Accepted Manuscript Comparative shoot proteome analysis of two potato (Solanum tuberosum L.) genotypes contrasting in nitrogen deficiency responses in vitro

Philipp Meise, Anna Maria Jozefowicz, Ralf Uptmoor, HansPeter Mock, Frank Ordon, Annegret Schum PII: DOI: Reference:

S1874-3919(17)30251-8 doi: 10.1016/j.jprot.2017.07.010 JPROT 2901

To appear in:

Journal of Proteomics

Received date: Revised date: Accepted date:

15 May 2017 10 July 2017 15 July 2017

Please cite this article as: Philipp Meise, Anna Maria Jozefowicz, Ralf Uptmoor, HansPeter Mock, Frank Ordon, Annegret Schum , Comparative shoot proteome analysis of two potato (Solanum tuberosum L.) genotypes contrasting in nitrogen deficiency responses in vitro, Journal of Proteomics (2016), doi: 10.1016/j.jprot.2017.07.010

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ACCEPTED MANUSCRIPT Comparative shoot proteome analysis of two potato (Solanum tuberosum L.) genotypes contrasting in nitrogen deficiency responses in vitro Philipp Meisea, Anna Maria Jozefowiczb, Ralf Uptmoorc, Hans-Peter Mockb, Frank Ordona, Annegret Schuma * a

Julius Kühn-Institute (JKI), Federal Research Centre for Cultivated Plants,

Institute for Resistance Research and Stress Tolerance,

b

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OT Groß Lüsewitz, Rudolf-Schick-Platz 3, 18190 Sanitz, Germany

Leibniz Institute of Plant Genetics and Crop Plant Research (IPK),

Department of Physiology and Cell Biology, Applied Biochemistry, OT Gatersleben, Corrensstraße 3, 06466 Stadt Seeland, Germany c

University of Rostock,

Justus-von-Liebig-Weg 6, 18055 Rostock, Germany

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* Corresponding author

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Faculty of Agricultural and Environmental Science,

Abstract

Aiming at a better understanding of the physiological and biochemical background of nitrogen use efficiency,

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alterations in the shoot proteome under N-deficiency were investigated in two contrasting potato genotypes grown in vitro with 60 and 7.5 mM N, respectively. A gel based proteomic approach was applied to identify

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candidate proteins associated with genotype specific responses to N-deficiency. 21 % of the detected proteins differed in abundance between the two genotypes. Between control and N-deficiency conditions 19.5 % were differentially accumulated in the sensitive and 15 % in the tolerant genotype. 93 % of the highly N-deficiency

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responsive proteins were identified by MALDI TOF/TOF mass spectrometry. The major part was associated with photosynthesis, carbohydrate metabolism, stress response and regulation. Differential accumulation of

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enzymes involved in the Calvin cycle and glycolysis suggest activation of alternative carbohydrate pathways. In the tolerant genotype, increased abundance under N-deficiency was also found for enzymes involved in chlorophyll synthesis and stability of enzymes, which increase photosynthetic carbon fixation efficiency. Out of a total of 106 differentially abundant proteins, only eight were detected in both genotypes. Our findings suggest that mutually responsive proteins reflect universal stress responses while adaptation to N-deficiency in metabolic pathways is more genotype specific.

Significance Nitrogen losses from arable farm land considerably contribute to environmental pollution. In potato, this is a special problem due cultivation on light soils, irrigation and the shallow root system. Therefore, breeding of cultivars with improved nitrogen use efficiency and stable yields under reduced N fertilization is an important issue. Knowledge of genotype dependent adaptation to N-deficiency at the proteome level can help to understand regulation of N efficiency and development of N-efficient cultivars.

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Keywords N-deficiency; Potato (Solanum tuberosum); Shoot proteome; Comparative proteomics; In vitro

Highlights 

Two potato genotypes responded differently to N-deficiency in morphological and physiological traits as well as in the proteome pattern.



A total of 59 protein spots in the sensitive genotype and 47 in the stable genotype differed in abundance

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under N-deficiency, of which 93 % were successfully identified.

Protein spots altering in both genotypes in the same direction were mostly associated with general stress response.

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Affected genotype specific protein species were mostly associated with chlorophyll metabolism and photosynthesis.

Introduction

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Nitrogen (N) is one of the most effective mineral nutrients with respect to yield and quality and is essential for efficient crop production. Global anthropogenic N fixation doubled between 1980 and 2010 [1] and N consumption for fertilizers increased from 83 million t N in 2002 to 109 million t in 2014 [2]. Synthetic N

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fertilizers were the basis of significantly increasing crop yields in the last century, however, they are also associated with environmental pollutions, i.e. leaching of nitrate, surface runoff into rivers and marine ecosystems as well as loss of gaseous compounds into the atmosphere. Crop plants take up only 30 - 50 % of the

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applied N [3, 4], depending on the crop, variety, technical management as well as on the amount and timing of application. Therefore, there is a concern about the excess of N that is not used by crops. This is a special issue in potato (Solanum tuberosum) because the common production in sandy soils with high N fertilization and

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irrigation combined with the shallow root system results in a high risk of nitrate leaching [5, 3]. In recent years, the necessity of sustainability in agricultural production has been increasingly recognized. One of the objectives

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is to reduce the negative environmental impacts of N fertilization while retaining high and stable yields. In this context, two approaches have been proposed: the optimization of fertilizer usage by precision farming and the reduction of N application by breeding of cultivars with optimized N use efficiency (NUE) [4].

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NUE of plants is a complex trait and, in addition, depends on soil texture, climate conditions, the interaction between soil and bacterial processes as well as on the genotype. Moll et al. [6] defined NUE as the crop yield per unit of available N in the soil. NUE is subdivided into two processes: uptake efficiency (NupE, the ability to remove N from the soil) and utilization efficiency (NutE, the ability to use the absorbed N to produce yield). Whereas the NupE is mainly affected by root morphology and N transporters located in the plasma membrane, the NutE is affected by physiological and biochemical processes. Both processes are under separate genetic control [7]. In potato, variation in NUE has been identified in cultivars and wild Solanum species [5, 8, 9, 10, 11] though the physiological basis of genotypic variation is poorly understood. The identification of key elements that limit and control NUE is of major importance to develop cultivars with improved NUE. Many processes are involved in the regulation of NUE, including N-uptake, assimilation, amino acid and protein synthesis, C/N storage and metabolism, signalling and regulation of N homeostasis as well as translocation, remobilization and senescence [12]. In addition to studies on the genetic basis of NUE such as genome wide association studies

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ACCEPTED MANUSCRIPT [13], investigations into the physiological and biochemical mechanisms of NUE are required to understand species and genotype dependent differences in a complex interaction framework of genes and metabolic pathways [7, 12]. Forward genetic tools such as proteomics are suitable to obtain a comprehensive overview of the changes in response to stress and may help to close the information gap between genotype and phenotype. Many proteomic analyses were successfully conducted to elucidate abiotic stress responses, mostly dealing with cold, heat, drought, salinity and toxic metals [14, 15]. In potato, comparative proteomic studies were performed, for example, with respect to osmotic stress [16], salt stress [17], salt and cold stress [18] and farming systems [19, 20]. Only a few studies were devoted to deficiency of mineral nutrients and differential genotype adaptation

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[21]. Proteomic investigations of N-deficiency response were conducted for example in Agrostis [22], Arabidopsis [23], barley [24], Indian mustard [25], maize [26, 27, 28], rice [29, 30, 31, 32], wheat [33, 34] and triticale [35]. To our knowledge, no corresponding studies have been conducted in potato so far. Therefore, this study aimed to analyse the shoot proteome pattern of two genotypes that responded differentially to high and low N availability.

Materials and Methods

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Plant material and growth conditions

The cultivar Topas was provided by Europlant Pflanzenzucht (Lüneburg, Germany) and the cultivar Lambada by NORIKA (Groß Lüsewitz, Germany). In vitro cultures were performed according to Schum and Jansen [11]. For

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the experiments ten shoot tips of two weeks old plantlets were fixed into perforated stainless steel plates and transferred to 500 ml glass vessels with 50 ml liquid Murashige and Skoog [36] basal medium. The original N concentration of 60 mM (high N, HN) was used for the control and 7.5 mM (low N, LN) for the N-deficiency

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treatment. Plants were grown in a growth chamber at 18 °C in a 16 h photoperiod at a light intensity of approx. 140 μmol m-2 s-1 PAR. Eleven days after culture initiation, shoot tips were harvested for proteomic analysis. In addition, biomass growth and physiological traits were investigated. Three independent time-shifted experiments

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were performed, each with three replications per cultivar, N treatment and duration of cultivation. The experimental setup for proteomic analyses is illustrated in the supplemental figure 1 (Fig. S1). The experiments

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were conducted separately for proteome analysis and for biomass determination.

Biomass determination and physiological parameters

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Shoots and roots were separated to determine the organ-specific fresh and dry matter. The assimilated N content in plant dry matter was analyzed as crude protein by NIR spectroscopy upon Kjeldahl calibration [37]. For calculation of the absorbed N, the remaining N (nitrate-N and ammonia-N) in the media at the end of each culture period was determined spectrophotometrically [11]. The chlorophyll content was indirectly measured with a SPAD-502 chlorophyll meter (Konica Minolta, Hamburg, Germany). Data were statistically analyzed by applying ANOVA procedure with SAS 9.4 software, using a general linear model with sum of squares type III.

Protein extraction and quantification Shoot tips of 1-1.5 cm length were harvested, frozen immediately in liquid N2 and stored at -80 °C until protein extraction. The shoot tips were ground in liquid N2 using mortar and pestle. For total protein extraction, the TCA method [38] was used with some modifications: about 1 g tissue powder was precipitated in 10 ml ice-cold extraction buffer [20 % (w/v) TCA and 0.2 % (w/v) DTT in acetone] and incubated at -20 °C overnight. The

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ACCEPTED MANUSCRIPT suspension was centrifuged at 21000 g for 20 min at 4 °C. The resultant pellet was washed two times with icecold washing buffer [0.2 % (w/v) DTT in acetone] by incubation at -20 °C for 1 h and centrifugation at 21000 g for 10 min at 4 °C per washing step. Subsequently, the pellet was dried in a vacuum centrifuge for 10 min and stored at -20 °C until analysis. The pellet was solubilized in rehydration buffer [7 M urea, 2 M thiourea, 2 % (w/v) CHAPS and 0.002 % (w/v) bromophenol blue], dissolved by sonication for 5 min and then incubated on a shaker for 1 h at room temperature. The mixture was centrifuged at 21000 g for 10 min at 4 °C and the supernatant was removed carefully. The protein concentration was determined using the 2D Quant Kit (GE Healthcare, Freiburg, Germany) with BSA as standard according to the manufacturer’s instructions. Samples

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were adjusted to identical protein concentrations and the buffer was added to 20 mM DTT, 0.5 % (v/v) IPG buffer pH 3-11 (GE Healthcare) and 0.012 % (v/v) DeStreak reagent (GE Healthcare).

Two-dimensional (2D) IEF/SDS PAGE

2D-PAGE was performed on 3 replicates of each independent experiment. In total 36 2D-PAGE gels (3 experiments x 3 replicates x 2 cultivars x 2 N-levels) were carried out for this analysis. For isoelectric focussing (IEF) 450 μg BSA equivalent protein per sample were loaded onto 18 cm Immobiline TM DryStrip gels (IPG), pH

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gradient pH 3-11, non-linear (GE Healthcare). IEF was carried out in a Protean IEF cell (BioRad, Munich, Germany) at 20 °C. Strips were rehydrated for 9 h at 50 V before isoelectric focusing involving the following steps: (I) 200 V for 1 h, (II) linear gradient to 1000 V over 1 h, (III) linear gradient to 10000 V over 6 h and (IV)

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10000 V for a total of 40 kVh for the entire run. For protein separation in the second dimension, IPG strips were equilibrated for 10 min in equilibration solution I [6 M urea, 30 % (v/v) glycerol, 2 % (w/v) SDS, 50 mM TrisHCl buffer at pH 8.8 and 1 % (w/v) DTT] and for 10 min in equilibration solution II [6 M urea, 30 % (v/v)

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glycerol, 2 % (w/v) SDS, 50 mM Tris-HCl buffer at pH 8.8 and 2.5 % (w/v) iodoacetamide]. The equilibrated strips and a PrecisionPlusProteinTM unstained standard (BioRad) were placed on top of vertical 12 % TricineSDS PAGE gels, according to Schägger [39]. Electrophoresis was performed for 21 h at 30 mA per gel using a

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Protean II XL gel system (BioRad, 18.5 cm x 20 cm and 1 mm thickness). After electrophoresis, gels were fixed with 10 % (v/v) acetic acid in 40 % (v/v) methanol for at least 2 h. Finally, proteins were stained with colloidal

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coomassie blue 250 G for 24 h on a tumbling shaker according to the procedure of Neuhoff el al. [40].

Gel imaging and statistical analysis

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Gels were scanned at a resolution of 200 dots per inch with an Epson GT-12000 Photo Scanner (Epson, Meerbusch, Germany) and image analysis was performed with the Delta 2D version 4.2 software (Decodon, Greifswald, Germany). After background subtraction, gel images were matched according to cultivar and treatment. A synthetic gel image of all 36 gels was compounded followed by automatic spot detection. The resulting spots were filtered by the relative spot volume set at > 0.02 % and a spot quality > 0.4. Spots meeting these specifications on the synthetic gel were in silico transferred to all gels of the experiment. Spot volumes were normalized to minimize methodical gel variation, whereby each spot on a gel image is expressed relative to the total volume of all spots that are present on this image, excluding the 10 spots with the highest volumes on each gel. A Welch’s t-test for unequal group variances based on the normalized relative spot volume was applied to determine significant alteration in spot patterns between the control and N-deficiency treatment of each cultivar. Only spots with a p-value ≤ 0.05 and with a ≥ 1.5 fold change (representing a ratio ≤ 0.667 and ≥ 1.5) were considered relevant for further analysis. The experimental molecular mass of each protein spot was

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ACCEPTED MANUSCRIPT estimated by alignment with the molecular weight standard and the experimental pI was estimated by migration of the protein spots on IPG strips.

Protein identification and data processing A total of 196 spots were submitted to MS-based protein identification, whereby each spot was picked from 2 gels. Protein spots were in-gel digested as described by Witzel et al. [41]. MALDI-TOF-MS/MS ultrafleXtreme TM (Bruker, Bremen, Germany) was used for the peptide mass fingerprinting (PMF) and MS/MS spectra acquisition. External calibration with subsequent internal mass correction was carried out. PMF and data

were

submitted

to

identify

matching

peptides

to

the

MASCOT

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MS/MS

search

engine

(www.matrixscience.com) through the Bruker BioTools interface software. Protein identification was performed by searching in a potato protein database based on the sequences from Solanum tuberosum group Phureja DM13 (http://solanaceae.plantbiology.msu.edu/pgsc_download.shtml) with following parameters: trypsin as specific protease; monoisotopic mass accuracy; peptide mass tolerance of +/- 50 ppm; fragment mass tolerance of +/-0.7 Da with the number of allowed missed cleavages set to one; possible modifications: carbamidomethyl (Cys), oxidation (Met) and propionamide (Cys). Mascot protein scores greater than 58 for PMF were considered

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significant (p ≤ 0.05) and individual ion score for MS/MS identification > 28 indicated statistical identity (p ≤ 0.05). Only spots with identical protein identification in two replicates were considered. Protein sequences of positively

identified

proteins

were

validated

by

alignment

against

NCBInr

database

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(http://www.ncbi.nlm.nih.gov/) using BLASTp. Basic information on the proteins and their functions was obtained using databases of UniProt (http://www.uniprot.org/), InterPro (http://www.ebi.ac.uk/interpro/) and KEGG (http://www.genome.jp/kegg/). Grouping of functional annotation of the identified proteins was based on

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GO biological processes (http://geneontology.org/).

Results

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Differential responses of morphological and physiological traits Figure 1 and Table 1 demonstrate the contrasting response of cvs. Lambada and Topas to limited N availability

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after 11 days of culture (DOC). Root and shoot biomass (FM) were significantly affected by genotype (G), N level (N) and respective interactions (G x N). Generally, cv. Lambada was characterized by a substantial reduction of biomass and chlorophyll content while cv. Topas proved to be more stable. Differences between the

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two genotypes regarding the N deficiency induced impact on specific parameters increased with prolonged culture period (Schum et al. submitted). Under both control and N-deficiency conditions, biomass production of cv. Lambada was higher as compared to cv. Topas after 11 DOC. However, under reduced N availability, losses of cv. Topas relative to the control were less. The FM of shoots and roots still reached 86% and 90% of the control, while it dropped in cv. Lambada to 63% and 73%, respectively. Genotype dependent differences were also observed in the ratio of root to shoot FM. Cv. Lambada showed higher ratios at both N levels (0.56 HN / 0.64 LN) compared to cv. Topas (0.41 HN / 0.42 LN). At this time point the effect of the N level was not significant. However, in the time course of culture until 18 DOC, the root to shoot ratios increased in both genotypes (cv. Lambada 1.07 HN / 0.83 LN; cv. Topas 0.54 HN / 0.61 LN) and significant differences were determined between N-levels and genotypes (Schum et al. submitted). While the root to shoot ratio dropped under reduced N availability compared to the control in cv. Lambada, it increased in cv. Topas due to a stimulation of root growth under N-deficiency conditions.

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ACCEPTED MANUSCRIPT The chlorophyll and crude protein contents were depending on the genotype and N level, while significant interactions of G x N were only observed for chlorophyll content after 11 DOC. Under HN, SPAD values with 41.1 and 45.8 as well as 34.1 % and 37.1 % for crude protein of shoot DM were on the same level for both cultivars. Under LN conditions, however, differences between cultivars became evident and were less pronounced in cv. Topas. In this cultivar, the chlorophyll and crude protein contents reached 93% and 64% of the control, while it was only 71% and 48% in cv. Lambada. Furthermore, effects of genotype, N-level and G x N interaction were also determined for the absorbed N. Under HN conditions, cv. Lambada absorbed 60% (25.0 mg) of the available N (42 mg), while cv. Topas absorbed only 41% (17.28 mg N). Under LN conditions, both

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genotypes totally absorbed the supplied N (5.3 mg).

Effects of nitrogen deficiency on genotype specific changes in 2D IEF/SDS-PAGE shoot proteome patterns Gel image analysis resulted in the detection of 513 differential spots that were included in the statistical analysis for comparing the relative normalized spot volume observed for the different cultivars under HN and LN conditions (Table 2). Cv. Lambada showed 100 differentially abundant protein spots (DAPS) (19.5 %) at a p ≤ 0.05, of which 59 spots were accumulated with a fold change ≥ 1.5. Thirty of these spots were more abundant

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under LN and 29 were more abundant under HN (Figure 2A). Cv. Topas showed 77 DAPS (15.0 %) at a p ≤ 0.05, of which 47 proteins were accumulated with a fold change ≥ 1.5. Out of these, 24 spots were more abundant under LN and 23 were more abundant under HN (Figure 2B). In accordance with the phenotypic data,

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cv. Lambada was more affected by N-deficiency and showed a larger change in the proteome pattern with 26% DAPS than cv. Topas with 22%. The comparison of the genotypes at either N level resulted in 133 DAPS (p ≤ 0.05) under HN and 145 DAPS under LN (Table 2). Principal compound analysis (PCA) performed on the

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whole spot pattern (Figure 3A) showed genotype and N level dependent clustering. When only DAPS from cv. Lambada were selected for PCA (Figure 3B) the clusters of HN and LN conditions were clearly separated and did not overlap with the clusters of cv. Topas HN and LN. Vice versa, when only DAPS from cv. Topas were

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taken into account (Figure 3C), the clusters of HN and LN were further separated and did not overlap with the clusters of cv. Lambada. This demonstrates the fundamental difference in DAPS patterns between cv. Lambada

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and cv. Topas. This finding was confirmed by the detection of only 8 DAPS from the 59 in cv. Lambada and 47 DAPS in cv. Topas that showed the same reaction in both genotypes.

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Identification of differentially expressed spots affected by nitrogen deficiency Shoot proteome patterns were significantly affected by N-deficiency and genotype specific changes were observed. 59 DAPS (p ≤ 0.05, fold change ≥ 1.5) in cv. Lambada (Figure 2A) and 47 DAPS in cv. Topas (Figure 2B) were subjected to MALDI TOF/TOF mass spectrometry. Each spot of interest was picked from two gels, so that a total of 196 spots were analyzed via MS. Only spots that were consistently identified in both replicates were considered. Overall, 93% of the selected N-deficiency responsive proteins were identified and are compiled in Tables 3-5. In case that two or three different proteins were identified in the same spot due to overlapping of proteins after 2D-electrophoresis, the respective spot numbers were marked with brackets. In some cases, identical proteins were determined in more than one spot with, however, similar tendencies of changes in abundance. In a few exceptions, the change of abundance was different, i.e. in case of polyadenylate-binding protein (spots T31/T35/T36, ratio 2.52/0.42/0.38) and rubisco activase (spots T13/X5, ratio 1.90/0.52). The big

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ACCEPTED MANUSCRIPT differences between calculated pI and/or MW (8.01/48.1) and observed values with 4.9/46.3 in spot T13 and 5.2/105.0 in spot X5 indicate posttranslational modifications. The identified proteins of both genotypes were categorized into 9 functional groups of biological processes based on information of Gene Ontology (GO) and KEGG databases: Stress response (18 % of the proteins in cv. Lambada / 23 % of the proteins in cv. Topas), protein synthesis/processing/degradation (17 % / 13 %), carbohydrate metabolism (14 % / 10 %), regulation of transcription/cell processes regulation (8 % / 13 %), photosynthesis ( 8 % / 10 %), secondary metabolism (10 % / 13 %), amino acid metabolism (5 % / 2 %), oxidative stress (6 % / 6 %), energy metabolism (3 % / 2 %), and miscellaneous (11 % / 8 %). The allocation of

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proteins to the respective groups is shown in Figure 4. Major differences were found between the genotypes in respect to number and direction of abundance changes within each of the categories.

Most of the identified proteins were affected by N-deficiency only in one of the investigated genotypes while they did not significantly change in abundance in the other cultivar. Only three proteins showed a differential reaction in the two cultivars, i.e. rubisco activase (X5 down, T13 up), glyceraldehyde-3-phosphate dehydrogenase (L8 down, T3 up) and glucose-1-phosphate adenylyltransferase (L4 down, T1 up). Table 3 shows the identified proteins of the eight DAPS that were modulated consistently in both genotypes. Interestingly, five

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of these proteins are associated with general stress response (21 kDa seed protein [X1], SGT1[X2], Patatin-05 [X2], glucan endo-1,3-beta-glucosidase [X3], PR protein P2 [X4]). In addition, two different peroxidases [X7, X3] are involved in oxidative stress defence. All of the aforementioned proteins showed an increased abundance

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under LN conditions. One additional protein with higher abundance is involved in cell redox homeostasis as well as folding and stabilization of proteins (disulfide-isomerase [X8]), two proteins with lower abundance are associated with photosynthesis (rubisco activase [X5]) and with protein processing (cell division cycle protein

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[X6]). Altogether, these findings suggest that proteins affected in both genotypes are rather involved in universal stress response while adaptation to N-deficiency in metabolic pathways is more genotype specific.

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Discussion

Morphological and physiological responses to N-deficiency

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Our study aimed at the determination of early proteomic responses by using an experimental system, which allowed to control environmental influences and to focus on N-deficiency. However, major drawbacks of in vitro culture systems for phenotyping as C-mixotrophy and reduced transpiration rates due to high air humidity have

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to be born in mind. The potato genotypes Lambada and Topas were selected according to results of an in vitro screening comprising 13 cultivars in response to N-deficiency by Schum and Jansen [11]. Cv. Lambada belongs to a group that produced the highest biomass under sufficient N supply but showed a strong decline when N availability was reduced. In contrast, cv. Topas produced low biomass under sufficient N conditions, but responded tolerant to N-deficiency and produced biomass comparable to cv. Lambada under N-limiting conditions. Further traits associated with N metabolism were also found to be affected differently in the two cultivars after 21 days of culture, including N-uptake capacity, stimulation of root growth under N-deficiency as well as crude protein and chlorophyll content [11]. In this study a consistent response to N limitation between the two contrasting genotypes was detected already as early as 11 DOC. According to the categorization of Gerloff [42], cv. Lambada is regarded as an efficient responder on the basis of biomass production. In contrast, cv. Topas is classified as an efficient non-responder, as this genotype produces high amounts of biomass under low N input but does not react to increased N. From the biological point of view, cv. Topas appears tolerant to

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ACCEPTED MANUSCRIPT N-deficiency, as biomass production is more stable under N limited conditions as compared to the sensitive cv. Lambada, which is characterized by a dramatic decline.

Alterations of shoot proteome patterns in response to N-deficiency Plots of a principal component analysis of protein spots (Figure 3) showed that the two genotypes responded quite differently to N-deficiency. Such genotype specific alterations of the shoot proteome in response to mineral deficiency were reported for example for phosphorus in Brassica napus [43] as well as for N in rice [30] and wheat [33]. Song et al. [30] identified differentially accumulated proteins associated with N-deficiency in the

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rice leaf proteome. Out of a total of 31 identified proteins, six proteins (rubisco activase, glyceraldehyde-3phosphate dehydrogenase, chlorophyll a-b binding protein, carbonic anhydrase, rubisco large subunit, eukaryotic initation factor 4A) were also detected in the present investigation. Bahrmann et al. [33] identified 14 proteins with significant genotype x N interaction in the leaf proteome of wheat, of which six proteins (methionine synthase, phosphoglycerate kinase, malate dehydrogenase, rubisco activase, fructose bisphosphate aldolase, oxygen evolving enhancer) were also detected in our analysis. Interestingly, only the rubisco activase was found to be affected in all three shoot proteome investigations regarding N-deficiency. The responding genotype in

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terms of biomass performance cv. Lambada exhibited more alterations in the shoot proteome under N-deficiency as compared to the less responding genotype Topas. Also in rice, more proteins changed in abundance under

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reduced N supply in the sensitive as compared with the tolerant cultivar [30].

Major N-deficiency induced metabolic alterations

Proteins involved in nearly all metabolic processes were affected by N-deficiency (Figure 4). The largest

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fractions comprise stress response proteins, which were mainly more abundant and proteins involved in protein metabolism with mostly lower abundance.

Affected proteins associated with amino acid and protein metabolism reflect the reduced amounts of assimilated

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N for subsequent metabolic processing (Table 4 and 5), which also became apparent in the reduced crude protein contents under N-deficiency (Table 1). N-deficiency induced regulation of protein processing became evident in

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changed levels of proteases, protease inhibitors as well as several proteins involved in RNA metabolism. In cv. Lambada several proteases were reduced in abundance (Thimet oligopeptidase [L26, L27], Clp protease ATPbinding subunit clpA [L28, L29]) while in cv. Topas a decrease was detected for a multifunctional

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aminopeptidase [T20] and a strong increase for a leucine aminopeptidase [T16, T17]. Interestingly, under Ndeficiency several protease inhibitors were affected especially in the sensitive cv. Lambada (cysteine protease inhibitor [L14], aspartatic protease inhibitor [L13, L15, L16]). Proteases are responsible for targeted protein degradation and remobilization of stored proteins. Proteases and their specific inhibitors are involved in selective protein turnover facilitating regulation in physiological processes and environmental stress response [44, 45, 46]. Altogether, our findings indicate N-deficiency induced higher proteolytic activity presumably due to incipient cell senescence and protein remobilization. N-limitation further influenced several proteins involved in RNA metabolism and cell regulation (Table 4 and 5). Among these, an auxin binding protein (ABP) was affected by N-deficiency specifically in the tolerant cv. Topas with a ratio of 5.44 in comparison to the control [T30], which was the strongest response among the differentially accumulated proteins that were identified in this investigation. ABPs are involved in rapid auxin effects on cell elongation [47]. Additionally, some ABPs exhibit

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ACCEPTED MANUSCRIPT beta-1,3-glucanases activity [48], which was also strongly affected by N-deficiency in both genotypes [X4, X3] and exclusively in cv. Topas [T6]. The predominant differences in genotype dependent responses to N-deficiency were detected in chlorophyll synthesis, photosynthesis, carbon fixation and metabolism and are summarized in Figure 5, 6 and 7. In cv. Lambada two enzymes involved in chlorophyll synthesis, i.e. the geranylgeranyl diphosphate reductase [L33] and the 4-hydroxy-3-methylbut-2-enyl diphosphate synthase (HDS) [L34] were detected with lower abundance under N-deficiency (Figure 5). This finding reflects major disturbances in chlorophyll synthesis and is consistent with the observed decline in chlorophyll content as compared to control conditions (Table 1).

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Likewise in Nicotiana, suppression of the geranylgeranyl diphosphate reductase resulted in decreased contents of chlorophyll and of the thylakoid membrane stabilizing tocopherol [49]. In cv. Topas the glutamate-1semialdehyde 2,1-aminomutase (GSA-AT) [T24] and a protochlorophyllide reductase (POR) [T27], that are involved in porphyrin and chlorophyll metabolism [50, 51], were less abundant, while considerably higher levels of Mg-protoporphyrin IX chelatase, a subunit of ChlI (Mg-chelatase) [T13] were accumulated. The latter enzyme catalyzes the insertion of Mg+ into protoporphyrin IX, a precursor of chlorophyll, which has been associated with chloroplast signalling under stress conditions [50]. It was shown that suppression of Mg-

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chelatase in transgenic Nicotiana plants resulted in chlorophyll-depleted leaves [52]. Possibly, the comparatively high chlorophyll content of cv. Topas under N-deficiency can be related to Mg-chelatase accumulation. Components of the light harvesting complexes were found to be affected by N-deficiency only in cv. Lambada,

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i.e. the chorophyll a/b binding protein with increased abundance [L14] and the PSII associated manganesestabilizing protein with decreased abundance [L18] (Figure 6). The carbon fixation process was affected by Ndeficiency in both genotypes. The large subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase (rubisco)

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was identified with lower abundance in cv. Lambada [L19, L29], obviously reflecting the reduced rubisco levels under N depletion. Similar observations were made by Song et al. [30] and Kim et al. [31], who studied N stress responsive proteins in rice. In cv. Topas the rubisco accumulation factor 1, which mediates the biogenesis of the

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rubisco holoenzyme [53], was reduced in abundance [T15] as well as the TOC75-III protein [T21], which is involved in the transfer of the rubisco small subunit (SSU) from the chloroplast to the cytosol. Two more

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enzymes involved in CO2 fixation, the phosphoglycerate kinase (PGK) and the glyceraldehyde-3-phosphate dehydrogenase (GADPH) were also reduced in abundance under N-deficiency in cv. Lambada [L3, L8], indicating a reduced synthesis of carbohydrate compounds. In contrast, the GADPH level increased under N-

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deficiency in the stable cv. Topas [T3]. Consistently with these findings, this enzyme accumulated in an N depleted tolerant rice genotype while it was non-responsive in the sensitive cultivar [30]. Fructose 1,6bisphosphate (FBP) aldolase, which is involved in transitory starch synthesis during photosynthesis, was more abundant under N-deficiency in cv. Lambada [L1]. An overexpression of FBP aldolase resulted in higher biomass accumulation and increased photosynthetic capacity in transgenic tobacco plants [54], which the authors attributed to the stimulated regeneration of rubisco in the Calvin cycle pathway and thereby enhanced CO 2 fixation. However, the PGK, GADPH and the FBP have functions in further cellular processes, e.g. in glycolysis and gluconeogenesis. The rubisco activase (RCA) restores the catalytic activity of rubisco by removal of inhibitors thus ensuring free access to the reaction site [55]. RCA was identified with reduced abundance under N-deficiency in both genotypes [X5], however, with a stress induced higher abundance in an additional spot of cv. Topas [T13]. Song et al. [30] found increased levels of RCA in response to N-deficiency in rice while, in contrast, Bahrman et al.

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ACCEPTED MANUSCRIPT [33] detected increased levels of the RCA with increasing N supply in wheat, which corresponded to the increased photosynthetic activity at high N levels. The carbonic anhydrase plays an important role in carbon fixation by promoting a continuous supply of CO2 to rubisco by recapturing CO2 from photorespiration and thereby improving the carboxylation rate of rubisco [56]. This enzyme was also more abundant in cv. Topas [T14] under N-deficiency. Several enzymes involved in carbohydrate processing were affected by N deficiency genotype specifically (Figure 7), thereby reflecting the close interrelationship of C- and N-metabolism. Glucose-1-phosphate adenylyltransferase provides ADP-glucose for leaf starch synthesis [57] and was found to be more abundant

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under N-deficiency in the stable cv. Topas [T1] and less abundant in cv. Lambada [L4]. The central metabolic pathway for degradation of glucose, the glycolysis, provides energy equivalents and carbon skeletons for different metabolic processes. Involved enzymes include a specific cytosolic pyrophosphate dependent phosphofructokinase enzyme (PFP), which was present to a lesser extent under N-deficiency in the sensitive cv. Lambada [L6]. The reversibility of the PFP catalyzed reaction enables rapid regulation in response to changes in the carbon availability and maintenance of the appropriate equilibrium between the hexose- and triose-phosphate pools [58]. Therefore, the stability of this enzyme in cv. Topas may reflect its advanced tolerance. In addition to

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their role in the Calvin cycle, the previously discussed fructose bisphosphate aldolase (FBP) [L1], glyceraldehyde-3-phosphate dehydrogenase (GADPH) [L8] [T3] and phosphoglycerate kinase (PGK) [L3] (Figure 6) also have functions in the glycolysis and gluconeogenesis and were affected by N-deficiency in a

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genotype dependent manner (Figure 7). Furthermore, a malic enzyme was accumulated to a higher level under N-deficiency in cv. Topas [T2] possibly facilitating the use of stored carboxylic acids and enhancing energy production through oxidative decarboxylation of malate in the TCA cycle. Such regulation has been discussed in

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relation to environmental or developmental stress [59, 60]. Also exclusively in cv. Topas, a mitochondrial malate dehydrogenase protein species, which is known to be involved in the oxidation of malate in the TCA cycle and in the reverse reaction during the conversion of glycine to serine for providing the glycine decarboxylase (GDC)

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with NAD+ [61], decreased under N-deficiency [T4]. Interestingly, the GDC was also affected by N-deficiency in our investigations. The unfavourable oxygenation reaction of rubisco generates 2-phosphoglycolate, which is

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recycled to 3-phosphoglycerate within the photorespiration pathway requiring a high energy input. The intermediate glycine is converted to serine mediated by the GDC and the serine hydroxymethlytransferase (SHMT) [62]. Under N-deficiency the GDC decreased in two spots of cv. Lambada [L5, L7] but was unaffected

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in cv. Topas, in which contrarily the SHMT was reduced [T5]. Timm et al. [63] found that overexpression of the GDC considerably enhanced net photosynthesis and growth of Arabidopsis thaliana. The conversion of glycine to serine releases cell toxic NH3, which is immediately processed by the GS/GOGAT system and further associated reactions. One of the respective enzymes, glutamate dehydrogenase (GDH), showed higher abundance under N-deficiency in cv. Lambada [L9]. Increased GDH activity has also been associated with increased proline synthesis [64], a widespread organic osmolyte, which is known to accumulate in response to diverse abiotic stresses. Overall, glycolysis, TCA cycle and gluconeogenesis are highly flexible metabolic pathways and enable the bypass and substitution of specific enzymatic reactions. Thereby, biochemical adaptations to developmental and environmental stresses like drought, cold, osmotic stress as well as nutrient deficiency are facilitated [65, 66]. Hence, the detected alteration in abundance of enzymes involved in these central metabolic pathways may be associated with the ability of genotypes to cope with N-deficiency.

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Affected proteins as non-specific stress response Several proteins were identified associated with general stress response [15, 67, 68] showing an increased abundance under N-deficiency in both genotypes (Table 3). Components involved in ROS detoxification were accumulated, e.g. two different peroxidases (X7, X3), but with a stronger increase and an additionally spot in cv. Lambada [L37]. Furthermore, different superoxide dismutases considerably increased in both genotypes [L38, T29]. Our results are consistent with investigations in Zea mays and Phaseolus vulgaris where higher levels of peroxidase activity were determined [69, 70]. Another group of stress responsive proteins are the pathogenesis-

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related proteins (PR), which comprise a diverse group of 18 protein families with various properties [71]. In both potato genotypes, beta-1,3-glucanases [X4, X3], members of PR-2 group, were identified with higher levels under N-deficiency. Interestingly, further PR proteins were only affected in the tolerant cv. Topas and all of them increased in abundance, i.e. a further beta-1,3-glucanase [T6], a PR-1 protein [T7], osmotin [T10] as a member of the PR-5 group, STH-2 [T8] belonging to the PR-10 group and a chitinase [T9]. Increasing levels of glycine betaine as stress response have been reported in many crops. It is mostly accumulated in chloroplasts, where it operates in the adjustment and protection of the thylakoid membrane thereby improving photosynthesis

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under difficult environmental conditions [72]. The final enzyme in glycine betaine synthesis is the betaine aldehyde dehydrogenase, which accumulated under N-deficiency specifically in the stable cv. Topas [T22]. Altogether, universal stress proteins increased under N-deficiency in both genotypes while additional stress

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related proteins with increased abundance were preferentially identified in the stable cv. Topas.

Conclusion

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The two potato genotypes Lambada and Topas investigated in this study contrasted in N-deficiency responses. The sensitive genotype in terms of biomass production, cv. Lambada, exhibited more alterations in shoot proteome patterns under N-deficiency as compared to the less sensitive genotype Topas. Interestingly, out of 59

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DAPS in cv. Lambada and 47 DAPS in cv. Topas, only eight protein spots changed in abundance in the same way in both genotypes. Identified proteins of these spots were predominately associated with general stress

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responses, and all of them accumulated to a higher level under N-deficiency. These findings suggest that proteins affected in both genotypes are rather involved in universal stress response while adaptation to N-deficiency in metabolic pathways is more genotype specific.

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Many enzymes that are involved in carbon fixation and carbohydrate metabolism were differentially changed, although in vitro cultures do not necessarily require assimilated carbohydrates due to external sucrose which can be absorbed and metabolized. It seems that N-deficiency altered the carbohydrate metabolism, independently from the carbon source, indicating the close interaction of N and carbohydrate metabolism. Besides the different genotypic responses with respect to biomass formation, the chlorophyll content responded also in a strong genotypic manner. Enzymes that increased chlorophyll metabolism and stability were more strongly affected in the tolerant cv. Topas, whereas respective enzymes in cv. Lambda were not changed in abundance or the level of accumulation even decreased. Moreover, also enzymes that enhanced the photosynthetic carbon fixation like rubisco activase or carbonic anhydrase increased in cv. Topas under N-deficiency, but were not affected in the sensitive cv. Lambada. However, at this time point interpretation of underlying mechanisms of increased tolerance to N-deficiency based on the analyzed proteomic data is merely speculative. Additional studies such as

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ACCEPTED MANUSCRIPT enzyme activity assays, transcriptomics and metabolomics are necessary to validate the results and to further elucidate the biochemical and physiological mechanisms involved in N efficiency.

Acknowledgements We thank Marlies Prechel, Antje Höxtermann-Gottlob and Simone Steuck for excellent technical assistance in the in vitro experiments, Gisela Jansen and Magrit Jugert for the analyses of crude protein contents and Annegret Wolf for helpful assistance in the mass spectrometry analyses. This work was funded by a grant of Fachagentur

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Nachwachsende Rohstoffe e.V. (FNR), FKZ 22023311.

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Figure legends: Figure 1: In vitro grown Solanum tuberosum cv. Lambada and cv. Topas 11 days after culture initiation on Murashige and Skoog basal medium with 60 mM N for the control and 7.5 mM N for the Ndeficiency variant.

Figure 2: 2D IEF/SDS-PAGE gels exhibiting significant (p < 0.05) and > 1.5 fold changes in abundance of protein spots in control vs. N-deficiency conditions of cv. Lambada (A) and cv. Topas (B). Red spots indicate higher abundance in control conditions and green spots indicate higher

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ACCEPTED MANUSCRIPT abundance in N-deficiency conditions. Spots are displayed on synthetic 2D IEF SDS PAGE images as a result of an overlay of all gels of the experiment. Proteins were separated in the horizontal dimension in a non-linear pH 3-11 IPG strip (18 cm) and in the vertical dimension in a 12 % polyacrylamide gel (18.5 x 20 cm).

Figure 3: Principal component analysis (PCA) of protein spots to visualize genotype and N-deficiency dependent clustering. Score scatter plot of PCA vectors 1 vs. 3 performed on the whole spot pattern (A), the first three PCA vectors explain 39.22 % of variation. Score scatter plots B / C were performed

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of PCA vectors 1 vs. 2 of subsets of spots with a significant (p < 0.05) change in relative abundance, control vs. N-deficiency in cv. Lambada (B) and control vs. N-deficiency in cv. Topas (C). The first three PCA vectors explain to 51.19 % and 53.01 % of variation in subset B and subset C, respectively.

Groups are colored green (cv. Lambada control), yellow (cv. Lambada N-deficiency), blue (cv. Topas

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control) and red (cv. Topas N-deficiency).

Figure 4: Functional groups of identified proteins according to GO biological function and KEGG annotation in cv. Lambada (A) and in cv. Topas (B). Bars express the number of proteins in each

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functional group, which were abundant to a higher (black) or lower (grey) extent in comparison to

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control condition.

Figure 5: Chlorophyll synthesis pathway adapted from Hu et al. [73]. Displayed enzymes (red) were affected in the present study in response to N-deficiency in the respective genotype. Bar charts show

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the relative spot volume of the corresponding enzyme; white bars control condition; grey bars N-

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deficiency; n=9; error bars indicate the standard error.

Figure 6: Photosynthesis pathway adapted from Hu et al. [73]. Displayed enzymes (red) were affected

AC

in the present study in response to N-deficiency in the respective genotype. Bar charts show the relative spot volume of the corresponding enzyme; white bars control condition; grey bars Ndeficiency; n=9; error bars indicate the standard error.

Figure 7: Schematic overview of glycolysis pathway. Displayed enzymes (red) were affected in the present study in response to N-deficiency in the respective genotype. Up-arrows indicate increased abundance under N-deficiency, vice versa down-arrows indicate decreased abundance under Ndeficiency of the respective enzyme.

17

MA

NU

SC RI PT

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

Fig. 1

18

SC RI PT

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

MA

NU

Fig. 2

19

SC RI PT

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

MA

NU

Fig. 3

20

MA

NU

SC RI PT

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

Fig. 4

21

MA

NU

SC RI PT

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

Fig. 5

22

NU

SC RI PT

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

MA

Fig. 6

23

PT

ED

MA

NU

SC RI PT

ACCEPTED MANUSCRIPT

AC

CE

Fig.7

24

ACCEPTED MANUSCRIPT

Table 1: Genotypic effect of N-deficiency on plant biomass, N-uptake, chlorophyll and crude protein content after 11 days of in vitro culture

Shoot FM -1 (g vessel )

Root FM -1 (g vessel )

Shoot DM -1 (g vessel )

Root DM -1 (g vessel )

Ratio root / shoot FM

Chlorophyll content (SPAD readings)

Crude protein content in shoot DM (%)

N uptake -1 (mg vessel )

Control

3.53 ± 0.86

1.92 ± 0.45

0.31 ± 0.08

0.12 ± 0.03

0.56 ± 0.12

41.13 ± 7.05

34.1 ± 5.2

25.00 ± 4.24

N-deficiency

2.22 ± 0.26

1.40 ± 0.16

0.26 ± 0.03

0.10 ± 0.02

0.64 ± 0.11

29.11 ± 6.92

16.5 ± 1.5

5.17 ± 0.02

-37

-27

-16

-17

+14

-29

-53

ǂǂ

Control

1.98 ± 0.35

0.81 ± 0.20

0.19 ± 0.04

0.04 ± 0.02

0.41 ± 0.10

45.83 ± 3.95

37.1 ± 0.9

17.28 ± 4.14

N-deficiency

1.71 ± 0.13

0.73 ± 0.27

0.18 ± 0.04

0.06 ± 0.05

0.42 ± 0.14

42.54 ± 2.60

23.8 ± 4.2

5.15 ± 0.07

-14

-10

-5

ǂ

+2

-7

-36

ǂǂ

% change cv. Topas

% change

Source of variation (ANOVA) F Cultivar

36.90 *** 21.31

**

F Cultivar x Nitrogen

11.40

**

F Replicate

1.67 n.s.

9.88

**

5.67

*

1.86 n.s.

44.84 ***

34.53 ***

16.84 **

20.47 **

3.65

n.s.

0.18

n.s.

1.01

n.s.

**

2.29

n.s.

3.64

n.s.

0.59

n.s.

1.77 n.s.

1.32 n.s.

14.65 4.75

0.78 n.s.

8.74 ** 101.10

*

2.42

1.03 n.s.

***

n.s.

0.61 n.s.

24.03 *** 311.09 *** 10.34 ** 3.26 *

NU

F Nitrogen

89.05 ***

SC RI PT

cv. Lambada

Values shown represent the arithmetic mean of at least five replicates (In-vitro culture vessel with 10 plantlets), ± indicates standard deviation. 60 mM N was supplemented to control and 7.5 mM N to N-

MA

deficiency variant. ǂ Calculation is not possible due to low biomass resulting in a high standard deviation. ǂǂ Nitrogen in the N-deficiency variant is completely absorbed. F values of experiment factors were calculated by applying ANVOA.

*

**

non-significant, P < 0.05, P < 0.01,

***

P < 0.001; FM

AC

CE

PT

ED

fresh mass; DM dry mass.

n.s.

25

ACCEPTED MANUSCRIPT Table 2: Qualitative and quantitative alterations in normalized spot volume (%) on 2D IEF/SDS PAGE spot patterns

Comparisons of normalized spot volumes (t-test p < 0.05)

Protein yield [µg] BSA equivalent [mg] -1 crude extract

Number of a detected spots

cv. Lambada control

0.63 ± 0.09

cv. Lambada N-deficiency

b

cv. Lambada N-deficiency vs.

cv. Topas control vs.

cv. Topas N-deficiency vs.

428 ± 61

-

100 54 incr. (1) 46 decr. (6)

133 53 incr. (3) 80 decr. (8)

177 79 incr. (5) 98 decr. (10)

0.42 ± 0.11

456 ± 57

100 46 incr. (6) 54 decr. (1)

-

158 55 incr. (6) 103 decr. (10)

145 63 incr. (7) 83 decr. (7)

cv. Topas control

0.55 ± 0.08

445 ± 40

133 80 incr. (8) 53 decr. (3)

158 103 incr. (10) 55 decr. (6)

-

77 38 incr. (4) 39 decr. (1)

cv. Topas N-deficiency

0.41 ± 0.10

453 ± 23

177 98 incr. (10) 79 decr. (5)

145 82 incr. (7) 63 decr. (7)

77 39 incr. (1) 38 decr. (4)

-

± indicates standard deviation, N = 9

Spots were detected with min. spot volume > 0.02 Vol. (%) and spot quality > 0.4 (Delta 2D specific

NU

a

SC RI PT

cv. Lambada control vs.

software algorithm). All spots were matched to a fused image which comprises all spots of the experiment, 513 unique spots were used for statistical analysis. Welch’ s t-test was used to compare normalized spot vol. of each spot in two groups, significant

MA

b

changes were accepted at p < 0.05. For quantitative changes ratios > 1 indicate increased abundance

AC

CE

PT

ED

< 1 indicate decreased abundance. Thereof number in brakes indicate qualitative spot changes.

26

ACCEPTED MANUSCRIPT Table 3: Identified proteins modulated under N-deficiency in cvs. Lambada and in Topas categorized in main functional groups

Spot a

Protein identity

b

Function

c

Accession

d

MS/M S Score e

Matche Sequenc d e peptide coverage s

MW / pI theo. f

MW / pI Ratio h, i exp. g

23.6/6.4

15.7/5.5

Stress response

(X2) (X2)

(X3)

X4

21 kDa seed protein-like PREDICTED SGT1 homolog PREDICTED

Protease inhibitor activity

Patatin-05

Defence response

Glucan endo-1,3-betaglucosidase, acidic isoform PR-Q-like PREDICTED Pathogenesis-related protein P2

GI:56537476 1 GI:56539400 1 GI:12221772 3

Defence response

Rubisco activase PREDICTED

(X3)

Peroxidase

10

3

50.0/4.9 39.2/10. 0

1.63/1.5 5

Defence response

GI:56881562 4

179

45

4

13.7/8.2 6

12.6/10. 0

1.56/2.0 4

Activation of rubisco

GI:56536560 1

232

15

5

48.1/8.0 1

105.0/5. 2

0.50/0.5 2

471

12

8

89.4/5.1 0

99.3/5.0

0.65/0.5 1

343

21

7

98

13

3

289

14

7

Protein processing

GI:56536088 6

Removal of hydrogen peroxide Removal of hydrogen peroxide

GI:56538649 5 GI:56534546 5

GI:56534629 3

ED

a

238

50.0/4.9

37.5/9.1 1

Cell redox homeostasis

Disulfide-isomerase

41.1/5.0 6 38.2/5.0 7

2

Miscellaneous X8

5

9

MA

Peroxidase

16

4.14/3.9 5 1.98/2.4 1 1.98/2.4 1

81

Oxidative stress X7

224

NU

Cell division cycle protein 48 homolog PREDICTED

3

GI:56536933 0

Protein synthesis / processing / degradation X6

21

Defence response

Photosynthesis X5

155

SC RI PT

X1

39.7/7.5 9 36.4/9.2 2

64.4/4.4 9

56.1/9.2 39.2/10. 0

86.0/4.2

2.08/1.6 4 1.63/1.5 5

2.25/2.4 0

b

Spot numbers in brackets indicate that the same spot is matched to distinct proteins. Protein name

PT

according to NCBInr database or Uniprot database when characterization of entry is available.

c

Function and protein classification according to GO biological process and of KEGG database. When

CE

several functions are described, the most relevant in terms of N-deficiency is reported. numbers retrieved from NCBInr database. f

indicate statistical identity (P < 0.05).

e

Accession

MASCOT protein score, individual ion scores > 28

Theoretical protein mass (kDa) and pI of identified proteins

retrieved from MASCOT in-house database search.

AC

d

g

Experimental protein mass (kDa) and pI of

identified protein spot, estimated by migration on 2D PAGE.

h

Ratio is expressed as relative spot vol.

(%) between control and N-deficiency treatment, green indicates higher abundance and red indicates i

lower abundance under N-deficiency The first ratio value represents the comparison cv. Lambada control vs. N-deficiency and the second of cv. Topas.

27

ACCEPTED MANUSCRIPT Table 4: Identified genotype specific proteins differing in abundance under N-deficiency in cv. Lambada categorized in main functional groups

Spot a

Protein identity

b

Function

c

Accession d

Matche MS/MS Sequenc d Score e peptide e coverage s

MW / pI theo. f

MW / pI exp. g

Ratio h

Carbohydrate metabolism

L3 L4 L5

L6

L7

L8

Glycolytic process Pentose phosphate pathway Glucose / glycolytic process Starch / sucrose metabolism

38.4/8.52

411

21

8

58.4/5.97

404

14

5

50.4/7.68

364

20

9

56.7/8.77

1.55 1.53 0.65 0.64 0.56

Glycolytic process

GI:6634341 17

92

6

3

61.8/6.01

70.8/5. 9

0.49

Photorespiration

GI:5653905 55

217

5

5

112.8/6.5 2

99.4/5. 8

0.40

Glucose / glycolytic process

GI:5653511 80

296

13

5

47.9/7.53

44.8/5. 9

0.27

309

15

5

44.6/6.20

50.2/6. 2

2.01

270

14

5

47.7/8.29

585

14

8

84.5/6.19

Cys, Met metabolism

GI:5653931 70 GI:5653476 30 GI:5682152 68

ED

Methionine synthase

Stress response

45.7/6. 7 89.7/5. 9

1.53 0.49

GI:4604117 09

282

30

4

16.8/4.10

15.4/3. 2

2.32

Inhibit aspartic-type endopeptidases

GI:5653940 33

195

24

4

23.9/8.04

23.6/9. 5

1.86

Inhibit cysteine-type endopeptidase

GI:5653747 67

393

21

3

25.1/4.80

23.5/4. 7

1.82

Inhibit aspartic-type endopeptidases

GI:5653940 33

517

40

7

23.9/8.04

22.1/9. 5

1.61

Inhibit aspartic-type endopeptidases

GI:5653940 33

152

16

3

23.9/8.04

22.3/9. 7

1.56

Defence response

GI:5654017 40

95

5

2

37.9/8.95

49.6/9. 2

1.53

30

4

1

28.0/5.14

472

27

6

35.3/5.84

183

9

3

40.2/7.23

191

9

3

40.2/7.23

PT

Calcium binding

CE

AC

4

100.0/5 .8

L11

L17

12

1.55

112.8/6.5 2

Phosphoserine aminotransferase

(L16 )

141

44.9/6. 9 44.9/6. 9 65.7/5. 6 48.4/5. 2 57.6/6. 6

4

L10

L15

38.6/7.51

4

Arg, Ala, Asn, Gln, Dglutamine, Dglutamate and N metabolism Gly, Ser, Thr metabolism

(L14 )

5

128

Glutamate dehydrogenase

L13

19

GI:5653905 55

L9

Calmodulin PREDICTED Aspartic protease inhibitor 5-like PREDICTED Cysteine protease inhibitor 1-like PREDICTED Aspartic protease inhibitor 5-like PREDICTED Aspartic protease inhibitor 5-like PREDICTED Polygalacturonase inhibitor-like 2-like PREDICTED

321

Photorespiration

Amino acid metabolism

L12

GI:5682151 94 GI:4604080 38 GI:5653430 73 GI:5682145 97 GI:8066385 23

SC RI PT

(L2)

Glycolytic process

NU

(L1)

Fructose-bisphosphate aldolase Fructose-bisphosphate aldolase Glucose-6-phosphate dehydrogenase Phosphoglycerate kinase Glucose-1-phosphate adenylyltransferase Glycine dehydrogenase (decarboxylating) PREDICTED Pyrophosphate-fructose 6-phosphate 1phospho-transferase subunit beta Glycine dehydrogenase (decarboxylating) PREDICTED Glyceraldehyde-3phosphate dehydrogenase

MA

(L1)

Photosynthesis (L14 ) L18 (L19 ) (L20 )

Chlorophyll a-b binding protein chloroplastic-like Chloroplast manganese stabilizing protein-II

Antenna protein PSI II

Rubisco large subunit

Carbon fixation

Rubisco large subunit

Carbon fixation

GI:5654001 04 GI:5653422 20 GI:3291246 77 GI:3291246 77

23.5/4. 7 29.5/5. 1 61.1/5. 3 60.7/5. 1

1.82 0.66 0.65 0.64

Protein synthesis / processing / degradation L21 (L19 )

60S acidic ribosomal protein P1-1-like PREDICTED Rab GDP dissociation inhibitor alpha-like PREDICTED

Synthesis

GI:5653653 91

40

14

1

11.3/4.38

10.1/3. 4

1.69

Transport

GI:5653689 13

220

11

3

49.4/5.52

61.1/5. 3

0.65

28

ACCEPTED MANUSCRIPT

(L23 ) L24 L25 L26 L27

L28

L29

Elongation factor (EF1A) Eukaryotic initiation factor (eIF4A2) PREDICTED Elongation factor (eEF1A) Peptidyl-prolyl cis-trans isomerase FKBP62-like PREDICTED Thimet oligopeptidaselike PREDICTED Thimet oligopeptidaselike PREDICTED ATP-dependent Clp protease ATP-binding subunit clpA PREDICTED ATP-dependent Clp protease ATP-binding subunit clpA PREDICTED

Synthesis

GI:5653613 59

456

15

5

51.7/6.10

52.0/5. 2

0.62

Synthesis

GI:4603990 92

219

9

3

46.9/5.54

52.0/5. 2

0.62

Synthesis

GI:8262119 0

168

7

3

49.2/9.20

68.6/9. 9

0.61

Folding/processing

GI:5653721 67

65

4

2

63.5/5.24

79.0/5. 1

0.57

121

5

3

91.5/6.37

83

3

3

91.5/6.37

4

3

102.1/5.9 9

GI:5653828 94 GI:5653828 94

Cleavage of peptides Cleavage of peptides

Degradation

GI:5653597 07

107

Degradation

GI:5653597 07

223

10

7

Cell wall compounds metabolism

GI:5653703 98

415

13

Cell wall compounds metabolism

GI:5653749 59 GI:5653746 92

220 226

Secondary metabolism

L33

L34

L35

Cutin synthesis

L38

Superoxide dismutase

0.25

6

67.8/7.82

76.2/6. 1

2.48

8

5

85.1/8.01

16

4

44.8/5.03

79.0/9. 5 60.7/5. 1

1.59 0.64

4

51.2/9.06

58.0/9. 2

0.61

Isoprenoid synthesis

GI:5653462 95

311

12

7

82.0/5.81

85.2/5. 3

0.60

GI:5653620 18

247

18

5

42.4/6.00

48.1/5. 9

0.42

Hydrolysis ATP to ADP

GI:5653572 44

78

7

2

26.5/9.58

22.3/9. 7

1.56

Hydrolysis ATP and ADP to AMP

GI:5653950 49

75

2

1

49.5/8.79

58.2/9. 1

0.58

GI:5653864 95 GI:5653819 33

203

20

7

39.7/7.59

77

3

1

28.3/6.60

262

34

5

17.3/5.26

195

20

5

29.3/4.78

149

16

3

29.0/4.74

30

2

1

51.8/6.33

Ascorbate, Aminoand nucleotide sugar metabolism

Removal of hydrogen peroxide Removal of superoxide radicals

CE

Peroxidase

94.3/5. 2

11

Oxidative stress L37

102.1/5.9 9

181

ED

L36

Atp synthase FO subunit delta PREDICTED Apyrase-like isoform x1 PREDICTED

0.32

GI:5653980 48

Energy (L16 )

0.38

Porphyrin and chlorophyll metabolism

NU

(L20 )

MA

L31

Beta-xylosidase alpha-larabinofuranosidase 2like PREDICTED Probable beta-dxylosidase PREDICTED BAHD acyltransferase DCR-like PREDICTED Geranylgeranyl diphosphate reductase PREDICTED 4-hydroxy-3-methylbut2-en-1-yl diphosphate synthase PREDICTED Gdp-mannose 3,5epimerase 1 PREDICTED

0.48

PT

L30

85.8/5. 2 85.7/5. 2 92.3/5. 2

SC RI PT

(L23 )

53.7/9. 2 19.8/5. 4

2.74 1.56

Regulation of transcription / cell processes regulation

(L40 ) (L40 ) (L2) L41

Glycine-rich RNAbinding protein 7-like isoform X2 PREDICTED 14-3-3-like protein Clike

AC

L39

Regulation of transcription Cell regulation

14-3-3-like protein 16R

Cell regulation

La-related protein 1-like PREDICTED Heterogeneous nuclear ribonucleoprotein 1-like PREDICTED

Regulation of transcription

GI:5653991 22 GI:5682155 31 GI:5682147 40 GI:5653621 55

12.9/4. 7 31.2/4. 4 31.2/4. 4 65.7/5. 6

2.51 1.82 1.82 1.53

RNA processing

GI:5653793 04

76

10

3

45.1/6.12

53.4/5. 9

0.30

Cell structure

GI:4603728 29

261

14

4

49.6/4.96

116.4/5 .0

1.71

Sulphur metabolism, cell detoxification

GI:5653584 30

61

6

2

41.0/6.76

36.4/5. 2

1.69

Nucleotide binding

GI:5653749 98

344

11

7

96.1/4.58

112.7/4 .2

1.67

Cell redox homeostasis

GI:5653549 33

129

25

4

23.0/9.48

16.2/7. 3

1.66

DNA repair

GI:5653754

350

23

6

40.2/8.61

52.0/9.

1.65

Miscellaneous L42

L43

L44

L45 L46

Tubulin alpha chain-like Thiosulfate/3-mercaptopyruvate sulfurtransferase 1 PREDICTED Apoptotic chromatin condensation inducer in the nucleus-like isoform X1 PREDICTED CBS domain-containing protein CBSX3 PREDICTED DNA-damage-

29

ACCEPTED MANUSCRIPT

(L16 )

repair/toleration protein DRT100-like PREDICTED Citrate-binding proteinlike PREDICTED

97

6

GI:5653687 66

Citrate binding

131

14

3

22.3/9. 7

25.3/9.18

1.56

Unidentified 95.5/5. 8 111.3/9 .8 98.0/5. 9 52.1/6. 0 78.2/5. 9

L47 L48 L49 L50

a

SC RI PT

L51

0.66 0.51 0.38 0.26 *

b

Spot numbers in brackets indicate that the same spot is matched to distinct proteins. Protein name

according to NCBInr database or Uniprot database when characterization of entry is available.

c

Function and protein classification according to GO biological process and of KEGG database. When several functions are described, the most relevant in terms of N-deficiency is reported. numbers retrieved from NCBInr database. indicate statistical identity (P < 0.05).

f

e

d

Accession

MASCOT protein score, individual ion scores > 28

Theoretical protein mass (kDa) and pI of identified proteins g

Experimental protein mass (kDa) and pI of

NU

retrieved from MASCOT in-house database search.

identified protein spot, estimated by migration on 2D PAGE.

h

Ratio is expressed as relative spot vol.

AC

CE

PT

ED

lower abundance under N-deficiency.

MA

(%) between control and N-deficiency treatment, green indicates higher abundance and red indicates

30

ACCEPTED MANUSCRIPT Table 5: Identified genotype specific proteins differing in abundance under N-deficiency in cv. Topas categorized in main functional groups

Spot a

Protein identity

b

Function

c

Accession d

MS/MS Score e

Sequenc Matche e d coverag peptide e s

MW / pI theo. f

MW / pI exp. g

Ratio h

Carbohydrate metabolism T1

Glucose-1-phosphate adenylyltransferase

Starch / sucrose metabolism

T2

Malic enzyme

Pyruvate metabolism

(T3)

Glyceraldehyde-3phosphate dehydrogenase

Glucose / glycolytic process

GI:2209484 0

68

10

2

36.6/6.34

40.3/5. 6

1.59

T4

Malate dehydrogenase

Pyruvate metabolism, TCA process

GI:2138854 4

124

11

3

36.1/9.00

35.9/7. 2

0.58

T5

Serine hydroxymethyltransfera se

Photorespiration

GI:5653998 70

372

16

6

52.0/6.84

59.2/6. 8

0.66

Gly, Ser, Thr, Cys, Met, Lys metabolism

GI:5653969 11

158

15

4

42.0/7.01

40.3/5. 6

1.59

Defence response

GI:5653693 30

256

16

5

37.5/9.11

39.1/9. 8

1.80

Defence response

GI:5682155 03

80

15

2

17.3/8.14

13.8/1 0.2

1.57

GI:5653477 58

407

33

3

17.3/5.31

17.3/5. 31

1.54

GI:5653476 12

110

16

4

27.5/5.91

22.4/5. 1

1.50

19.8/5. 5

1.30

Amino acid metabolism (T3)

Aspartate-semialdehyde dehydrogenase-like PREDICTED

T9 T10 T11 (T1 2)

Annexin

T14 (T1 5)

Mg-protoporphyrin IX chelatase, subunit ChlI Carbonic anhydrase isoform X1 PREDICTED Rubisco accumulation factor 1 PREDICTED

AC

(T1 3)

Rubisco activase PREDICTED

Defence response, degradation of chitin

3

57.2/5.87

166

10

5

64.1/5.71

56.6/5. 2 72.1/5. 5

1.69 1.67

Defence response

GI:5654052 45

122

14

2

23.6/7.90

Chaperone

GI:5653638 33

423

10

6

90.9/4.90

Calcium-phospholipid binding

GI:8247363

42

4

1

35.8/5.40

Activation of rubisco

GI:5653656 01

273

15

5

48.1/8.1

46.3/4. 9

1.90

Catalyses the insertion of Mg into protoporphyrin

GI:5653906 73

76

11

3

46.4/6.07

46.3/4. 9

1.90

Hydration of CO2

GI:5653815 93

151

17

2

15.8/5.78

28.1/5. 8

1.83

Assembly and stability of rubisco

GI:5653686 60

78

2

1

50.2/5.19

53.0/4. 6

0.59

GI:21487

84

6

1

19.9/8.52

64.6/5. 2

3.20

GI:5653668 63

135

4

2

54,7/5.84

64.3/5. 4

1.60

Synthesis

GI:5653615 61

501

39

6

22.3/4.43

31.2/4. 1

0.67

Synthesis

GI:5682146 33

269

16

3

33.9/5.12

38.2/5. 0

0.65

Processing and regular of protein turnover

GI:5653541 12

195

10

4

55.5/6.81

99.0/5. 3

0.64

Transport

GI:5653683 05

401

17

10

91.4/8.42

84.8/7. 1

0.55

CE

Photosynthesis (T1 3)

Defence response

MA

T8

ED

T7

Glucan endo-1,3-betaglucosidase, acidic isoform PR-Q-like PREDICTED Pathogenesis-related protein 1b Pathogenesis-related protein STH-2-like PREDICTED Acidic endochitinase pcht28 PREDICTED Osmotin-like protein OSML13-like PREDICTED Endoplasmin homolog PREDICTED

PT

T6

7

NU

Stress response

107

SC RI PT

GI:5653666 71 GI:5653574 92

92.1/4. 5 38.8/5. 2

0.66 0.53

Protein synthesis / processing / degradation T16

T17

T18

(T1 9) T20

T21

Leucine aminopeptidase Leucine aminopeptidase 2 PREDICTED Nascent polypeptideassociated complex subunit alpha-like protein 2-like PREDICTED P0 ribosomal proteinlike M1 family aminopeptidase-like isoform X1 PREDICTED Protein TOC75-3 PREDICTED

Processing and regular of protein turnover Processing and regular of protein turnover

31

ACCEPTED MANUSCRIPT Secondary metabolism

T23

T24

T25

T26 (T1 2) T27

Betaine aldehyde dehydrogenase PREDICTED Linoleate 13Slipoxygenase 2-1 Glutamate-1semialdehyde 2,1aminomutase PREDICTED Rhamnose biosynthetic enzyme 1-like PREDICTED Rhamnose biosynthetic enzyme 1-like PREDICTED Hyoscyamine 6dioxygenase-like PREDICTED Protochlorophyllide reductase PREDICTED

Gly, Ser, Thr, glycine betaine metabolism

GI:5653563 08

43

2

1

55.9/5.27

64.1/5. 1

1.61

Linoleic acid metabolism

GI:5682146 19

126

6

5

101.9/6.15

97.0/5. 6

1.73

Porphyrin and chlorophyll metabolism

GI:5653870 12

349

16

7

51.4/6.54

50.4/5. 5

0.62

Cell wall compounds metabolism

GI:5653632 19

212

10

5

75.7/6.75

82.6/6. 3

0.61

Cell wall compounds metabolism

GI:5653632 19

101*

-

75.7/6.75

82.8/6. 9

0.59

Alkaloid metabolism

GI:5653831 40

71

5

3

37.9/5.54

38.8/5. 2

0.53

Porphyrin and chlorophyll metabolism

GI:5653863 52

440

23

9

42.8/9.19

41.8/9. 3

0.46

Atp metabolic process

GI:5653978 54

201

14

5

58.4/5.45

60.9/4. 8

0.65

Removal of superoxide radicals

GI:5653819 33

214

19

5

28.3/6.60

19.1/5. 5

1.72

GI:5653508 34

181

27

3

22.0/5.84

15.5/6. 2

5.44

GI:5653591 73

117

8

4

70.1/7.62

79.0/6. 8

2.52

GI:5653960 89

288

27

5

32.6/4.91

26.4/4. 3

0.62

GI:5653960 89

388

27

5

32.6/4.91

27.7/4. 5

0.51

GI:5653960 89

584

29

8

32.6/4.91

27.7/4. 4

0.43

74

4

2

70.1/7.62

554

17

7

70.1/7.62

Energy T28

V-type ATPase subunit B2-like isoform X1 PREDICTED

T29

Superoxide dismutase

NU

Oxidative stress

T34

T35 T36

RNA processing

ED

T33

RNA binding

RNA processing

PT

T32

Auxin-activated signaling pathway

RNA processing

RNA binding

CE

T31

Auxin-binding protein ABP19a-like PREDICTED Polyadenylate-binding protein 29 kDa ribonucleoprotein B, isoform X1 PREDICTED 29 kDa ribonucleoprotein B, isoform X1 PREDICTED 29 kDa ribonucleoprotein B, isoform X1 PREDICTED Polyadenylate-binding protein Polyadenylate-binding protein

Miscellaneous

MA

Regulation of transcription / cell processes regulation T30

RNA binding

SC RI PT

T22

GI:5653591 73 GI:5653591 73

79.7/6. 9 80.6/7. 3

0.42 0.38

Single-stranded DNA binding protein precursor

DNA repair

GI:5682146 43

440

20

4

31.3/4.65

26.1/4. 0

0.67

(T1 5)

RAD23-like

Ubiquitin / proteasome driven DNA repair

GI:7774547 5

55

2

1

40.7/4.72

53.0/4. 6

0.59

(T1 9)

Uncharacterized protein LOC102581561 PREDICTED

GI:5653796 91

52*

-

42.7/5.70

38.2/5. 0

0.65

AC

T37

Unidentified 34.5/5. 3 22.9/5. 4

T38 T39

a

2.63 0.45

b

Spot numbers in brackets indicate that the same spot is matched to distinct proteins. Protein name

according to NCBInr database or Uniprot database when characterization of entry is available.

c

Function and protein classification according to GO biological process and of KEGG database. When several functions are described, the most relevant in terms of N-deficiency is reported.

d

Accession

32

ACCEPTED MANUSCRIPT numbers retrieved from NCBInr database. indicate statistical identity (P < 0.05).

f

e

MASCOT protein score, individual ion scores > 28

Theoretical protein mass (kDa) and pI of identified proteins

retrieved from MASCOT in-house database search.

g

Experimental protein mass (kDa) and pI of

identified protein spot, estimated by migration on 2D PAGE.

h

Ratio is expressed as relative spot vol.

(%) between control and N-deficiency treatment, green indicates higher abundance and red indicates

AC

CE

PT

ED

MA

NU

SC RI PT

lower abundance under N-deficiency

33

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

MA

NU

SC RI PT

Graphical abstract

34