Banana (Musa spp.) as a model to study the meristem proteome: Acclimation to osmotic stress

RESEARCH ARTICLE

Banana (Musa spp.) as a model to study the meristem

proteome: Acclimation to osmotic stress

Sebastien C. Carpentier1, Erwin Witters2, Kris Laukens2, Harry Van Onckelen2,Rony Swennen1 and Bart Panis1

1 Laboratory of Tropical Crop Improvement, Division of Crop Biotechnics, Department of Biosystems,Katholieke Universiteit Leuven, Leuven, Belgium

2 Centre for Proteome Analysis and Mass spectrometry, University of Antwerp, Antwerp, Belgium

Banana (Musa spp.) multiple shoot meristems are an excellent model to study the meristemproteome. Using a 2-DE protocol developed for small amounts of tissue and MS-based crossspecies polypeptide identification, we have revealed the meristem proteome and investigated theinfluence of sucrose-mediated osmotic stress in a dehydration-tolerant variety. Proteins that weresignificantly up- or down-regulated due to the high-sucrose treatment were classified using non-parametric univariate statistics. Our results suggest that the maintenance of an osmoprotectiveintracellular sucrose concentration, the enhanced expression of particular genes of the energy-conserving glycolysis and the conservation of the cell wall integrity are essential to maintainhomeostasis, to acclimate and to survive dehydration. By comparing the dehydration-tolerantvariety with a dehydration-sensitive variety, we were able to distinguish several genotype-specificproteins (isoforms), and could associate the dehydration-tolerant variety with proteins involvedin energy metabolism (e.g., phosphoglycerate kinase, phosphoglucomutase, UDP-glucose pyro-phosphorylase) and proteins that are associated with stress adaptation (e.g., OSR40-like protein,abscisic stress ripening protein-like protein). This work shows that proteome analysis can beused successfully to perform quantitative difference analysis and to characterize genetic varia-tions in a recalcitrant crop.

Received: July 20, 2006Revised: October 3, 2006

Accepted: October 3, 2006

Keywords:

Acclimation / Meristem / Osmotic stress / Plant proteomics

92 Proteomics 2007, 7, 92–105

1 Introduction

Understanding growth, cell differentiation and organ for-mation at the cellular and molecular level is the ultimate goalof many developmental biologists. In plants, cell divisions

are concentrated in specialized regions called meristems.Meristematic tissue consists of undifferentiated pluripotentcells whose function is analogous to stem cells in animals.The primary shoot and root meristem are formed duringembryogenesis. Cells derived from those meristems developinto tissues and organs. The shoot apical meristem builds upthe above-ground part of the plant, while the root meristemgives rise to the underground part. The extremely small sizeand relative inaccessibility of the shoot apex represent amajor obstacle for molecular studies of meristems. Medfordet al. [1] were the first to use cauliflower meristems as amodel and as a source of accessible shoot meristems yieldingsufficient material to characterize the meristem tran-scriptome. Numerous rationales can be given for developingmodel systems, but perhaps the most decisive one is mini-mization of experimental variation. Experiments usingtightly controlled model systems result in a high reproduci-

Correspondence: Sebastien Carpentier, Laboratory of TropicalCrop Improvement, Division of Crop Biotechnics, Catholic Uni-versity of Leuven, Kasteelpark Arenberg 13, 3001 Leuven, Bel-giumE-mail: [email protected]: 132-16-321993

Abbreviations: ASR, abscisic stress ripening protein-like protein;HSP, heat shock protein; INIBAP, International Network for theImprovement of Banana and Plantain; MIPS, Munich Informationcenter for Protein Sequences; SuSy, Sucrose synthase;UGPase, UDP-glucose pyrophosphorylase

DOI 10.1002/pmic.200600533

© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

Proteomics 2007, 7, 92–105 Plant Proteomics 93

bility and give credibility to conclusions across repeatedexperiments. Banana (Musa spp.) is an excellent model forthe study of meristems thanks to the development of theshoot meristem tip culture technique [2]. Apical dominanceis broken, and the axillary meristems are triggered to initiatenew axillary meristems that proliferate to form a uniformmultiple cauliflower-like meristem culture (Fig. 1). Bananasand plantains (Musa spp.), with an annual production ofabout 100 million tons, are important throughout the devel-oping countries of the (sub)tropics both as a subsistence andexport crop. Through human selection and prevailing agro-ecological conditions, numerous varieties have arisen withdifferent degrees of tolerance towards (a)biotic stresses. TheLaboratory of Tropical Crop Improvement (K. U. Leuven,Belgium) hosts, under the authority of the InternationalNetwork for the Improvement of Banana and Plantain (INI-BAP), the largest collection of bananas in the world—theINIBAP International Musa Germplasm Collection—underin vitro conditions [3]. Cryopreservation of shoot meristemscomplements the conservation of this biodiversity. Duringthis ultra-low temperature freezing process, lethal intracel-lular ice crystal formation is avoided by a considerablereduction in moisture content and high cooling rates. Wehave previously shown that a 2-week acclimation of the cau-liflower-like shoot meristems on 0.4 M sucrose is essential tosurvive the severe dehydration treatment prior to cryopre-servation [4, 5].

Proteomic research of poorly characterized experimentalsystems like banana is often hampered by the lack of routinesample preparation procedures and the dependence of pro-tein identification based on similarity with orthologouspolypeptides. Sample preparation is a critical step in a 2-DEproteomic approach, and is absolutely essential for repro-ducible results. Banana tissues are known for their extremehigh levels of oxidative enzymes, phenol compounds andcarbohydrates [6]. Although we successfully optimized themeristem culture technique, there was still a need to scaledown the quantity of sample material to concentrate thesample and to remove the interfering substances. Our 2-DEprotocol was developed to remove excessive interfering

Figure 1. Multiple shoot tip meristem culture (variety Cachaco).

compounds and was optimized for small amounts of tissue[7]. The banana genome is poorly characterized. Peptidesequence data analysis and cross-species identification is thepreferred technique for protein identification whenever agenome is poorly characterized [8–11]. Cross-species identi-fication is successful when both the mass information andsequence information of multiple peptides is used. Thisprotein selection procedure prior to MS analysis ensures theconnectivity between the peptides, significantly reduces thecomplexity and avoids various pitfalls associated with recon-structing the abundance of individual proteins. The mainobjective of this work was to gain further understanding ofhow the meristem proteome changes upon acclimation tosucrose-mediated osmotic stress. Acclimation to altered car-bohydrate availability is complex. In general, abundant car-bon resources repress the expression of genes involved inphotosynthesis and reserve mobilization, while they favorgenes involved in carbon metabolism and storage and triggerother classes like defense genes, secondary product pathwaysand storage proteins [12].

The large-scale protein study of meristems presentedhere investigated a sucrose-mediated acclimation, necessaryto survive a severe dehydration. To our knowledge, it is thefirst time that a meristem proteome has been investigated.This work proves that proteome analysis can be successful,even for limited amounts of tissue of a recalcitrant crop.

2 Materials and methods

2.1 Plant material

In vitro plants were provided by the INIBAP transit center,Belgium. Selected varieties Cachaco (ABB cooking banana)and Mbwazirume (AAA highland banana) belong to differ-ent genomic groups that are known to behave differently to-wards dehydration tolerance [6, 13] and cryopreservation [5].Multiple shoot meristem cultures were initiated as describedby Strosse et al. [2] and subsequently maintained on thestandard control medium (Murashige and Skoog mediumsupplemented with benzylaminopurine). The meristem cul-tures were kept on two different media for 2 weeks: (i)standard control medium (containing 0.09 M sucrose) and(ii) high-sucrose medium containing 0.4 M sucrose. All cul-tures were kept in the dark at 25 6 27C.

2.2 Water status

Five biological repetitions were used to analyze the sugarcontent and to determine the relative water content and theosmotic potential. Analysis of sucrose was performed byanion exchange chromatography (Dionex ChromatograhpyCo.). Freeze-dried powdered meristem cultures were homo-genized in 80% ethanol. Supernatant was collected andfreeze-dried under reduced pressure in a speed-vac con-centrator. The dried extract was dissolved in distilled water


94 S. C. Carpentier et al. Proteomics 2007, 7, 92–105

and filtered. Sugar separation on a CarboPac PA-100 (Dio-nex) column was achieved using an isocratic eluant (150 mMNaOH). The osmotic potential was determined using a dewpoint microvolt meter according to the manufacturerinstructions (Wescor, model C-52/HR-33T, distributed byEijkelkamp, Giesbeek, The Netherlands).

2.3 Protein extraction and 2-DE

Samples were extracted and separated according to Carpen-tier et al. [7]. The top layer of 1–2 mm meristematic tissuewas excised and ground in liquid nitrogen, and 30–50 mgwas resuspended in 500 mL ice-cold extraction buffer(100 mM Tris-HCl pH 8.5, 5 mM EDTA, 100 mM KCl, 1%DTT, 30% sucrose, complete protease inhibitor cocktail;Roche Applied Science, Vilvoorde, Belgium) and vortexed for30 s. Ice-cold Tris-buffered phenol (500 mL, pH 8.0) wasadded and the sample was vortexed for 15 min at 47C. Aftercentrifugation (3 min, 60006g, 47C) the phenolic phase wascollected, re-extracted with 500 mL extraction buffer and vor-texed for 30 s. After centrifugation (3 min, 60006g, 47C) thephenolic phase was collected and precipitated overnight withfive volumes 100 mM ammonium acetate in methanol at–207C, and rinsed twice with ice-cold acetone containing0.2% DTT. The pellet was air dried at room temperature anddissolved in 100 mL lysis buffer (7 M urea, 2 M thiourea, 4%CHAPS, 0.8% IPG buffer, 1% DTT). The sample was dilutedwith rehydration buffer (6 M urea, 2 M thiourea, 0.5%CHAPS, 10% glycerol, 0.002% bromophenol blue, 0.5% IPGbuffer, 0.28% DTT) to 40 mg (silver staining) or 400 mg pro-tein (CBB staining) per 150 mL and was applied via anodiccup loading. The concentration of the protein mixture wasestimated using the 2-D quant kit from GE Healthcare asdescribed by the manufacturer (GE Healthcare, Diegem,Belgium). IPG strips (24 cm, pI 4–7; GE Healthcare) wererehydrated for at least 8 h in 450 mL rehydration buffer. IEFwas carried out on the IPGphor II (GE Healthcare) at 207Cwith current limit 50 mA/strip: 3 h at 300 V, 6 h at 1000 V, 3 hat 8000 V (gradient) and 24 000 Vh at 8000 V for low loads,and 40 000 Vh at 8000 V for high loads. Prior to the seconddimension, the individual strips were equilibrated for15 min in 6 mL equilibration solution (6 M urea, 30%glycerol, 2% SDS, 0.002% bromophenol blue, 50 mM Tris,pH 8.8) containing 1% DTT and subsequently for 15 min in6 mL equilibration buffer containing 4.5% iodoacetamide.The separation in the second dimension was realized on theEttan DALT 6 System (GE Healthcare) with lab cast 1.5-mmSDS polyacrylamide gels (12.5%): 45 min 12 W, 5 h 100 W.Acrylamide and protein standard were purchased from Bio-Rad (Nazareth, Belgium). Proteins were visualized either bysilver staining [14] or by colloidal CBB staining [15]. Gelswere scanned and calibrated with labscan 5 software (GEHealthcare). Image analysis was performed with ImageMaster 2D platinum™ 5.00 (GE Healthcare). Spots werequantified using the % volume criterion.

2.4 Protein identification

The banana genome is poorly characterized, with only a3’ EST database of leaves and fruits of an AAA variety(Cavendish subgroup), containing 15 661-derived peptidesequences, being available. The database was donated to theMusa Genomics consortium by Syngenta and is maintainedat the MIPS (Munich Information center for ProteinSequences, Germany). Protein spots were picked from theslab gel (Propic, Perkin Elmer, USA) and collected inmicrotiter plates. The plates were processed using a liquidhandler (Multiprobe II, Perkin Elmer). The individual gelplugs were consecutively rinsed with 20 mL H2O (MS grade,Biosolve) and dehydrated with 40 mL 95% CH3CN. Thisprocess was repeated three times. Dehydrated gel particleswere incubated at 47C in 2 mL digest buffer containing 25 ngtrypsin MS Gold (Promega, Leiden, The Netherlands),50 mM NH4HCO3 and 10% CH3CN. After 30 min of rehy-dration, 10 mL of a buffer containing 25 mM NH4HCO3 and10% CH3CN was added. After 3 h of proteolysis at 377C, theresulting peptides were desalted on column with microtipsolid phase extraction (ZipTip C18 200nL bed volume; Milli-pore, Brussels, Belgium), mixed with matrix solution(7 mg/mL CHCA in 50% ACN containing 0.1% TFA),spotted in a 1.2-mL volume on a MALDI-target and analyzedby MALDI-TOF-MS/MS (4700 Proteomic Analyzer, AppliedBiosystems, Foster City, CA, USA). Processed peptide massfingerprint and peptide fragmentation spectra (GPSExplorer 3.5; Applied Biosystems) of each sample weresubmitted for identification using an in house databasesearch engine (MASCOT 2.1, Matrix Science, UK). Takingthe green plants as taxonomy, several publicly availabledatabases (Swiss-Prot; NCBI nr; and dbEST) were consultedas well as the proprietary Musa EST database, donated to theMusa Genomics consortium. The query parameters allowedfor one single miscleavage, a variable oxidation state ofmethionine and a 50-ppm mass window resolution. Thesupplementary material contains a table listing the proteinswith significant homology, their theoretical and experi-mental molecular masses and pI and the confirmation viathe proprietary EST database (Supplementary Table 1). Thenumber of peptides used to identify the proteins, thesequence and charge state of each peptide and the totalpercent of sequence coverage are also available as supple-mentary files for the publicly available sequences. In thecase of MS/MS data, the ions scores for individual peptidematches are statistically meaningful. Proteins were assessedusing the probability-based MOWSE score [16]. Proteinsidentified based on MS/MS data of a single significant pep-tide were only accepted if that peptide was highly decisiveand/or the PMF-based homology identification was positiveand/or the peptide identification was confirmed usingthe EST database. To estimate the false-positive rate ofthe protein homology dataset, a decoy database fromnrNCBI (release date: 20060216 with a taxonomic restric-tion to Viridiplantae containing 3 292 813 sequences and



1 128 164 434 residues) was generated. Each protein aminoacid sequence was shuffled with the EMBOSS shuffle tool[17]. The score distribution of the spectra from the individ-ual experiments using the decoy database was plotted (Sup-plemental Fig. 1). Significant EST hits were further ana-lyzed for annotation using the PBLAST interface.

2.5 Statistics

Univariate statistical methods examine the individual pro-tein spots. Parametric univariate statistical tests are verypowerful, but the data must respect the restrictive assump-tions (continuous and normally distributed data, homo-geneity of variance and independent samples). If oneassumption is not met, the significance levels and the powerof the test are invalidated. Although some empirical evidenceillustrates that slight deviations in meeting the assumptionsunderlying parametric tests may not have radical effects onthe obtained probability levels, there is no general agreementas to what is a “slight” deviation [18]. An alternative for theparametric tests is the less powerful non-parametric tests(assumptions are: independent and continuous ordinaldata). Varying the number of replicates is the best way tocontrol the power of the statistical test. The power of a sta-tistical test (i.e., the reduction of false-negative results)depends on the variance, the change in expression, thenumber of replicates, the chosen statistical test and the pre-determined significance level (i.e., the accepted level of hav-ing false-positive results). We opted for the non-parametricunivariate Kolmogorov-Smirnov test (Image Master Plati-num Software; GE-Healthcare). It is a two-sample test with ahigh power-efficiency for small sample sizes. The reducedpower of a non-parametric test was anticipated by includinga higher number of biological replicates (6). Using theDIGE™ approach, Karp and Lilley [19] gathered strong argu-ments to assume that the restrictive assumptions of para-metric statistics are met after the logarithmic transformationof the standardized abundance. However, with the typicalheterogeneity of variance associated with classical dyes andthe limited sample size of 6, a non-parametric statistical testseems the best choice.

All indicated numbers of variance are standard errors.

3 Results

3.1 Acclimation of the meristem proteome of a

dehydration-tolerant variety to osmotic stress

3.1.1 Water status, osmotic potential and sucrose

concentrations

The relative water content of the control samples was92.6 6 0.2% and 78.2 6 0.4% in the sucrose-stressed cells.The osmotic potential fell from –0.6 MPa in control samplesto –1.6 MPa in sucrose-treated samples, and the sucrose

concentration rose significantly from 9.95 6 0.45 mmol/gfresh weight in control samples to 211 6 11 mmol/g freshweight in sucrose-treated samples.

3.1.2 Sucrose-mediated osmotic stress

A pI 3–10 separation (not shown) indicates that the majority(81%) of the meristem proteome is situated between pIvalues of 4 and 7, and that to separate individual proteins ahigher resolution is needed. A total of 1186 6 17 spots weredetected after silver staining (24-cm gel, pI 3–10). For furtheranalysis, we therefore concentrated on the 4–7 pI range sub-set of the proteome (Fig. 2).

For proteome analysis of the dehydration-tolerant varietyCachaco, six replicate extractions (biological replicates) wereperformed for each treatment (control and high sucrose) andtwo different, but complementary staining techniques wereapplied. The silver-stained and colloidal CBB-stained gelswere run and analyzed separately, resulting in 24 gels. Allspots were detected without any editing and were auto-matically screened for good quality based on the parameterspresent in the software Image Master PlatinumTM (GEHealthcare). Silver staining is very sensitive, but is readilysaturated, has a limited dynamic range and has a lot ofstaining steps. CBB is less sensitive but has a broader dy-namic range and is a very simple staining procedure. Sup-plementary Tables 2 and 3 illustrate the complementarinessof both stainings. Only the proteins that were statisticallysignificant with both stainings (a�0.1) were retained inTables 1 and 2.

Automatic spot detection of the 12 CBB-stained gelsrevealed 1427 6 68 spots for the control treatment and1657 6 64 spots for the high-sucrose treatment. Using theunivariate statistical approach, 123 spots were significantlydifferent (a�0.05), of which 77 were up-regulated by thehigh-sucrose treatment and 46 down-regulated. Spot detec-tion of the ten-times-less-loaded silver-stained gels revealed1072 6 157 spots for the control treatment and 1137 6 143spots for the high-sucrose treatment; 66 spots were signifi-cantly different (a�0.05), of which 53 were up-regulated bythe high-sucrose treatment and 13 down-regulated. Giventhe high reproducibility and the high quality of the gels, wewere able to significantly (a�0.05) detect differences down toa ratio of ~1.5 with classical visible staining techniques(Tables 1 and 2).

3.1.3 Identification

PMF analysis combined with the additional informationfrom the subsequent MS was compared with translationproducts from publicly available primary sequence databasesand the proprietary banana EST database. Of the proteins,80% (99) were identified by searching publicly availablesequences; the remaining 20% (25) could only be identifiedby the proprietary EST database; 55% of the cross-species-identified proteins were confirmed by the EST database



Figure 2. A representative silver-stained 24-cm pI 4–7 gel of banana meristematic tissue (variety Cachaco). Proteins are numbered andindicated with a white arrowhead.

(Supplementary Table 1). Relatively small differences wereobserved between the theoretical and the predicted molec-ular masses. The molecular mass is robust towards aminoacid changes. The pI values, however, vary more sub-stantially, probably due to occurrence of isoforms and aminoacid changes between species.

The individual proteins were classified according to theMIPS functional catalogue (FunCat). High-sucrose up-regu-lated categories, ranked according to decreasing prevalence,are: (i) energy, (ii) cell rescue, defense, cell death and ageing(iii) protein destination, (iv) metabolism, (v) cellular organi-zation, (vi) transcription, (vii) transport facilitation, and (viii)cellular communication and signal transduction (Table 1).High-sucrose down-regulated categories are: (i) cell rescue,defense, cell death and ageing, (ii) metabolism, (iii) proteinsynthesis and (iv) protein destination (Table 2).

3.1.4 Construction of a web accessible protein

repository and characterization of the

meristem proteome

To facilitate future proteome analysis of meristem cellsand to make the data accessible, an on-line database wasconstructed, essentially as described by Laukens et al.[20]. All identification data were integrated and can beaccessed at http://www.pdata.ua.ac.be/musa. The identi-fied protein spots are hyperlinked to individual proteinentries. Each protein entry contains all identificationinformation, as well as links to relevant entries in otheron-line databases. Comprehensive search functions areimplemented. A reference database reveals supportiveprotein information that can be used to confirm proteinidentity or to reduce the need for MS upon future analy-



Table 1. List of individual significantly high-sucrose up-regulated proteins confirmed by silver and CBB staining in Cachaco (dehydration-tolerant variety)a)

No. Protein name Species Accessionno.

Theoretical Experimental Silver CBB

Mol.mass

pI Mol.mass

pI Ratio a Ratio a

01 Metabolism

01.01 Amino acid metabolism62 Glutamate decarboxylase Oryza sativa gi)32309578 56 5.72 53 6.69 2.1 0.1 1.6 0.0501.03 Nucleotide metabolism97 Adenokinase Oryza sativa gi)38568064 45 5.16 40 5.46 1.8 0.1 1.7 0.0501.20 Secondary metabolism106 2’-Hydroxyisoflavone reductase Oryza sativa gi)51090448 34 6.19 35 6.37 2.2 0.01 1.5 0.1

02 Energy

02.01 Glycolysis and gluconeogenesis28 Phosphoglucomutase Zea mays gi)12585310 63 5.47 73 6.08 1.4 0.1 1.6 0.0553 Enolase Musa acuminata gi)21630092 ps ps 57 5.55 1.5 0.05 1.3 0.156 Enolase Zea mays gi)22273 48 5.20 55 5.99 2.3 0.05 1.6 0.0558 Enolase Zea mays gi)22273 48 5.20 52 6.14 1.4 0.05 1.5 0.0564 UGPase Musa acuminata gi)6625908 52 5.48 52 5.84 2.3 0.01 2.1 0.0565 UGPase Musa acuminata gi)6625908 52 5.48 52 5.71 2.1 0.05 1.8 0.0580 GDP-mannose epimerase Arabidopsis thaliana gi)21436019 43 5.85 47 6.61 1.9 0.01 2.4 0.0585 Phosphoglycerate kinase Spinacia oleracea gi)21272 46 5.70 44 5.36 3.9 0.01 4.5 0.0586 Phosphoglycerate kinase Spinacia oleracea gi)1346698 46 5.82 44 5.63 4.8 0.1 2.1 0.0594 Phosphoglycerate kinase Populus nigra gi)3738259 43 5.70 43 6.38 1.9 0.05 5.0 0.05

04 Transcription

04.05.03 mRNA processing67 Dead box RNA helicase Oryza sativa gi)34913868 51 6.26 51 5.74 1.4 0.1 2.4 0.05

06 Protein destination

06.01 Protein folding and stabilization23 HSP 70 Malus domestica gi)6969976 72 5.17 81 5.41 2.2 0.05 2.8 0.0506.04 Proteolysis5 Amino peptidase Arabidopsis thaliana gi)34098843 99 5.43 111 6.04 2.3 0.05 1.8 0.0516 Post proline cleaving enzyme Arabidopsis thaliana gi)15217929 82 5.26 96 6.11 1.5 0.1 7.0 0.05

07 Transport facilitation

07.22 Transport ATPases27 ATPase subunit A Daucus carota gi)137460 69 5.29 73 5.47 2 0.05 1.9 0.0551 ATPase subunit B Gossypium hirsutum gi)2493129 54 4.96 58 5.34 1.7 0.1 1.6 0.05

11 Cell rescue, defense, cell death and ageing

11.01 Stress responses34 Dihydroxyacetone kinase Arabidopsis thaliana gi)42562609 62 5.18 67 5.32 2.1 0.05 3.7 0.0569 Cellulase Citrus sinensis gi)7488904 56 5.89 50 5.58 5.8 0.01 5.3 0.0570 Cellulase Citrus sinensis gi)7488904 56 5.89 50 5.72 5.5 0.01 2.9 0.05

30 Cellular organization

30.01 Organization of the cell wall95 Cellulose synthase Oryza sativa gi)7488889 40 6.24 42 6.06 1.3 0.1 2.4 0.0530.04 Organization of the cytoskeleton82 Actin Musa acuminata gi)33339126 42 5.23 45 5.43 1.8 0.1 1.7 0.05

a) No., number corresponding to the proteins in Fig. 2; molecular mass in kDa; silver, silver-stained gels; CBB, CBB-stained gels; ratio, ratioof the average % vol of sucrose-stressed samples to the average % vol of control samples; a, significance level according to the Kol-mogorov-Smirnov statistical test; ps, partial sequence known.



Table 2. List of individual significantly high-sucrose down-regulated proteins confirmed by silver and CBB staining in Cachaco (dehydra-tion-tolerant variety)a)

No Protein name Species Accessionno.

Theoretical Experimental Silver CBB

Mol.mass

pI Mol.mass

pI Ratio a Ratio a

01 Metabolism

01.05 C-compound and carbohydrate metabolism6 Sucrose synthase Tulipa gesneriana gi)1255982 93 6.12 109 6.25 2.0 0.05 2.3 0.058 Sucrose synthase Tulipa gesneriana gi)1255982 93 6.12 107 6.58 8.5 0.01 4.3 0.059 Sucrose synthase Tulipa gesneriana gi)1255982 93 6.12 107 6.65 10.5 0.01 4.0 0.0510 Sucrose synthase Tulipa gesneriana gi)1255982 93 6.12 107 6.69 4.7 0.01 1.5 0.0511 a-Glucosidase Oryza sativa gi)34895554 103 6.08 106 5.67 1.6 0.05 2.4 0.0114 Raffinose synthase Oryza sativa gi)55773698 84 6.06 100 4.71 4.5 0.01 8.0 0.0184 a-Amylase Musa acuminata gi)22536012 47 5.83 47 5.83 3.6 0.05 4.0 0.01

05 Protein synthesis

05.10 tRNA synthesis19 Threonyl tRNA synthase Oryza sativa gi)50943671 86 8.19 87 6.78 2.1 0.05 1.5 0.1

06 Protein destination

06.20 storage proteins121 Acid phosphatase Arabidopsis thaliana gi)18379219 31 9.22 26 6.45 3.3 0.05 1.7 0.1

11 Cell rescue, defense, cell death and ageing

11.01 Stress responses126 ACC oxidase Elaeis guineensis gi)30060226 34 5.68 24 5.84 3.9 0.05 4.2 0.01133 ASR Musa acuminata gi)47575681 16 6.99 12 6.60 7.1 0.1 11.3 0.0511.05.03 Defense related proteins134 Lectin Musa acuminata gi)21392369 15 6.26 12 6.00 4.9 0.01 11.5 0.01135 Lectin Musa acuminata gi)21392369 15 6.26 11 6.76 4.4 0.01 8.9 0.01136 Lectin Musa acuminata gi)21392369 15 6.26 11 6.53 4.9 0.01 5.3 0.05138 Lectin Musa acuminata gi)21392369 15 6.26 11 5.98 4.8 0.01 4.0 0.0111.17 Degradation of exogenous polysaccharides112 Chitinase Musa acuminata gi)41818408 36 7.59 29 6.22 1.8 0.05 1.7 0.05113 Chitinase Musa acuminata gi)41818408 36 7.59 28 6.28 2.8 0.01 3.2 0.01

a) No., number corresponding to the proteins in Fig. 2; Accession no., GenBank accession number; molecular weight in kDa; ratio, ratio ofthe average % vol of control samples to the average % vol of sucrose pretreated samples; a, significance level according to the Kolmo-gorov-Smirnov statistical test.

sis. This database will continuously be extended withnew data including spectral information of the identifiedproteins.

3.2 Dehydration-tolerant versus -sensitive variety

To find proteins typically correlated to the dehydration-tolerant variety, we also characterized the proteome of adehydration susceptible variety Mbwazirume. The twovarieties belong to different genomic groups known tobehave differently towards dehydration tolerance [6, 13].Mbwazirume, an East African Highland banana doesnot survive the severe dehydration associated with cryo-preservation [5]. To characterize the genetic variation,three replicate extractions (control conditions) were per-

formed for each variety and the proteins were separatedin the same run. The average matching between thegels of the two cultivars was 59 6 3.5%, while thematching between the same Cachaco gels was82 6 2.4% and between the same Mbwazirume gels was82 6 2.2%. The genetic variation of proteins that aresignificantly regulated by stress may be related to thevariation of tolerance. Therefore, also three repetitionsof Mwbazirume treated under control and sucrose-stressed conditions were run simultaneously. We wereable to indicate statistically that, of the identified spots,spots 56, 58, 65, 90, 69, 134, 136 and 113 respond in thesame way in both varieties. The genotype-specific pro-teins and proteins that differentially respond to sucrosein the two varieties are listed in Table 3.



Table 3. Genotype-specific proteins and proteins that respond differently to sucrose in both varieties (Kolmo-gorov-Smirnov statistical test)a)

No Protein name % volume

Control Sucrose

Mbwazirume Cachaco Mbwazirume Cachaco

28 Phosphoglucomutase nv 0.07 nv 0.10b)

40 HSP 60 0.58 0.17 0.90b) 0.2044 HSP 60 nv 0.59 nv 0.67b)

45 Ferric leghemoglobin reductase 0.07 0.39 0.06 0.2046 T-complex protein 0.06 0.47 0.05 0.2555 F1 ATPase 0.94 0.15 0.88 0.0657 S-Adenosyl-L-homocysteine hydrolase 0.03 0.67 0.23 0.4664 UGPase 0.04 0.32 0.04 0.66b)

86 Phosphoglycerate kinase 0.63 0.01 1.21b) 0.04b)

85 Phosphoglycerate kinase 0.04 0.39 0.05 1.4b)

89 Phosphoglycerate kinase 0.17 0.98 0.17 0.8787 Phosphoglycerate kinase 0.08 0.15 0.11 0.27b

88 Phosphoglycerate kinase 0.81 0.05 0.51 0.0792 Malate dehydrogenase 0.93 0.37 0.77 0.4894 Phosphoglycerate kinase 0.02 0.32 0.03 0.44b)

99 OSR40 0.14 0.93 0.10 1.28b)

100 Malate dehydrogenase 0.25 0.52 0.22 0.57112 Chitinase 0.03 0.61 0.03 0.41c)

128 Putative cysteine proteinase inhibitor 1.21 0.05 0.39c) 0.04129 ASR nv 1.45 nv 1.02

a) No, number corresponding to the proteins in Fig. 2; % volume, average percentage of spot volume; nv, notvisible.

b) Up-regulated within the variety after high sucrose stress; significance level a�0.05, according to the Kolmo-gorov-Smirnov statistical test (3 repetitions).

c) Down-regulated within the variety after high sucrose stress.

4 Discussion

4.1 Acclimation of the meristem proteome of a

dehydration-tolerant variety to osmotic stress

4.1.1 Altered carbohydrate metabolism favors the

energy-conserving glycolysis pathway and

maintains an osmoprotective intracellular

sucrose concentration

The prime functions of glycolysis are to participate in thebreakdown of carbohydrates to generate ATP, reductant andcarbon skeletons for anabolic pathways. Figure 3 shows theglycolytic pathway and highlights the identified enzymes andtheir up- or down-regulation under 0.4 M sucrose in com-parison to control conditions. The cytosolic glycolytic net-work furnishes plants with the metabolic options needed fordevelopment and acclimatization to unavoidable environ-mental stresses [21]. Under stress situations, cells have ahigher energy demand for appropriate responses [22–25].Non-green tissues, like our samples, are entirely dependenton glycolysis and oxidative phosphorylation for energy sup-

ply. Our results suggest that the induction of specific genesfor energy-conserving glycolysis is needed to maintainhomeostasis.

Phosphoglycerate kinase (identified as spots 85, 86, 87,88, 89 and 94; Fig. 2) catalyses the formation of 3-phos-phoglycerate from 1,3-bisphosphoglycerate (Fig. 3). Phos-phoglycerate kinase is significantly up-regulated after high-sucrose stress (Table 1), making it one of the most abundantproteins observed. During this reaction the phosphate groupis transferred to ADP, generating ATP. The products of thereaction are strongly favored due to the presence of theunstable high-energy anhydride bond of 1,3-bisphos-phoglycerate [26]. The multiple protein spots are probablydifferent isoforms. Until now, three different isoforms havebeen identified in Arabidopsis along with several polymorph-isms (At1g79550 and splice variant At1g79550.2 (cytoplasm),At1g56190 (mitochondrion), At3g12780 (mitochondrion).

Enolase (identified as spots 53, 56 and 58; Fig. 2) cata-lyses the reversible dehydration of 2-phosphoglycerate toform phosphoenolpyruvate. The phosphate attached to the2-position of pyruvate also has a high negative free energy ofhydrolysis, allowing transfer of the phosphate group to ADP



Figure 3. Plant glycolytic path-way. Identified proteins arehighlighted in gray. Proteinsthat were significantly up- ordown-regulated are shown withan up- or downwards pointingarrow.

in the subsequent reaction [26]. Enolase was significantly up-regulated due to sucrose stress (Table 1). It is noteworthy thatan up-regulation of enolase has already been associated withwater deficit [24] in maize, salt stress in rice [27] and iceplant[28], drought stress in Arabidopsis [29] and heat shock in yeast[30].

Sucrose synthase (SuSy) catalyses the reversible conver-sion of sucrose into fructose and UDP-glucose. SuSy exists inseveral isoforms that have different biochemical properties[31]. The SuSy polypeptides are located in the cytoplasm or

are tightly attached to the cellulose synthase complex at theplasma membrane or at the actin cytoskeleton [32–34].Phosphorylation of SuSy is known to occur on at least twoconserved sites and the phosphorylation status is believed tobe implicated as part of the mechanism regulating proteoly-tic turnover [35], catalytic activity and influence on mem-brane association [36]. We identified SuSy as a single spotand as a spot train (spots 6, 7, 8, 9 and 10; Fig. 2). Until now,six different isoforms of SuSy have been identified in Arabi-dopsis along with several polymorphisms (At1g73370,



At3g43190, At4g02280, At5g20830 and At5g49190). SuSy wasone of the most abundant proteins in the control samples.SuSy plays a crucial role in sugar distribution and metabo-lism. SuSy is strongly expressed in most sink tissues and itsactivity is often correlated with sugar import, starch synthe-sis, sink strength and cellulose biosynthesis. Current under-standing of how SuSy activity specifically regulates sucroseaccumulation or growth remains far from complete. Sucroseunloading in sink tissues takes place primarily via the sym-plast and the quantity unloaded is mainly determined by theSuSy activity [37–40]. Catabolism of sucrose generates UDP-glucose and keeps the intracellular sucrose concentrationlow, maintaining a concentration gradient for sucroseuptake. The down-regulation of SuSy (Table 2) creates anosmoprotective advantage of an endogenous high-sucroseenvironment in the cytoplasm, resulting in a weak gradientand thus in a reduced sucrose uptake. We confirmed thishigh osmoprotective intracellular sucrose concentration byanion exchange chromatography.

4.1.2 Up-regulation of UGPase ensures production of

UDP-glucose for preservation of the cell wall

and for production of carbohydrate moiety of

glycoproteins and glycolipids

UDP-glucose pyrophosphorylase (UGPase) catalyzes thereversible production of UDP-glucose and pyrophosphatefrom glucose-1-P and UTP. UDP-glucose and other nucleo-tide sugars can be produced by either SuSy or by nucleotidesugar pyrophosphorylases like UGPase. UDP-glucose is notonly a necessary metabolite for cell wall biogenesis, but isalso involved in the synthesis of the carbohydrate moiety ofglycolipids and glycoproteins [41]. Kleczkowski and co-work-ers [42, 43] revealed an unknown phosphorylated inter-mediate in Arabidopsis that antagonistically regulates SUS1and UGP gene expression. This may represent a mechanismwhere UDP-glucose is assured to be produced if one of theproducing pathways is down-regulated or inactivated. Suchan antagonistic effect is confirmed by our results. High-sucrose concentrations result in a down-regulation of SuSyand an up-regulation of UGPase. The down-regulation ofSuSy, the provider of UDP-glucose during normal growth, iscompensated by the up-regulation of UGPase, assuringUDP-glucose. Exogenous applied sucrose and ethyleneincreased banana UGPase transcript abundance [44]. Basedon southern blot analysis, the authors speculated the pres-ence of different UGPase members in the banana genome.Here, UGPase was identified as two differently up-regulatedproteins (spots 64 and 65; Fig. 2; Table 1) and was among themost abundant proteins after high-sucrose stress. An up-regulation of UGPase has already been associated with low-temperature stress in potato [45, 46] and Arabidopsis [42] andsalt stress in rice [27].

The plant cell wall is not an inert and static exoskeleton,and its major biological functions are mechanical supportand stress protection of the cell. The wall serves as an extra-

cellular matrix that interacts with cell surface proteins, pro-viding positional and developmental information. It alsocontains numerous enzymes that can modify its physicalproperties. Enzymes involved in sugar nucleotide productionand transport are important because of their potential tomanipulate the composition of the cell wall through sub-strate level control [47]. When the life cycle of plants isinfluenced by various environmental signals, the mechanicalproperties of the cell wall significantly change [48]. The sig-nals caused by water stress modify the levels and structure ofthe cell wall constituents, and such modifications are sup-posed to be the cause of the changes in the wall mechanicalproperties [49]. The walls of higher plants consist of a fibrousmaterial embedded in an amorphous matrix. The majorcomponents are cellulose, pectin, and lignin. The basis of thecellulose-xyloglucan network modification remains largelyunclear; however, the involvement of different classes ofenzymes have been suggested, including endo-1.4-a-D-glu-canases (cellulases), xyloglucan endoglycosyltransferasesand exo-glycosylhydrolases (glycosidases) [50]. Several pro-teins are involved in nucleotide sugar metabolism and cellwall modification, and were identified as being significantlydifferent between the two treatments (Tables 1, 2). Two cel-lulase proteins (up-regulated upon high-sucrose stress, spot69, 70; Fig. 4) most likely bring on cell wall loosening bycleavage of the xyloglucan cross-links. However, in theabsence of compensating synthesis and incorporation intothe cell wall, this would lead to an irreversible loss of cell wallintegrity. This up-regulation of cellulase (spot 69 and 70) wasaccompanied by the up-regulation of alpha-1,4-glucan-pro-tein synthase involved in cellulose biosynthesis (spot 95), aswell as other cell wall and nucleotide sugar modifyingenzymes like UGPase (spot 65), GDP-Man epimerase (spot80) and 2’-hydroxyisoflavone reductase (spot 106).

4.1.3 Abundant storage proteins are low abundant

under sucrose stress and may be broken down

and recycled to act as a source of amino acids

Once proteins are irreversibly damaged they are eliminated,preventing aggregation and encouraging homeostasis. Thetreatment with high concentrations of sucrose is associatedwith the up-regulation of some proteases (spots 5 and 16;Table 1). Analysis of the down-regulated proteins alsorevealed proteins involved in defense/storage (spots 112,113, 121, 134, 135, 136 and 138; Table 2). Based on literatureand our protein pattern, we hypothesize that several defense-related proteins act as storage proteins. Classical plant lectinsare moderately to abundantly present, representing 0.1–10%of the total protein content [51]. Most of the classical plantlectins do not fulfill a specific role, but rather represent aspecial class of aspecific defense proteins that help the plantto cope with attacks. If they are not recruited for defensepurposes, they act as genuine storage proteins [52]. Five pro-teins have been identified as lectins (spot 134, 135, 136, 137,and 138), and are abundantly present under control condi-



Figure 4. Cellulase after (a) high-sucrose treatment and (b) undercontrol conditions. Identified proteins are numbered and indi-cated with a white arrowhead. Histograms illustrate the centraltendency (% spot volume) and the dispersion interval of threerepetitions. Experimental molecular mass (spot 69) 50 kDa, pI5.58; experimental molecular mass (spot 70) 50 kDa, pI 5.82.

tions. Peumans et al. identified some particular lectins [53]and a chitinase-related protein [54] that were abundantlypresent in unripe banana fruit. The chitinase-related protein,identified as an acidic class III chitinase, showed no enzy-matic activity and behaved as a vegetative storage protein,accumulating during early fruit set and disappearing duringripening, most likely serving as a source of amino acids forthe synthesis of ripening associated proteins [54]. Three pro-teins have been identified as chitinase (spot 107, 112, and113), spot 112 is highly abundant under control conditions.

4.1.4 Molecular chaperones are present in cells

under both optimal and adverse growth

conditions

Molecular chaperones are proteins that bind to nascent orunfolded polypeptides and ensure correct folding or trans-port [55]. They occur in the cytoplasm as well as in organelles[56]. During normal cell metabolism, they are responsible forproper protein folding, assembly, degradation and theimport into plastids and mitochondria. They are alsobelieved to help cells to overcome a range of unfavorable en-vironmental conditions, such as heat, cold, drought andchemical stresses. Characterization of the meristem pro-teome revealed that heat shock proteins (HSPs) are presentunder control conditions (Fig. 2) and that some members arehigh-sucrose up-regulated (Table 1). Five major families areconservatively recognized (HSP 60, HSP 70, HSP 90, HSP100 and sHSP) [57, 58]. We have identified members of thefamilies HSP 60 (spots 32, 40, 41, 42, 44, 46, 47 and 49), HSP70 (spots 20, 21, 22, 23, 24, and 25) and HSP 90 (spot 13).

4.1.5 Response mediated by phytohormones

Upon exposure to osmotic stress, plants can generate a widerange of responses. Some of these responses are triggered bythe primary osmotic stress signals, whereas others may

result from secondary stress signals such as phytohormones(e.g., ABA, ethylene), reactive oxygen species and intracel-lular second messengers (e.g., phospholipids) [59]. Bananahas a well-known ethylene-responsive fruit physiology and isa typical climacteric species [60]. During fruit ripening, eth-ylene production triggers a developmental cascade that isaccompanied by a massive conversion of starch to sugars, anassociated burst of respiratory activity and an increase inprotein synthesis. The differential regulation of several pro-teins in our meristematic tissue can be linked to ethylene.Ethylene is produced by almost all parts of higher plants. Ingeneral, meristematic and nodal regions are the most activein ethylene biosynthesis. Ethylene biosynthesis is induced bywounding, and physiological stresses such as flooding, chil-ling, disease, temperature and drought stress [61]. The stressinduced up-regulation of certain proteins: cellulase (spots 69and 70) (Fig. 4) [62], a ripening associated ascorbate peroxi-dase (spot 116) [63], ACC oxidase (spot 101) [64] and UDP-glucose pyrophosphorylase (spot 64 and 65) [44], brings onthe assumption of an enhanced ethylene production due tothe high-sucrose stress. Additionally, enhanced ethyleneproduction could explain the down-regulation of certainproteins like SuSy, lectin and chitinase. Hubbard et al. [65]have shown that the SuSy activity in banana drops dramati-cally to an undetectable level after exposure to ethylene.Study of banana lectins [63] and a chitinase [54, 63, 66]showed a similar expression pattern. These results suggest aprominent role for ethylene in abiotic stress and sugar me-tabolism. Noteworthy is the evidence that many jasmonate,ABA and stress-inducible genes are co-regulated by sugars[67]. Further studies are needed to reveal the genetic andmolecular basis of sensing and signaling pathways connect-ing sugar and stress in plants.

4.2 Comparison between varieties

Characterization of individual proteins revealed interestingdifferences between the tolerant variety Cachaco and thesusceptible variety Mbwazirume (Table 3). Genotype-specificexpression is a complex matter and can be the consequenceof multiple mechanisms: different gene loci, multiple alleles,different subunit interaction, different splice forms, or dif-ferent PTMs. We observed that some proteins (or isoforms)are unique (e.g. chitinase, spot 112; ASR, spot 129), or thatsome proteins (isoforms) are expressed at different levels(e.g. OSR40, spot 99; HSP 60, spot 44; phosphoglyceratekinase, spots 85, 86, 87, 88, 89 and 94; UGPase, spot 64;phosphoglucomutase, spot 28). We were able to discriminatebetween different isoforms and show the variety-specificexpression and stress responses (Table 3). This demonstratesthe power of 2-DE. We observed a genotype-specific expres-sion of certain proteins (isoforms) involved in energy me-tabolism (e.g., phosphoglycerate kinase, phosphoglucomu-tase, UGPase) and proteins that are involved in the stressadaptation (e.g., OSR40-like protein, ASR). These isoforms orunique proteins are correlated to the dehydration-tolerant



cultivar and await further research to obtain causative evi-dence. The candidates will be validated by screening the dif-ferent genotypes of the banana collection and their use aspotential transgenes in dehydration-sensitive varieties will beinvestigated. Also the membrane proteome should not beneglected from future research to pinpoint proteins relevantin response to dehydration tolerance.

The abscisic acid and salt stress responsive plant genefamily OSR40, encoding hydrophilic proteins with duplicateddomains, was for the first time characterized in a salt-tolerantrice variety by Moons et al. [68, 69]. In rice, OSR40 is inducedby ABA, is not responsive to salicylic acid and ethylene, and isrepressed by jasmonic acid, indicating an osmotic-stress-spe-cific response. Riccardi et al. identified the same type of pro-tein in maize during water-deficit response [24], and linked itto a dehydration-tolerant variety [70]. A BLAST search againstOryza sativa with OSR40 (gi)34902150) as query, returned sixsignificant subjects: r40c1, r40g2, r40c2, r40g3, unknownprotein and a putative r40c1. A BLAST search against Arabi-dopsis thaliana returned one entry (hydroxyproline-rich glyco-protein family protein) with an expectancy of 3e -54. Weidentified two isoforms of the OSR40 family (spots 98, 99).OSR40 was slightly up-regulated after high-sucrose stress(Table 3). In the dehydration-tolerant variety, OSR40 was avery abundant protein under high concentrations of sucrose,while the expression level of OSR40 in dehydration-suscep-tible variety is a factor 6.4 lower (Fig. 5.I).

ASR (spot 129) can only be detected in the dehydration-tolerant variety Cachaco (Fig. 5.II). This protein was descri-bed by Iusem et al. [71] in tomato as an ABA/water-stressripening-related protein. Three different hypotheses havebeen proposed concerning its function: (i) a non-histonechromosomal protein [72], (ii) accumulation in response toabiotic stress as protective hydrophilins [73, 74], or (iii) a linkbetween sugar metabolism and ABA signaling [75]. Thesefunctions are likely to be complementary [76]. ASR could actas a non-histone chromosomal protein that plays a role intranscriptional modulation of one or many genes related tocarbohydrate mobilization and/or osmoregulation. ASR wasalso characterized in maize by Riccardi et al. [24, 70]. As inour case, Riccardi et al. did not find any expression of ASR inthe dehydration-susceptible variety, but it was specificallyexpressed in the roots and young leaves of the tolerant vari-ety. A banana ASR has been sequenced and has a molecularmass of 16 264 Da. ASR is a very abundant protein in thedehydration-tolerant variety under control conditions. It hasbeen shown that ASR is inducible by sucrose and limitedlight [75], and also that ASR is up-regulated by ABA and thatsucrose is necessary for ABA up-regulation. Our controlsamples were grown on 0.09 M sucrose in the dark. Expres-sion of ASR was slightly down-regulated during high-sucrose stress, but the expression could still be sufficient toexert its protective function. Interestingly, Frankel et al. [77]demonstrated accelerated rates of mutations in the Asr2 genein tomato lineages adapted to dry habitats, leading to aminoacid substitutions. The substitution of a few amino acids in

Figure 5. Variety-specific proteins. (I) OSR40 expression undercontrol conditions (experimental molecular mass: 40 kDa, pI6.84). (II) ASR expression under control conditions (experimentalmolecular mass 23 kDa, pI 6.49). (a) Dehydration-resistant varietyCachaco and (b) dehydration-susceptible variety Mbwazirume.Identified proteins are numbered and indicated with a whitearrowhead. Histograms illustrate the central tendency (% spotvolume) and the dispersion interval of three repetitions.

tomato is responsible for a pI shift (from pI 6.76 to 6.61, and6.76 to 6.78). The proteins in our dehydration-susceptiblevariety Mbwazirume with the same molecular mass andwithin 0.1 pI range have been identified to check the possi-bility of an amino acid substitution-mediated pI shift. Nopeptides related to ASR could be detected.

4.3 Overall conclusions

Banana (Musa spp.) cauliflower-like meristems are an excel-lent model to study meristematic cells at the proteome level.This work proves that quantitative differential proteomeanalysis is successful, even for limited amounts of tissue of arecalcitrant crop with an unsequenced genome. We havepreviously shown that a preculture of the cauliflower-likemeristems on 0.4 M sucrose is essential for the acquisition oftolerance towards the severe dehydration associated withcryopreservation [4, 5]. The large scale protein study pre-sented here implies links between sugar metabolism, cellwall integrity and ethylene signaling. The maintenance of anosmoprotective intracellular sucrose concentration, theenhanced expression of particular genes of the energy-con-serving glycolysis, and the conservation of the cell wallintegrity may be essential to maintain homeostasis and tosurvive dehydration. We confirm the cross-talk model be-tween UGPase and SuSy [43], and suggest that ethylene has arole in this model. Finally, we put forward some interestingvariety-specific candidates that may contribute towardsdehydration tolerance (specific isoforms of phosphoglyceratekinase, UGPase, phosphoglucomutase, ASR, OSR40).

Access to the Syngenta Musa 3’ EST database, donated bySyngenta to the INIBAP for use within the framework of theGlobal Musa Genomics Consortium is acknowledged. Financial



support from the Belgian National Fund for Scientific Research(FWO-Flanders) is gratefully acknowledged. This research wasinitiated with financial support from the Commission of theEuropean Communities (QLK5-CT-2002-1279, coord. R. Swen-nen, Catholic University of Leuven, Belgium, within the Qualityof Life and Management of Living Resources Program). Thestudy does not necessarily reflect the Commission’s views and in noway anticipates its future policy in this area. The authors wouldalso like to thank Stef Vandamme for technical assistance, Dr.Stéphane Dussert (IRD, France) for the sugar analysis, Prof. JanGeuns (K. U. Leuven, Belgium) for the use of the dew pointmicrovolt meter and Annelies Vertommen for critical reading.

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Banana (Musa spp.) as a model to study the meristem proteome: Acclimation to osmotic stress