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DOI 10.1002/pmic.201400018
Proteomics 2015, 15, 124–134
RESEARCH ARTICLE
In vitro culture may be the major contributing factor for transgenic versus nontransgenic proteomic plant differences ´ ´ ˆ Catia Fonseca1,2 , Sebastien Planchon3 , Tania Serra4 , Subhash Chander2 , Nelson J. M. Saibo2 , Jenny Renaut3 , M. Margarida Oliveira2,4 and Rita Batista1,2 1
National Health Institute, Lisboa, Portugal ´ Instituto de Tecnologia Qu´ımica e Biologica, Universidade Nova de Lisboa, Oeiras, Portugal 3 Department of Environment and Agrobiotechnologies (EVA), Centre de Recherche Public, Gabriel Lippmann, Belvaux, Luxembourg 4 IBET, Oeiras, Portugal 2
Identification of differences between genetically modified plants and their original counterparts plays a central role in risk assessment strategy. Our main goal was to better understand the relevance of transgene presence, genetic, and epigenetic changes induced by transgene insertion, and in vitro culture in putative unintended differences between a transgenic and its comparator. Thus, we have used multiplex fluorescence 2DE coupled with MS to characterize the proteome of three different rice lines (Oryza sativa L. ssp. japonica cv. Nipponbare): a control conventional line (C), an Agrobacterium-transformed transgenic line (Ta ) and a negative segregant (NSb ). We observed that Ta and NSb appeared identical (with only one spot differentially abundant—fold difference ࣙ 1.5), contrasting with the control (49 spots with fold difference ࣙ1.5, in both Ta and NSb vs. control). Given that in vitro culture was the only event in common between Ta and NSb , we hypothesize that in vitro culture stress was the most relevant condition contributing for the observed proteomic differences. MS protein identification support our hypothesis, indicating that Ta and NSb lines adjusted their metabolic pathways and altered the abundance of several stress related proteins in order to cope with in vitro culture.
Received: January 20, 2014 Revised: September 9, 2014 Accepted: September 29, 2014
Keywords: Genetically modified foods safety assessment / In vitro culture / Multiplex fluorescence 2DE / Negative segregant / Plant proteomics
1
Additional supporting information may be found in the online version of this article at the publisher’s web-site
Introduction
The current risk assessment strategy for genetically modified (GM) plants aimed for food / feed applications focuses on the identification of similarities and differences between the ´ Correspondence: Dr. Rita Batista, Instituto Nacional de Saude Dr. Ricardo Jorge, Av. Padre Cruz, 1649–016 Lisboa, Portugal E-mail: [email protected] Fax: +351217508153 Abbreviations: GM, genetically modified; GMO, genetically modified organism; NADP, nicotinamide adenine dinucleotide phosphate
C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
GM plant and its comparators, taking into account natural variation [1]. One of the most important and most challenging issues is the selection of the best comparators for this risk assessment. Presently, risk assessment of predictable effects is easily attained through specific in vitro and clinical tests. However, there has been an increasing demand for new methodologies to also estimate any unpredictable and unintended effects [2, 3]. Unintended differences in GM versus non-GM plants may (a) be dependent on the transgene expression; (b) occur as a consequence of epigenetic changes, host DNA disruption Colour Online: See the article online to view Figs. 1–3 in colour.
www.proteomics-journal.com
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Proteomics 2015, 15, 124–134
or DNA sequence rearrangements promoted by transgene insertion; be due to the in vitro culture associated procedures used for the transformation process [4]. The challenge is to design control strategies allowing evaluation of the potential unintended effects caused by the incidents (a) or (b) discounting potential effects due to in vitro culture associated with the methodology. In vitro culture is noncontroversial and largely used for clonal propagation and general strategies of plant improvement (e.g. production of disease free plants [5], production of haploids [6]). Ideally, non-GM control plants should have passed all in vitro culture steps needed for the transformation process lacking only the transformation event itself. However, this type of control would be tremendously difficult for GM plants with several stacked events. In the “European Food Safety Authority (EFSA) guide on selection of comparators for risk assessment of GM plants [7], additional comparators are also considered to supplement the conventional non-GM counterpart (a genotype with a genetic background as close as possible to the GM plant). The possibility of using negative segregants (homozygous individuals lacking the introduced DNA, obtained from self-fertilization of hemizygous genetically modified individuals or from crosses between hemizygous and conventional lines) is implied. Some scientists suggest that negative segregants would be better comparators for risk assessment of genetically modified organisms (GMO) since they allow for discounting the differences promoted by the in vitro tissue culture. However, others state that the impact of genetic modification cannot be completely assessed using only a negative segregant as a comparator, since the genetic or epigenetic changes promoted by transgene insertion may have remained after segregation (EFSA Consultative Workshop on the Draft Guidance on Selection of Comparators for the Risk Assessment of GM Plants, 2011). In fact, the use of negative segregants, as controls in GM risk assessment, will potentially discount genetic and/or epigenetic changes induced by transgene insertion. Thus, potentially important effects will be discounted and evade evaluation. On the other hand, the use of conventional counterparts, as controls, will not permit subtracting differences putatively caused by the in vitro culture process. As a result, some of the differences found, between the control and the transgenic plant, will be due to the in vitro culture process itself. These differences, though not of concern, will not be excluded from the evaluation. The question is which of these factors, transgene insertion or in vitro culture, more strongly impacts the potential unexpected changes? This study aims to evaluate the relative contribution of in vitro culture and transgene insertion/expression, on the proteomic profiles of a GM plant and its non-GM counterpart. In order to achieve this goal, we have used multiplex fluorescence 2DE coupled with MS to characterize the proteome of three rice lines (Oryza sativa L. ssp. japonica cv. Nipponbare): a control conventional counterpart, an Agrobacteriumtransformed transgenic line (Ta ), and a negative segregant (NSb ), progeny of a different transgenic line. C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
2
Materials and methods
2.1 Plant materials Three different lines of Oryza sativa L. ssp. japonica cv. Nipponbare were used: a control line (C); a GM line obtained by Agrobacterium-mediated transformation (Ta ), and a non-GM negative segregant control line (NSb , – progeny of Transgenic b) (Fig. 1A). Ta carried one copy of OsICE1 transcription factor, fused to a TAP-tag construct, driven by the maize ubiquitin promoter. NSb was a F1 descendent of a transgenic line (Tb ) also containing the OsICE1 transcription factor driven by the maize ubiquitin promoter but in this case lacking the TAP-tag (See transformation vectors information on Supporting Information Fig. 1). Transformation and regeneration procedures used to generate Ta and Tb lines were as previously described [8]. Prior to the experiment, each of the tested lines (C, Ta , and NSb ) was grown for two generations in exactly the same conditions (mixture 2:2:1, soil: peat: vermiculite, 28⬚C light/24⬚C night, 12 h photoperiod, 70% relative humidity). 2.2 Seed germination and seedling growth for proteomic assays Eighteen seeds from the second generation plants (randomly collected from one plant of each line- C, Ta , and NSb ) were manually peeled and disinfected as previously described [8]. Seeds were kept for 48 h in the final wash at 28⬚C, in the dark, and were then transferred to Yoshida’s medium [9] and maintained at 28⬚C light/24⬚C night, 12 h photoperiod and 70% relative humidity, for another 13 days. Transgene presence was confirmed by PCR for each Ta seedling (Supporting Information Fig. 2). The up-regulation of OsICE1 transcription factor in Ta line was confirmed by microarrays expression analysis (Supporting Information Fig. 3). 2.3 Characterization of GM plants (Ta and Tb ) 2.3.1 Southern blot analysis Rice genomic DNA was extracted from four-leaf stage seedlings and quantified by gel electrophoresis with DNA (Fermentas Inc.). Fifteen micrograms of rice genomic DNA from each line (Control, Ta and Tb ) were digested with several different restriction enzymes for Southern blot analysis. Gel electrophoresis, DNA blotting, DNA labeling, and hybridization conditions were performed as previously described [10].
2.3.2 Chromosome walking To identify the transgene insertion site in both transgenic rice lines (Ta and Tb - hemizygous transgenic parental line of NSb ) www.proteomics-journal.com
126
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Proteomics 2015, 15, 124–134
Figure 1. (A) Schematic representation of plant rice lines and the potential factors contributing to their differences—IV In vitro culture promoted changes; TIPAa , Transgene a insertion promoted alterations; TIPAb , Transgene b insertion promoted alterations; ta , Transgene a expression promoted differences; tb , Transgene b expression promoted differences; . g(Ci), f(Ci)- Functions that transform each control elements (Ci -protein spots) into Ta or into NSb elements (protein spots), respectively. The plant lines analyzed in this study are represented in red. Each of the tested lines (C, Ta , and NSb -Oryza sativa L. ssp. japonica cv. Nipponbare) was grown for two generations in the same conditions before the experiment. (B) Mathematical explanations supporting the hypothesis of in vitro culture as the major factor impacting Ta versus C proteomic differences.
C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
www.proteomics-journal.com
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Proteomics 2015, 15, 124–134
a Genome Walker library was prepared using the Genome Walker Universal kit (www.clontech.com). The identification of the insertion sites was performed by amplification and sequencing of the regions flanking the right and the left border of the T-DNA insert, using a primer combination from the Genome Walker kit and from the right or left border of T-DNA insert.
2.4 Protein extraction and RuBisCO depletion For protein extraction, whole seedlings at the four leaf stage were used. Three pools of seedlings (three biological replicates), of each tested line, were ground in a mortar with liquid nitrogen and proteins extracted with 6 mL of Extraction Buffer [100 mM HEPES-KOH pH 7.5; 5% Glycerol; 5 mM EDTA; 0.1% -Mercaptoethanol; 1% Proteinase Inhibitor Cocktail for plant proteins (Sigma)] for 10 min at 4⬚C. After double centrifugation at 10 000 × g, for 10 min at 4⬚C, final supernatants were filtered through a 25 mm diameter, 0.45 m cellulose mixed ester filter (BGB Analytic AG). Rubisco depletion was achieved by ammonium sulphate stepwise precipitation (35 and 60%) followed by phenol extraction. The resulting Rubisco depleted pellets were dissolved in Lysis Buffer [30 mM Tris-HCl (pH 8.5), 7 M Urea, 2 M Thiourea, 4% CHAPS] and the protein was measured according to Ramagli [11], with albumin from chicken egg white (Sigma) as standard.
2.5 Refraction 2D—multiplex fluorescence gel electrophoresis technology Fifty micrograms of protein, of each of the three biological replicates, and each of the three rice lines (nine samples total) was labeled according to the manufacturer’s instructions (NH DyeAgnostics) with G-Dye300 and G-Dye200 dyes. An internal standard (containing the same amount of all the samples under study) labeled with G-Dye100, was used to normalize spot volumes and assist in gel alignment procedures. The 13-cm-long, 3–11 NL pH range, IPG strips (Amersham Biosciences) were passively rehydrated, for at least 12 h, with two different protein samples, labeled with the two different dyes, and the internal standard sample (50 g × 3 = 150 g total protein in each strip/gel). For rehydration the labeled proteins were diluted in 250 L of rehydration solution (RH) [7 M urea, 2 M Thiourea, 4% w/v CHAPS, 1% immobilized pH gradient (IPG) buffer 3–11, 65 mM DTT]. IPG strips were focused using the following program: 1 h at 250 V, 90 min at 500 V, 90 min at 1000 V, 1 h at 2500 V, 24 min of a linear gradient to 8000 V and 3 h at 8000 V, as previously described [12]. Strips were equilibrated at room temperature for 15 min in 50 mM Tris-HCl, pH 8.8, 6 M urea, 30% v/v glycerol, 2% w/v SDS (equilibration buffer) with 1% DTT, followed by protein alkylation with 2.5% w/v iodoacetamide in the equilibration buffer. SDS-PAGE was performed on 12.5% T, 1.4% C gels in a Hoefer SE 600 system (Amersham Biosciences) and run C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
at 15⬚C with a 15 mA/gel constant current for 15 min, and then at 30 mA/gel (see experimental details of refraction 2D experiment on Supporting Information Fig. 4).
2.5.1 Imaging Gels were scanned using a Fuji FLA-5100 while in the low fluorescence glass cassettes. G-Dye100, G-Dye200, and G-Dye 300 colored samples were scanned using the following parameters, respectively: 498 nm /524 nm, 554 nm/575 nm, and 648 nm/663 nm (laser/emission filter). For each gel scanning we optimized laser voltage to maximum dynamic range without reaching image saturation. All 18 gel images (three rice lines, three biological replicates, and two dyes) were accepted for further analysis by Samespots image quality control.
2.5.2 Statistical analysis Progenesis Samespots DIGE enable (v4.5) visual tools were used to individually validate all the 447 spots selected for subsequent statistical analysis. Samespots identification of differentially abundant proteins was based on the spots normalized volume and performed by one way ANOVA. Spots with fold differences ࣙ1.5, Anova p-values
DOI 10.1002/pmic.201400018
Proteomics 2015, 15, 124–134
RESEARCH ARTICLE
In vitro culture may be the major contributing factor for transgenic versus nontransgenic proteomic plant differences ´ ´ ˆ Catia Fonseca1,2 , Sebastien Planchon3 , Tania Serra4 , Subhash Chander2 , Nelson J. M. Saibo2 , Jenny Renaut3 , M. Margarida Oliveira2,4 and Rita Batista1,2 1
National Health Institute, Lisboa, Portugal ´ Instituto de Tecnologia Qu´ımica e Biologica, Universidade Nova de Lisboa, Oeiras, Portugal 3 Department of Environment and Agrobiotechnologies (EVA), Centre de Recherche Public, Gabriel Lippmann, Belvaux, Luxembourg 4 IBET, Oeiras, Portugal 2
Identification of differences between genetically modified plants and their original counterparts plays a central role in risk assessment strategy. Our main goal was to better understand the relevance of transgene presence, genetic, and epigenetic changes induced by transgene insertion, and in vitro culture in putative unintended differences between a transgenic and its comparator. Thus, we have used multiplex fluorescence 2DE coupled with MS to characterize the proteome of three different rice lines (Oryza sativa L. ssp. japonica cv. Nipponbare): a control conventional line (C), an Agrobacterium-transformed transgenic line (Ta ) and a negative segregant (NSb ). We observed that Ta and NSb appeared identical (with only one spot differentially abundant—fold difference ࣙ 1.5), contrasting with the control (49 spots with fold difference ࣙ1.5, in both Ta and NSb vs. control). Given that in vitro culture was the only event in common between Ta and NSb , we hypothesize that in vitro culture stress was the most relevant condition contributing for the observed proteomic differences. MS protein identification support our hypothesis, indicating that Ta and NSb lines adjusted their metabolic pathways and altered the abundance of several stress related proteins in order to cope with in vitro culture.
Received: January 20, 2014 Revised: September 9, 2014 Accepted: September 29, 2014
Keywords: Genetically modified foods safety assessment / In vitro culture / Multiplex fluorescence 2DE / Negative segregant / Plant proteomics
1
Additional supporting information may be found in the online version of this article at the publisher’s web-site
Introduction
The current risk assessment strategy for genetically modified (GM) plants aimed for food / feed applications focuses on the identification of similarities and differences between the ´ Correspondence: Dr. Rita Batista, Instituto Nacional de Saude Dr. Ricardo Jorge, Av. Padre Cruz, 1649–016 Lisboa, Portugal E-mail: [email protected] Fax: +351217508153 Abbreviations: GM, genetically modified; GMO, genetically modified organism; NADP, nicotinamide adenine dinucleotide phosphate
C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
GM plant and its comparators, taking into account natural variation [1]. One of the most important and most challenging issues is the selection of the best comparators for this risk assessment. Presently, risk assessment of predictable effects is easily attained through specific in vitro and clinical tests. However, there has been an increasing demand for new methodologies to also estimate any unpredictable and unintended effects [2, 3]. Unintended differences in GM versus non-GM plants may (a) be dependent on the transgene expression; (b) occur as a consequence of epigenetic changes, host DNA disruption Colour Online: See the article online to view Figs. 1–3 in colour.
www.proteomics-journal.com
125
Proteomics 2015, 15, 124–134
or DNA sequence rearrangements promoted by transgene insertion; be due to the in vitro culture associated procedures used for the transformation process [4]. The challenge is to design control strategies allowing evaluation of the potential unintended effects caused by the incidents (a) or (b) discounting potential effects due to in vitro culture associated with the methodology. In vitro culture is noncontroversial and largely used for clonal propagation and general strategies of plant improvement (e.g. production of disease free plants [5], production of haploids [6]). Ideally, non-GM control plants should have passed all in vitro culture steps needed for the transformation process lacking only the transformation event itself. However, this type of control would be tremendously difficult for GM plants with several stacked events. In the “European Food Safety Authority (EFSA) guide on selection of comparators for risk assessment of GM plants [7], additional comparators are also considered to supplement the conventional non-GM counterpart (a genotype with a genetic background as close as possible to the GM plant). The possibility of using negative segregants (homozygous individuals lacking the introduced DNA, obtained from self-fertilization of hemizygous genetically modified individuals or from crosses between hemizygous and conventional lines) is implied. Some scientists suggest that negative segregants would be better comparators for risk assessment of genetically modified organisms (GMO) since they allow for discounting the differences promoted by the in vitro tissue culture. However, others state that the impact of genetic modification cannot be completely assessed using only a negative segregant as a comparator, since the genetic or epigenetic changes promoted by transgene insertion may have remained after segregation (EFSA Consultative Workshop on the Draft Guidance on Selection of Comparators for the Risk Assessment of GM Plants, 2011). In fact, the use of negative segregants, as controls in GM risk assessment, will potentially discount genetic and/or epigenetic changes induced by transgene insertion. Thus, potentially important effects will be discounted and evade evaluation. On the other hand, the use of conventional counterparts, as controls, will not permit subtracting differences putatively caused by the in vitro culture process. As a result, some of the differences found, between the control and the transgenic plant, will be due to the in vitro culture process itself. These differences, though not of concern, will not be excluded from the evaluation. The question is which of these factors, transgene insertion or in vitro culture, more strongly impacts the potential unexpected changes? This study aims to evaluate the relative contribution of in vitro culture and transgene insertion/expression, on the proteomic profiles of a GM plant and its non-GM counterpart. In order to achieve this goal, we have used multiplex fluorescence 2DE coupled with MS to characterize the proteome of three rice lines (Oryza sativa L. ssp. japonica cv. Nipponbare): a control conventional counterpart, an Agrobacteriumtransformed transgenic line (Ta ), and a negative segregant (NSb ), progeny of a different transgenic line. C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
2
Materials and methods
2.1 Plant materials Three different lines of Oryza sativa L. ssp. japonica cv. Nipponbare were used: a control line (C); a GM line obtained by Agrobacterium-mediated transformation (Ta ), and a non-GM negative segregant control line (NSb , – progeny of Transgenic b) (Fig. 1A). Ta carried one copy of OsICE1 transcription factor, fused to a TAP-tag construct, driven by the maize ubiquitin promoter. NSb was a F1 descendent of a transgenic line (Tb ) also containing the OsICE1 transcription factor driven by the maize ubiquitin promoter but in this case lacking the TAP-tag (See transformation vectors information on Supporting Information Fig. 1). Transformation and regeneration procedures used to generate Ta and Tb lines were as previously described [8]. Prior to the experiment, each of the tested lines (C, Ta , and NSb ) was grown for two generations in exactly the same conditions (mixture 2:2:1, soil: peat: vermiculite, 28⬚C light/24⬚C night, 12 h photoperiod, 70% relative humidity). 2.2 Seed germination and seedling growth for proteomic assays Eighteen seeds from the second generation plants (randomly collected from one plant of each line- C, Ta , and NSb ) were manually peeled and disinfected as previously described [8]. Seeds were kept for 48 h in the final wash at 28⬚C, in the dark, and were then transferred to Yoshida’s medium [9] and maintained at 28⬚C light/24⬚C night, 12 h photoperiod and 70% relative humidity, for another 13 days. Transgene presence was confirmed by PCR for each Ta seedling (Supporting Information Fig. 2). The up-regulation of OsICE1 transcription factor in Ta line was confirmed by microarrays expression analysis (Supporting Information Fig. 3). 2.3 Characterization of GM plants (Ta and Tb ) 2.3.1 Southern blot analysis Rice genomic DNA was extracted from four-leaf stage seedlings and quantified by gel electrophoresis with DNA (Fermentas Inc.). Fifteen micrograms of rice genomic DNA from each line (Control, Ta and Tb ) were digested with several different restriction enzymes for Southern blot analysis. Gel electrophoresis, DNA blotting, DNA labeling, and hybridization conditions were performed as previously described [10].
2.3.2 Chromosome walking To identify the transgene insertion site in both transgenic rice lines (Ta and Tb - hemizygous transgenic parental line of NSb ) www.proteomics-journal.com
126
C. Fonseca et al.
Proteomics 2015, 15, 124–134
Figure 1. (A) Schematic representation of plant rice lines and the potential factors contributing to their differences—IV In vitro culture promoted changes; TIPAa , Transgene a insertion promoted alterations; TIPAb , Transgene b insertion promoted alterations; ta , Transgene a expression promoted differences; tb , Transgene b expression promoted differences; . g(Ci), f(Ci)- Functions that transform each control elements (Ci -protein spots) into Ta or into NSb elements (protein spots), respectively. The plant lines analyzed in this study are represented in red. Each of the tested lines (C, Ta , and NSb -Oryza sativa L. ssp. japonica cv. Nipponbare) was grown for two generations in the same conditions before the experiment. (B) Mathematical explanations supporting the hypothesis of in vitro culture as the major factor impacting Ta versus C proteomic differences.
C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
www.proteomics-journal.com
127
Proteomics 2015, 15, 124–134
a Genome Walker library was prepared using the Genome Walker Universal kit (www.clontech.com). The identification of the insertion sites was performed by amplification and sequencing of the regions flanking the right and the left border of the T-DNA insert, using a primer combination from the Genome Walker kit and from the right or left border of T-DNA insert.
2.4 Protein extraction and RuBisCO depletion For protein extraction, whole seedlings at the four leaf stage were used. Three pools of seedlings (three biological replicates), of each tested line, were ground in a mortar with liquid nitrogen and proteins extracted with 6 mL of Extraction Buffer [100 mM HEPES-KOH pH 7.5; 5% Glycerol; 5 mM EDTA; 0.1% -Mercaptoethanol; 1% Proteinase Inhibitor Cocktail for plant proteins (Sigma)] for 10 min at 4⬚C. After double centrifugation at 10 000 × g, for 10 min at 4⬚C, final supernatants were filtered through a 25 mm diameter, 0.45 m cellulose mixed ester filter (BGB Analytic AG). Rubisco depletion was achieved by ammonium sulphate stepwise precipitation (35 and 60%) followed by phenol extraction. The resulting Rubisco depleted pellets were dissolved in Lysis Buffer [30 mM Tris-HCl (pH 8.5), 7 M Urea, 2 M Thiourea, 4% CHAPS] and the protein was measured according to Ramagli [11], with albumin from chicken egg white (Sigma) as standard.
2.5 Refraction 2D—multiplex fluorescence gel electrophoresis technology Fifty micrograms of protein, of each of the three biological replicates, and each of the three rice lines (nine samples total) was labeled according to the manufacturer’s instructions (NH DyeAgnostics) with G-Dye300 and G-Dye200 dyes. An internal standard (containing the same amount of all the samples under study) labeled with G-Dye100, was used to normalize spot volumes and assist in gel alignment procedures. The 13-cm-long, 3–11 NL pH range, IPG strips (Amersham Biosciences) were passively rehydrated, for at least 12 h, with two different protein samples, labeled with the two different dyes, and the internal standard sample (50 g × 3 = 150 g total protein in each strip/gel). For rehydration the labeled proteins were diluted in 250 L of rehydration solution (RH) [7 M urea, 2 M Thiourea, 4% w/v CHAPS, 1% immobilized pH gradient (IPG) buffer 3–11, 65 mM DTT]. IPG strips were focused using the following program: 1 h at 250 V, 90 min at 500 V, 90 min at 1000 V, 1 h at 2500 V, 24 min of a linear gradient to 8000 V and 3 h at 8000 V, as previously described [12]. Strips were equilibrated at room temperature for 15 min in 50 mM Tris-HCl, pH 8.8, 6 M urea, 30% v/v glycerol, 2% w/v SDS (equilibration buffer) with 1% DTT, followed by protein alkylation with 2.5% w/v iodoacetamide in the equilibration buffer. SDS-PAGE was performed on 12.5% T, 1.4% C gels in a Hoefer SE 600 system (Amersham Biosciences) and run C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
at 15⬚C with a 15 mA/gel constant current for 15 min, and then at 30 mA/gel (see experimental details of refraction 2D experiment on Supporting Information Fig. 4).
2.5.1 Imaging Gels were scanned using a Fuji FLA-5100 while in the low fluorescence glass cassettes. G-Dye100, G-Dye200, and G-Dye 300 colored samples were scanned using the following parameters, respectively: 498 nm /524 nm, 554 nm/575 nm, and 648 nm/663 nm (laser/emission filter). For each gel scanning we optimized laser voltage to maximum dynamic range without reaching image saturation. All 18 gel images (three rice lines, three biological replicates, and two dyes) were accepted for further analysis by Samespots image quality control.
2.5.2 Statistical analysis Progenesis Samespots DIGE enable (v4.5) visual tools were used to individually validate all the 447 spots selected for subsequent statistical analysis. Samespots identification of differentially abundant proteins was based on the spots normalized volume and performed by one way ANOVA. Spots with fold differences ࣙ1.5, Anova p-values
