Enhanced Resistance of atnigr1 against Pseudomonas syringae pv. tomato Suggests Negative Regulation of Plant Basal Defense and Systemic Acquired Resistance by AtNIGR1 Encoding NAD(P)-Binding Rossmann-Fold in Arabidopsis thaliana

Abstract

Nitric oxide (NO) regulates several biological and physiological processes in plants. This study investigated the role of Arabidopsis thaliana Negative Immune and Growth Regulator 1 (AtNIGR1), encoding an NAD(P)-binding Rossmann-fold superfamily, in the growth and immunity of Arabidopsis thaliana. AtNIGR1 was pooled from the CySNO transcriptome as a NO-responsive gene. Seeds of the knockout (atnigr1) and overexpression plants were evaluated for their response to oxidative [(hydrogen peroxide (H₂O₂) and methyl viologen (MV)] or nitro-oxidative [(S-nitroso-L-cysteine (CySNO) and S-nitroso glutathione (GSNO)] stress. Results showed that the root and shoot growth of atnigr1 (KO) and AtNIGR1 (OE) exhibited differential phenotypic responses under oxidative and nitro-oxidative stress and normal growth conditions. To investigate the role of the target gene in plant immunity, the biotrophic bacterial pathogen Pseudomonas syringae pv. tomato DC3000 virulent (Pst DC3000 vir) was used to assess the basal defense, while the Pst DC3000 avirulent (avrB) strain was used to investigate R-gene-mediated resistance and systemic acquired resistance (SAR). Data revealed that AtNIGR1 negatively regulated basal defense, R-gene-mediated resistance, and SAR. Furthermore, the Arabidopsis eFP browser indicated that the expression of AtNIGR1 is detected in several plant organs, with the highest expression observed in germinating seeds. All results put together suggest that AtNIGR1 could be involved in plant growth, as well as basal defense and SAR, in response to bacterial pathogens in Arabidopsis.

1. Introduction

Plants are sessile organisms and they are constantly vulnerable to biotic and abiotic stresses [1]. Unlike animals, plants lack mobile defender cells and a somatic adaptive immune system to fight pathogen infection [1,2]. Therefore, plants rely on their innate immune system to detect and transmit signals and to react to infectious pathogens [2]. The plant’s protective immunological response is divided into pathogen- or microbial-associated molecular patterns (PAPMs/MAMPs-triggered immunity (PTI)), resistance (R) gene or effector-triggered immunity (ETI), and systemic acquired resistance (SAR) [3]. One of the earliest adaptations toward microbial infections is the oxidative burst, which triggers the hypersensitive response (HR) and results in programmed cell death (PCD) at the infection site [4]. The HR is frequently connected to a resistance response and is mediated by interactions between the avirulence proteins of the pathogen and plant resistance proteins, as well as various signaling pathways, both indirectly and directly [1]. Plants use pattern recognition receptors (PRRs) to recognize PAMPs/MAMPs and induce PTI. PTI is considered to be inhibited by a class of pathogen-encoded effector proteins known as avirulence (avr) factors [5], which are identified by host-encoded R proteins, and impart a long-lasting and strong resistance known as resistance mediated by the R-gene or ETI [6].

In response to biotic and abiotic stress conditions, plants produce reactive oxygen species (ROS), reactive nitrogen species (RNS), and melatonin, which are pivotal signaling molecules [4,7,8]. ROS and RNS play a dual role in plants: when produced in optimal conditions, they act as signaling molecules; when produced excessively, they act as toxic molecules, causing oxidative damage to the plants [9,10]. Recently, the role of ROS and RNS in plant growth and development and symbiotic association and defense responses against biotic and abiotic stress conditions has been reviewed in detail [7,8,9,10,11,12]. Among RNS, NO has emerged as a core signaling molecule, with regard to the increasing interest in NO-related research in plant bioscience [13], since it was designated “Molecule of the Year in 1992” for its outstanding regulatory roles in both plants and animals [8,14]. NO regulates a variety of biological processes in plants, including plant growth and development and adaptive response mechanisms under abiotic and biotic stress conditions [15,16]. Previous reports revealed the roles of the NO-induced genes AtCLV1, AtCLV3, AtAO3, AtbZIP62, and AtILL6 in plant growth and defense against biotic and abiotic stresses. These NO-induced genes differentially regulate plant growth and defense responses against biotic and abiotic stress conditions [1,4,17,18].

The role of NO in biological systems was also revealed through RNA-seq-mediated transcriptomic studies. The latter have reported differential gene expression patterns in plants upon CySNO (an NO donor, 1 mM) application. The associations of target NO-responsive genes with the regulation of plant defense, the abiotic stress response, hormone signaling, and other developmental processes have equally been established [19]. Among the differentially expressed genes (DEGs) reported earlier, Arabidopsis thaliana Negative Immune and Growth Regulator 1 (AtNIGR1) with gene number AT1G66130 was identified among the topmost down-regulated genes (fold change –5.34). This gene belongs to NAD(P) Rossmann-fold superfamily proteins and participates in oxidoreductase activity, catalytic activity, and metabolic processes (The Arabidopsis Information Resource, https://www.arabidopsis.org/ (accessed on 3 January 2022)). We obtained this data from the said website on 3 January 2022.

The advent of high-throughput sequencing technologies, advances in omics-related studies, and the development of bioinformatics tools and the abundance of complex biological data have offered tremendous opportunities to shift our common understanding of plant metabolism and biological processes, as well as their associated genetic factors, under both normal and stress conditions. Several bioinformatics tools available in online data, such as string (https://string-db.org, allowing for the prediction of protein–protein interactions (accessed on 7 January 2023)) have been developed to analyze multiple information resources generated using experimental or predictive models. We obtained this data from the said website on 7 January 2023. Considering the progress recorded in this field and the easy access to the public, the use of bioinformatics in molecular biology-related studies will increase with time.

This study aimed to investigate the role of the NO-downregulated AtNIGR1gene in plant growth and development. To achieve that, Arabidopsis plants were exposed to oxidative and nitro-oxidative stress conditions. To further investigate the role of our target gene in plant basal defense, R-gene-mediated resistance, and SAR, Arabidopsis mutant lines lacking (knockout, KO) atnigr1 and overexpressing (OE) AtNIGR1, along with relevant control plants were inoculated with virulent and avirulent pathogenic bacteria.

2. Materials and Methods

2.1. Plant Materials and Growth Conditions

The Nottingham Arabidopsis Stock Center (http://arabidopsis.info/ (accessed on 7 January 2023)) provided seeds of the Arabidopsis thaliana wild-type (WT) ecotype Columbia zero (Col-0) and the mutants atnigr1 (KO), AtNIGR1 (OE), atgsnor1–3, atcat2, and atsid2. We ordered the seeds from the said center and website on 7 January 2023. The SALK number of the T-DNA insertion is SALK_064843. All of the genotypes used in this investigation had a Col-0 genetic background. For seeds, sterilization, sowing, transplantation, and collection of the samples for genotyping, plant growth and immunity-related parameter analyses were performed as previously described [17]. In brief, samples were obtained at the rosette stage (4-week-old plants) for genotyping and T-DNA insertion confirmation using PCR. To confirm genotypes of the atnigr1 (KO) and AtNIGR1 (OE) plants of the AtNIGR1 (AT1G66130), gene PCR was run with gene-specific forward (F) and reverse (R) primers and F border, 35SF and gene-specific R primers (Supplementary Figure S1A,B). Relative controls were used based on their established roles in plant growth and immunity, as previously suggested [4]. The atgsnor1–3 mutant was used as a sensitive or susceptible control for nitro-oxidative and biotic stress. GSNOR is known to play a function in a variety of plant developmental programs, as well as plant immunity [20]. It is a typical line for testing the Arabidopsis response under variable nitro-oxidative stress conditions. The atcat2 mutant line was used as a sensitive control for oxidative stress conditions. In Arabidopsis, AtCAT2 is a class I catalase expressed in the leaves, roots, and seeds, with much higher transcript abundance than the other catalases, and contributes to the circadian and photosynthetic-type rhythm [21]. In Arabidopsis, AtCAT2 is responsible for the majority of catalase activity, as knockout lines of atcat1 and atcat3 show a smaller reduction in leaf catalase activity than atcat2 [4,21]. Therefore, atcat2 mutant lines are frequently used as an oxidative stress model. The atsid2-knockout mutant line was used to study the salicylic acid (SA) pathway [4,22]. In Arabidopsis, Isochorismate Synthase 1 (ICS1) is encoded by the Salicylic Acid Induction Deficient 2 (AtSID2) gene. The atsid2-mutant line is incapable of accumulating SA and lacks SA-dependent defensive responses.

2.2. Redox Stress Assay

To investigate the role of the AtNIGR1 gene in plant growth and development under control and redox stress, the plants were exposed to control (only ½ MS media), oxidative stress (supplemented with either 2 mM H₂O₂ or 1 µM MV), and nitro-oxidative stress (supplemented with 0.75 mM CySNO or 0.75 mM GSNO) as described previously [4]. Before sowing, the seeds were surface-sterilized for 5 min in a 50-percent commercial bleach solution provided with 0.1-percent Triton X-100 (Sigma Aldrich, USA). After that, the seeds were rinsed three times with sterilized distilled water and stratified for 24 h at 4 °C. Furthermore, following the same author, the results for phenotypic evaluation and root and shoot lengths were collected after two weeks, with at least three replicates per treatment.

2.3. Pathogenic Growth, Inoculation, and Electrolyte Leakage Assay

The biotrophic bacterial pathogen Pseudomonas syringae pv. tomato DC3000 virulent (Pst DC3000 vir) was used to assess the basal defense, while the Pst DC3000 avirulent (avrB) strain was used to investigate R-gene-mediated resistance and SAR as described earlier [23]. For selection, the bacteria were cultivated on Luria-Bertani (LB) agar media supplemented with suitable antibiotics and incubated overnight at 28 °C. The single colony was transferred to LB broth, which was supplemented with antibiotics, and cultured at 28 °C with constant shaking overnight. The bacterial strains were inoculated at a concentration of 5 × 10⁵ colony forming units (CFU) into the abaxial side of the leaves of different plant lines, including wild-type (WT), atgsnor1–3, atsid2, and KO and OE lines of the AtNIGR1 gene. In the case of basal defense, the samples were collected for colony counts and gene expression at 0, 1, 2, 3, and 4 days and 0, 12, 24, and 48 h post-inoculation, respectively. Moreover, some of the plants were retained in the experimental setup to observe the development of disease symptoms. For R-gene-mediated resistance, the samples were collected at 0, 6, 12, and 24 h post-inoculation. Meanwhile for SAR, the samples were collected from distal leaves at 0, 6, 12, and 24 h post-inoculation. Only 10 mM MgCl₂ was used to infiltrate the control plants. For this purpose, we followed previously used methods [4].

Bacterial infection-mediated oxidative stress affects the integrity of the cell membrane, and this event is followed by ion leakage out of the cell that may lead to the activation of programmed cell death and plant growth failure. In order to quantify the Pst DC3000-induced cell death or membrane injury, we conducted an electrolyte leakage assay after Pst DC3000 avrB inoculation as previously described [1]. Briefly, 10 uniform leaf discs (1 cm diameter) were collected with a cork borer from different plants of each Arabidopsis genotype at 1, 2, 4, 6, 8, 12, and 24 h after inoculation with Pst DC3000 avrB. Leaf samples were then rinsed three times with deionized water in petri plates to remove surface electrolytes, and transferred to 6-well culture plates (SPL Life Sciences, Pocheon-si, Korea) and floated in 5 mL of deionized water in each well for about 30 min. The electrolyte leakage of each sample was recorded over time using a portable conductivity meter (HURIBA Twin Cond B-173, Kyoto, Japan).

2.4. qRT-PCR (Quantitative Real-Time PCR) Analysis

For RNA extraction, complementary DNA (cDNA) synthesis, and qRT-PCR analysis, previously described methods were used [1]. The TRI-Solution™ Reagent [(Cat. No: TS200-001, Virginia Tech Biotechnology, Lot: 337871401001)] was used to extract total RNA from leaf samples, as directed by the manufacturer’s protocol and described earlier. In brief, using the BioFACT™ RT-Kit (BioFACT™, Daejeon, Korea) and the manufacturer’s standard methodology, 1 µg of RNA was used to synthesize complementary DNA (cDNA). For gene expression analysis, cDNA was used as a template in the Eco™ real-time PCR machine (Illumina, San Diego, CA, USA), using the 2X Real-time PCR Master Mix (including SYBR Green 1 BioFACT™, Daejeon, Korea), along with 100 ng of template DNA and 10 nM of each forward and reverse primer to a final volume of 20 µL. The No Template Control (NTC), which includes simply distilled water instead of template DNA, was utilized as a negative control. The real-time PCR machine was run in a 2-step reaction that included polymerase activation at 95 °C for 15 min, denaturation at 95 °C for 5 s, and annealing and extension at 65 °C for 30 s. The data were standardized using the relative expression of Arabidopsis Actin2, and the total reaction cycles were 40 [17].

2.5. Functional Categorization and Gene Ontology Annotation

A gene ontology (GO) annotation search was carried out for the AtNIGR1 gene using the TAIR GO Annotations tool (Home > Tools > Bulk Data Retrieval > GO Annotations: https://www.arabidopsis.org/tools/bulk/go/index.jsp (accessed on 7 January 2023)). We obtained this data from the said website on 7 January 2023. For this purpose, the locus identifier was searched for GO annotations using the option of whole-genome characterization. The output was observed as an HTML and submitted for functional characterization. Data were retrieved for GO Cellular Component, GO Molecular Function, and GO Biological Process.

2.6. Gene Structure and Domain Analysis

Gene structure and domain analyses were performed using UniProtKB (uniport.org (accessed on 7 January 2023)), where the locus identifier for the AtNIGR1 gene is Q9C8D3. We obtained this data from the said website on 7 January 2023. Data regarding the number, type, location, and sequence of different domains were retrieved from the Family & Domains section. The 3D structure for the alpha fold was also downloaded from the UniprotKB database.

2.7. Identification of Plant Homologs and Phylogenetic Analysis

To identify homolog genes of AtNIGR1 in other plant species, the TAIR Plant Homologs tool PhyloGenes was employed. The tool helped us retrieve data from gene families of PANTHER16.0. PhyloGenes (http://www.phylogenes.org/ (accessed on 7 January 2023)) and displays pre-computed phylogenetic trees of gene families, along with experimental gene function data, to facilitate the inference of unknown gene functions in plants. We obtained this data from the said website on 7 January 2023.

2.8. Expression Pattern of AtNIGR1 in Different Organs

The Arabidopsis eFP Browser 2.0 of the Bio-Analytic Resource of Plant Biology, available at http://bar.utoronto.ca/efp2/Arabidopsis/Arabidopsis_eFPBrowser2.html (accessed on 7 January 2023), was used to gather relevant information on the proposed expression of our target gene (ANIGR1) in different plant organs. We obtained this data from the said website on 7 January 2023.

2.9. In Silico Prediction of S-Nitrosylation Sites

An in silico analysis-based approach facilitated by computer simulations using the GPS-SNO algorithm [24] allowed us to predict S-nitrosylation target cysteines. To achieve that, the amino acid sequence was used for the prediction. The 3D structure was downloaded from UniProtKB as a PDB file and opened in PyMol (https://pymol.org/2/ (accessed on 7 January 2023)). We obtained this data from the said website on 7 January 2023. The 3D structure is shown as a green cartoon structure, whereas the predicted S-nitrosylation cysteines were shown as pink bolls.

2.10. Protein Interaction Analysis

The interaction of AtNIGR1 with other proteins was predicted via SMART (http://smart.embl-heidelberg.de/(accessed on 7 January 2023)) [25,26]. We obtained this data from the said website on 7 January 2023. The protein sequence was submitted for analysis, and the results were downloaded as an SVG image.

2.11. Statistical Analysis

The experiments were repeated thrice for each assay, and the representative findings are shown. The data point for media stress conditions is the mean of three replicates, with five plants pooled in each replicate, whereas the data point for the pathogenicity assay is the mean of three replicates. One-way analysis of variance (ANOVA) was used to determine the significant differences between each treatment, followed by Duncan’s multiple range test using a statistical analysis system (SAS 9.1). Microsoft Excel was used to calculate mean values, standard deviations, and standard errors. GraphPad Prism software (version 6.0, San Diego, CA, USA) was used to visualize the data.

3. Results

3.1. Root and Shoot Growth Patterns of AtNIGR1 KO and OE

Initially, we were interested in assessing the change in the phenotype of the atnigr1-related Col-0 in response to oxidative and nitro-oxidative stress. To achieve that, seeds of the atnigr1 (KO) and AtNIGR1 (OE) lines, along with the relevant controls, were grown on ½ MS media modified with H₂O₂ or MV (for oxidative stress), nitro-CySNO, or GSNO (for nitro-oxidative stress). All of the genotypes used in this investigation had a Col-0 genetic background. Col-0 was used as the wild-type (WT) control, the atgsnor1–3 mutant was used as a sensitive control for nitro-oxidative stress, and the atcat2 mutant line was used as a sensitive control for oxidative stress conditions. As shown in panels A and B of Figure 1, atnigr1 plants had longer roots under control conditions compared to Col-0. A similar pattern was also observed when atnigr1 plants were grown on H₂O₂, CySNO, and GSNO media. Under GSNO treatment, atnigr1 and atcat2 exhibited similar root growth patterns. However, an opposite root growth pattern (reduced root elongation) was recorded in plants overexpressing the AtNIGR1 gene under all tested conditions, except MV, compared to Col-0. As expected, atgsnor1–3 did not germinate on H₂O₂-medium but showed a significant root-inhibition pattern on MV, CySNO, and GSNO. In addition, atcat2 and atnigr1 had similar root phenotypes under control, MV, and GSNO conditions, but not under H₂O₂ and CySNO. Furthermore, plants overexpressing AtNIGR1 exhibited shorter roots compared to Col-0 WT under all tested conditions.

In the same way, the shoot height was higher in atnigr1 but lower in AtNIGR1 OE plants compared to that recorded in Col-0 WT under all growth conditions (Figure 1A,C).

3.2. AtNIGR1 Negatively Regulates Plant Basal Defense

Plants lacking AtNIGR1 (atnigr1) or overexpressing the AtNIGR1 gene along with the relevant controls were challenged with Pst DC3000 vir to investigate the possible involvement of the target gene in basal defense in plants. All of the genotypes used in this investigation had a Col-0 genetic background. Col-0 was used as the wild-type (WT) control, while atgsnor1–3 and atsid2 mutant lines were used as susceptible controls for biotic stress. The results of the pathogenesis test revealed that atnigr1 plants exhibited an enhanced resistance toward Pst DC3000 vir, while those overexpressing AtNIGR1 showed a highly susceptible phenotypic response similar to that observed in the susceptible controls, atgsnor1–3 and atsid2 (Figure 2A). For further confirmation, we evaluated the pathogenic growth in the KO and OE plants of the AtNIGR1 gene, along with atgsnor1–3, and atsid2. No significant change in pathogenic growth was observed with either genotype at 0 days post-inoculation (dpi). However, at 1–4 dpi, atnigr1 plants showed a significant decrease in pathogenic growth, while and AtNIGR1 (OE) plants exhibited an opposite pattern (Figure 2B).

Generally, when plants are infected with pathogenic bacteria, salicylic acid (SA) accumulates as part of the signaling event to activate the appropriate defense mechanism. In this regard, we measured the transcript accumulation of the well-known pathogenesis-related genes AtPR1 and AtPR2 (SA-dependent pathway marker genes) in the atnigr1 (KO) and AtNIGR1 (OE) plants, as well as in the susceptible control lines. The qPCR data in panels C and D of Figure 2 show that the expression level of AtPR1 and AtPR2 increased over time, and the peak expression level was recorded 24 hpi in atnigr1 (susceptible) compared to the Col-0 WT. However, both AtPR1 and AtPR2 showed much lower expression levels in AtNIGR1 (OE) plants compared to that recorded in the Col-0 background.

3.3. Negative Regulation of R-Gene-Mediated Resistance by the AtNIGR1 Gene

To assess the possibility for the AtNIGR1 to be involved in the signaling network upon bacterial pathogen infection, as well as in the R-gene mediated resistance, we inoculated atnigr1 (KO) and AtNIGR1 (OE) plants along with Col-0 (WT), atgsnor1–3, and atsid2, with Pst DC3000 avrB. All of the genotypes used in this investigation had a Col-0 genetic background. Col-0 was used as the wild-type (WT) control, while atgsnor1–3 and atsid2 mutant lines were used as susceptible controls for biotic stress. The results show that after 6, 12, and 24 h of inoculation with avrB, a significant increase and decrease in the transcript accumulation of AtPR1 and AtPR2 were observed in the atnigr1 (KO) and AtNIGR1 (OE) plants compared to that in the Col-0 WT (Figure 3A,B). Furthermore, when compared to the Col-0 WT, the atnigr1 (KO) and AtNIGR1 (OE) plants showed lower and higher electrolyte leakage, respectively (Figure 3C). In addition, compared to Col-0 WT, the disease-susceptible controls, atgsnor1–3 and atsid2, showed lower transcript accumulation of AtPR1 and AtPR2 genes and higher loss of electrolytes (Figure 3A–C). Collectively, these results indicate that the AtNIGR1 gene negatively regulates resistance mediated by the R gene.

3.4. AtNIGR1 Negatively Regulates Systemic Acquired Resistance

A number of SAR-associated signals have been identified so far. These include salicylic acid and its methylated derivative MeSA, azelaic acid (AZA), and glycerol-3-phosphate dehydrogenase (G3Pdh). To determine the possible role of NO-downregulated AtNIGR1 in SAR activation, we studied the expression of AtPR1, AtPR2, AtG3Pdh, and AtAZI genes in systemic leaves. For this purpose, we inoculated atnigr1 (KO) and AtNIGR1 (OE), plants along with Col-0 (WT), atgsnor1–3, and atsid2, with Pst DC3000 avrB. All of the genotypes used in this investigation had a Col-0 genetic background. Col-0 was used as a wild-type (WT) control, while the atgsnor1–3 and atsid2 mutant lines were used as susceptible controls for biotic stress. After 6, 12, and 24 h, the transcript accumulation of AtPR1, AtPR2, AtG3Pdh, and AtAZI genes was significantly higher and lower in the atnigr1 (KO) and AtNIGR1 (OE) plants of the AtNIGR1 gene as compared to that in the Col-0 WT (Figure 4A–D).

3.5. In Silico Characterization, Gene Ontology, Predicted Organ-Specific Expression, and Homology

Prior to conducting biological assays that attempted to investigate the role of AtNIGR1 in plant defense and oxidative and nitro-oxidative stress, we were interested in uncovering the basic biological processes, as well as predictive molecular functions, in which AtNIGR1 may be involved. It was interesting to see that gene ontology (GO) analysis proposed AtNIGR1 to be involved in the chlorophyll biosynthetic process and response to light stimulus (biological process) (Figure S2A). In addition, Figure S2B suggests that AtNIGR1 would be associated with nucleotide binding (molecular function). Figure S2C indicates that AtNIGR1 could be located in the cytosol and nucleus.

Furthermore, Figure S3 indicates that the oxidoreductase NAD(P)-binding Rossman fold protein is encoded by many other genes in other plant species, including Musa acuminate ssp. malaccensis, rice, Triticeae, Malvaceae, etc. Of all species, AtNIGR1 is suggested to be closer to its ortholog in Brassica.

Moreover, the prediction of organ-specific expression analysis (eFP browser, TAIR) suggests AtNIGR1 expression in almost all shoot components of the plant to varying degrees. However, the highest expression is proposed in germinating seeds, followed by the cotyledonary leaves, vegetative rosette leaves, and rosette leaves after flowering. Significant expression was also observed in the siliques (Figure S4).

3.6. In Silico Prediction of Protein Interaction and S-Nitrosylation Sites

The prediction of protein–protein interaction proposes possible interactions of AtNIGR1 with other proteins, including the Mevalonate/galactokinase family protein GALK, Galacturonic acid kinase GalAK, arabinose kinase ARA1, putative xylulose kinase XK-2, GroES-like zinc-binding alcohol dehydrogenase, and various Glyceraldehyde-3-phosphate dehydrogenases (GAPs) (Figure 5A and

Table 1. Predicted functional partners of AtNIGR1.

Symbols	Full Name	Score
GALK	Mevalonate/galactokinase family protein	0.829
GalAK	Galacturonic acid kinase	0.829
AT3G42850	Mevalonate/galactokinase family protein	0.829
ARA1	Arabinose kinase; Arabinose kinase	0.829
AT5G18200	UDP glucose-hexose-1-1-phosphate uridylyltransferase	0.689
XK-2	Putative xylulose kinase	0.671
GAPA-2	Glyceraldehyde-3-phosphate dehydrogenase (NADP+) (phosphorylating)	0.653
AT5G51970	GroES-like zinc-binding alcohol dehydrogenase family protein	0.649
GAPB	Glyceraldehyde-3-phosphate dehydrogenase (NADP+) (phosphorylating)	0.639
GAPA	Glyceraldehyde-3-phosphate dehydrogenase (NADP+) (phosphorylating)	0.630

). In addition, the prediction of potential S-nitrosylated sites allowed us to predict that the cysteine residues Cys-225 and Cys-359 may be exposed with a high probability of being S-nitrosylated (Figure 5B and

Table 2. Cysteine molecules predicted as potential targets for S-nitrosylation.

Position	Peptide	Score	Cut Off	Cluster
225	SVGTILSCTASLQFG	2.647	2.454	Cluster B
359	KKSVDIGCEVVHL	21.547	20.743	Cluster C

). C225 was found to be located in the middle of Cluster B, whereas C359 was located at the end of Cluster C.

4. Discussion

4.1. NO-Downregulated AtNIGR1 Gene Negatively Regulates Root and Shoot Lengths of A. thaliana

Nitric oxide (NO) is important in diverse cellular activities and biological processes, including plant growth and development, and responses to biotic stress [8,9,11]. Microarrays [27], RNA-seq [19], and qPCR [28] have helped reveal changes in transcript accumulation at a genome-wide level in response to NO. Under normal conditions, plants allocate their energy to the growth and development process. However, in the event of stress, plants tend to redirect their resources to trigger the defense mechanisms, which may result in delayed or reduced growth. On the one hand, our data showed that atnigr1 plants exhibited longer roots and higher shoot heights compared to the WT under normal, oxidative, and nitro-oxidative stress conditions. On the other hand, plants overexpressing the AtNIGR1 had shorter roots and shoot lengths than Col-0 WT (Figure 1A–C). The observed differences in root and shoot growth between the atnigr1 (KO) and AtNIGR1 (OE) of the AtNIGR1 gene (Figure 1) suggest that the NO-downregulated AtNIGR1 gene may play a role in regulating plant growth processes.

4.2. NO-Downregulated AtNIGR1 Gene Negatively Regulates Basal Defense, R-Gene-Mediated Resistance, and SAR of A. thaliana

Different genotypes exposed to a particular pathogen are expected to exhibit different phenotypic responses toward that pathogen [1,17]. Within the plant, a wide range of defense mechanisms and signaling networks are induced to defend the plant. Sensitive genotypes are likely to show severe damage compared to resistant ones, in part, due to the presence or activation of several defense factors that trigger the innate immune system [29,30]. Here, we inoculated the atnigr1 (KO) plants and those overexpressing the AtNIGR1 gene to assess their phenotypic response toward a bacterial pathogen, along with the Col-WT and the disease-susceptible mutant lines, atgsnor1–3 and atsid2. Therefore, the observed enhanced resistance of the atnigr1 (KO) line and the susceptibility of the AtNIGR1 (OE) line (Figure 2A,B) following Pst DC3000 vir inoculation, coupled with the pathogenic growth suggests that the AtNIGR1 gene would act as a negative regulator of plant basal defense against bacterial pathogens. The negative regulation of plant basal dense by the NO-downregulated AtNIGR1 gene was further confirmed via the transcript accumulation of AtPR1 and AtPR2 genes. The results showed that after inoculating the Pst DC3000 vir bacteria, in comparison to that in the Col-0 WT, the expression of AtPR1 and AtPR2 genes significantly increased and decreased in the atnigr1 (KO) and AtNIGR1 (OE) plants, respectively (Figure 2C,D). Therefore, we could then suggest that AtNIGR1 would be involved in the negative regulation of basal defense in Arabidopsis.

To explore the role of the NO-downregulated AtNIGR1 gene in the R-gene-mediated resistance of A. thaliana, the plants were inoculated with Pst DC3000 avrB. The results showed that after inoculating the pathogenic bacteria, in comparison to that in Col-0 WT, the expression of AtPR1 and AtPR2 genes significantly increased and decreased in the atnigr1 (KO) and AtNIGR1 (OE) plants, respectively (Figure 3A,B). Furthermore, electrolyte leakage experiments showed that the atnigr1 (KO) and AtNIGR1 (OE) plants had lower and higher electrolyte leakage over time than the Col-0 WT plants (Figure 3C). The current study hypothesized that the NO-downregulated AtNIGR1 gene negatively regulates R-gene-mediated resistance based on the results of transcript accumulation of AtPR1 and AtPR2 genes and electrolyte leakage. The NO-downregulated AtNIGR1 negatively regulates systemic acquired resistance in plants.

Plants, like other multicellular organisms, have established an intrinsic mechanism to systemically communicate the occurrence of a wound or an external stimulus to enable them to escape or defend themselves [31]. During pathogen attacks, signaling in plants is critical for triggering the required defense mechanisms to counteract the stress. However, one of the plant’s responses to pathogen infection is the production of long-term constitutive barriers known as SAR [4,32], which is characterized by the activation of a wide range of host defense mechanisms, both on a local and systemic level [32,33]. We found that after inoculating Pst DC3000 avrB, the expression of AtPR1, AtPR2, AtG3Pdh, and AtAZI genes was enhanced at all-time points in the atnigr1 (KO) plants compared to that in the Col-0 WT and the disease-susceptible controls (atgsnor1–3 and atsid2 plants) (Figure 4). However, at all-time points, the transcript accumulation of AtPR1, AtPR2, AtG3Pdh, and AtAZI genes in the OE of the AtNIGR1 gene was significantly reduced in comparison to that in the Col-0 WT (Figure 4). Therefore, the current investigation suggests that the NO-downregulated gene AtNIGR1 negatively regulates SAR in Arabidopsis in response to the inoculation of Pst DC3000 avrB.

Furthermore, relying on the predicted putative protein–protein interaction network (Figure 5A and Table 1), we could say that the regulatory role of the NO-downregulated AtNIGR1 gene might involve active interaction with many other proteins that may antagonize or work in synergy during a bacterial pathogen infection.

5. Conclusions

Plant responses to pathogenic attacks include activating various signaling networks and metabolic pathways to equip the plant with a robust defense system. In the process, both positive and negative regulators are either induced or suppressed, and their interaction is crucial to ensure balanced cellular activity. The current study investigated the role of the AtNIGR1 gene in plant growth and development, as well as under oxidative and nitro-oxidative stress conditions. In addition, the involvement of the AtNIGR1 gene in plant basal defense, R-gene-mediated defense, or systemic acquired resistance (SAR) was assayed. Based on the recorded enhanced resistance of atnigr1 (KO) and the susceptible response of the AtNIGR1 (OE), coupled with differential transcript accumulation patterns of PR-related genes (AtPR1 and AtPR1, as well as that of the SAR-related genes (AtAZI and AtG3Pdh) in the target mutant lines, AtNIGR1 is here proposed to negatively regulate the plant basal defense, R-gene-mediated resistance, and SAR in response to pathogenic bacteria. To gain further insight into the role of AtNIGR1, additional experiments, such as in vitro protein–protein interaction studies and promoter analysis, could be conducted. These experiments would provide a more detailed understanding of the specific mechanisms by which AtNIGR1 operates and its potential as a target for stress adaptation in plants.