PROTEOMICS OF THE RED ALGA, GRACILARIA CHANGII (GRACILARIALES,RHODOPHYTA)1

Pooi-Fong Wong

Department of Medical Microbiology, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia

Li-Jing Tan

Laboratories of Organismal Biosystems, Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita,

565-0871 Osaka, Japan

Hannah Nawi

Malaysia Biotechnology Corporation, Level 23, Menara Naluri, 161, Jalan Ampang, 50450 Kuala Lumpur, Malaysia

and

Sazaly AbuBakar2

Department of Medical Microbiology, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia

The application of proteomics in alga research isstill quite limited. The present report describes theestablishment of the proteome of a red alga of eco-nomic importance, Gracilaria changii (Xia et Abb-ott) Abbott, Zhang et Xia. Initially, four proteinextraction methods including direct precipitationby trichloroacetic acid/acetone, direct lysis usingurea buffer, Tris buffer, and phenol/chloroform ex-traction were compared for their suitability to gen-erate G. changii proteins for two-dimensional gelelectrophoresis (2-DE). The phenol/chloroform pro-tein extraction method gave the best 2-DE resolu-tion of the proteins. Using these 2-DE gels and massspectrometry, several proteins including pigmentproteins, metabolic enzymes, and ion transporterswere identified. These findings highlight the poten-tial of using proteomic approaches for the investi-gation of G. changii protein function.

Key index words: gracilaria changii; mass spectro-metry; proteomics; rhodophyta; two-dimensionalelectrophoresis

Abbreviations: 2-DE, two-dimensional electropho-resis; CHAPS, 3- [(3-cholamidopropy/dimethy-am-monia]-1-propanesulfonate; DTT, dithioethreitol;Exp, experimental; IEF, isoelectric focusing; IPG,immobilized pH gradients; MALDI-ToF, matrix-as-sisted laser desorption ionization-time of flight; MS,mass spectrometry; MS/MS, mass spectrometry/mass spectrometry, TBP, tributylphosphine; TCA,trichloroacetic acid

INTRODUCTION

The Rhodophyta is a large, morphologically diversegroup of algae consisting of more than 700 genera and6000 species (Chapman et al. 1998). Among these redalgae, the genus Gracilaria (Gracilariales) in particularhas become an important commercial agarophyte be-cause it contributes to about 70% of the raw materialsrequired for the production of hydrocolloid agar(McHugh 2002). There are more than 40 differentspecies of Gracilaria distributed worldwide (Phang1994). At least 20 species are present in Malaysia withG. changii (Xia et Abbott) Abbott, Zhang et Xia beingone of the most abundant (Phang et al. 1996, Lim andPhang 2004). This relatively bushy alga is purple todark brown in color, and is distinguished by abruptconstrictions at the base of the lateral branches, form-ing a slender stipe (Phang 1994). The agar found inthe cell walls of this alga is used in food and fertilizers,and in industrial, scientific, and medical applications(Indergaard 1983). In Malaysia, G. changii is also usedas food, as a local delicacy, and as a food source forshellfish aquaculture (Phang and Lewmanomont2001). In comparison with many common vegetables,the presence of high levels of fiber, minerals, and ome-ga fatty acids, and moderate concentrations of lipidsand proteins, makes G. changii suitable as a potentialhealth food (Norziah and Chio 2000). Combined withits high tolerance to harsh conditions and a wide rangeof salinities, cultivation of this species shows great eco-nomic potential (Phang 1998). Taxonomic difficultiesassociated with a shortage of knowledge of its repro-ductive features and a high degree of morphologicalvariability have hampered significant progress in ourunderstanding of G. changii, particularly with respectto specific protein functions.

The application of proteomic tools has helped tounravel the functions of many proteins in a number of

1Received 20 May 2005. Accepted 31 October 2005.2Author for correspondence: e-mail: sazaly@ummc.edu.my.

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J. Phycol. 42, 113–120 (2006)r 2006 Phycological Society of AmericaDOI: 10.1111/j.1529-8817.2006.00182.x

higher plants including Arabidopsis thaliana L. (Heynh.)(Kamo et al. 1995, Gallardo et al. 2001, 2002), Oryzasativa L. (Koller et al. 2002, Komatsu et al. 2004, Ko-matsu and Tanaka 2005), and Zea mays L. (Higginbot-ham et al. 1991, Porubleva et al. 2001, Mechin et al.2004). The proteins profiles of at least five differenttissues (seed, leaf, root, stem, and callus) of A. thalianawere presented by Kamo et al. (1995) and in subse-quent proteomic studies, specific sets of proteins in-volved in the different germination stages includingthe seed storage proteins, catabolic enzymes, defensemechanism proteins, and proteins with novel roles ingermination (Gallardo et al. 2001, 2002) were identi-fied. In algal research, proteomics studies on subcel-lular compartment protein expressions such as thetransmembrane thykaloids and chloroplast of thegreen algae Chlamydomonas reinhardtii P.A. Dangeard(Yamaguchi et al. 2002, Stauber et al. 2003), cell wall ofHaematococcus pluvialis Flotow (Wang et al. 2004), andmitochondria of the colorless alga Polytomella species(van Lis et al. 2005) have been reported. Comparativeanalysis for detection of genetic diversity of differentstrains, comparison of different genotypes for phylo-genetic analysis, and mutant characterization were alsomade possible using proteomics technologies(Thiellement et al. 1999, Jacobs et al. 2000). Compar-isons between species and strains of healthy and dis-eased plants could enable identification of strain-specific proteins or disease-associated proteins. Theoutcome of such studies would provide a better un-derstanding of the biosynthetic pathways useful per-haps for crop quality improvement. The success ofthese studies, however, relies on the critical componentof proteomics, which involves high-resolution separa-tion of proteins using two-dimensional electrophoresisand identification of proteins using mass spectrometry(MS). The former would require that representativeproteins extracted from tissues and the proteins aresolubilized in buffer appropriate for isoelectric focus-ing (IEF) and MS. In the present study, methods forextraction of G. changii proteins and separations bytwo-dimensional electrophoresis (2-DE) were optimi-zed to enable establishment of the G. changii proteome.This was followed by an initial attempt to annotate theproteome using MS.

MATERIALS AND METHODS

Sample Preparation. The seaweed G. changii was collectedfrom the mangroves of Morib, Selangor, west coast of Penin-sula Malaysia, in late February 2003. The seaweeds werecarefully chosen, removing those suspected of having endo-parasitic infections. Epiphytes, sand and silt were removed bysuccessive washing in sterile seawater using a soft brush witha final rinse in distilled water. The samples were then sepa-rately sonicated in a water bath sonicator and the individualspecimens were separated into single use packs, labeled, andkept frozen at � 701 C until required. For protein samplepreparation, the frozen seaweed was ground to a fine powderwith a mortar and pestle in liquid nitrogen. Approximately100 mg of the resulting powder was placed into a 1.5 mL tubefor a single extraction. Several extractions were performed to

obtain sufficient proteins for 2-DE. Proteins were extractedusing Tris buffer, lysis buffer, trichloroacetic acid (TCA)/ace-tone precipitation, or phenol/chloroform, as shown schemat-ically in Fig. 1. For Tris buffer protein extraction, theseaweed powders were mixed with buffer containing40 mM Tris-HCl pH 8.8, 5 mM MgCl2 and sonicated in anice water bath for 15–30 min. The suspension was then centri-fuged at 20,000g for 30 min at 41 C to obtain the supernatant.Sodium dodecyl sulfate was added to the supernatant to a finalconcentration of 1%, followed by 0.02 unit �mL�1 endo-nuclease (E8263, Sigma Aldrich, St. Louis, MO, USA). Themixture was then centrifuged at 20,000g for 10 min at 41 C,and the resulting supernatant was collected. For lysis bufferprotein extraction, the seaweed powder were treated with 8 Murea, 4% w/v 3- [(3-cholamidopropy/dimethy-ammonia]-1-propanesulfonate (CHAPS) (Pierce, Rockford, IL, USA),40 mM tris, 0.2% Bio-Lyte 4–7 (Bio-Rad Laboratories, Her-cules, CA, USA), and 2 mM tributylphosphine (TBP) (Bio-RadLaboratories). The mixture was sonicated as above. Endonuc-lease (0.02 unit �mL�1) was then added to the sample and itwas incubated overnight at 41 C. Following the incubation, thesample was centrifuged at 40,000g for 1 h at 41 C and thesupernatant was reserved. For protein precipitation usingTCA/acetone, the powder was mixed with a pre-chilled(� 201 C) solution of 10% TCA in acetone with 20 mM di-thioethreitol (DTT). Proteins were precipitated in TCA over-night at � 201 C; then, the sample was sedimented at 40,000gat 41 C. The resulting protein pellet was washed twice with ice-cold acetone containing 20 mM DTT. The pellet was thendried in a vacuum concentrator and resolubilized in a buffer(50 mL/mg of dried pellet) containing 9.5 M urea, 1.25% SDS,0.5% DTT, 6% CHAPS. TRI reagent (Molecular ResearchCenter Inc., Cincinnati, OH, USA) containing phenol andguanidine-isothiocyanate was used for phenol/chloroformprotein extraction. The reagent was added to the seaweedpowder (1 mL/100 mg), and proteins were extracted followingthe protocol recommended by the manufacturer (Fig. 1).Protein pellets were washed, dried, and resolubilized in40 mM Tris buffer pH 8.8 containing 8 M urea, 4% CHAPS,and 2 mM TBP.

Two-dimensional electrophoresis. The immobilized pH gradi-ents (IPG) strips [pI 3–10, 4–7; 7 cm and 18 cm (AmershamBiosciences, Uppsala, Sweden) and pI 5–8; 7 and 17 cm (Bio-Rad Laboratories)] were rehydrated with the protein samplesovernight at 50 V at 201 C in a total volume of 125 mL (7 cmstrips) and 350 mL (17–18 cm strips) of rehydrating buffer(8 M urea, 2% CHAPS, 0.0007% of bromophenol blue,18 mM DTT, 0.8% ampholytes of pH 3–10 (Amersham Bio-sciences). A total of 100 and 500 mg of protein was used forthe 7 and 17–18 cm IPG strips, respectively. IEF was per-formed at 201 C using the following parameters for 17–18 cmstrips: 200 V for 200 V/h, 500 V for 500 V/h and 1000 V for1000 V/h at gradient mode, 8000 V for 4000 V/h, and 8000 Vfor 40,000 V/h at step and hold mode; for 7 cm strips similarparameters were used, except for step 4, in which 4000 V wasapplied for 16,000 V/h. Proteins were focused with IPG phor(Amersham Biosciences). After IEF, the IPG strips wereequilibrated in equilibration buffer I (6 M urea, 2% SDS,0.375 M Tris-HCl, 20% glycerol, and 65 mM DTT) followedby equilibration buffer II (6 M urea, 2% SDS, 0.375 M Tris-HCl, 20% glycerol and 260 mM iodoacetamide) for 15 mineach at room temperature. The gel strips were then rinsed inwater and equilibrated for 2 min in SDS-PAGE running buff-er. After the equilibration, excess liquid on the gel strips wasblotted dry with a hand towel. The gel strip was positioned ontop of a vertical 15% polyacrylamide gel, held in place by 1%agarose gel, and electrophoresed at a constant current of15 mA for 1 h, 17.5 mA for 1 h, and finally 20 mA for 6.5 h pergel. The gels were stained with either silver stain (Blum et al.

P. -F. WONG ET AL.114

1987) or hot Coomassie Blue (Westermeier and Naven 2002).The stained gels were then imaged with an Epson 1600 ProScanner (Nagano, Japan). Images from triplicate gels of the17–18 cm strips of pH 4–7 and 5–8 were analyzed quantita-tively for differentially expressed proteins using PDQUESTversion 7.1.1 (Bio-Rad Laboratories). Prior to protein spotsdetection, images were filtered to remove the backgroundnoise and all gels were aligned, normalized, and matched.

Peptide Mass Fingerprinting. Coomasie blue-stained pro-tein spots were excised from the gel using a spot picker (Am-ersham Biosciences). The gel plugs were destained, trypsin-digested, and the peptides were extracted using an automat-ed spot digester (Amersham Biosciences). For MS analysis,the peptides were mixed with a saturated matrix (a-cyano-4-hydroxycinnamic acid (LaserBio Labs, Sophia-Antipolis Ce-dex, France) prepared in 0.5% trifluoroacetic acid and 50%acetonitrile) in a 1:1 ratio. The matrix-peptides mixture(0.5 mL) was spotted onto the sample plate for MS. Peptidemasses were derived following ionization using matrix-assist-ed laser desorption ionization-time of flight MS (MALDI-ToF) (Amersham Biosciences). Protein identifications werethen performed using MASCOT (http://www.matrixsci-ence.com) and ProFound (http://www.unb.br/cbsp/pagini-

ciais/profound.htm) to query against the NCBI proteindatabase of Eukaryotes (Profound) or Other Eukaryotes(MASCOT). MASCOT uses a probability-based MOWSEscore. The total score is the absolute probability that the ob-served match is a random event. The match is significant ifthe score is greater than 56 (Po0.05). The proteins areranked with decreasing probability of being a random matchto the experimental data (Perkins et al. 1999). Profound usesBayesian theory to rank the protein sequences in the data-base by their probability of occurrence. A Z score is used as anindicator of the quality of the search results where a Z scorecorresponds to the percentile of the search in the randommatch population. A score of 1.65 or lower indicates that thecandidate is likely to be a random match (Zhang and Chait2000). The following parameters were considered during thesearch: monoisotopic masses, iodoacetic acid modification ofcysteine, oxidation of methionine, mass tolerance of 0.5 or1 Da, and one missed cleavage for trypsin. To denote a pro-tein as unambiguously identified, the hit must have the high-est score or must be significant (Po0.05). The candidateprotein is ranked first together with the family of similarprotein and belonging to the alga family. In cases wherethere is no significant match (due to not enough mass value

FIG. 1. Schematic diagram ofthe protein extraction methodsfor Gracilaria changii.

PROTEOME OF GRACILARIA CHANGII 115

or inaccurate mass), a best match is reported. The best matchmust belong to the alga family, the coverage of the protein bythe matching peptides must have a minimum of 14% with atleast four matched peptides, and the molecular mass and pIof the hit are close to the experimental mass and pI. When-ever necessary, MS-Digest (http://prospector.ucsf.edu/ucsfhtml4.0/msdigest.htm) was used to perform in silico di-gestion to assist peptide matching and to obtain theoreticalmasses and pH of the identified proteins.

RESULTS

The red seaweeds have tough cell walls that containcellulose fibrils embedded in an extensive gelatinousmatrix composed of a variety of sulfated galactose pol-ymers (Michel et al. 2003). The presence of these fi-brillar polymers renders protein extraction difficult,and the polymers also cause interference during IEF.All four protein extraction methods examined in thepresent investigation resulted in different quantity andquality of protein yield. The Tris buffer pH 8.8 proteinextraction yielded the most protein (24.7mg protein/gof seaweed powder), followed by lysis buffer proteinextraction (8.32mg/g), phenol/chloroform extraction(5.22mg/g), and TCA/acetone precipitation (3.00mg/g). The 2-DE gels resolution of the Tris buffer pH8.8-extracted, lysis buffer-extracted, and TCA/acetone-precipitated proteins, however, were poor (Fig. 2a).The resulting 2-DE gels showed mainly unfocusedproteins, with a limited number of resolved proteinspots and the presence of vertical and horizontalstreakings. Proteins extracted using the phenol/chlo-roform method, however, were very well resolved by 2-DE (Fig. 2b). Defined protein spots were noted, andthe gels were relatively clean with minimal streaking.Based on this observation, the phenol/chloroform pro-tein extraction method was used for all the subsequentprotein sample preparations.

The G. changii proteome was successfully estab-lished using the 7 cm IPG strips of pH range 3–10,4–7, and 5–8 (Fig. 3a–c). Improved protein separationwas observed with the narrower pH (i.e. pH 4–7 and5–8) IPG strips as compared with the pH 3–10 IPGstrips. Hence, for analytical purposes, the proteinswere focused using 17–18 cm IPG strips of pH 4–7and pH 5–8. Approximately 424 protein spots weredetected in the pH 4–7 gels and 186 proteins spots inpH 5–8 gels. The 2-DE protein profile consisted of

mostly protein spots with a molecular mass lower than66.4 kDa, and was mainly distributed in a pH range of3–7. A composite gel image was obtained by mergingthe two pH range gel images through exclusion ofoverlapping protein spots. Approximately 516 proteinspots were detected in the merged image. MS was thenperformed as an initial attempt to identify the proteins.Forty-two well-defined protein spots were chosen, ex-cised, digested, and subjected to MALDI-ToF MS. Thepeptides masses were queried against the availablepublic protein databases. Here, we report 15 proteinspots that yielded significant matches (Table 1). Two ofthese protein spots (SSP no. 3301 and 3203) werematched to a R-phycoerythrin a subunit, probably be-cause these are isomers that migrated close to eachother as visualized in the Coomasie blue-stained gel.The remaining protein spots resulted in insignificantmatches that would require other means of identifica-tion such as mass spectrometry/mass spectrometry(MS/MS) and amino-acid sequencing. The 15 peptidesidentified matched to proteins of Gracilaria speciessuch as Gracilaria tenuistipitata var. liui Zhang et Xia(six matches), Gracilaria gracilis (Stackhouse) Steentoft,Irvine et Farnham (three matches), and Gracilariopsislemaneiformis (Bory de Saint-Vincent) E.Y. Dawson, Ac-leto et Foldvik (single match). The remaining identi-fied proteins matched proteins belonging to other redalgae such as the Porphyra pulchra Hollenberg (Bangi-ales), Porphyridium aerugineum Geitler (Porphyridiales),Cyanidioschyzon merolae strain 10D (Cyanidiales), andthe Cryptophyta (Guillardia theta Hill et Wetherbee).There were no matches to any G. changii protein, prob-ably due to the lack of G. changii genomic sequences inthe public databases.

DISCUSSION

Two-dimensional gel electrophoresis and MS havebecome important tools for protein studies in manyfields. The applications of these tools in alga researchwould certainly complement ongoing alga genomeprojects such as the brown macroalga Ectocarpus sili-culosus (Dillwyn) Lyngbye sequencing initiatives by theMarine Genomic Europe Network. The present studyis aimed at developing a model multicellular alga pro-teome using the red seaweed, G. changii. Several pro-

FIG. 2. Two-dimensional gels of Gracil-aria changii proteins. G. changii proteinswere extracted using (a) Tris buffer pH8.8 and (b) the phenol/chloroform meth-od. The isoelectric focusing (IEF) was per-formed on 7 cm immobilized pH gradientsstrips, pI 4–7, using 100mg protein extract.The proteins were visualized by silverstaining. Horizontal axis of the gel showsprotein separation by IEF point, and thevertical axis shows protein separation bymolecular mass.

P. -F. WONG ET AL.116

tein extraction methods were evaluated, and it wasfound that the phenol/chloroform extraction methodgave the most reliable and consistent results. An ade-quate number of proteins was resolved by 2-DE, andthe proteins could be used for MS. The sequentialsteps in the phenol/chloroform protein extractionmethod probably removed most of the interferingcompounds such as pigments, polysaccharides, nuc-leic acids, and salt that usually interfere with IEF. Sol-ubilization of the resulting protein pellets with urea incombination with detergents further improved thequality of the protein extract. Even though proteinyield is much lower than those extracted with Tris andlysis buffer and also considering that seaweed proteincontent is approximately 6.9% of wet weight (Norziahand Chio 2000), it was counterbalanced by a relativelyclean protein sample. Computational gel analysis re-vealed approximately 500 proteins spots. These spotsrepresented perhaps the high abundance of solubleG. changii proteins. Hydrophobic proteins such as themembrane proteins could be lost during extractionowing to their inherent solubility. The high molecularmass proteins may also be lost during IEF steps asthese proteins would have difficulty migrating into theIEF strips. Likewise, the precipitation steps using is-opropanol could have excluded most of the alcohol-

soluble proteins. Despite these potential shortcomingsthe extraction protocol yielded a reasonable numberof seaweed proteins that were highly resolved by the2-DE.

In the current study, at least 15 well-resolved G.changii protein spots were successfully identified from2-DE gels by peptide mass fingerprinting. Although atotal of over 500 protein spots were resolved in the pHrange 4–8, identification of the remaining proteinspots was hampered, as only one complete chloroplastgenome of a Gracilarialean alga, Gracilaria tenuistipitata,is presently available in the public data base (Hagopienet al. 2004). The availability of this plastid genome andan additional few nuclear-encoded red algal genes inthe public databases, however, enabled successfulmatching of the G. changii peptides to seven chlorop-last-encoded proteins, six nuclear-encoded proteinsand one from a plasmid. Successful identifications ofthe photosynthetic pigments characteristics of theRhodophyta, phycoerythrin, allophycocyanin, andphycocyanin, nonetheless, confirmed that the phenol/chloroform protein extraction method that involvedprotein precipitation by isopropanol and protein re-solubilization using urea and detergents is reliable andsuitable for MS analysis. Ribulose-1, 5-bisphosphatecarboxylase/oxygenase (RUBISCO), the enzyme that

FIG. 3. Two-dimensional gels of Gracilaria changii proteins. One hundred micrograms and 500 mg of proteins were resolved using7 cm immobilized pH gradients (IPG) strips of (a) pI 3–10, (b) pI 4–7, (c) pI 5–8, (d) 18 cm/17 cm IPG strips of pI 4–7 and (e) pI 5–8. Theproteins were extracted using phenol/chloroform and solubilized in Tris buffer pH 8.8 containing urea, 3- [(3-cholamidopropy/dimethy-ammonia]-1-propanesulfonate, and tributylphosphine. The proteins were visualized with silver stain. Protein spots with identificationsare marked by arrow and standard spots numbers (SSPs).

PROTEOME OF GRACILARIA CHANGII 117

facilitates the primary CO2 fixation step in photosyn-thesis, which is plastid encoded and is used to infertaxonomic relationships in several groups of red algae(Freshwater et al. 1994), was successfully identifiedfrom the G. changii proteome. The enzyme identifiedin this study, however, had a better peptide mass matchto that of Porphyridium aerugineum even though the G.changii enzyme sequence is available in the database.This is probably because peptide mass fingerprintingidentification relies on high mass accuracy and enzymespecificity. Miscleavages and incomplete tryptic diges-tion can result in peptides with a different observedmass as compared with the theoretical mass. The massresolving power of the instrument is also crucial inproducing high-resolution mass peaks. In addition,post-translational modifications can result in a shift inmolecular mass. In order to obtain a precise match toG. changii RUBISCO, the observed masses and theo-retical masses should have minimal differences. There

is no doubt on the identity of the enzyme, however, asthe peptide masses obtained matched only to RUB-ISCO proteins. Other metabolic enzymes that wereidentified include a-1,4-glucan lyase, aminolevulinicacid dehydratase, and serine acetyltransferase. Thenuclear-encoded serine acetyltransferase was matchedto that of the ultra small unicellular red alga, Cyanid-ioschyzon merolae P. De Luca, R. Taddei & L. Varano,while g tubulin was matched to that of G. theta D. R. A.Hill & R. Wetherbee. Even though these gene sequenc-es were not presently available for G. changii, the pep-tide sequences could be obtained by a post-sourcedecay (PSD) technique as an extension of the MA-LDI-ToF MS. This would involve generation of frag-ment ions, or alternatively use of the higher capabilityand accuracy mass spectrometer for MS/MS analysis(Spengler 1997). The peptide sequence in turn can beused to derive nucleotide sequences to generate prim-ers for PCR amplification of the genes for further

TABLE 1. Gracilaria changii proteins identified by MALDI-ToF mass spectrometry.

SSP No.a

Experimentalmolecular

massb (kDa)Experimental

pIc Protein nameCoveraged

(%)

No. ofpeptidesmatchede

Theoreticalmolecular

massf (kDa)Theoretical

pIg

NCBIaccession

no.

3301 24.00 4.5 R-phycoerythrin a subunit[Gracilaria tenuistipitata var. liui]

73 8 17.95 5.2 50657774

3203 22.40 4.5 R-phycoerythrin a subunit[Gracilaria tenuistipitata var. liui]

63 7 17.95 5.2 50657774

7101 15.44 5.2 Allophycocyanin a subunit[Gracilaria tenuistipitata var. liui]

17 5 17.62 4.9 51209969

6201 22.40 5.5 Putative NAD-myo-inositoldehydrogenase [Gracilariagracilis]

25 6 23.33 4.9 4325275

2603 42.70 4.3 LysR-like transcriptionalregulator [Cyanidioschyzonmerolae]

23 8 34.47 8.25 30409180

5501 36.50 4.75 ABC transporter subunit[Gracilaria tenuistipitata var. liui]

27 8 28.89 6.6 51209989

1102 16.01 4.2 Solute carrier protein [Gracilariagracilis]

18 4 23.43 10.08 4325249

7001 14.30 5.1 Hypothetical protein [Porphyrapulchra]

25 6 20.00 9.8 11466615

2001 14.30 4.3 c-phycocyanin a subunit[Gracilaria tenuistipitata var. liui]

30 5 17.69 6.56 51210030

2605 44.70 4.6 a-1,4-glucan lyase, isozyme 5(Fragment) [Gracilariopsislemaneiforis]

14 8 65.51 4.81 5689734

4501 36.50 4.7 Aminolevulinic aciddehydratase [Gracilaria gracilis]

18 5 33.01 5.80 13560094

9604R 42.70 6.7 Ribulose biphosphatecarboxylase large chain[Porphyridium aerugineum]

21 7 54.41 6.10 730477

9601R 40.20 6.2 g-tubulin [Guillardia theta] 16 6 48.32 8.88 59015838702R 55.60 5.7 C-type cytochrome biogenesis

protein [Gracilaria tenuistipitatavar. liui]

20 6 50.34 9.26 51209870

8401 34.20 5.2 Serine acetyltransferase[Cyanidioschyzon merolae]

17 5 43.95 9.49 6594273

aStandard spot numbers. The respective SSP no. correspond to those marked in Fig. 3d.bMolecular mass of the protein spot estimated from the 2-DE gel image analysis.cpI of the protein spot estimated from the 2-DE gel image analysis.dPercentage of the protein sequence covered by the matching peptides.eNumber of peptides that matched the protein sequence.fCalculated molecular mass of the protein.gCalculated pI of the protein.

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studies. The match to G. theta g tubulin is interesting asthe GenBank database presently lacks red algae g tub-ulin gene sequences but contains only a and b tubulinsof red algae including Chondrus crispus Stackhouse, Po-rphyra purpurea R. C. Agardh, Porphyra yezoensis Ueda,Cyanidium caldarium (J. Tilden) L. Geitler, Griffithsiajaponica Okamura, and Cyanidioschyzon merolae strain10D. The match to a g tubulin sequence is possiblebecause the g tubulin gene sequence of G. theta is verydifferent from that of its a and b tubulins (Keelinget al. 1999), hence, is not a mismatch due to sequencesimilarity. Even though G. theta a and b tubulins aremost closely related to those of the red algae and maybe coded by the red algal nucleomorph found insideGuillardia theta, it is presently uncertain whether the gtubulin gene of G. theta originated from a red algalnucleomorph, as the G. theta g tubulin gene sequence isdifferent from that of the red alga Galdieria sulphuraria(Galdieri) Merola. This is in contrast to the high sim-ilarity of the a and b tubulins of G. theta to those ofGaldieria sulphuraria (Keeling et al. 1999). Neverthe-less, it is possible that the g tubulin of G. changii wasmatched to that of G. theta because no red algal g tub-ulin gene is presently available in the GenBank. Thematching may improve as other red algal g tubulin se-quences become available.

The total proteins identified from the present study,however, represent only a small percentage of the totalprotein classes. This is in light of the recently se-quenced unicellular red alga, Cyanidioschzon merolae,which has a nuclear genome size of 16 Mb, and is hy-pothesized to encode for over 4000 proteins (Mats-uzaki et al. 2004). A multicellular alga like G. changiiwould be expected to encode for many more proteinsperhaps due to its relatively large genome size( � 392 Mb) (Kapraun 2005). Many more proteinidentifications using proteomics tools will be possiblein the future as the full genome sequences of these or-ganisms and organelles become available. The presentstudy describes the first successful protein extractionmethod applicable for 2-DE and MS analysis of pro-teins from red alga. The model red seaweed proteomedeveloped in the present study could be used for com-parisons and differentiations between closely relatedspecies. Such information is a prerequisite for futurestudies on seaweed marker proteins for species iden-tification to facilitate taxonomic investigation, identifi-cations of halotolerant proteins, indicators of heavymetal pollution, and proteins critical to the speciessurvival.

The authors would like to thank Professor Mohamed Isa Ab-dul Majid for his support of this research, and Professor SiewMoi Phang for her assistance with the seaweed identificationand collection. This research was funded by the Ministry ofScience, Technology and Innovation (MOSTI), Malaysia (Bio-technology Research Grant No. 06-02-02-003 BTK/ER/016).

Blum, H., Beier, H. & Gross, H. J. 1987. Improved silver stainingof plant proteins, RNA and DNA in polyacrylamide gels. Elec-trophoresis 8:93–9.

Chapman, R. L., Bailey, J. C. & Waters, D. A. 1998. MacroalgalPhylogeny. In Cooksey, K. E. [Ed.] Molecular Approaches to theStudy of the Ocean. Chapman & Hall, London, pp. 389–407.

Freshwater, D. W., Fredericq, S., Butler, B. S., Hommersand, M. H.& Chase, M. W. 1994. A gene phylogeny of the red algae(Rhodophyta) based on plastic rbcL. Plant Biol. 91:7281–5.

Gallardo, K., Job, C., Groot, S. P., Puype, M., Demol, H., Vande-kerckhove, J. & Job, D. 2001. Proteomic analysis of Arabidopsisseed germination and priming. Plant Physiol. 126:835–48.

Gallardo, K., Job, C., Groot, S. P., Puype, M., Demol, H., Vande-kerckhove, J. & Job, D. 2002. Proteomics of Arabidopsis seedgermination. A comparative study of wild-type and gibber-ellin-deficient seeds. Plant Physiol. 129:823–37.

Hagopian, J. C., Reis, M., Kitajima, J. P., Bhattacharya, D. &Oliveira, M. C. 2004. Comparative analysis of the completeplastid genome sequence of the red alga Gracilaria tenuistipitatavar. liui provides insights into the evolution of rhodoplasts andtheir relationship to other plastids. J. Mol. Evol. 59:464–77.

Higginbotham, J. W., Smith, J. S. & Smith, O. S. 1991. Quantitativeanalysis of two-dimensional protein profiles of inbred lines ofmaize (Zea mays L.). Electrophoresis 12:425–31.

Indergaard, M. 1983. The aquatic resource. I. The wild marineplants: a global bioresource. In Cote, W. A. [Ed.] BiomassUtilization. Plenum Publishing Corporation, New York,pp. 137–68.

Jacobs, D. I., van der Heijden, R. & Verpoorte, R. 2000. Proteomicsin plant biotechnology and secondary metabolism research.Phytochem. Anal. 11:277–87.

Kamo, M., Kawakami, T., Miyatake, N. & Tsugita, A. 1995. Sepa-ration and characterization of Arabidopsis thaliana proteins bytwo-dimensional gel electrophoresis. Electrophoresis 16:423–30.

Kapraun, D. F. 2005. Nuclear DNA content estimates in multicel-lular green, red and brown algae: phylogenetic consideration.Ann. Bot. 95:7–44.

Keeling, P. J., Deane, J. A., Hink-Schauer, C., Douglas, S. E., Maier,U-G. & McFadden, G. I. 1999. The secondary endosymbiontof the Cryptomonad Guillardia theta contains alpha-, beta-, andgamma-tubulin genes. Mol. Biol. Evol. 16:1308–13.

Koller, A., Washburn, M. P., Lange, B. M., Andon, N. L., Deciu, C.,Haynes, P. A., Hays, L., Schieltz, D., Ulaszek, R., Wei, J., Wol-ters, D. & Yates, J. R. 3rd. 2002. Proteomic survey of metabolicpathways in rice. Proc. Natl. Acad. Sci. USA. 99:11969–74.

Komatsu, S., Kojima, K., Suzuki, K., Ozaki, K. & Higo, K. 2004.Rice proteome data base based on two-dimensional polyacryl-amide gel electrophoresis 2003: its status in. Nucleic Acids Res.32:D388–92.

Komatsu, S. & Tanaka, N. 2005. Rice proteome analysis: a steptoward functional analysis of the rice genome. Proteomics5:938–49.

Lim, P. E. & Phang, S. M. 2004. Gracilaria species (Gracilariales,Rhodophyta) of Malaysia including two new records. Malay-sian J. Science 23:71–80.

Matsuzaki, M., Misumi, O., Shin-I, T., Maruyama, S., Takahara, M.,Miyagishima, S.Y., Mori, T., Nishida, K., Yagisawa, F., Nishida,K., Yoshida, Y., Nishimura, Y., Nakao, S., Kobayashi, T.,Momoyama, Y., Higashiyama, T., Minoda, A., Sano, M.,Nomoto, H., Oishi, K., Hayashi, H., Ohta, F., Nishika, S.,Haga, S., Miura, S., Morishita, T., Kabeya, Y., Terasawa, K.,Suzuki, Y., Ishii, Y., Asakawa, S., Takano, H., Ohta, N.,Kuroiwa, H., Tanaka, K., Shimizu, N., Sugano, S., Sato, N.,Nozaki, H., Ogasawara, N., Kohara, Y. & Kuroiwa, T. 2004.Genome sequence of the ultrasmall unicellular red alga Cya-nidioschyzon merolae 10D. Nature 428:653–7.

McHugh, D. J. 2002. Prospects for Seaweed Production in DevelopingCountries FAO Fisheries Circular No. 968 FIIU/C968 (En). Foodand Agriculture Organization of the United Nations Publica-tion, Rome, pp. 2–6.

Mechin, V., Balliau, T., Chateau-Joubert, S., Davanture, M., Lang-ella, O., Negroni, L., Prioul, J. L., Thevenot, C., Zivy, M. &Damerval, C. 2004. A two-dimensional proteome map ofmaize endosperm. Phytochemistry 65:1609–18.

PROTEOME OF GRACILARIA CHANGII 119

Michel, G., Helbert, W., Kahn, R., Dideberg, O. & Kloareg, B.2003. The structural bases of the processive degradation ofiota-carrageenan, a main cell wall polysaccharide of red algae.J. Mol. Biol. 334:421–33.

Norziah, M. H. & Chio, Y. C. 2000. Nutritional composition ofedible seaweed Gracilaria changii. Food Chem. 68:69–76.

Perkins, D. N., Pappin, D. J., Creasy, D. M. & Cottrell, J. S. 1999.Probability-based protein identification by searching sequencedata bases using mass spectrometry data. Electrophoresis20:3551–67.

Phang, S. M. 1994. Some species of Gracilaria from Peninsular Ma-laysia and Singapore. In Abbott, I. A. [Ed.] Taxonomy of Eco-nomics Seaweeds with Reference to Some Pacific Species, vol V.California Sea Grant College Publication, La Jolla, CA, pp.125–34.

Phang, S. M. 1998. The seaweed resources of Malaysia. In Critch-ley, A. T. & Ohno, M. [Ed.] Seaweed Resources of the World.Kanagawa International Fisheries Training Centre Publica-tion, Yokosuka-shi, pp. 79–91.

Phang, S. M. & Lewmanomont, K. 2001. Gracilaria changii (B. M.Xia & I. A. Abbott) I. A. Abbott, C. F. Chang & B. M. Xia. InReine, P. & Trono, G. C. Jr. [Ed.] Plant Resources of South-EastAsia. No. 15(1) Cryptogams: Algae. Backhuys Publishers, Leiden,pp. 178–80.

Phang, S. M., Shaharuddin, S., Noraishah, H. & Sasekumar, A.1996. Studies on Gracilaria changii (Gracilariales, Rhodophyta)from Malaysian mangroves. Hydrobiologia 326/27:347–52.

Porubleva, L., Velden, K. V., Kothari, S., Oliver, D. J. & Chitnis, P.R. 2001. The proteome of maize leaves: use of gene se-quences and expressed sequence tag data for identification

of proteins with peptide mass fingerprints. Electrophoresis22:1724–38.

Spengler, B. 1997. Post-source decay analysis in matrix-assisted la-ser desorption/ionization mass spectrometry of biomolecules.J. Mass Spectrometry 32:1019–36.

Stauber, E. J., Fink, A., Markert, C., Kruse, O., Johanningmeier, U.& Hippler, M. 2003. Proteomics of Chlamydomonas reinhardtiilight-harvesting proteins. Eukaryot. Cell. 2:978–94.

Thiellement, H., Bahrman, N., Damerval, C., Plomion, C., Ros-signol, M., Santoni, V., de Vienne, D. & Zivy, M. 1999. Pro-teomics for genetic and physiological studies in plants.Electrophoresis 20:2013–26.

van Lis, R., Gonzalez-Halphen, D. & Atteia, A. 2005. Divergence ofthe mitochondrial electron transport chains from the greenalga Chlamydomonas reinhardtii and its colorless close relativePolytomella sp. Biochim. Biophys. Acta 1708:23–34.

Wang, S. B., Hu, Q., Sommerfeld, M. & Chen, F. 2004. Cell wallproteomics of the green alga Haematococcus pluvialis (Chloro-phyceae). Proteomics 4:692–708.

Westermeier, R. & Naven, T. 2002. Proteomics in Practice: A LaboratoryManual of Proteome Analysis. Wiley–Vch, Weinheim, pp. 233–8.

Yamaguchi, K., Prieto, S., Beligni, M. V., Haynes, P. A., McDonald,W. H., Yates, J. R. III & Mayfield, S. P. 2002. Proteomic char-acterization of the small subunit of Chlamydomonas reinhardtiichloroplast ribosome: identification of a novel S1 domain-con-taining protein and unusually large orthologs of bacterial S2,S3, and S5. Plant Cell 14:2957–74.

Zhang, W. & Chait, B. T. 2000. ProFound: an expert systemfor protein identification using mass spectrometric peptidemapping information. Anal Chem. 72:2482–9.

P. -F. WONG ET AL.120