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2024 Volume 4
Article Contents
Abstract
Introduction
Materials and methods
Plant materials
Protein extraction
Trypsin digestion
Affinity enrichment of ubiquitinated peptides
LC-MS/MS and data analysis
Bioinformatics methods
Results
Overview of the ubiquitomic analysis
Properties of ubiquitinated proteins and motifs
A temperature-regulated rice endosperm ubiquitome
Functions for differentially expressed ubiquitinated proteins
Discussion
Ubiquitination of heat shock proteins and transcription factors under high-temperature stress
Sucrose and starch metabolism are modified by ubiquitination under high-temperature stress
Ubiquitination affects sucrose hydrolysis
Ubiquitination of ADP-glucose pyrophosphorylase (AGPase)
Ubiquitination regulates amylose biosynthesis
Ubiquitination regulates amylopectin biosynthesis
Ubiquitination affects ribosomal systems under high-temperature stress
Author contributions
Data availability
Acknowledgments
Conflict of interest
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References
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ARTICLE   Open Access    

Identification of Ralstonia solanacearum resistant solanum plants as potential rootstock to manage bacterial wilt disease in tomato production

  • 1.

    Plant Health Division, CSIR-Crops Research Institute, Kumasi, Ghana

  • 2.

    Horticulture Division, CSIR-Crops Research Institute, Kwadaso, Ghana

  • 3.

    Biotechnology, Seed and Post-Harvest Division, CSIR-Crops Research Institute, Kumasi, Ghana

  • 4.

    CSIR- Soil Research Institute, Kwadaso, Ghana

  • 5.

    Allium Vegetable Research Institute-National Institute of Horticulture and Herbal Science, Vegetable Research Institute, Muan-gun, Republic of Korea

More Information
  • Using morphological and molecular markers, this study screened tomato (Solanum lycopersicum) and garden egg (Solanum melongena) accessions for resistance to bacterial wilt disease. The solanum plants were inoculated with Ralstonia solanacearum and evaluated for disease incidence and severity in a field trial set up in a Randomised Complete Block Design with four replications. Molecular markers conferring resistance to R. solanacearum Phylotype I and II were used to identify durable and partial resistance. Results showed significant variation in disease incidence and severity among accessions, with tomato accessions exhibiting higher susceptibility. Accession CRI-01 had the highest disease incidence (54.0%), while accession GD had the lowest (13.0%). Accession CRI-04 showed moderate resistance with a disease severity index of 0.37, while accession GC had the highest disease severity index (0.90). Accession L_020 demonstrated moderate resistance in the field (43.0% disease incidence) and possessed durable resistant genes, making it a promising rootstock for managing bacterial wilt disease in tomato production. This research contributes to the development of integrated pest management strategies for sustainable tomato production.

  • Introduction

    Rice (Oryza sativa L.) is a world staple crop that feeds over half of the world's population[1,2]. In recent years, high-temperature events are becoming more frequent and intensive as a result of global warming, which can severely affect rice grain yield and quality[3,4]. During flowering and grain filling stages, high-temperature stress can result in a significant reduction in seed setting rate and influence amylose content, starch fine structure, functional properties and chalkiness degree of rice[5−7]. Transcriptome and proteome analysis in rice endosperm have also been used to demonstrate the differences in high-temperature environments at gene and protein expression levels[8−10]. In addition, as an important post-translational modification, protein phosphorylation has proven to be involved in the regulation of starch metabolism in response to high-temperature stress[11]. However, little is known about whether protein ubiquitination regulates seed development under high-temperature stress.

    Ubiquitination is another form of post-translational modification that plays key roles in diverse cellular processes[12]. Several reports have described the functions of ubiquitination in rice defense responses based on ubiquitome analysis. Liu et al.[13] investigated relationships between ubiquitination and salt-stress responses in rice seedlings using a gel-based shotgun proteomic analysis and revealed the potential important role of protein ubiquitination in salt tolerance in rice. Xie et al.[14] identified 861 peptides with ubiquitinated lysines in 464 proteins in rice leaf cells by combining highly sensitive immune affinity purification and high resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS). These ubiquitinated proteins regulated a wide range of processes, including response to stress stimuli. A later study revealed the relationships between ubiquitination status and activation of rice defense responses, and generated an in-depth quantitative proteomic catalog of ubiquitination in rice seedlings after chitin and flg22 treatments, providing useful information for understanding how the ubiquitination system regulates the defense responses upon pathogen attack[15]. Although many studies have shown that ubiquitination plays improtant roles in the heat response of plant[16,17], there has been little systematic discussion on the ubiquitome of rice endosperm in the context of global climate change.

    In this study, we examine the high-temperature induced ubiquitination change in two rice varieties with different starch qualities, through a label-free quantitative ubiquitome analysis. This study provides a comprehensive view of the function of ubiquitination in high-temperature response of rice developing seed, which will shed new light on the improvement of rice grain quality under heat stress.

    Materials and methods

    Plant materials

    Two indica rice varieties with different starch quality, 9311 and Guangluai4 (GLA4), were used as materials. 9311 is a heat-sensitive variety, which displays low amylose content with good starch quality; while GLA4 is known to be the parental variety of HT54, an indica breeding line with heat tolerance, and thus GLA4 is possibly heat tolerant, which shows high amylose content with poor starch quality[18,19]. Rice growth conditions, sample treatment and collection were conducted as previously described[11].

    Protein extraction

    Husk, pericarp and embryo were detached from immature rice grains on ice[20]. Rice endosperm was then ground with liquid nitrogen, and the cell powder was sonicated 10 rounds of 10 s sonication and 15 s off-sonication on ice in lysis buffer (6 M Guanidine hydrochloride, pH 7.8−8.0, 0.1% Protease Inhibitor Cocktail) using a high intensity ultrasonic processor. Following lysis, the suspension was centrifuged at 14,000 g for 40 min at 4 °C to remove the debris. The supernatant was collected, and the protein concentration was estimated using BCA assay (Pierce BCA Protein assay kit, Thermo Fisher Scientific, Waltham, MA, USA) before further analysis.

    Trypsin digestion

    The protein mixture was reduced by DTT with the final concentration of 10 mM at 37 °C for 1 h, alkylated by iodoacetamide with a final concentration of 50 mM at room temperature in the dark for 0.5 h, and digested by trypsin (1:50) at 37 °C for 16 h. Then the sample was diluted by adding trifluoroacetic acid (TFA) to the final concentration of 0.1%. The enzymatic peptides were desalted on a Sep-Pak C18 cartridge (Waters, Milford, MA, USA), concentrated by lyophilization and reconstituted in precooled IAP buffer (50 mM MOPS-NaOH PH 7.2, 10 mM Na2HPO4, 50 mM NaCl) for further analysis.

    Affinity enrichment of ubiquitinated peptides

    The peptides solution was incubated with prewashed K-ε-GG antibody beads (PTMScan Ubiquitin Remnant Motif (K-ε-GG) Kit), and gently shaken at 4 °C for 1.5 h. The suspension was centrifuged at 2,000 g for 30 s, and the supernatant was removed. The Anti-K-ε-GG antibody beads were washed with IAP Buffer three times and with ddH2O three times. The peptides were eluted from the beads with 0.15% trifluoroacetic acid (TFA). Finally, the eluted fractions were combined and desalted with C18 Stage Tips.

    LC-MS/MS and data analysis

    LC-MS/MS analysis were performed using the methods of Pang et al.[11]. Raw mass spectrometric data were analyzed with MaxQuant software (version 1.3.0.5) and were compared with the indica rice protein sequence database (Oryza sativa subsp. indica-ASM465v1). Parameters were set according to Pang et al.[11]. All measurements were obtained from three separate biological replicates.

    Bioinformatics methods

    Quantification of the modified peptides was performed using the label-free quantification (LFQ) algorithm[11]. Differentially ubiquitinated sites (proteins) in response to high-temperature were identified by Student's t-test (p < 0.05, log2(fold-change) > 1) with at least two valid values in any condition or the ubiquitination sites that exhibited valid values in one condition (at least two of three replicates) and none in the other.

    Subcellular localization was performed using CELLO database (http://cello.life.nctu.edu.tw). Gene Ontology (GO) annotation proteome was derived from the AgriGO (http://bioinfo.cau.edu.cn/agriGO/). The differential metabolic profiles were visualized with MapMan software (version 3.6.0RC1). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation was performed by using KEGG Automatic Annotation Server (KAAS) software. A p-value of < 0.05 was used as the threshold of significant enrichment. SWISS-MODEL was used to generate the tertiary structure of GBSSI (SWISS-MODEL, http://swissmodel.expasy.org/). The figures were annotated with Adobe Illustrator (Adobe Systems, San Jose, CA, USA).

    Results

    Overview of the ubiquitomic analysis

    To elucidate how high-temperature stress influences rice developing endosperm at the ubiquitination level, a label-free analysis was performed to quantify ubiquitome from two indica rice varieties under normal (9311-C and GLA4-C) and high-temperature conditions (9311-H and GLA4-H). The distribution of mass error of all the identified peptides was near zero and most of them (71.5%) were between -1 and 1 ppm, suggesting that the mass accuracy of the MS data fits the requirement (Fig. 1a). Meanwhile, the length of most peptides distributed between 8 and 42, ensuring that sample preparation reached standard conditions (Fig. 1b).

    Figure 1.  Characteristics of the ubiquitinated proteome of rice endosperm and QC validation of MS data. (a) Mass error distribution of all identified ubiquitinated peptides. (b) Peptide length distribution. (c) Frequency distribution of ubiquitinated proteins according to the number of ubiquitination sites identified.
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    In all endosperm samples, a total of 437 ubiquitinated peptides were identified from 246 ubiquitinated proteins, covering 488 quantifiable ubiquitinated sites (Supplemental Table S1). Among the ubiquitinated proteins, 60.6% had only one ubiquitinated lysine site, and 18.7%, 8.1%, 5.3%, or 7.3% had two, three, four, or five and more ubiquitinated sites, respectively. In addition, four proteins (1.6%, BGIOSGA004052, BGIOSGA006533, BGIOSGA006780, BGIOSGA022241) were ubiquitinated at 10 or more lysine sites (Fig. 1c, Supplemental Table S1). The proteins BGIOSGA008317 had the most ubiquitination sites with the number of 16. It was noted that besides ubiquitin, two related ubiquitin-like proteins NEDD8 and ISG15 also contain C-terminal di-Gly motifs generated by trypsin cleavage, and the modifications of these three proteins cannot be distinguished by MS[21]. Here, the di-Gly-modified proteome therefore represents a composite of proteins modified by these three proteins. However, the sites from NEDD8 or ISG15 modifications were limited because they mediate only a few reactions in cells[21].

    Properties of ubiquitinated proteins and motifs

    To better understand the lysine ubiquitome changes in rice endosperm induced by high-temperature, we performed a Gene Ontology (GO) functional annotation analysis on all identified ubiquitinated proteins (Fig. 2a). In the biological process GO category, 'metabolic process' and 'cellular process' were mainly enriched, accounting for 75.1% and 74.1% of ubiquitinated proteins, respectively. In addition, 34.6% proteins were associated with 'response to stimulu', emphasizing the regulatory role of ubiquitination modification in response to high-temperature stress. From the cellular component perspective, ubiquitinated proteins were mainly associated with 'cellular anatomical entity' (99.4%), 'intracellular' (84.4%) and 'protein-containing complex' (29.9%). The molecular function category result suggested that these proteins were largely involved in 'binding' (62.7%), 'catalytic activity' (43.4%) and 'structural molecule activity' (16.5%). Furthermore, subcellular location annotation information indicated that 34.7%−39.4% proteins were located in the cytoplasm, and other were mostly located in the nucleus (23.5%−27.7%), plasma membrane (9.4%−11.4%), and chloroplast (9.6%−12.8%) (Fig. 2b). It is noteworthy that the ubiquitinated proteins located in the cytoplasm were decreased in high-temperature environments in both varieties.

    Figure 2.  Analysis of ubiquitinated proteins and motifs. (a) Gene ontology (GO) functional characterization of ubiquitinated proteins. (b) Subcellular localization of ubiquitinated proteins. From the inside out, the ring represents 9311-C, 9311-H, GLA4-C and GLA4-H, respectively. (c) Motif enrichment analysis of ubiquitinated proteins.
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    The following two significantly enriched motifs from all of the identified ubiquitinated sites were identified using MoDL analysis: [A/S]xKub and Kubxx[E/Q/R/V]x[E/G/L/P/Q/R/Y], which covered 84 and 100 sequences, respectively (Fig. 2c). Further analysis showed that the conserved alanine (A) and glutamic acid (E) were included in upstream and downstream of the ubiquitinated lysine sites in rice endosperm. A similar phenomenon also occurred in rice leaf[14], wheat leaf[22], and petunia[23], indicating that alanine (A) and glutamic acid (E) were likely to be the specific amino acids in conserved ubiquitination motifs in plants. Additionally, serine (S) was enriched at the position -2 (upstream) of the ubiquitinated lysine, while various amino acids such as arginine (R), glutamic acid (E), glutamine (Q), valine (V) were found at positions +3 and +5 (downstream).

    A temperature-regulated rice endosperm ubiquitome

    To detect possible changes in rice endosperm ubiquitome attributable to high-temperature stress, we then performed LFQ analysis on all quantifiable ubiquitination sites within our dataset. As shown in Fig. 3a, more ubiquitinated proteins, peptides and sites were detected in the treatment groups (9311-H and GLA4-H), suggesting that exposure to high-temperature stress may increase the ubiquitination events in rice endosperm. Only 282 common ubiquitinated sites in 158 proteins were quantifiable for all sample groups due to reversible ubiquitination induced by high-temperature (Fig. 3b). Principal component analysis (PCA) showed that three repeats of each sample clustered together, and four groups were clearly separated (Fig. 3c). Furthermore, the differentially expression profiles of ubiquitination sites (proteins) in 9311 and GLA4 under high-temperature stress were depicted to further understand the possible changes (Fig. 3d). Where LFQ values were missing, the data were filtered to identify those ubiquitination sites with a consistent presence/absence expression pattern. These analyses yielded 89 ubiquitination sites that were only present in 9311-H and six that were only present in 9311-C (Fig. 3d, Supplemental Table S2). Similarly, 51 differentially expressed ubiquitination sites were present in GLA4-H and 13 ubiquitination sites only occurred in GLA4-C (Fig. 3d & Supplemental Table S3). Beyond that, a total of 113 and 50 significantly changed ubiquitination sites (p < 0.05, log2(fold-change) >1) were screened out in 9311 and GLA4, respectively (Fig. 3d, Supplemental Tables S4 & S5). For subsequent comparative analysis, the ubiquitination expression profiles with consistent presence/absence and ubiquitination sites with significant differences in statistical testing were combined and named as 9311-Up, 9311-Down, GLA4-Up, and GLA4-Down, respectively (Fig. 3d). The number of significantly up-regulated ubiquitination sites was far greater than down-regulated ubiquitination sites in both 9311 and GLA4 varieties. These findings indicated that high temperature not only induced the occurrence of ubiquitination sites, but also significantly upregulated the intensity of ubiquitination. Beyond that, the magnitude of the up-regulation in 9311 was higher than that in GLA4 (Fig. 3b & d), indicating that the ubiquitination modification of heat-sensitive varieties was more active than heat-resistant varieties in response to high-temperature stress.

    Figure 3.  A temperature regulated rice endosperm ubiquitome. (a) The number of ubiquitinated proteins, peptides and sites detected in four group samples. (b) Venn diagram of ubiquitination sites (proteins) detected in four group samples. (c) PCA based on ubiquitination intensity across all four sample groups with three biological repetitions. (d) Differentially expression profiles of ubiquitination sites (proteins) in 9311 and GLA4 under high-temperature stress. The expression profiles of selected ubiquitination sites (p < 0.05, log2(fold-change) >1) were normalized using the Z-score and presented in a heatmap.
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    To further investigate the ubiquitination regulatory pattern under high temperature stress in two varieties, four groups with significantly regulated sites were analyzed. There were 37 ubiquitination sites showed the same regulatory trend in 9311 and GLA4, accounting for 17.8% and 32.5% of the total differentially expressed sites in 9311 and GLA4, respectively. Among them, 36 ubiquitination sites were upregulated and one site was downregulated (Fig. 4a). In addition, 159 upregulated ubiquitination sites and three downregulated sites were only present in 9311, while 53 upregulated sites and 15 downregulated sites were only present in GLA4. Moreover, nine ubiquitination sites showed opposite regulatory trends in 9311 and GLA4. A similar regulatory trend of ubiquitination proteins is shown in Fig. 4b. It is noted that some proteins had both upregulated and downregulated ubiquitination sites (Supplemental Tables S6 & S7), indicating that significant differences in ubiquitination were, to some extent, independent of protein abundance.

    Figure 4.  Comparison of differentially ubiquitinated sites and proteins in 9311 and GLA4 under high-temperature stress.
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    Functions for differentially expressed ubiquitinated proteins

    To understand the function of ubiquitination in response to the high-temperature stress of rice endosperm, we conducted GO enrichment-based clustering analysis of the differentially ubiquitinated proteins in 9311 and GLA4 at high temperature, respectively (Fig. 5). In the biological process category of 9311, proteins were relatively enriched in the carbohydrate metabolic process, polysaccharide metabolic process, starch biosynthetic process, cellular macromolecule localization, protein localization, intracellular transport, and phosphorylation (Fig. 5). For the molecular function analysis, we found that the proteins related to kinase activity, nucleotidyltransferase activity, phosphotransferase activity, and nutrient reservoir activity were enriched (Fig. 5). The two principal cellular components were intrinsic component of membrane and integral component of membrane (Fig. 5). There was no significantly enriched GO term in the GLA4 group due to the dataset containing relatively few proteins, and thus, further enrichment analysis was conducted on the proteins that were common to both varieties. The results showed that proteins were over-represented in carbon metabolism, including starch biosynthesis and metabolism, glucan biosynthesis and metabolism, and polysaccharide biosynthesis and metabolism (Fig. 5), indicating the importance of carbohydrate synthesis and metabolism in the ubiquitination regulatory network.

    Figure 5.  Enrichment analysis of differentially expressed ubiquitinated proteins based on Gene Ontology (GO) terms.
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    To identify pathways which were differentially ubiquitinated under high-temperature stress, the KEGG pathway-based clustering analysis was conducted. The results showed that the differentially ubiquitinated proteins in both 9311 and GLA4 were mostly abundant in the pathways of carbohydrate metabolism, starch and sucrose metabolism, folding, sorting and degradation, translation, ribosome, and protein processing in endoplasmic reticulum (Fig. 6a). In the 9311 group, the pathways of carbohydrate metabolism, starch and sucrose metabolism, glycosyltransferases, glycolysis, and energy metabolism were enriched in the differentially ubiquitinated proteins (Fig. 6b); while there was no significantly enriched KEGG pathway in the GLA4 group. We further found the proteins that were common to both varieties were only significantly enriched in the starch and sucrose metabolism pathways (p = 0.04). The ubiquitination proteins involved in the starch and sucrose metabolism mainly include: sucrose hydrolysis (SUS, FK, UGPase), and starch synthesis (AGPase, GBSSI, BEI, BEIIb, PUL, PHO1), which are discussed below.

    Figure 6.  KEGG classification and enrichment analysis of differentially ubiquitinated proteins. (a) Number of differentially ubiquitinated proteins based on KEGG classification in 9311 and GLA4. (b) KEGG enrichment analysis of differentially ubiquitinated proteins in 9311.
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    Discussion

    Although many reports have described specific examples of ubiquitination in rice defense responses[13,15,16], our knowledge on global changes in the developing endosperm ubiquitome under high-temperature stress is still lacking. In this study, a label-free quantitative proteomic analysis of ubiquitination was applied to examine the high-temperature induced ubiquitination change of two indica rice varieties (9311 and GLA4) with distinct starch quality. We identified many new lysine modification sites on proteins involved in various pathways, highlighting the complexity of the ubiquitination-mediated regulatory system in high-temperature stress responses in rice.

    Ubiquitination of heat shock proteins and transcription factors under high-temperature stress

    Heat shock proteins accumulate under various stresses and play important roles in plant defenses against abiotic stresses[24,25]. Research has shown that a number of heat shock proteins were prominent in the rice ubiquitome network, of which OsHSP71.1, and OsHSP82A showed increased ubiquitination levels under chitin and flg22 treatment[15]. Here, seven lysine residues on five heat shock proteins possessed ubiquitination modification in rice endosperm. Three sites (BGIOSGA011420-K78, BGIOSGA026764-K99, BGIOSGA029594-K106) showed significant up-regulation in 9311 under high-temperature stress, while in GLA4, the ubiquitination level of BGIOSGA011420-K78 was down-regulated. This differential ubiquitination of heat-tolerant and heat-sensitive varieties provided a basis for studying the regulation of post-translational modification of heat shock proteins under high-temperature stress, despite the regulatory role of those heat shock proteins being still unclear.

    Transcription factors (TFs) play an essential role in the regulation of gene expression. A total of three transcription factors were identified in the ubiquitination dataset, of which two were NAC family members. As one of the largest plant-specific TF families, NAC is involved in the responses to abiotic and biotic stresses[26]. The ubiquitination modification of K173 in BGIOSGA018048 was specifically expressed in the 9311-H group, which may affect the stress resistance level in high-temperature environments. In addition, two sites K148 and K149 of ERF TF family member BGIOSGA024035 was downregulated in GLA4 under high-temperature stress. This differential ubiquitination was likely to affect the expression of related genes regulated by this transcription factor.

    Sucrose and starch metabolism are modified by ubiquitination under high-temperature stress

    Ubiquitination affects sucrose hydrolysis

    The results of GO and KEGG enrichment analysis of differential ubiquitination proteins indicated that the sucrose and starch metabolic pathway was largely affected by ubiquitination regulation under high-temperature stress (Figs 5 & 6). The ubiquitination sites involved in sucrose and starch metabolism are listed in Table 1. To assess how high-temperature stress affects the crucial pathway, the significantly differential ubiquitination sites in 9311 and GLA4 were displayed in the heatmap of specific proteins (Fig. 7).

    Table 1.  Ubiquitination sites related to sucrose and starch metabolism in rice endosperm.
    Gene nameAnnotationProtein entryModification site(s)
    SUS1Sucrose synthase 1BGIOSGA010570K172, K177
    SUS2Sucrose synthase 2BGIOSGA021739K160, K165, K176, K804
    SUS3Sucrose synthase 3BGIOSGA026140K172, K177, K541, K544, K588
    FKFructokinaseBGIOSGA027875K143
    UGPaseUDP-glucose pyrophosphorylaseBGIOSGA031231K27, K150, K303, K306
    AGPS1ADP-glucose pyrophosphorylase small subunit 1BGIOSGA030039K94, K464, K484
    AGPS2ADP-glucose pyrophosphorylase small subunit 2BGIOSGA027135K106, K132, K385, K403, K406, K476, K496
    AGPL2ADP-glucose pyrophosphorylase large subunit 2BGIOSGA004052K41, K78, K134, K191, K227, K254, K316, K338, K394, K396, K463, K508, K513
    AGPL3ADP-glucose pyrophosphorylase large subunit 3BGIOSGA017490K509
    GBSSIGranule bound starch synthase IBGIOSGA022241K130, K173, K177, K181, K192, K258, K371, K381, K385, K399, K462, K517, K530, K549, K571, K575
    BEIStarch branching enzyme IBGIOSGA020506K103, K108, K122
    BEIIbStarch branching enzyme IIbBGIOSGA006344K134
    PULStarch debranching enzyme:PullulanaseBGIOSGA015875K230, K330, K431, K736, K884
    PHO1Plastidial phosphorylaseBGIOSGA009780K277, K445, K941
     | Show Table
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    Figure 7.  Sucrose and starch pathway at the ubiquitination levels in rice endosperm under high-temperature stress.
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    In cereal endosperm, sucrose is the substrate for the biosynthesis of starch. The formation of glucose 1-phosphate (G1P, used in starch synthesis, see below) from sucrose requires a series of enzymes[27]. Here, we found that sucrose synthase 1 (SUS1), SUS2, SUS3, fructokinase (FK), and UDP-glucose pyrophosphorylase (UGPase) were ubiquitinated among all sample groups (Table 1, Fig. 7). In the ubiquitome of seedling and leaf in japonica rice, ubiquitination sites have been found in SUS1, SUS2, UGPase, and FK, which were related to sucrose hydrolysis[14,15]. SUS catalyzed the process of cleaving sucrose into UDP-glucose (UDPG) and fructose. Two ubiquitination sites, K172 and K177, were identified in SUS1 in rice endosperm, which were also found in rice leaves[14]. A total of four ubiquitination sites were identified in SUS2, two of which were also reported in rice seedling and leaf, indicating the conservation of the lysine residues in different rice tissues. It was noted that all four ubiquitination sites in SUS2 were upregulated in high-temperature environments, although the regulated sites of 9311 and GLA4 were different. In 9311, the ubiquitination levels of K160, K174, and K804 were increased, while GLA4 was only upregulated in K176. The ubiquitination sites K541, K544, and K588 in SUS3 were screened from developing rice seeds for the first time. In addition, SUS3 had two completely overlapping sites K172 and K177 with SUS1, and it was difficult to determine which enzymes the two sites belonged to. The ubiquitination levels of SUS3-K541 and SUS3-K544 in 9311 significantly increased in high-temperature environments, while there was no significant difference in the ubiquitination level of SUS3 in GLA4. Overall, the ubiquitination sites of SUS in rice endosperm were located in the functional domain except for SUS2-K804, reflecting the importance of ubiquitination regulation in SUS.

    UGPase catalyses the conversion of glucose 1-phosphate and UTP into UDPG[28]. Research has shown that the mutation of UGPase gene lead to chalky endosperm[29]. As shown in Table 1, four ubiquitination sites K27, K150, K303, and K306 were identified in rice endosperm, which were completely inconsistent with the seven ubiquitination sites in rice seedlings and two in leaves[14,15], reflecting the tissue specificity. We speculated that the UGPase with different modification sites may play different regulatory roles in metabolic pathways in different tissues. Under high-temperature stress, the ubiquitination level of UGPase-K27 was 8.1-fold up-regulated. Liao et al.[10] demonstrated that the expression of UDPase was down-regulated in both heat-tolerant and heat-sensitive rice lines under high temperature conditions, which could reasonably explain the significant up-regulation of UGPase-K27 ubiquitination level. The ubiquitination site K143 of FK was also reported in seedling tissues[15].

    Ubiquitination of ADP-glucose pyrophosphorylase (AGPase)

    The AGPase reaction represents the first committed step of starch biosynthesis[27]. A total of 22 lysine ubiquitination sites were identified in four AGPase subunits (AGPL2, AGPL3, AGPS1, AGPS2). AGPL2 had 13 ubiquitination sites, of which six were located in NTP_transferase domain, including K254, K338, K191, K134, K227, and K316. High-temperature stress resulted in an increase in the ubiquitination level of K254 in both 9311 and GLA4, and significant upregulation of K508 and K513 in 9311, as well as K191, K227, and K316 in GLA4. In contrast, AGPL2-K394 were significantly downregulated in GLA4. AGPL3 contained one ubiquitination site K509, and the modification level of AGPL3-K509 was up-regulated in high-temperature environments in 9311. AGPS1 had one specific ubiquitination site K464 and another two sites K94 and K484 that completely overlapped with AGPS2-K106 and AGPS2-K496, respectively. The modification levels of K464 and K484 significantly increased in high-temperature environments in 9311, and K94 was significantly up-regulated in both varieties. There were seven ubiquitination sites in AGPS2 in rice endosperm, which were different with the sites found in rice leaves[14]. In addition to the two sites that overlapped with AGPS1, AGPS2 had another two ubiquitination sites (K406 and K132) that upregulated in high-temperature environments.

    Ubiquitination regulates amylose biosynthesis

    Amylose content is one of the key determinants that strongly influence rice grain quality[30]. The biosynthesis of amylose requires the catalytic effect of granule-bound starch synthase I (GBSSI)[30,31]. Here, a total of 16 ubiquitination sites were identified in GBSSI (Table 1, Fig. 8a). Among these ubiquitination sites, six lysine residues (K130, K173, K177, K181, K192, K258) were located in glycosyltransferase 5 (GT5) domain, and three sites (K399, K462, K517) were located in GT1 domain (Fig. 6), indicating the important role of ubiquitination regulation of GBSSI. Under high-temperature stress, the ubiquitination levels of six sites (K130, K177, K399, K381, K385, K549) increased in two indica rice varieties, while one sites (K258) showed downregulation in 9311 (Fig. 8a). Numerous studies had described that the amylose content was reduced under high-temperature stress in rice[5,7], which might be due to the degradation of GBSSI proteins caused by the increased significantly up-regulated ubiquitination sites. These ubiquitination sites identified in rice GBSSI with significant differences under high-temperature stress were expected to become a new breakthrough point for the improvement of starch quality.

    Figure 8.  Structure of GBSSI. (a) Domain structure of GBSSI and ubiquitination sites with significant differences in response to high-temperature stress. (b) 3D model of GBSSI and the relationship between ubiquitination sites K462 and ADP, SO4 (salt bridge or hydrogen bond).
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    To further determine the regulatory role of the ubiquitination sites in GBSSI, SWISS-MODEL was used to predict 3D structural model. As shown in Fig. 8b, GBSSI had three SO4 (sulfate ions) and one ADP ligand. These ligands interact with GBSSI through hydrogen bonds and salt bridges. Three sites, K447, R458, and K462, were associated with SO4 through salt bridges, while G100, N265, Q412, K462, and Q493 interact with the hydrogen bonds of ADP in GBSSI[32,33]. Based on this finding, it can be reasonably inferred that the K462 site with ubiquitination modification located in the GT1 domain played an important role in the interaction between GBSSI, SO4, and ADP. An in-depth investigation was necessary to gain a more comprehensive understanding of the regulatory function of ubiquitination modification at GBSSI-K462, although there was no significant difference in the ubiquitination level under high-temperature stress.

    Ubiquitination regulates amylopectin biosynthesis

    Amylopectin, the major component of starch, is synthesized by the coordinated action of multiple enzymes including soluble starch synthase (SSs), starch branching enzyme (BEs), starch debranching enzyme (DBEs), and phosphorylases (PHOs or Phos) with ADPG as a substrate. In this study, ubiquitination sites were detected in BEs, DBEs, and Phos.

    BEs, covering two isoforms, BEI and BEII, are responsible for catalyzing the formation of α-1,6-glucosidic linkages of amylopectin[34]. There were three ubiquitination sites (K103, K108, and K122) identified in BEI (Fig. 9a). K122 was the first amino acid in the carbohydrate-binding module 48 (CBM48) domain. Sequence alignment analyses of BEs from eight plants revealed K122 was conserved among all plants' BEI (Fig. 9a), suggesting a high probability of the functional effects of ubiquitination modification at this site. In high-temperature environments, ubiquitination levels of K108 and K122 were significantly up-regulated in 9311, while no significantly regulated ubiquitination sites of BEI were observed in GLA4. Only one ubiquitination site, K134, was found in BEIIb (Fig. 9a). The ubiquitination levels showed a slightly upward trend with no significant differences in high-temperature environments in both varieties. These changes could be one of the reasons for increased gelatinization temperature and relative crystallinity of rice starch in response to high-temperature[5].

    Figure 9.  Domain structure of (a) BEs, (b) PUL and (c) Pho1 as well as their ubiquitination sites with significant differences in response to heat stress. Residues in red indicate the ubiquitination site. Non-ubiquitinated residues are shown in dark grey.
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    DBEs consists of isoamylase (ISA) and pullulanase (PUL) with catalytic function for hydrolyzing α-1,6-glucosic linkages[35]. In the present study, we found that only PUL was ubiquitinated in rice endosperm (Fig. 9b). Among five ubiquitination sites (K230, K330, K432, K736, and K884) identified in PUL, K230 was located in the PULN2 domain, while K330 was in the CBM48 domain. Under high-temperature stress, K330 showed completely opposite regulatory trends in two cultivars. In addition, the ubiquitination level of K884, located in the DUF3372 domain, was significantly up-regulated in 9311. Previous study has reported that the expression of PUL was significantly up-regulated in 9311 under high-temperature stress, while GLA4 showed down-regulation in PUL abundance[11]. Consequently, there might be two possible functions of these ubiquitination sites. One possibility is that ubiquitination sites were unrelated to protein degradation; instead, they regulated the biosynthesis of amylopectin by affecting other functions of the protein. Secondly, ubiquitination sites were associated with protein degradation, and the levels of ubiquitination modification were based on protein abundance, resulting in a completely consistent regulation of ubiquitination modification and protein abundance under high-temperature stress.

    PHOs, including two types, Pho1/PHO1 and Pho2/PHO2, are responsible for the transfer of glucosyl units from Glc-1-P to the non-reducing end of a-1,4-linked glucan chains[36]. Pho1 is a temperature-dependent enzyme and considered crucial not only during the maturation of amylopectin but also in the initiation process of starch synthesis[37,38]. The three ubiquitination sites (K277, K445, K941) identified in Pho1 were located in two phosphorylase domains. We found that two sites, Pho1-K277 and Pho1-K445, were only ubiquitinated in high-temperature environments in 9311 and GLA4, respectively. Pang et al.[11] has demonstrated that the protein abundance of Pho1 decreased under high-temperature stress, especially in GLA4. Satoh et al.[38] reported that the functional activity of Pho1 was weakened under conditions of high temperature and its function might be complement by one or more other factors. Hence, these ubiquitination modifications that specifically occurred in high-temperature environments might be related to the degradation of Pho1 proteins.

    Ubiquitination affects ribosomal systems under high-temperature stress

    As a factory for protein synthesis in cells, the ribosome is an extremely crucial structure in the cell[39]. It has been proven that multiple ribosomal subunits were abundantly ubiquitinated in Arabidopsis and wheat[22]. In the present study, 57 ubiquitination sites involving 33 ribosome subunits were identified in 40S and 60S ribosome complexes in rice. Under high-temperature stress, the ubiquitination levels of some sites were significantly upregulated or downregulated, implying that ubiquitination of ribosomal proteins is likely to be an important regulatory mechanism in high-temperature response in rice endosperm. The results of GO and KEGG enrichment analysis indicated that the ribosome system was one of the most active systems for ubiquitination regulation under high-temperature stress. We speculated that the ubiquitin-proteasome system might be involved in the removal of subunits or entire ribosomes that were improperly folded in high-temperature environments. As shown in Fig. 10, the S10e, L18Ae, S27Ae, L9e, S3e, S28e, S20e, and S2e subunits were significantly up-regulated in 9311, while L13e subunits showed a completely opposite regulatory trend at the ubiquitination sites K81 and K88. In GLA4, the ubiquitination levels of S10e, S27Ae, L10Ae, L9e, S3e, S2e, and L4e showed a significant increase, while the ubiquitination level of L17e was significantly down-regulated under high-temperature stress. A total of seven ubiquitination sites involving S10e, S27Ae, L9e, S3e, and S2e subunits were jointly up-regulated in both two varieties. These sites might be related to the degradation of improperly folded ribosome subunits under high-temperature stress, while other ubiquitination sites with variety specificity might be associated with ribosomal function.

    Figure 10.  Ribosome system at the ubiquitination levels in rice endosperm under high-temperature stress. Grey shadings represent ubiquitinated proteins with no significant differences under heat stress. Red and blue shadings indicate up-regulated and down-regulated ubiquitinated proteins, respectively. Orange shading displays a combination of up- and down-regulated ubiquitinated sites in the same ubiquitinated protein.
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    In conclusion, this study provides the first comprehensive view of the ubiquitome in rice developing endosperm, and demonstrated that ubiquitination has diverse functions in the high-temperature response of rice endosperm by modulating various cellular processes, especially the sucrose and starch metabolism. Comparative analysis of the temperature-induced ubiquitination status revealed some similarities and more interesting differences between 9311 and GLA4. These differences might be the reason for the different qualities formation of the two indica rice varieties, which could provide potential genetic resources for the improvement of the heat resistance in rice. Considering the diversity of ubiquitination modification, it is worthwhile to further validate and explore the function and regulatory mechanism of the key targets and key pathways. The findings provide valuable insights into the role of ubiquitination in response to high-temperature stress and lay a foundation for further functional analysis of lysine ubiquitination in rice.

    Author contributions

    The authors confirm contribution to the paper as follows: study conception and design: Bao J, Pang Y; data collection: Pang Y; analysis and interpretation of results: Pang Y; draft manuscript preparation: Ying Y; Revised manuscript preparation: Ying Y, Pang Y, Bao J. All authors reviewed the results and approved the final version of the manuscript.

    Data availability

    The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

    Acknowledgments

    This work was financially supported by the AgroST Project (NK2022050102) and Zhejiang Provincial Natural Science Foundation (LZ21C130003).

  • The authors declare that they have no conflict of interest.

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  • Cite this article

    Adomako J, Osei MK, Prempeh RNA, Osei-Bonsu I, Gyau J, et al. 2024. Identification of Ralstonia solanacearum resistant solanum plants as potential rootstock to manage bacterial wilt disease in tomato production. Technology in Horticulture 4: e020 doi: 10.48130/tihort-0024-0017
    Adomako J, Osei MK, Prempeh RNA, Osei-Bonsu I, Gyau J, et al. 2024. Identification of Ralstonia solanacearum resistant solanum plants as potential rootstock to manage bacterial wilt disease in tomato production. Technology in Horticulture 4: e020 doi: 10.48130/tihort-0024-0017
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Identification of Ralstonia solanacearum resistant solanum plants as potential rootstock to manage bacterial wilt disease in tomato production

  • 1.

    Plant Health Division, CSIR-Crops Research Institute, Kumasi, Ghana

  • 2.

    Horticulture Division, CSIR-Crops Research Institute, Kwadaso, Ghana

  • 3.

    Biotechnology, Seed and Post-Harvest Division, CSIR-Crops Research Institute, Kumasi, Ghana

  • 4.

    CSIR- Soil Research Institute, Kwadaso, Ghana

  • 5.

    Allium Vegetable Research Institute-National Institute of Horticulture and Herbal Science, Vegetable Research Institute, Muan-gun, Republic of Korea

  • Received: 13 May 2024
  • Revised: 25 July 2024
  • Accepted: 29 July 2024
  • Published online: 04 September 2024
Technology in Horticulture  4,  Article number: e020  (2024)  |  Cite this article

Abstract: Using morphological and molecular markers, this study screened tomato (Solanum lycopersicum) and garden egg (Solanum melongena) accessions for resistance to bacterial wilt disease. The solanum plants were inoculated with Ralstonia solanacearum and evaluated for disease incidence and severity in a field trial set up in a Randomised Complete Block Design with four replications. Molecular markers conferring resistance to R. solanacearum Phylotype I and II were used to identify durable and partial resistance. Results showed significant variation in disease incidence and severity among accessions, with tomato accessions exhibiting higher susceptibility. Accession CRI-01 had the highest disease incidence (54.0%), while accession GD had the lowest (13.0%). Accession CRI-04 showed moderate resistance with a disease severity index of 0.37, while accession GC had the highest disease severity index (0.90). Accession L_020 demonstrated moderate resistance in the field (43.0% disease incidence) and possessed durable resistant genes, making it a promising rootstock for managing bacterial wilt disease in tomato production. This research contributes to the development of integrated pest management strategies for sustainable tomato production.

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    Introduction

    • Tomato (Solanum lycopersicum) is affected by several soil-borne diseases, however, bacterial wilt disease caused by Ralstonia solanacearum is of great concern to farmers due to the pathogen's high genetic diversity, wide host range, and adaptation to several environmental conditions[1]. The destructive nature of the disease in vegetable production and more especially on the economy of tomatoes has been reported by multiple studies. Previous studies[2−4] have reported a high yield loss of about 90% in tomatoes under severe bacterial wilt disease outbreaks. Since the wilt disease on tomatoes was reported in Ghana[5], no resistant cultivar has been identified, confirming that most commercial tomato varieties are susceptible to the disease[6].

      High pathogen aggressiveness, numerous host ranges, and highly favorable environmental conditions make controlling of the disease difficult. Notwithstanding, several cultural practices including field sanitation, soil amendments, and field and crop rotations have been employed to reduce the impact of the disease. In addition to the limited number of effective chemical management strategies, the use of synthetic chemicals is highly discouraged due to numerous harmful side effects on the environment, animal and human life, and increased development of chemical resistance[7,8]. The habitation of the pathogen in the xylem of its host and the ability to reside deep in the soil makes the use of chemicals ineffective[9].

      The use of resistant varieties to manage diseases is both environmentally friendly and relatively cost-effective for farmers[10]. A major hindrance to the use of resistant varieties in tomato production has been the negative correlation between crop yield and bacterial wilt disease resistance[11]. To overcome this, the grafting of desirable susceptible varieties onto resistant rootstocks has recently been explored and popularized as an effective control mechanism against R. solanacearum-induced wilting in several crops. Earlier studies[12,13] have reported on the use of resistant solanum rootstocks to reduce the incidence and severity of bacterial wilt disease in susceptible tomatoes culminating in the high demand for bacterial wilt disease suppressive rootstocks in several countries including the USA. In addition to disease management, utilization of rootstocks has been found to improve plant establishment in disease-endemic fields, increase the tolerance level of the scion to environmental stress, and ultimately increase the yield of the desired crop[12,14]. Given the above benefits, multiple efforts have been geared toward screening and identifying R. solanacearum-tolerant rootstocks. For example, Ramesh et al. & Namisy et al.[3,9] screened and identified varieties of Solanum torvum rootstocks resistant to bacterial wilt disease. Again, in several countries, commercial rootstocks have been developed and marketed to farmers to control the disease. In Ghana, however, no commercially available rootstock has been developed and little information exists on the use of rootstocks to manage bacterial wilt disease in tomatoes. Equally, farmers do not have access to any management intervention against the wilt disease, hence leaving infected plants unmanaged. Developing an accessible technology that is eco-friendly, easy to adapt, and less costly to smallholder farmers will enormously increase tomato production and productivity in the country. Identifying and promoting the use of resistant rootstocks could be a valuable tool for tomato growers in Ghana. To achieve this, there is the need to continually screen available germplasm or accession to identify promising lines or rootstocks. Therefore, in this study, it was hypothesized that evaluating some solanum plants may lead to the identification of R. solanacearum-resistant accession(s) for use as rootstock. To test this hypothesis, 13 solanum accessions were evaluated to select resistant rootstocks to provide alternate control and mitigate the negative impact of bacterial wilt disease in Ghana.

    Materials and methods

      Germplasm collection and raising of seedlings

    • Thirteen accessions comprising seven tomatoes (Solanum lycopersicum), and six garden eggs (Solanum melongena) breeding lines and cultivars were obtained from different sources (Table 1). Seeds of the various accessions were surface sterilized in 70% ethanol and serially rinsed in sterile distilled water as described by Davoudpour et al.[15] before sowing in separate trays filled with commercial cocopeat.

      Table 1.  List of tomato and garden egg accessions evaluated in the study.

      No. Code Solanum spp. Biological status Source Country/Region of origin
      1 BL 729 Tomato Breeding line Worldveg Taiwan
      2 BL 9884 Tomato Breeding line Worldveg Taiwan
      3 L_020 Tomato Open pollinated TGRC, UC Davis USA
      4 GC Tomato Open-pollinated TGRC, UC Davis USA
      5 BL 1534 Tomato Breeding line Worldveg Taiwan
      6 GD Tomato Open pollinated TGRC, UC Davis USA
      7 GG Tomato Open pollinated TGRC, UC Davis USA
      8 CRI-06 Garden eggs Breeding line CSIR-CRI Ghana
      9 CRI-04 Garden eggs Breeding line CSIR-CRI Ghana
      10 CRI-03 Garden eggs Breeding line CSIR-CRI Ghana
      11 CRI-02 Garden eggs Breeding line CSIR-CRI Ghana
      12 CRI-01 Garden eggs Breeding line CSIR-CRI Ghana
      13 Black Beauty Garden eggs Open pollinated CSIR-CRI Ghana

      Isolation of R. solanacearum and preparation of bacterial inoculum

    • Pure cultures of the bacterial pathogen were obtained from the Plant Pathology Laboratory of the CSIR-Crops Research Institute (CSIR-CRI), Kumasi, Ghana. The pathogen was initially isolated from garden eggs and tomatoes and properly identified and reported by Newton et al.[16] as R. solanacearum. The obtained pathogen was multiplied on a susceptible tomato variety, Pectomech[16]. To diagnose the presence of the bacterial pathogen, the streaming test was carried out on inoculated plants showing symptoms of wilt disease. The bacterial pathogen was further re-isolated from the infected tomato by dipping a sterilized inoculation loop in the ooze and streaking on Nutrient Agar media[17]. The streaked plates were incubated for 48 h at a temperature of 28 ± 2 °C. Colonies of the bacteria growing on the plates were harvested into sterilized distilled water in glass vials and stored at room temperature until used as inoculum. The inoculum concentration was adjusted to 108 cfu/mL before use.

      Phenotypic screening of Solanum plants for R. solanacearum resistance

    • Three-week-old seedlings of each accession were transplanted at a spacing of 0.5 m × 0.5 m, onto raised beds with plot sizes of 10 m × 1 m. Before transplanting, the roots of the seedlings were gently wounded by cutting the tips of the tertiary roots using sterilized scissors. The scissors were sterilized after each use. The wounded roots were dipped separately into R. solanacearum inoculum suspension for 30 min before transplanting. The experiment was laid out in a completely randomized block design with four replications where each replication consisted of 20 plants. The experimental field had initially been cropped to maize and had no history of bacterial wilt disease incidence. All agronomic practices such as the application of fertilizer at the rate of 60-40-40 kg/ha, N, P2O5, and K2O respectively, and weed control were carried out when needed.

      Bacterial wilt disease assessment

    • The inoculated plants were monitored daily after inoculation for the appearance of wilt symptoms. Following the expression of wilt symptoms, disease incidence, and severity were recorded every 5 d over 30 d. Disease incidence was determined as the proportion of plants showing wilt symptoms in relation to the number of stands per accession. Plants showing symptoms of bacterial wilt disease were further assessed and scored for disease severity on a 0–5, rating scale (0- no wilted leaves, 5-dead plants) as shown in Fig. 1[9].

      Figure 1. 

      Bacterial wilt disease rating scale (0 = no symptoms, 1 = only one leaf partially wilted, 2 = two or three leaves wilted, 3 = all leaves except two or three wilted, 4 = all leaves wilted, 5 = dead plant).

      The disease severity index (DI) was calculated following the formula: DI = (N1 × 1 + N2 × 2 + N3 × 3 + N4 × 4 + N5 × 5)/ (Nt/5)[9], where N1 to N5 = the number of plants with disease rating scale values from 0 to 5, and Nt = the total number of plants observed. Based on the disease index, each Solanum line was categorized as resistant or susceptible as shown in Table 2[18].

      Table 2.  Scale based on disease index for the classification of solanum germplasm.[2]

      DI score (0−1) Reaction
      0.00−0.20 Highly resistant
      0.21−0.30 Resistant
      0.31−0.40 Moderately resistant
      0.41−0.50 Moderately susceptible
      0.51−0.60 Susceptible
      0.61−0.90 Highly susceptible
      0.91−1.00 Extremely susceptible

      Molecular screening of Solanum plants for R. solanacearum resistance

      Sampling for genomic DNA extraction

    • Leaves of approximately 0.2 g were collected into sampling bags, transferred into pre-frozen mortars, and homogenized. Subsequently, samples were transferred into 2 mL Eppendorf tubes for DNA isolation.

      Extraction of Genomic Deoxyribonucleic Acid (gDNA) and Polymerase Chain Reaction (PCR)

    • Genomic DNA was isolated using CTAB (Cetyltrimethylammonium bromide)[19]. DNA was quantified using a Nanodrop 2000 C Spectrophotometer (Thermoscientific, USA) and quality was checked on a 0.8% agarose gel. Nine bacterial wilt trait-linked markers were used for the study as presented in Table 3[20]. These primers are linked to QTLs (Quantitative Trait Loci) Bwr 12 and 6 which confer resistance to bacterial wilt disease PCR was performed using SeeAmp (Hangzhou Bioer Technology Co. Ltd, China) thermal cycler. The PCR amplification reaction of 10 μL contained 10X DreamTaq PCR buffer, 10 mM dNTPs, 10 μM of forward and reverse primer, 2.5 U/μL DNA polymerase, 50 ng DNA template, and nuclease-free water. For the PCR, three controls were used to prevent the scoring of false bands. These comprised a known positive control, a known negative control, and a no template control (NTC). All samples including the positive controls were duplicated to ensure the reliability and reproducibility of results. Amplified products were separated on 1.5% agarose gel in TBE buffer, stained with ethidium bromide, and an image was captured using AlphaImager HP (Proteinsimple, USA). Scoring of bands was conducted using AlphaImager HP Software Version. 3.4.

      Table 3.  Sequences and expected product size of primers used for the study.

      Trait Primer R-gene Forward primer (5'-3') Reverse primer (3'-5') Annealing temperature (°C) Product size (bp) Ref.
      Resistant genotype Susceptible genotype
      Bacteria wilt resistance SLM12–2 Bwr-12 ATCTCATTCAACGCACACCA AACGGTGGAAACTATTG
      AAAGG      		 55 209 No reference band [12]
      SLM12–10 Bwr-12 ACCGCCCTAGCCATAAAGAC TGCGTCGAAAATAGTTGCAT 242
      SLM6–124 Bwr-6 CATGGGTTAGCAGATGATT
      CAA      		 GCTAGGTTATTGGGCCAGAA 292
      SLM6–118 Bwr-6 TCCCAAAGTGCAATAGG
      ACA      		 CACATAACATGGAGTTCGACAGA 183
      SLM6–119 Bwr-6 GCCTGCCCTACAACAAC
      ATT      		 CGACATCAAACCTATGAC
      TGGA      		 255
      SLM6–136 Bwr-6 CCAGGCCACATAGAACTC
      AAG      		 ACAGGTCTCCATACGGCATC 290
      SLM6–17 Bwr-6 TCCTTCAAATCTCCCA
      TCAA      		 ACGAGCAATTGCAAGG
      AAAA      		 186
      SLM6–94 Bwr-6 CTAAATTTAAATGGACAA
      GTAATAGCC      		 CACGATAGGTTGGTATTTTCTGG 276
      Scoring of bands/amplicons

    • The band size for resistant genotypes was scored as present (+) whilst that of susceptible genotypes was scored as absent (−).

      Statistical analysis

    • One-way ANOVA at a probability level of 5% (p < 0.05) was performed for the wilting incidence and disease severity index using Statistix version 8.0. Before analysis, data on percent wilting was arcsine transformed to improve normality. Differences between the means were compared and separated using Fisher's Least Significant Difference (LSD) test.

    Results

      Incidence and severity of bacterial wilt disease in inoculated solanum plants

    • The various accessions screened showed symptoms of bacterial wilt disease with varied levels of reaction to the R. solanacearum infection at the various assessment periods. Thirty days after inoculation, significant differences (p < 0.05) in percent wilting incidence were observed among the garden egg accessions. Among the garden egg accessions, wilting incidence ranged from 54.0% to 71.0% in accessions CRI-01 and CRI-03 respectively (Fig. 2). A similar trend was observed among the tomato accessions evaluated as significant differences (p < 0.05) in disease incidence were observed among them. Among the tomato lines, accessions L_020, and GD, GC recorded the lowest and highest disease incidence of 56% and 90% respectively (Fig. 2) at the end of the assessment period. Generally, the tomato accessions recorded higher disease incidence compared to garden eggs.

      Figure 2. 

      Wilting incidence among 13 solanum accessions. Error bars represent the standard error of the treatment means.

      Disease severity among the garden egg accessions ranged from 0.45 to 0.61 with no significant differences among them (Table 4). This was, however, not the case with the tomato accessions as significant differences (p < 0.05) in disease severity index were observed among the various genotypes. The lowest disease severity (0.37) was recorded for accession (L_020) compared to 0.90 recorded for accession GC (Table 5). Based on the disease severity index, none of the accessions evaluated was found to be highly resistant to the bacterial pathogen. Two accessions (CRI-04 and L_020), however, were moderately resistant with accessions BL1534, GD, GG, and GC recording disease severities above 0.6 and therefore classified as highly susceptible to the pathogen.

      Table 4.  Mean bacterial wilt disease severity among garden egg accessions evaluated.

      Accession Mean disease
      severity index (0–1)      		 Host reaction
      CRI-06 0.45 Moderately susceptible
      CRI-03 0.56 Susceptible
      CRI-04 0.37 Moderately resistant
      CRI-02 0.47 Moderately susceptible
      CRI-01 0.52 Susceptible
      Black Beauty 0.61 Susceptible
      p < 0.05 NS

      Table 5.  Bacterial wilt disease severity and host reaction status among tomato accessions evaluated.

      Accession Disease severity index (0–1) Host reaction
      BL 729 0.53ab Susceptible
      BL 9884 0.44b Moderately susceptible
      GG 0.71ab Highly susceptible
      L_020 0.39b Moderately resistant
      GC 0.90a Highly susceptible
      BL 1534 0.70ab Highly susceptible
      GD 0.70ab Highly susceptible
      Means followed by different letters are significantly different.

      Molecular identification of genotypes with BW resistance

    • All the samples produced visible bands following the PCR amplification (Fig. 3), however only samples with the expected band size were scored as positive. Three of the tomato genotypes (L_020, GG, and GC) representing 23%, showed expected bands for all two primers of Bwr-12 whilst none of the garden egg genotypes showed expected bands for Bwr-12 (Table 6). Genotypes that showed expected bands for primers linked to Bwr-6 ranged from two to eight. Four tomato genotypes (BL1534, BL729, GG, and BL9884) and four garden egg genotypes (Black Beauty, CRI-01, CRI-02, and CRI-03) scored the maximum number of alleles for primer SLM 6-118 whilst only two tomato genotypes (BL729 and GD) scored the minimum number of alleles for SLM 6-17. Two of the garden egg genotypes (CRI-01 and CRI-06) showed alleles for only one of the Bwr-6 genes (SLM 6-118 and 6-110 respectively). The genotypes screened for all the nine primers showed alleles ranging from one to seven. Across all the nine primers used, only one tomato genotype (GG) had alleles for seven of the primers whilst none of the garden eggs had alleles across all nine primers. Only one tomato genotype (BL729) had alleles for six of the primers linked to Bwr-6 whilst the garden egg genotype (Black Beauty) had four alleles (Table 6). Genotypes with both Bwr-6 and Bwr-12 exhibit stable resistance against Phylotype I and II strains of the bacteria; hence this study identified some genotypes that had partial resistance (only Bwr-6) and others with durable resistance (combination of both genes). In effect, genotypes that showed amplification for at least one primer of both QTLs (Bwr-6 and Bwr-12) were classified as durable resistance, hence a total of three genotypes were identified. Genotypes with only one marker (either Bwr-6 or Bwr-12) were classified as partial resistance, hence a total of 10 genotypes were identified.

      Figure 3. 

      Agarose gel image of the marker SLM 12-2 for the detection of the Bwr-12 gene L = Molecular weight ladder; SP = Space; P = Positive control; Well 1 & 2 = L_020; 3 & 4 = BL1534; 5 & 6 = BL729; 7 & 8 = GG; 9 & 10 = GC; 11 & 12 = GD; 13 & 14 = BL9884; 15 & 16 = Black Beauty; 17 & 18 = CRI 01; 19 & 20 = CRI 02; 21 & 22 = CRI 03; 23 & 24 = CRI 04; 25 & 26 = CRI 06; C = Negative control.

      Table 6.  Scores for bacteria wilt resistant gene(s) in tomato and garden egg genotypes.

      Genotypes SSR markers Disease reaction
      Bwr-12 Bwr-6
      SLM 12-2 SLM 12-10 SLM 6-136 SLM 6-119 SLM 6-94 SLM 6-118 SLM 6-110 SLM 6-124 SLM 6-17
      L_020 +/+ +/+ +/+ +/+ +/+ −/− −/− −/− −/− Durable resistance
      BL1534 −/− −/− +/+ −/− −/− +/+ −/− −/− −/− Partial resistance
      BL729 −/− −/− −/− +/+ +/+ +/+ +/+ +/+ +/+ Partial resistance
      GG +/+ +/+ +/+ +/+ −/− +/+ +/+ +/+ −/− Durable resistance
      GC +/+ +/+ +/+ −/− +/+ −/− +/+ +/+ −/− Durable resistance
      GD −/− −/− −/− −/− −/− −/− −/− −/− +/+ Partial resistance
      BL9884 −/− −/− +/+ +/+ −/− +/+ −/− +/+ −/− Partial resistance
      Black Beauty −/− −/− −/− +/+ +/+ +/+ +/+ +/+ −/− Partial resistance
      CRI 01 −/− −/− −/− −/− −/− +/+ −/− −/− −/− Partial resistance
      CRI 02 −/− −/− +/+ −/− −/− +/+ −/− −/− −/− Partial resistance
      CRI 03 −/− −/− +/+ −/− −/− +/+ −/− −/− −/− Partial resistance
      CRI 04 −/− −/− −/− −/− −/− −/− −/− −/− −/− Partial resistance
      CRI 06 −/− −/− −/− −/− −/− −/− +/+ −/− −/− Partial resistance
    Discussion

    • Bacterial wilt disease caused by R. solanacearum is a major constraint to global tomato production[2−4]. The negative effect of the disease is further aggravated by the limited number of management options available to farmers to effectively control the disease[6]. Grafting of susceptible cultivars with desired traits unto a bacterial wilt-resistant rootstock has been identified and promoted as a sustainable means to manage the disease. Both phenotypic and molecular tools have been employed and used successfully to select suitable rootstocks for grafting. The current study screened six tomato and seven garden egg accessions using artificial inoculation procedures and molecular markers to identify and/or select bacterial wilt-resistant rootstocks. The present results showed that all the test materials artificially inoculated with R. solanacearum showed symptoms of wilting. Previous studies[16,21,22] reported that host plants of Solanum spp. present symptoms of wilting following infection and establishment of the pathogen in them. Although all the accessions showed symptoms of infection, they varied in the disease parameters like the incidence and severity of wilting assessed. This assertion is supported by the fact that 57.0% and 16.0% of the tomato and garden eggs lines respectively recorded a wilting incidence of more than 70%. The significant variations in disease expression among and between the accessions as recorded in this study corroborate previous studies[6,23] that reported similar trends in solanaceous cultivars. Based on the phenotypic parameters (wilting incidence and severity scores) measured for this study, none of the test materials screened could be described as resistant to the bacterial wilt disease, although, accessions, L_020 (tomato) and CRI-04 (garden eggs) were found to be moderately resistant. The identification of moderately resistant accessions in the present work supports the findings of Namisy et al. & Stella et al.[9,24] who identified moderately resistant tomato and garden egg lines from field trials for use as rootstocks to manage bacterial wilt disease. The large number of R. solanacearum-susceptible accessions recorded in this study confirms the wide host range of the pathogen causing bacteria wilt disease and the limitation in the identification and selection of resistant rootstocks to manage the disease. Although artificial inoculation procedures have successfully been used to select bacterial wilt-resistant rootstocks, complementing it with marker-assisted selection is considered a standard approach for resistance screening. For this study, in addition to the field evaluation, molecular markers were used to enable efficient identification of genotypes with resistant genes for bacterial wilt diseases as well as multiple resistant gene combinations, which would not have been possible with symptom expression alone. These multiple resistant genotypes could be used in areas where the diseases occur sequentially or simultaneously. Two strains of R. solanacearum that cause bacterial wilt have been reported as being prevalent in Ghana[5]. Bwr-6 and Bwr-12 QTLs have been identified to confer resistance to the disease with Bwr-6 conferring resistance against phylotypes I and II; Bwr-12 conferring resistance against only phylotype I[25]. It has also been reported that genotypes with both Bwr-6 and Bwr-12 show stable resistance against Phylotypes I and II[25], hence any genotype with a combination of both QTLs expresses more durable resistance than genotypes with only one of the genes. Markers used in this study were able to identify genotypes with either Bwr-6 or Bwr-12 or a combination of both. Since genotypes with both Bwr-6 and Bwr-12 show stable resistance, this study identified three tomato genotypes (L_020, GG and GC) that had a combination of both genes and thus, agree with the findings of Carmeille et al.[26] who detected both QTLs in some tomato lines. Furthermore, four of the genotypes had either of the QTLs, indicating partial resistance. All the garden egg genotypes had one or more of the alleles for Bwr-6, indicating partial resistance. In a similar study,[27] it was found that stable QTLs for bacterial wilt resistance in garden eggs were located on chromosomes 3 and 6. The QTLs on chromosome 6 overlap with the BW-resistant QTL (Bwr-6) in tomatoes. This explains the current results where there was no amplification for Bwr-12 QTL in the garden egg genotypes but there was amplification in the Bwr-6 QTL. Contrary to the morphological studies, two accessions (GC and GG) classified as resistant were identified as highly susceptible to the pathogen under field conditions. The difference in morphological and molecular categorization as obtained in this study is consistent with Olasanmi et al.[28] who reported inconsistencies in cassava mosaic disease resistance levels in cassava genotypes based on field and molecular marker data. Accessions classified as resistant based on molecular markers but identified as susceptible under phenotypic evaluation according to Wang & Lin[29] may be attributed to the presence and interaction of other strains of the R. solanacearum on the field, inoculum density, soil moisture, temperature, and presence of root-knot nematodes which can affect the stability of bacterial wilt resistance in crop genotypes.

    Conclusions

    • The results presented in this study show variations in the reaction of different accessions to bacterial wilt disease using both phenotypic and molecular markers. Using only phenotypic scores two accessions were classified as moderately resistant while three accessions were selected as resistant based on the molecular markers used. However, only accession L_020 phenotypically identified as moderately resistant was further confirmed as resistant based on the molecular data and therefore, selected as a promising genotype to be exploited as a potential rootstock to manage bacterial wilt disease. Due to the inconsistent phenotypic and molecular data obtained in this study, accessions (CRI-04, GG, and GC) cannot be selected as potential rootstocks to manage bacterial wilt disease in tomato production. These accessions can be screened further with additional molecular markers and under different fields to confirm the results obtained.

    Author contributions

    • The authors confirm contribution to the paper as follows: performing the research: Adomako J, Prempeh RNA; data analysis and technical help: Osei MK, Gyau J, draft of the manuscript: Cho MC, Adomako J, Prempeh RNA, Osei MK; experiments design, study supervision and manuscript revision: Boakye-Mensah IN, Osei-Bonsu I, Ofori P. All authors reviewed the results and approved the final version of the manuscript.

    Data availability

    • The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

      Acknowledgments

      • This study was supported by a grant from KAFACI, Rural Development Administration of Korea (Grant No. KAH2000106).

      Conflict of interest

      • The authors declare that they have no conflict of interest.

      Rights and permissions
      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (3)  Table (6) References (29)
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    Cite this article
    Adomako J, Osei MK, Prempeh RNA, Osei-Bonsu I, Gyau J, et al. 2024. Identification of Ralstonia solanacearum resistant solanum plants as potential rootstock to manage bacterial wilt disease in tomato production. Technology in Horticulture 4: e020 doi: 10.48130/tihort-0024-0017
    Adomako J, Osei MK, Prempeh RNA, Osei-Bonsu I, Gyau J, et al. 2024. Identification of Ralstonia solanacearum resistant solanum plants as potential rootstock to manage bacterial wilt disease in tomato production. Technology in Horticulture 4: e020 doi: 10.48130/tihort-0024-0017
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  • Introduction
  • Materials and methods

  • Germplasm collection and raising of seedlings

  • Isolation of R. solanacearum and preparation of bacterial inoculum

  • Phenotypic screening of Solanum plants for R. solanacearum resistance

  • Bacterial wilt disease assessment

  • Molecular screening of Solanum plants for R. solanacearum resistance

  • Sampling for genomic DNA extraction
  • Extraction of Genomic Deoxyribonucleic Acid (gDNA) and Polymerase Chain Reaction (PCR)
  • Scoring of bands/amplicons

  • Statistical analysis

  • Results

  • Incidence and severity of bacterial wilt disease in inoculated solanum plants

  • Molecular identification of genotypes with BW resistance

  • Discussion
  • Conclusions
  • Author contributions
  • Data availability
  • Acknowledgments
  • Conflict of interest
  • Rights and permissions
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