<i>X</i>. <i>campestris</i> pv. <i>vesicatoria</i> induces expression of <i>SP1-1</i> in tomato fruits.

<p>Expression of <i>SP1-1</i> was analyzed by quantitative RT-PCR in tomato fruits of T583-4, T583-5 and T583-6 36 h after inoculation and normalized to two internal reference genes (ubiquitin and actin). Expression of <i>SP1-1</i> after Mock treatment (MgCl₂) was set to 1. Fold change of expression of <i>SP1-1</i> in <i>X</i>. <i>campestris</i> pv. <i>vesicatoria</i> treated samples is given relative to the expression in Mock treated samples. Data are the mean ±SD of two to three biological replicates. Significant differences from the control are indicated: ***, P<0.001 **, P<0.01 and *, P<0.05</p

Induction of pathogen-inducible promoter 4XW2 in response to Pep25 and <i>X</i>. <i>campestris</i> pv. <i>vesicatoria</i>.

<p>The 4XW2-GFP-GUS was transiently transformed into TH3 tomato protoplasts using a modified PEG method. GFP fluorescence was monitored 12–16 h after water (A and B), pep25 (C and D) and <i>X</i>. <i>campestris</i> pv. <i>vesicatoria</i> treatment (E and F). (G) Number of protoplasts showing GFP fluorescence is given in percent. (H) Quantification of GFP fluorescence intensity was done using the Image J software (<a href="http://imagej.nih.gov/ij/" target="_blank">http://imagej.nih.gov/ij/</a>). Scale bar: 20 μm. Asterisks indicate significant different in comparison to the corresponding control treatment, *P<0.05, **P<0.01, ***P<001.</p

Resistance of tomato fruits of T0 transgenic plants against <i>X</i>. <i>campestris pv</i>. <i>vesicatoria</i> infection.

<p>(A) Infection symptoms of WT and transgenic T0 tomato fruits overexpressing <i>SP1-1</i> (T583-4, T583-5 and T583-6) after Mock treatment (MgCl₂) or inoculation with <i>X</i>. <i>campestris</i> pv. <i>vesicatoria</i> (10⁶ CFU/ml). Pictures are taken two days after treatment. (B) Incidence of infection symptoms two days after inoculation with <i>X</i>. <i>campestris</i> pv. <i>vesicatoria</i> is given in percentage. The values represent the mean of three independent experiments +/- SE.</p

Transgenic tomato Micro Tom lines expressing the AMP SP1-1.

<p>(A) Schematic illustration of PMIGW-4XW2/4XS::SP1-1 vector construct. The vector contains a CaMV35S promoter-driven phosphomannose isomerase (PMI) gene for mannose selection. B1, B2, B3 and B4 represent attB Gateway recombination sites. SP, signal peptide RsAFP1 from radish; SP1-1, synthetic antimicrobial peptide; TNos, nopaline synthase gene terminator; RB, right border; LB, left border; W2 <i>cis</i>-acting elements from the parsley PR1 gene; S, <i>cis</i>-elements from the parsley EL17 gene; CaMV35S, minimal promoter containing the sequence -46 to +8 from the cauliflower mosaic virus 35S promoter; T35S, terminator from the cauliflower mosaic virus 35S. (B) Molecular characterization of transformed plants. PCR was done using DNA from young leaves as template and RsAFP1-TNos-specific primers. PCR fragments were obtained for T583-4, T583-5 and T583-6. PMIGW-4XW2/4XS::SP1-1 transformation vectors and WT Micro Tom tomato plants were used as positive and negative controls respectively. (C and D) Morphological phenotypes of six weeks old WT and transgenic T1 Micro Tom tomato plants. Transgenic and WT plants were grown in climate chambers for 6 weeks. (E) Detached leaves of line T583 were infiltrated with water (H) or pep25 peptide (P). Total RNA was extracted before induction (BI) and 0, 3, and 22 h after induction. RT-PCR was carried out with gene-specific primers for RsAFP1-SP1-1 and actin and fragments of 163 bp and 586 bp were expected, respectively. Genomic DNA of the transgenic line T583 was used as control (+). Total RNA from WT plants and water (-) was used as negative control. The SP1-1 band is marked with an arrow. M, 100 bp DNA ladder.</p

Antibacterial activity of synthetic peptide SP1-1 in the presence of tomato apoplastic fluid.

<p><i>X</i>. <i>campestris</i> pv <i>vesicatoria</i> (10⁵ cfu/ml) was incubated with 0 or 10 μg/ml of peptide SP1-1 in the presence or absence of 10 μg/ml of tomato apoplastic fluid. Bacterial growth was determined by measuring OD_600nm (OD 0.2 = 10⁸ cfu/ml) 15 hours after APO; tomato apoplastic fluid. Values represent the mean of at least three biological replicates ± standard error of the mean. Asterisks indicate significant different in comparison to the corresponding control treatment, *P<0.05, **P<0.01.</p

Computational Prediction of Candidate Proteins for S-Nitrosylation in <i>Arabidopsis thaliana</i>

<div><p>Nitric oxide (NO) is an important signaling molecule that regulates many physiological processes in plants. One of the most important regulatory mechanisms of NO is S-nitrosylation—the covalent attachment of NO to cysteine residues. Although the involvement of cysteine S-nitrosylation in the regulation of protein functions is well established, its substrate specificity remains unknown. Identification of candidates for S-nitrosylation and their target cysteine residues is fundamental for studying the molecular mechanisms and regulatory roles of S-nitrosylation in plants. Several experimental methods that are based on the biotin switch have been developed to identify target proteins for S-nitrosylation. However, these methods have their limits. Thus, computational methods are attracting considerable attention for the identification of modification sites in proteins. Using GPS-SNO version 1.0, a recently developed S-nitrosylation site-prediction program, a set of 16,610 candidate proteins for S-nitrosylation containing 31,900 S-nitrosylation sites was isolated from the entire <i>Arabidopsis</i> proteome using the medium threshold. In the compartments “chloroplast,” “CUL4-RING ubiquitin ligase complex,” and “membrane” more than 70% of the proteins were identified as candidates for S-nitrosylation. The high number of identified candidates in the proteome reflects the importance of redox signaling in these compartments. An analysis of the functional distribution of the predicted candidates showed that proteins involved in signaling processes exhibited the highest prediction rate. In a set of 46 proteins, where 53 putative S-nitrosylation sites were already experimentally determined, the GPS-SNO program predicted 60 S-nitrosylation sites, but only 11 overlap with the results of the experimental approach. In general, a computer-assisted method for the prediction of targets for S-nitrosylation is a very good tool; however, further development, such as including the three dimensional structure of proteins in such analyses, would improve the identification of S-nitrosylation sites.</p></div

Percentage of candidate proteins for <i>S</i>-nitrosylation in different functional categories.

<p>Functional assignment has been done using the MapMan Ontology tool (<a href="http://mapman.gabipd.org/web/guest/mapman" target="_blank">http://mapman.gabipd.org/web/guest/mapman</a>).</p

Subcellular compartment classification of <i>Arabidopsis</i> proteins.

<p>Total number of proteins, number of predicted candidates for <i>S</i>-nitrosylation, and the number of candidates with the highest 10% prediction confidence were assigned to their subcellular localization according to gene ontology cellular component classification. The prediction confidence was calculated by dividing the raw score value by the cutoff value of a particular cluster.</p><p>Subcellular compartment classification of <i>Arabidopsis</i> proteins.</p

Prediction of <i>Arabidopsis</i> candidate proteins for S-nitrosylation using the GPS-SNO 1.0 software.

<p><i>Arabidopsis</i> amino acid sequences were extracted from TAIR 10 database (<a href="http://www.arabidopsis.org" target="_blank">www.arabidopsis.org</a>) and analysed by GPS-SNO 1.0 software using medium threshold condition. The 10% of predicted sites with the highest prediction confidence were determined by ranking the prediction results according to the raw score divided by the threshold (Cutoff) for a particular cluster.</p><p>Prediction of <i>Arabidopsis</i> candidate proteins for S-nitrosylation using the GPS-SNO 1.0 software.</p

Computational prediction of <i>S</i>-nitrosylation sites from experimentally identified <i>S</i>-nitrosylated proteins in plants using GPS-SNO 1.0, iSNO-PseAAC, iSNO-AAPair, and SNOSite software.

<p>Amino acid sequences were downloaded from the most recent version of the <i>Arabidopsis</i> information resource TAIR (TAIR10, <a href="http://www.arabidopsis.org" target="_blank">www.arabidopsis.org</a>) and subjected to the different programs for prediction of S-nitrosylation sites. NPR1, non-expresser of pathogenesis related genes 1; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; SABP3, salicylic acid binding protein 3; TGA1, TGACG motif binding factor; cALD2, cytosolic fructose 1,6-bisphosphate aldolase; TIR1, transport inhibitor response 1; CDC48, cell division cycle 48; AtMYB30, <i>Arabidopsis thaliana</i> MYB transcription factor.</p><p>C in bold, matched cysteine residues, "_" not predicted</p><p>Computational prediction of <i>S</i>-nitrosylation sites from experimentally identified <i>S</i>-nitrosylated proteins in plants using GPS-SNO 1.0, iSNO-PseAAC, iSNO-AAPair, and SNOSite software.</p