The analyzed MS/MS data from DeCyderMS was then submitted for a database search (against NCBI) using the Mascot software in order to identify candidate proteins (Matrix Science, London, UK,). Mascot was set up to search green plants only. Search parameters included; enzyme (trypsin) with up to three potential missed cleavage sites, fixed modification (carbamidomethylated cysteine), variable modification (methionine residues), peptide mass tolerance 1.2 Da, fragment mass tolerance 0.6 Da, peptide charge state (1+, 2+ or 3+). Identified proteins with at least 2 peptides present in MASCOT with a score corresponding to p<0.05 were considered a true match. Proteins with protein ID score >10 were selected for further analysis by bioinformatics tools.

2.6 Statistical Analysis of Latex ProteinsStatistical analysis was performed using

one-way ANOVA. P-values ≤ 0.05 by Student’s t-test were considered significant. The peptide intensities were analyzed using Paired-Samples t-test for determining significance level of those proteins in Jatropha latex.

2.7 Bioinformatics Analysis of Latex ProteinsBlast2GO (Version 3.0) [25] was employed

for the bioinformatics analyses. Initially, a BLAST search of the peptides was performed against the UniProtKB database (Release 2015_03) to obtain the Uniprot ID number and extract the corresponding protein sequence. Afterwards, the retrieved protein sequences were used as queries to search the Swiss-Prot database an E-value of 1e-3 was used as the threshold. Subsequently, Gene Ontology (GO) terms were mapped on the query sequences (after a BLAST search). Furthermore, the sequences were annotated using default parameters and afterward the annotation results were constructed as pie charts, and sequences abundance was shown. GO level distribution of each category was set at level 2 for general annotation. The roles of proteins were described in three categories: biological process, molecular function and cellular component. The number shown on the figure referred to the number of sequences per GO term.

To further identify specific pathways and explore protein functions we used the KOBAS (http://kobas.cbi.pku.edu.cn/home.do) [26, 27, 28] and DAVID (https://david.ncifcrf.gov) online platforms [29, 30]. A BLAST search of the 368 shared proteins was performed against the Arabidopsis thaliana proteome with a cutoff of 1-e10 and the corresponding A. thaliana proteins and TAIR identification numbers were obtained from The Arabidopsis Information Resource (https://www.arabidopsis.org). Two hundred and fifty shared protein sequences had a match and these were mapped by KOBAS against the KEGG pathway database and statistical significant pathways were retrieved at the default values (cut off FDR ≤ 0.05). The vast majority of input proteins were connected to metabolic pathways and biosynthesis of secondary metabolites. Additionally, three pathways were found to be significant at P ≤ 0.05; including purine metabolism, RNA

Chiang Mai J. Sci. 2017; 44(4) 1383

polymerase and pyrimidine metabolism. For protein functional annotation, the TAIR IDs were annotated using the DAVID Bioinformatics Database.

3. RESULTS3.1 Proteins Analysis by Gel Electrophoresis and LC-MS/MS Identification

The pattern of protein bands was similar between the two varieties with one notable difference: some distinct proteins were detected with molecular weight mass just below 30 kDa (band 3, Figure 1). These protein bands were very intense in the toxic accession (possessed two bands at this location, band 3) but almost invisible in the non-toxic sample (Figure 1) hinting that there might be some different proteins between these two varieties, not only in this segment but also the whole profile.

Proteomic analysis by MASCOT revealed 421 proteins present in Jatropha latex (Supplementary Table 1). The two varieties shared 368 proteins with 15 and 38 proteins being unique in toxic and non-toxic latex respectively (Figure 2, Table 1). Out of 15 identified proteins, Patellin-3 was detected in toxic latex but was absent in the non-toxic sample. Other known proteins present in both varieties were involved in binding and catalytic activity.

3.2 Distribution of Peptides from Toxic and Non-toxic Varieties

Distribution of unique peptides by mass of the two varieties (toxic and non-toxic) is shown in Figure 3. The range of the molecular mass of peptides in the non-toxic variety is wide and extends from 400-2,400 Da, while that of the toxic accession is much narrower falling lower than 1,200 Da and ranging between 500-1,100 Da. Statistical analysis using the paired samples t-test showed that there was a statistically significant difference in the intensity of peptide between toxic and non-toxic latex with the mass range 700-1,500 Da and 2,200

Da, except 1,100 Da (data not shown).

3.3 Protein Function AnnotationTo represent functional classification of

proteins in Jatropha latex, all 421 identified proteins in toxic and non-toxic were categorized according to Swiss-Prot database. Of the 421 proteins, 250 had a functional annotation, whereas 118 were unknown. The annotated proteins were mainly related to cellular, metabolic and single-organism processes as well as response to stimulation, biological regulation and cellular component biogenesis. Most proteins were associated to binding and catalytic activity and distributed in organelle and cell membrane.

Functional classes of the unique proteins from toxic and non-toxic latex were compared separately. Gene Ontology (GO) annotations at the level of biological process, molecular function and cellular component were carried out (Figure 4). At the level of biological process, the major functions of proteins were cellular, metabolic and response to stimulus with all three categories being more abundant in non-toxic latex. Proteins associated with rhythmic process, reproduction, signaling, growth and localization were present only in non-toxic latex. At the molecular function category, proteins related to transporter activity and binding were found in both varieties, however, those of binding category were more abundant in the toxic variety. Notably, proteins that were assigned in the catalytic activity, molecular function regulator and protein tag activity were only present in the non-toxic variety (Figure 4). Analysis at the level of the cellular component, showed a similar distribution among the components with the majority of the proteins being distributed in the cell and the organelle in both varieties (Figure 4).

Significant functional annotations of the shared proteins were retrieved from the DAVID Bioinformatics Database (cut off P ≤ 0.05). There were 230 proteins (TAIR IDs)

Chiang Mai J. Sci. 2017; 44(4)1384

Table 1. Identification and annotation of unique proteins in toxic and non-toxic Jatropha latex from a total of 421 identified proteins.

Toxic latex

NCBI Database ID No.

Protein name Species Protein ID Score

UniProt data accession No.

gi|326487826 predicted protein Hordeum vulgare subsp. Vulgare 18.50 F2D3T1

gi|228017374 RNA polymerase beta’’ chain Larix occidentalis 19.80 C3W1R8

gi|242039831 hypothetical protein Sorghum bicolor 16.72 C5WNA3

gi|18424457 uncharacterized protein Arabidopsis thaliana 38.10 Q94B75

gi|168047369 predicted protein Physcomitrella patens 11.12 A9TBX9

gi|15218383 patellin-3 Arabidopsis thaliana 16.29 Q56Z59

gi|15240840 exonuclease family protein Arabidopsis thaliana 15.11 Q9FLR0

gi|225428883 uncharacterized protein Vitis vinifera 14.77 D7UC14

gi|303279500 predicted protein Micromonas pusilla CCMP1545 16.82 C1MSF1

gi|4309750 hypothetical protein Arabidopsis thaliana 15.99 Q9ZQL5

gi|147775536 hypothetical protein Vitis vinifera 21.84 A5AVE7

gi|15219078 histone H2A protein 9 Arabidopsis thaliana 24.79 Q9C944

gi|168071054 predicted protein Physcomitrella patens 14.37 A9U855

gi|226532516 LOC100282842 Zea mays 34.88 B6TBW8

gi|297819760 hypothetical protein Arabidopsis lyrata subsp. lyrata 21.19 D7LTH8

Non-toxic latex

NCBI Database ID No.

Protein name Species Protein ID score

UniProt data accession No.

gi|15239070 FAD/NAD(P)-binding oxidoreductase family protein Arabidopsis thaliana 11.51 Q9FLC2

gi|115487910 Os12g0230100 Oryza sativa Japonica Group 13.22 Q2QVG9

gi|159479676 cation channel protein Chlamydomonas reinhardtii 35.70 A8J8K6

gi|115488640 Os12g0497400 Oryza sativa Japonica Group 15.98 Q0IN89

gi|147770970 hypothetical protein Vitis vinifera 14.63 A5B5E0

gi|147811095 hypothetical protein Vitis vinifera 12.66 A5BH12

gi|147820741 hypothetical protein Vitis vinifera 15.62 A5B3L0

gi|15217957 CC-NBS-LRR class disease resistance protein Arabidopsis thaliana 18.61 Q8W3K3

gi|15230914 cyclin-related protein Arabidopsis thaliana 17.49 Q9SJT3

gi|159487975 predicted protein Chlamydomonas reinhardtii 32.84 Q9LJN1

gi|168054597 predicted protein Physcomitrella patens 17.99 A8I9M5

Chiang Mai J. Sci. 2017; 44(4) 1385

Non-toxic latex

NCBI Database ID No.

Protein name Species Protein ID score

UniProt data accession No.

gi|225217013 exopolygalacturonase precursor Oryza coarctata 24.32 A9TM65

gi|242056311 hypothetical protein Sorghum bicolor 14.98 C0JAB9

gi|255537972 DAZ-associated protein, putative Ricinus communis 12.29 C5XP64

gi|255540469 cytochrome P450, putative Ricinus communis 13.86 B9R6V8

gi|297836268 hypothetical protein Arabidopsis lyrata subsp. lyrata 12.25 B9RAS4

gi|302766215 hypothetical protein Selaginella moellendorffii 16.21 D7L6F8

gi|302821735 hypothetical protein Selaginella moellendorffii 15.67 D8R5W2

gi|37574476 ribulose 1,5-bisphosphate carboxylase/oxygenase Pogonatum nipponicum 13.51 D8TAA4

gi|4063751 putative ABC transporter Arabidopsis thaliana 19.79 Q6YLP8

gi|63259081 Cys2/His2 zinc-finger transcription factor Silene latifolia 15.44 Q9ZUU9

gi|115450323 Os03g0116700 Oryza sativa Japonica Group 10.98 Q4U315

gi|168043761 predicted protein Physcomitrella patens 13.25 Q10SN2

gi|159472304 predicted protein Chlamydomonas reinhardtii 15.99 A9T6V0

gi|308811713 Vacuolar sorting protein VPS33/slp1 (Sec1 family) (ISS) Ostreococcus tauri 18.03 A8IYX7

gi|145354667Ribosomal protein L21, component of cytosolic 80S ribosome and 60S large subunit

Ostreococcus lucimarinus CCE9901 16.34 Q2QTL5

gi|125857787ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit

Treichelia longebracteata 20.28 A4S8D5

gi|147774645 hypothetical protein Vitis vinifera 13.11 A2VAL3

gi|147787085 hypothetical protein Vitis vinifera 10.69 A5BAC2

gi|168025157 GAPN Physcomitrella patens 18.58 A5AKH2

gi|224064031 predicted protein Populus trichocarpa 22.71 A9SFH2

gi|224576639 At1g03560-like protein Capsella grandiflora 18.90 B9GQ94

gi|297723967 Os05g0320650 Oryza sativa Japonica Group 27.78 C0JC31

gi|32489477 OSJNBa0028M15.23 Oryza sativa Japonica Group 7.80 C7J341

gi|147816786 hypothetical protein Vitis vinifera 14.43 A5CAU4

gi|145349658 predicted protein Ostreococcus lucimarinus CCE9901 17.07 A4S212

gi|15220940 G1 to S phase transition protein Arabidopsis thaliana 13.62 Q8L835

gi|255569048 leucine-rich repeat-containing protein, putative Ricinus communis 16.23 B9SHM4

Table 1. Continnued.

Chiang Mai J. Sci. 2017; 44(4)1386

368 3815

Only in non-toxicOnly in toxic

Both in toxic and non-toxic

Figure 2. Venn diagram depicting the number of shared and unique proteins in toxic and non-toxic Jatropha curcas latex.

0

1

2

3

4

5

6

7

Freq

uenc

y in

late

x

Mass (Da)

Toxic

Non-toxic

Figure 3. Distribution of unique peptides from toxic and non-toxic latex of Jatropha curcas according to mass (Daltons).

that significantly matched the DAVID record (Supplementary Table 2). GO enrichment of these TAIR IDs categorized them into biological process (BP), molecular function (MF) and cellular component (CC) (Figure 5). A total of 59.1% of proteins were involved in BP, 66.5% in MP and 55.7% in CC. In the BP category, 11% of GO annotations were related to response to abiotic stimulus, 15% were involved in various stress responses (e.g. salt, osmotic and cellular stress), while 10% involved in post-embryonic development and

9% were assigned to reproductive developmental process. Other proteins in this category were associated with DNA metabolic process (5%) and intracellular transport (5%). In the MF category, over 3/4 of GO annotations were connected to nucleotide binding (78%), while several proteins were related to ATP binding (9%), ATPase activity (5%), helicase activity (1%). In the CC category, the largest groups of proteins were predicted to localize in photosynthesis organelle accounting for 50%. In addition, the second and third groups constituted by proteins localizing in the envelope (11%) and mitochondrion (10%). Other groups were localized in organelle membrane (6%) and endoplasmic reticulum (4%).

Mapping against the KEGG database and clustering in DAVID identified proteins belonging to multiple pathways, most especially to biosynthesis of secondary metabolites and metabolism (Supplementary Table 1). More specifically, components of the phenylpropanoid, carotenoid and flavonoid biosynthesis pathways were identified.

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T/BP

T/MF

T/CC

NT/BP

transporter activity, 4

binding, 27

protein tag, 1

molecular function

regualtor, 1

catalytic activity, 20

NT/MF

NT/CC

symplast, 2

organelle, 6

nucleiod , 1

membrane, 3

cell, 6

extracellular region, 3

macromolecular complex, 2

symplast, 7

organelle, 25

cell junction, 7

membrane, 18

cell, 28

extracellular region, 4

macromolecular complex, 9

single-organism process , 4

response to stimulus , 4

reproductive process , 2

multicellular organismal process , 3

metabolic process , 5biological

regulation , 3

cellular component

organization biogenesis , 3

cellular process , 5

developmental process , 4

immune system process , 1

locomotion , 2single-organism

process , 28

response to stimulus , 19

reproductive process , 13

multicellular organismal process , 19

multi-organism process, 13

metabolic process , 28biological

regulation , 19

cellular component organization

biogenesis , 20

cellular process , 28

developmental process , 19

immune system process

, 5

locomotion , 3signaling, 10

rhythmic process, 1growth, 9

localization, 15reproduction, 10

transporter activity, 1

binding, 4

Figure 4. Functional annotation of unique proteins in toxic (T) and non-toxic (NT) Jatropha curcas latex classified by biological process (BP), molecular function (MF) and cellular component (CC). The annotations were assigned with the statistical package GO.

4. DISCUSSIONLatex proteins have been studied in many

plants [11, 12] including the economically important crop H. brasiliensis [13]. However, to our knowledge, no study has examined protein profile in Jatropha latex. Herein, we provide the first analysis and comparison between the proteomic profiles of toxic and non-toxic latex varieties using LC-MS/MS and bioinformatics analyses.

In our study, the SDS-PAGE banding patterns of the three replicates within toxic (Chiang Mai) and non-toxic (Mexican) Jatropha varieties were virtually identical, indicating a low level of intra-accession polymorphism of protein patterns. The inter-accession banding patterns were mostly similar however there were some notable differences in the banding intensities. This prompted us to perform LC-MS/MS analysis to examine whether these

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differences are also reflected in the proteomic profiles. Four hundred and twenty one latex proteins were identified, 368 of which are shared between the two accessions. Compared with previous latex proteome works, 587 proteins were detected in lettuce, 160 non-redundant proteins in papaya and a total of 234 proteins in H. brasiliensis [3, 11]. Noticeably, the proteomic analysis in Jatropha seeds indicated nearly 2,000 proteins including proteins related to toxicity, like curcins [17, 18]. On the contrary, there was no protein related to toxic components found in latex, for it is generally reserved in other parts of the plants like endosperm and leaves [31] suggested that the proteins related to toxic components might not localized or synthesized in the latex instead of transport throughout the plants.

We performed functional annotation of the shared and the unique proteins at the biological process, molecular function and

cellular component hierarchical levels. Our bioinformatics analyses indicated that most of the shared proteins in Jatropha latex are involved in cellular and metabolic processes. This is similar to other studies, whereby metabolic genes constitute the majority, reflecting the abundance of biosynthetic processes present in all multicellular organisms [11]. As Jatropha is a latex-producing plant, latex synthesis is an indispensable process. Herein, many of shared proteins were involved in ATP binding and ATPase activity. This is consistent with the observation of ATPase in H. brasiliensis latex, whereby the enzyme is a key player during latex biosynthesis [32].

Moreover, we found that though the two Jatropha accessions share proteins associated with binding and transporter functions, however both of these categories are more strongly represented in the non-toxic variety. Furthermore, the non-toxic accession has an

Molecular function

Cellular component

Biological processresponse to

abiotic stimulus11%

post-embryonic development

10%

reproductive developmental

process9%

reproductive structure

development9%

cellular response to stress

5%response to osmotic stress

5%intracellular transport

5%

response to salt stress5%

DNA metabolic process

5%

others36%

nucleotide binding

78%

ATP-binding9%

ATPase activity5%

helicase activity1%

iron ion binding3%

Others3%

chloroplast50%

mitochondrion10%

organelle membrane

6%

envelope11%

chloroplast envelope

9%

endoplasmic reticulum

4%

Figure 5. GO enrichment of TAIR IDs categorized into biological process (BP), molecular function (MF) and cellular component (CC) using DAVID Bioinformatics Database.

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abundance of proteins associated with catalytic activity, while these are absent in the toxic. This implies an expanded repertoire of enzymes and corresponding catalytic functions, possibly reflecting specialized mechanisms to deal with external and internal cues.

Nonetheless, some proteins were associated specifically with immune system processes and defense response mechanisms. These mechanisms are initiated upon contact with invading organisms via signal transduction cascades [33]. One such effector is the nucleotide binding (NB) – ARC protein of the NB domain, which was found in both toxic and non-toxic latex. NB-ARC domain is believed to act as a molecular switch, which defines the R-protein activity [34].

Several of the shared proteins were assigned to pathways associated with maintenance of the cell as well as secondary metabolite biosynthesis, among those are C-8,7 sterol isomerase (EC:5.3.3.5) and violaxanthin de-epoxidase (EC:1.23.5.1). These two enzymes are involved in the pathway of sterol biosynthesis for regulating stomatal development [35] and xanthophyll cycle (carotenoid biosynthesis) [36] respectively. In general, secondary metabolites are responsible for protection and for eliciting response to biotic and abiotic stress factors. Many of the shared proteins were also located in the mitochondria and chloroplast organelles. This finding is consistent with previous proteome analysis of opium poppy and lettuce latex, which found that latex proteins were also abundantly located in the plastids and mitochondria [11, 12]. Markedly, energy produced by mitochondria (in laticifer) is required for the import of the sucrose precursor in the latex biosynthesis pathway along with the involvement of ATPase activity [37].

In addition to secondary metabolites synthesis, some proteins were assigned to the phenylpropanoid and flavonoid biosynthesis pathway. One of the proteins in phenylpropanoid

biosynthesis belongs to the family of peroxidase (EC:1.11.7), some of which respond to wounding, pathogen attack and oxidative stress. Another was matched to ferulate-5-hydroxylase (EC:1.14.-.-) associated in lignin biosynthetic process. Noticeably, these metabolisms are requisite for cell wall protection [38]. Besides, a key enzyme in flavonoid biosynthesis, chalcone synthase (EC:2.3.1.74) was also observed in this mandatory pathway, as its regulation mechanism in salt tolerance was investigated in soybean and tobacco [39].

Regarding the unique proteins, the two varieties share the same basic processes at all three hierarchical levels. Interestingly, some categories are more represented in the non-toxic than the toxic accession. One of the unique proteins of toxic latex is Patellin-3 (PATL3), which plays a role in plant defense against pathogens [40], as well as, biotic and abiotic stresses [1, 41].

For the non-toxic latex, we identified stand-alone LRR domains, but also attached to CC-NBS, along with a protein that is associated with wounding response (Os05g0320650). All of these proteins are members of the R gene family, which plays a crucial role in plant defense. The expression of LRR is regulated by wounding and pathogen infection and is involved in activating protective immune signaling, the primary warning process in plants [42]. The LRR domain can attach to other protein domains including the NBS class disease resistance proteins and Coiled-coil (CC) domain. Interaction of these domains with the LRR domain enhances specificity of the resistance mechanism and mediate signaling and protein interaction during recognition of pathogens. This may further activate defense response to the effectors [34, 43, 44]. The differences in the unique proteins between the two accessions suggest differential responses to environmental, stress and immune factors.

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5. CONCLUSIONThe proteome profiles of toxic and non-

toxic Jatropha curcas latex were generated and compared. The two accessions shared many proteins but they also had a few that were unique to each accession. Functional annotation analysis indicated that some unique latex proteins are defense-related proteins highlighting the special role of latex in plant defense mechanism. Our study provides baseline data for further study on the biology and synthesis of secondary metabolite. Furthermore, this proteome data will be useful for future research on genetic improvement of Jatropha for desirable traits.

ACKNOWLEDGEMENTWe are grateful to Miss Atchara Paemanee

for providing facilities, performing LC-MS/MS and data analysis. We also appreciate to Mr. Yodying Yingchutrakul for preparation of samples prior to LC-MS/MS analysis.

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