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Article

Whole-Genome Sequence and Characterization of Ralstonia solanacearum MLY102 Isolated from Infected Tobacco Stalks

by
Guan Lin
1,
Juntao Gao
1,
Junxian Zou
1,
Denghui Li
1,
Yu Cui
1,
Yong Liu
1,*,
Lingxue Kong
2,* and
Shiwang Liu
1
1
School of Biological & Chemical Engineering, Zhejiang University of Science & Technology, Hangzhou 310023, China
2
Institute for Frontier Materials, Deakin University, Geelong, VIC 3216, Australia
*
Authors to whom correspondence should be addressed.
Genes 2024, 15(11), 1473; https://doi.org/10.3390/genes15111473
Submission received: 25 October 2024 / Revised: 6 November 2024 / Accepted: 7 November 2024 / Published: 15 November 2024
(This article belongs to the Section Plant Genetics and Genomics)
Browse Figures
Figure 1
<p>Colony appearance (<b>A</b>) and cellular morphology (<b>B</b>) of <span class="html-italic">R. solanacearum</span> MLY91.</p> "> Figure 2
<p>Circle graphs of the <span class="html-italic">R. solanacearum</span> MLY102 chromosome (<b>A</b>) and giant plasmid (<b>B</b>).</p> "> Figure 3
<p>Distribution of gene lengths of <span class="html-italic">R. solanacearum</span> MLY102.</p> "> Figure 4
<p>Functional classification of genes in <span class="html-italic">R. solanacearum</span> MLY102. (<b>A</b>): COG function classification; (<b>B</b>): GO function classification; (<b>C</b>): KEGG function classification.</p> "> Figure 5
<p>Heatmap of average nucleotide identity (ANI) between eleven strains of <span class="html-italic">R. solanacearum</span>.</p> "> Figure 6
<p>Heatmap of dispensable genes (<b>A</b>), Venn diagram of the pan gene set (<b>B</b>) and statistics of the number of homologous genes in the gene families (<b>C</b>) of <span class="html-italic">R. solanacearum</span> MLY102 and the reference strains.</p> "> Figure 7
<p>Phylogenetic trees of <span class="html-italic">R. solanacearum</span> MLY102 and reference strains based on core pan (<b>A</b>) and gene family (<b>B</b>) results.</p> ">
Review Reports Versions Notes

Abstract

:
Background/Objectives: Bacterial wilt disease is a soil-borne disease caused by Ralstonia solanacearum that causes huge losses to crop economies worldwide. Methods: In this work, strain MLY102 was isolated and further identified as R. solanacearum from a diseased tobacco stalk. The genomic properties of MLY102 were explored by performing biochemical characterization, genome sequencing, compositional analysis, functional annotation and comparative genomic analysis. Results: MLY102 had a pinkish-red color in the center of the colony surrounded by a milky-white liquid with fluidity on TTC medium. The biochemical results revealed that MLY102 can utilize carbon sources, including D-glucose (dGLU), cane sugar (SAC) and D-trehalose dihydrate (dTRE). Genome sequencing through the DNBSEQ and PacBio platforms revealed a genome size of 5.72 Mb with a G+C content of 67.59%. The genome consists of a circular chromosome and a circular giant plasmid with 5283 protein-coding genes. A comparison of the genomes revealed that MLY102 is closely related to GMI1000 and CMR15 but has 498 special genes and 13 homologous genes in the species-specific gene family, indicating a high degree of genomic uniqueness. Conclusions: The unique characteristics and genomic data of MLY102 can provide important reference values for the prevention and control of bacterial wilt disease.

1. Introduction

Ralstonia solanacearum is a Gram-negative bacterium belonging to the phylum Proteobacteria [1]. The bacterium is rod-shaped, rounded at both ends and bears 1–4 polar flagella with a cell length of approximately 0.5–1.5 μm [2]. R. solanacearum has complex physiological and biochemical properties and can infect more than 450 species of plants in more than 54 families, including common crops such as chili, tomato, tobacco, potato, peanut, ginger, mulberry and eucalyptus [3,4,5]. Plants infected with R. solanacearum develop bacterial wilt disease and gradually wilt and die. Bacterial wilt disease is widely distributed in tropical, subtropical and temperate regions and causes severe economic damage to crops [6]. Tobacco is a widely grown cash crop. Bacterial wilt disease was first identified in tobacco in 1880 and is categorized as an important disease in tobacco production because of its potential threat to tobacco [7]. The infestation of tobacco with R. solanacearum causes significant economic losses and yield reductions, contributing to 10–30% of production losses globally [8]. Therefore, studying the R. solanacearum genome helps us understand its pathogenicity and the development of resistance.
R. solanacearum is spread through soil, it is widely distributed and very viable and it can survive for several years without any nutrients [9]. R. solanacearum can be classified into four phylotypes based on geographic location: phylotype I (Asia), phylotype II (America), phylotype III (Africa) and phylotype IV (Indonesia) [10]; another type of classification is based on the use of carbohydrates (lactose, maltose, fiber diatoms and mannitol, etc.), and R. solanacearum can be classified into five biochemical variants [1]. In addition, after infesting a plant, R. solanacearum can return to the soil from fallen tissues, causing a secondary infestation [11].
The whole-genome sequencing of R. solanacearum can provide a basis for the study of its pathogenesis at the genome level. GMI1000, a model strain, was isolated from tomato plants, and its complete nucleotide genome sequencing has been completed [12]. These findings provide important reference information for subsequent studies on the evolution of the diversity of R. solanacearum and the pathogenesis of related diseases. The genome of R. solanacearum is approximately 5.8 Mb in size and consists of two circular replicons (a circular chromosome and a circular megaplasmid), and a few have a small plasmid (e.g., Rs-P.362200) [2]. The pathogenicity of bacterial wilt disease is closely related to its virulence factors. Virulence factors include extracellular polysaccharides, effector proteins and flagella [13]. By invading plant conduits, bacterial wilt disease synthesizes large amounts of extracellular polysaccharides, which block vascular tissues to impede water transport and ultimately lead to plant wilting and death. The more studied virulence factor is the type III secretion system effector protein (T3SS) [14]. R. solanacearum injects the T3SS into plant cells via its syringe-like Type III secretion system, and its effects include interfering with the basic defense system of the plant, interfering with plant metabolic processes, promoting infestation, and stimulating immune responses of the host plant [2,15,16,17]. Currently, the T3SS genes of R. solanacearum, commonly known as Rip genes, include 102 Rip genes and 16 T3SS candidate genes [18]. To date, the NCBI database has published the complete draft genomes of 507 R. solanacearum strains, which mainly include isolates from tomato, tobacco, chili and sesame [4]. The use of these R. solanacearum genomes can help us better understand the regulatory mechanisms of R. solanacearum and provide important reference values for controlling bacterial wilt disease at the gene level.
There are large differences in virulence among different R. solanacearum strains. In this study, we performed physiological, biochemical and whole-genome sequencing analyses (Process: Figure S1) of the R. solanacearum strain MLY102, which was isolated from an onset tobacco sample from a plot with a high incidence of bacterial wilt disease. Due to the economic losses caused by R. solanacearum, we hope to find some basis for the high pathogenicity of this strain through functional annotation and comparative genomics, which will provide key data for the development of new control strategies. This is not only crucial for the sustainable development of the tobacco industry but also has broad implications for disease prevention and control in other crops.

2. Materials and Methods

2.1. Materials and Equipment

TTC medium, PDA medium and yeast extract were obtained from Hangzhou Microbial Reagent Co., Ltd. (Hangzhou, China). The universal primers Eubac27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and Eubac1492R (5′-GGTTACCTTGTTACGACTT-3′) were obtained from Beijing Tsingke Biotechnology Co., Ltd. (Beijing, China). A scanning electron microscope (SEM) SU1510 was obtained from Hitachi (Mitoshi, Japan), and NanoSuit® solution I was obtained from Nisshin EM Co., Ltd. (Tokyo, Japan). The automated bacterial identification instrument VITEK 2 Compact and GN Identification Card were obtained from BioMérieux Corporate (Lyon, France). The single-molecule real-time (SMRT) PacBio RS II sequencing instrument was obtained from Pacific Biosciences (Menlo Park, CA, USA).

2.2. Isolation and Identification of R. solanacearum MLY102

2.2.1. Isolation of R. solanacearum MLY102

Samples of diseased tobacco stalks were collected from farmland in Tianzhu County, Guizhou Province, China, which has a high incidence of bacterial wilt disease throughout the year. The stem of a diseased tobacco plant was taken, its surface sterilized, and the diseased tissue within the stem removed and suspended in sterile water. A bacterial suspension was obtained via sufficient shaking; it was then appropriately diluted and coated on NA medium and incubated at 30 °C for 48 h. The stem of the diseased tobacco plant was then incubated at 30 °C for 48 h. The diseased tobacco stem was then disinfected with a surface disinfectant. The 16S ribosomal RNA gene was amplified with the universal primers Eubac27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and Eubac1492R (5′-GGTTACCTTGTTACGACTT-3′). The DNA sequences were sequenced and blasted in GenBank to identify the species affiliation of the isolate MLY102.

2.2.2. Biochemical Characterization Tests of R. solanacearum MLY102

A fresh pure culture of R. solanacearum MLY102 was collected, suspended in saline solution (0.45–0.50% NaCl), and transferred to a VITEK® 2 suspension tube containing 3 mL of saline, with the McFarland turbidity adjusted to 0.50–0.63. The suspension tube was then attached to the GN card, and the biochemical reaction pattern was analyzed using the VITEK® 2 Compact System.

2.3. R. solanacearum MLY102 Genome Sequencing and Assembly

The genome of strain MLY102 was sequenced at the Beijing Genome Institute (BGI, Shenzhen, China) via the PacBio and DNBSEQ platforms. DNA from MLY102 was extracted using the MGIEasy Microbiome DNA Extraction Kit. The extracted DNA was fragmented to the target fragment range (15–20 K) using a Megaruptor on the PacBio platform and then precisely recovered via Sage ELF to obtain libraries with high-fidelity reads for sequencing. The PacBio Sequel platform uses SMRT cells to generate subreads. Subreads shorter than 1000 bp in length were filtered out and then self-corrected via Canu v1.5 [19]. To obtain high-confidence assembled sequences, single-base corrections were performed via GATK v1.6-13 [20].

2.4. Genome Component Prediction

Gene prediction of R. solanacearum was performed via Glimmer v3.02 [21]. RNAmmer v1.2, tRNAscan v1.3.1 and Rfam v9.1 were used to recognize rRNA, tRNA and sRNA, respectively [22,23,24]. Tandem repeat sequences were obtained via Tandem Repeat Finder v4.04 and screened for microsatellite and minisatellite sequences therein on the basis of the length and number of repeat units [25].

2.5. Functional Annotation of the Genome

The genes were blasted with Diamond v0.8.31 in different databases [26], such as VFDB (virulence factor database) v2023-4-28 [27], ARDB (Antibiotic Resistance Genes Database) v1.1 [28], CAZy (Carbohydrate-Active enZYmes Database) v2022-9-15 [29], Swiss-Prot vrelease-2022-03 [30], COG (Cluster of Orthologous Groups of proteins) v2020-11-25 [31], CARD (The Comprehensive Antibiotic Resistance Database) v3.0.9 [32], GO (Gene Ontology) v2019-07-01 [33], KEGG (Kyoto Encyclopedia of Genes and Genomes) v106.0 [34], T3SS (Type III secretion system Effector protein) v1.0 [35] and NR (Non-Redundant Protein Database databases, v2023-4-20). The highest quality comparison results were selected for gene annotation.

2.6. Comparative Genomic Analysis

2.6.1. Structural Variation (Synteny)

MLY102 and 10 other reference strains (CFBP2957, CMR15, GMI1000, PSI07, Po82, RS-CIAT078, RS-Rs5, RS-SL2064, RS-T95 and RS-UW251) were analyzed. The gene sequence comparison was performed using MUMmer v3.22 [36]. Protein comparison was performed using a BLASTp comparison of the target bacterial protein set to the reference bacterial protein set. Finally, according to its location information, it was reduced to the same scale and labeled on the figure.

2.6.2. Genome-Wide Similarity Analysis

Genome-wide similarity was analyzed on the basis of average nucleotide identity (ANI), and fastANI v1.32 software was used to perform the analysis (parameters: -c 1024) [37].

2.6.3. Core and Pan Genome Analysis

Analysis of the core and pan genomes was performed via CD-HIT v4.6.6 (parameters: -c 0.5 -n 3 -p 1 -g 1 -d 0) [38]. The protein-encoding gene sets of all the strains to be analyzed were subjected to CD-HIT clustering analysis, and the final gene set of the clusters was used as the pan gene set. The sequences present in each sample in the cluster in the extracted clustering results were the core gene set, the gene set that was unique to each sample was the special gene set and the pan gene set with the removal of the core gene set and the unique gene set was the dispensable gene set.

2.6.4. Gene Family Analysis

Gene family clustering analysis was performed on MLY102 and the reference strains CFBP2957, CMR15, GMI1000, PSI07, Po82, RS-CIAT078, RS-Rs5, RS-SL2064, RS-T95 and RS-UW251. The protein sequences were subjected to BLAST comparison to remove redundancy, and the gene families were then clustered. After a multiple sequence comparison of clustered gene families using Muscle v3.8.31 [39,40], gene families were analyzed with TreeBeST v1.9.2 using the Neighbor-Joining method for tree-building (parameters: treebest nj -b 1000) [41].

2.6.5. Species Evolution Analysis

A phylogenetic tree was constructed on the basis of the single-nucleotide polymorphism (SNP) matrices of MLY102 and the reference strains CFBP2957, CMR15, GMI1000, PSI07, Po82, RS-CIAT078, RS-Rs5, RS-SL2064, RS-T95, and RS-UW251. The phylogenetic tree was constructed using the Maximum Likelihood algorithm of TreeBeST v1.9.2 (parameters: treebest phyml -b 1000) [41].

3. Results and Discussion

3.1. Morphological and Biochemical Characteristics of R. solanacearum MLY102

R. solanacearum MLY102, which was isolated from morbid tobacco stalks, was pink in color at the center of the colony on TTC medium and was surrounded by a milky white liquid with fluidity (Figure 1A), which was generally consistent with the morphology of a single colony of R. solanacearum on TTC medium [42]. When R. solanacearum invades the xylem, more extracellular polysaccharides would promote the colonization of R. solanacearum and inhibit the conduit water flow, which would ultimately lead to tobacco death [43,44]. Scanning electron microscopy revealed that R. solanacearum MLY102 is short and rod-shaped and that the size of the organism is 0.7–0.8 μm × 1.6–1.8 μm (Figure 1B) [5].
Table 1 summarizes the biochemical characteristics of R. solanacearum MLY102, as determined via the VITEK 2 Compact automated bacterial identification system using GN cards. The carbon sources that R. solanacearum MLY102 was able to utilize included D-glucose (dGLU), cane sugar (SAC) and D-trehalose dihydrate (dTRE) but not D-cellobiose (dCEL), the fermentation of glucose (OFF), D-maltose monohydrate (dMAL), D-mannose (dMNE), paleo sugar (PLE) or D-tagatose (dTAG). SAC and dTRE are considered necessary in R. solanacearum infection [45]. R. solanacearum may use SAC and dTRE in plants to increase its infestation capacity [46]. It is also worth noting that in addition to carbon sources, R. solanacearum infestation led to reductions in ammonium nitrogen in soil and total nitrogen in tobacco [47].

3.2. Whole Genome of R. solanacearum MLY102

The genome of R. solanacearum strain MLY102 was sequenced via PacBio (8,738,130 reads; 1293 Mb clean data) and DNBSEQ (372,737 reads, with an N50 of 10,408 bp for a total of 3552,404,998 bp) platforms. The genome was assembled, and the assembly resulted in a circular chromosome and a circular plasmid (Figure 2). The size of the genome was 5.72 Mb, which was smaller than that of CQPS-1 (5.89 Mb), FJ1003 (5.90 Mb) and gd-2 (5.93 Mb) isolated from tobacco [1].
The depth of the genome was 43.10× with a G+C content of 67.59%. A total of 5283 protein-coding genes were identified via gene prediction (Figure 3), similar to gd-2 (5074), FJ1003 (5010) and CQPS-1 (5229) [48].
The non-coding RNA (ncRNA) gene characteristics of R. solanacearum MLY102 are shown in Table 2. The amount of tRNA was similar to that of gd-2 (59) and CQPS-1 (58) and greater than that of FJ1003 (35) [49]. In addition, 308 tandem repeat fragments, 211 minisatellite DNA sequences, and 33 microsatellite DNA sequences were identified. The different characteristics possessed by strains isolated from tobacco show the complex diversity of R. solanacearum [50,51]. This provides additional key evidence at the genetic level for the management of tobacco bacterial wilt disease prevention and control.

3.3. Gene Function Annotation of R. solanacearum MLY102

The total number of annotated genes reached 5202 (98.46%), with gene annotation rates of 9.06% (VFDB), 0.51% (ARDB), 2.04% (CAZy), 79.57% (IPR), 38.06% (Swiss-Prot), 73.14% (COG), 0.05% (CARD), 57.08% (GO), 57.9% (KEGG), 97.95% (NR) and 15.65% (T3SS). Among the COG, GO and KEGG terms, the top three terms were amino acid transport and metabolism (401), transcription (389) and general function prediction only (327); cellular process (1759), catalytic activity (1686) and metabolic process (1679); and global and overview maps (1020), amino acid metabolism (284) and carbohydrate metabolism (275) (Figure 4). By screening the VFDB and CARD genes, we identified four hundred and seventy-nine candidate virulence factors and three possible antibiotic resistance genes. The identification of virulence factors and antibiotic resistance genes facilitated the understanding of virulence mechanisms and drug design [51]. The virulence factors mainly include anti-inflammatory proteins and heat shock protein (Hsp) 60, flagellum, and Cya; antibiotic resistance genes are mainly related to antibiotic inactivation and antibiotic efflux and include Vibrio cholerae varG and adeF, which are similar to R. solanacearum gd-2 [1]. This provides a key basis for understanding the development of pathogenicity and resistance, thereby supporting the prevention, control and management of tobacco bacterial wilt disease [42].

3.4. Comparison of R. solanacearum MLY102 and Reference Strains

3.4.1. Structural Variation and Average Nucleotide Identity (ANI) Analysis of MLY102 and Reference Strains

By comparing MLY102 with the reference strains, structural variations can be used to detect gene positional variations caused by gene recombination and migration. A comparison of the differences between the strains at the nucleotide level (Table S1) and amino acid level (Table S2) revealed that MLY102 and the reference strains CFBP2957, CMR15, GMI1000, PSI07, Po82, RS-CIAT078, RS-Rs5, RS-SL2064, RS-T95 and RS-UW251 have homology. ANI was analyzed using fastANI v1.32 (parameters: -c 1024) [37]. The ANI results also revealed similarity between MLY102 and the reference strains (Figure 5). Although the ANI does not rigorously measure the evolutionary relevance of the core genome, as immediate homologs may differ significantly between compared genome pairs, it is able to closely reflect the relevance of DNA–DNA hybridization used to define species in traditional microbiological concepts because it takes into account the mobility of the bacterial gene pool. It also indirectly considers the sharing of functionality between bacteria. Both the MLY102 strain and R. solanacearum GMI1000 have ANI values above 99%, indicating a close genetic relationship between them [37]. MLY102 can be identified as phylotype I.

3.4.2. Analysis of Core and Pan Genomes of Eleven Strains

The core and pan genomes were analyzed using CD-HIT v4.6.6 (parameters: -c 0.5 -n 3 -p 1 -g 1 -d 0) [38]. The core genome is needed to maintain the basic biological characteristics of all strains [52]. A sequence comparison of eleven strains of R. solanacearum revealed 4378 homologous gene groups (HGGs), 2273 of which were shared by eleven genomes, constituting the core genome of R. solanacearum (Figure 6B) [5]. The number of genes specific to each strain varied widely, and these differences support the high complexity and genomic diversity of R. solanacearum [51]. In addition, a heatmap of dispensable genes was drawn on the basis of the distribution of dispensable genes in different samples (Figure 6A). The results revealed that CFBP2957 was independent of other branches and presented unique properties; MLY102 and GMI1000 clustered into a cluster and clustered into a branch with CMR15, which expressed a high degree of similarity. PSI07, RS-SL2064 and RS-T95 formed a branch. Another important branch was formed by Po82, RS-CIAT078, RS-Rs5 and RS-UW251. The pan gene set Venn diagram and statistical graph of the number of gene family homologs revealed that, compared with the reference strain, MLY102 presented the second highest number of special genes (493) and the greatest number of species-specific gene family homologs (13) (Figure 6C). Dispensable genes and special genes play important roles in the genetic diversity of species and in adverse environments [5]. These genes may provide important clues for understanding the species evolution and biodiversity of R. solanacearum.

3.4.3. Evolutionary Relationship Between MLY102 and Reference Strains

We constructed phylogenetic trees using the Maximum Likelihood method (parameters: treebest phyml -b 1000) [41]. The results of core pan and gene family analyses revealed that RS-SL2064 clustered with RS-T95; Po82 clustered with RS-CIAT078 (Figure 7). This is consistent with the analysis results of ANI and the dispensable gene heatmap. MLY102 had the maximum ANI value (99.01%) with only GMI1000 among all the reference strains and was clustered into the same branch in the dispensable gene heatmap, whereas, in sharp contrast, the two strains were classified into different main branches in the phylogenetic tree.

4. Conclusions

The identification and genomic analysis of the R. solanacearum strain MLY102 provided significant data on the genetic evolutionary relationships of R. solanacearum. MLY102 is able to utilize specific carbon sources, which provide the basis for its ability to infest plants. Comprehensive genome sequencing demonstrated the unique genetic characteristics of R. solanacearum, including a single megaplasmid (and, in some cases, a single miniplasmid). In addition, comparative genetic analyses of eleven different strains of R. solanacearum provided important clues to the diversity and phylogenetic relationships of R. solanacearum. Genomic information can be applied in the field for early detection, which is beneficial for disease detection and management. In addition, comparative genomic studies of different strains of R. solanacearum can be expanded in future studies, which will help reveal differences in the adaptability of R. solanacearum in different ecosystems and provide a scientific basis for regional management of the disease.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes15111473/s1. Figure S1. Bioinformatics Analysis Flowchart; Table S1. Synteny rates at nucleic acid level; Table S2. Synteny statistics at amino acid level between MLY102 and reference strains.

Author Contributions

Conceptualization, G.L. and Y.L.; methodology, G.L., J.G. and L.K.; software, J.Z. and Y.C.; investigation, G.L. and Y.L.; resources, G.L. and S.L.; data curation, D.L.; writing—original draft preparation, G.L. and Y.L.; writing—review and editing, Y.L. and L.K.; supervision, S.L.; project administration, G.L. and Y.L.; funding acquisition, Y.L. and L.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the China Scholarship Council, support No. 202107570001.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The MLY102 genome sequence was deposited in the DDBJ/ENA/GenBank database (BioProject/BioSample PRJNA1177238/SAMN44414988).

Acknowledgments

The authors would like to acknowledge Shunli Kou for support with SEM observation.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Xiao, Z.; Li, G.; Yang, A.; Liu, Z.; Ren, M.; Cheng, L.; Liu, D.; Jiang, C.; Wen, L.; Wu, S.; et al. Comprehensive genome sequence analysis of Ralstonia solanacearum gd-2, a phylotype I sequevar 15 strain collected from a tobacco bacterial phytopathogen. Front. Microbiol. 2024, 15, 1335081. [Google Scholar] [CrossRef] [PubMed]
  2. Chen, K.; Wang, L.; Chen, H.; Zhang, C.; Wang, S.; Chu, P.; Li, S.; Fu, H.; Sun, T.; Liu, M.; et al. Complete genome sequence analysis of the peanut pathogen Ralstonia solanacearum strain Rs-P.362200. BMC Microbiol. 2021, 21, 118. [Google Scholar] [CrossRef] [PubMed]
  3. Li, J.; Yan, Y.; Yang, L.; Ding, S.; Zheng, Y.; Xiao, Z.; Yang, A.; Liang, W. Duality of H2O2 detoxification and immune activation of Ralstonia solanacearum alkyl hydroperoxide reductase C (AhpC) in tobacco. Int. J. Biol. Macromol. 2024, 279, 135138. [Google Scholar] [CrossRef]
  4. Shi, L.; Shi, W.; Qiu, Z.; Yan, S.; Liu, Z.; Cao, B. CaMAPK1 Plays a vital role in the regulation of resistance to Ralstonia solanacearum infection and tolerance to heat stress. Plants 2024, 13, 1775. [Google Scholar] [CrossRef]
  5. Li, X.; Huang, X.; Chen, G.; Zou, L.; Wei, L.; Hua, J. Complete genome sequence of the sesame pathogen Ralstonia solanacearum strain SEPPX 05. Genes Genom. 2018, 40, 657–668. [Google Scholar] [CrossRef]
  6. Huang, M.; Tan, X.; Song, B.; Wang, Y.; Cheng, D.; Wang, B.; Chen, H. Comparative genomic analysis of Ralstonia solanacearum reveals candidate avirulence effectors in HA4-1 triggering wild potato immunity. Front. Plant Sci. 2023, 14, 1075042. [Google Scholar] [CrossRef]
  7. Hayward, A.C. Biology and epidemiology of bacterial wilt caused by Pseudomonas solanacearum. Annu. Rev. Phytopathol. 1991, 29, 65–87. [Google Scholar] [CrossRef]
  8. Alariqi, M.; Wei, H.; Cheng, J.; Sun, Y.; Zhu, H.; Wen, T.; Li, Y.; Wu, C.; Jin, S.; Cao, J. Large-scale comparative transcriptome analysis of Nicotiana tabacum response to Ralstonia solanacearum infection. Plant Biotechnol. Rep. 2022, 16, 757–775. [Google Scholar] [CrossRef]
  9. Alvarez, B.; Lopez, M.M.; Biosca, E.G. Survival strategies and pathogenicity of Ralstonia solanacearum phylotype II subjected to prolonged starvation in environmental water microcosms. Microbiology 2008, 154, 3590–3598. [Google Scholar] [CrossRef]
  10. Castillo, J.A.; Greenberg, J.T. Evolutionary dynamics of Ralstonia solanacearum. Appl. Environ. Microbiol. 2007, 73, 1225–1238. [Google Scholar] [CrossRef]
  11. Gao, J.; Lin, G.; Deng, X.; Zou, J.; Liu, Y.; Chen, X.; Liu, S. Development of tetramycin-loaded core—Shell beads with hot-wet-responsive release properties for control of bacterial wilt disease. Agronomy 2024, 14, 1199. [Google Scholar] [CrossRef]
  12. Salanoubat, M.; Genin, S.; Artiguenave, F.; Gouzy, J.; Mangenot, S.; Arlat, M.; Billault, A.; Brottier, P.; Camus, J.C.; Cattolico, L.; et al. Genome sequence of the plant pathogen Ralstonia solanacearum. Nature 2002, 415, 497–502. [Google Scholar] [CrossRef] [PubMed]
  13. Xiao, Z.; Liu, Z.; Zhang, H.; Yang, A.; Cheng, L.; Liu, D.; Jiang, C.; Yu, S.; Yang, Z.; Ren, M.; et al. Transcriptomics and virus-induced gene silencing identify defence-related genes during Ralstonia solanacearum infection in resistant and susceptible tobacco. Genomics 2024, 116, 110784. [Google Scholar] [CrossRef] [PubMed]
  14. Tan, X.; Qiu, H.; Li, F.; Cheng, D.; Zheng, X.; Wang, B.; Huang, M.; Li, W.; Li, Y.; Sang, K.; et al. Complete genome sequence of sequevar 14 M Ralstonia solanacearum strain HA4-1 reveals novel type III effectors acquired through horizontal gene transfer. Front. Microbiol. 2019, 10, 1893. [Google Scholar] [CrossRef]
  15. Landry, D.; Gonzalez-Fuente, M.; Deslandes, L.; Peeters, N. The large, diverse, and robust arsenal of Ralstonia solanacearum type III effectors and their in planta functions. Mol. Plant Pathol. 2020, 21, 1377–1388. [Google Scholar] [CrossRef]
  16. Xian, L.; Yu, G.; Wei, Y.; Rufian, J.S.; Li, Y.; Zhuang, H.; Xue, H.; Morcillo, R.; Macho, A.P. A bacterial effector protein hijacks plant metabolism to support pathogen nutrition. Cell Host Microbe 2020, 28, 548–557. [Google Scholar] [CrossRef]
  17. Cheng, D.; Zhou, D.; Wang, Y.; Wang, B.; He, Q.; Song, B.; Chen, H. Ralstonia solanacearum type III effector RipV2 encoding a novel E3 ubiquitin ligase (NEL) is required for full virulence by suppressing plant PAMP-triggered immunity. Biochem. Biophys. Res. Commun. 2021, 550, 120–126. [Google Scholar] [CrossRef]
  18. Sabbagh, C.; Carrere, S.; Lonjon, F.; Vailleau, F.; Macho, A.P.; Genin, S.; Peeters, N. Pangenomic type III effector database of the plant pathogenic Ralstonia spp. PeerJ 2019, 7, e7346. [Google Scholar] [CrossRef]
  19. Koren, S.; Walenz, B.P.; Berlin, K.; Miller, J.R.; Bergman, N.H.; Phillippy, A.M. Canu: Scalable and accurate long-read assembly via adaptivek k-mer weighting and repeat separation. Genome Res. 2017, 27, 722–736. [Google Scholar] [CrossRef]
  20. Mckenna, A.; Hanna, M.; Banks, E.; Sivachenko, A.; Cibulskis, K.; Kernytsky, A.; Garimella, K.; Altshuler, D.; Gabriel, S.; Daly, M.; et al. The genome analysis toolkit: A map reduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010, 20, 1297–1303. [Google Scholar] [CrossRef]
  21. Delcher, A.L.; Bratke, K.A.; Powers, E.C.; Salzberg, S.L. Identifying bacterial genes and endosymbiont DNA with Glimmer. Bioinformatics 2007, 23, 673–679. [Google Scholar] [CrossRef] [PubMed]
  22. Lagesen, K.; Hallin, P.; Rødland, E.A.; Stærfeldt, H.; Rognes, T.; Ussery, D.W. RNAmmer: Consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res. 2007, 35, 3100–3108. [Google Scholar] [CrossRef] [PubMed]
  23. Lowe, T.M.; Eddy, S.R. tRNAscan-SE: A program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997, 25, 955–964. [Google Scholar] [CrossRef]
  24. Gardner, P.P.; Daub, J.; Tate, J.G.; Nawrocki, E.P.; Kolbe, D.L.; Lindgreen, S.; Wilkinson, A.C.; Finn, R.D.; Griffiths-Jones, S.; Eddy, S.R.; et al. Rfam: Updates to the RNA families database. Nucleic Acids Res. 2009, 37, D136–D140. [Google Scholar] [CrossRef]
  25. Akhter, S.; Aziz, R.K.; Edwards, R.A. PhiSpy: A novel algorithm for finding prophages in bacterial genomes that combines similarity- and composition-based strategies. Nucleic Acids Res. 2012, 40, e126. [Google Scholar] [CrossRef]
  26. Buchfink, B.; Xie, C.; Huson, D.H. Fast and sensitive protein alignment using Diamond. Nat. Methods 2015, 12, 59–60. [Google Scholar] [CrossRef]
  27. Chen, L.; Zheng, D.; Liu, B.; Yang, J.; Jin, Q. VFDB 2016: Hierarchical and refined dataset for big data analysis-10 years on. Nucleic Acids Res. 2016, 44, D694–D697. [Google Scholar] [CrossRef]
  28. Liu, B.; Pop, M. ARDB--Antibiotic Resistance Genes Database. Nucleic Acids Res. 2009, 37, D443–D447. [Google Scholar] [CrossRef]
  29. Cantarel, B.L.; Coutinho, P.M.; Rancurel, C.; Bernard, T.; Lombard, V.; Henrissat, B. The Carbohydrate-Active EnZymes database (CAZy): An expert resource for Glycogenomics. Nucleic Acids Res. 2009, 37, D233–D238. [Google Scholar] [CrossRef]
  30. Huerta-Cepas, J.; Szklarczyk, D.; Forslund, K.; Cook, H.; Heller, D.; Walter, M.C.; Rattei, T.; Mende, D.R.; Sunagawa, S.; Kuhn, M.; et al. eggNOG 4.5: A hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 2016, 44, D286–D293. [Google Scholar] [CrossRef]
  31. Galperin, M.Y.; Wolf, Y.; Makarova, K.S.; Alvarez, R.V.; Landsman, D.; Koonin, E. COG database update: Focus on microbial diversity, model organisms, and widespread pathogens. Nucleic Acids Res. 2021, 49, D274–D281. [Google Scholar] [CrossRef] [PubMed]
  32. Alcock, B.P.; Raphenya, A.R.; Lau, T.T.Y.; Tsang, K.K.; Bouchard, M.; Edalatmand, A.; Huynh, W.; Nguyen, A.; Cheng, A.A.; Liu, S.; et al. CARD 2020: Antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res. 2020, 48, D517–D525. [Google Scholar] [CrossRef]
  33. Ashburner, M.; Ball, C.A.; Blake, J.A.; Botstein, D.; Butler, H.; Cherry, J.M.; Davis, A.P.; Dolinski, K.; Dwight, S.S.; Eppig, J.T.; et al. Gene Ontology: Tool for the unification of biology. Nat. Genet. 2000, 25, 25–29. [Google Scholar] [CrossRef]
  34. Kanehisa, M.; Sato, Y.; Kawashima, M.; Furumichi, M.; Tanabe, M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 2016, 44, D457–D462. [Google Scholar] [CrossRef]
  35. Vargas, W.A.; Martin, J.M.; Rech, G.E.; Rivera, L.P.; Benito, E.P.; Diaz-Minguez, J.M.; Thon, M.R.; Sukno, S.A. Plant defense mechanisms are activated during biotrophic and necrotrophic development of colletotricum graminicola in maize. Plant Physiol. 2012, 158, 1342–1358. [Google Scholar] [CrossRef]
  36. Kurtz, S.; Phillippy, A.; Delcher, A.L.; Smoot, M.; Shumway, M.; Antonescu, C.; Salzberg, S.L. Versatile and open software for comparing large genomes. Genome Biol. 2004, 5, R12. [Google Scholar] [CrossRef]
  37. Jain, C.; Rodriguez-R, L.M.; Phillippy, A.M.; Konstantinidis, K.T.; Aluru, S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat. Commun. 2018, 9, 5114. [Google Scholar] [CrossRef]
  38. Fu, L.; Niu, B.; Zhu, Z.; Wu, S.; Li, W. CD-HIT: Accelerated for clustering the next-generation sequencing data. Bioinformatics 2012, 28, 3150–3152. [Google Scholar] [CrossRef]
  39. Edgar, R.C. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004, 32, 1792–1797. [Google Scholar] [CrossRef]
  40. Edgar, R.C. MUSCLE: A multiple sequence alignment method with reduced time and space complexity. BMC Bioinform. 2004, 5, 113. [Google Scholar] [CrossRef]
  41. Nandi, T.; Ong, C.; Singh, A.P.; Boddey, J.; Atkins, T.; Sarkar-Tyson, M.; Essex-Lopresti, A.E.; Chua, H.H.; Pearson, T.; Kreisberg, J.F.; et al. A genomic survey of positive selection in Burkholderia pseudomallei provides insights into the evolution of accidental virulence. PLoS Pathog. 2010, 6, e1000845. [Google Scholar] [CrossRef] [PubMed]
  42. Zhao, Q.; Geng, M.; Xia, C.; Lei, T.; Wang, J.; Cao, C.; Wang, J. Identification, genetic diversit, and pathogenicity of Ralstonia pseudosolanacearum causing cigar tobacco bacterial wilt in China. FEMS Microbiol. Ecol. 2023, 99, fiad018. [Google Scholar] [CrossRef] [PubMed]
  43. Kai, K. The phc quorum-sensing system in Ralstonia solanacearum species complex. Annu. Rev. Microbiol. 2023, 77, 213–231. [Google Scholar] [CrossRef] [PubMed]
  44. Li, S.; Yang, L.; Ran, Y.; Ding, W. A epsB mutant of Ralstonia solanacearum as novel biocontrol agent of tobacco bacterial wilt via activating salicylic acid signalling. Physiol. Mol. Plant Pathol. 2022, 119, 101834. [Google Scholar] [CrossRef]
  45. Hamilton, C.D.; Steidl, O.R.; Macintyre, A.M.; Hendrich, C.G.; Allen, C. Ralstonia solanacearum depends on catabolism of myo-inositol, sucrose, and trehalose for virulence in an infection stage-dependent manner. Mol. Plant Microbe Interact. 2021, 34, 669–679. [Google Scholar] [CrossRef]
  46. Lowe-Power, T.M.; Khokhani, D.; Allen, C. How Ralstonia solanacearum exploits and thrives in the flowing plant xylem environment. Trends Microbiol. 2018, 26, 929–942. [Google Scholar] [CrossRef]
  47. Wang, Z.; Zhang, Y.; Bo, G.; Zhang, Y.; Chen, Y.; Shen, M.; Zhang, P.; Li, G.; Zhou, J.; Li, Z.; et al. Ralstonia solanacearum infection disturbed the microbiome structure throughout the whole tobacco crop niche as well as the Nitrogen metabolism in soil. Front. Bioeng. Biotechnol. 2022, 10, 903555. [Google Scholar] [CrossRef]
  48. Tan, X.; Dai, X.; Chen, T.; Wu, Y.; Yang, D.; Zheng, Y.; Chen, H.; Wan, X.; Yang, Y. Complete genome sequence analysis of Ralstonia solanacearum strain PeaFJ1 provides insights into its strong virulence in peanut plants. Front. Microbiol. 2022, 13, 830900. [Google Scholar] [CrossRef]
  49. Chen, K.; Zhuang, Y.; Wang, L.; Li, H.; Lei, T.; Li, M.; Gao, M.; Wei, J.; Dang, H.; Raza, A.; et al. Comprehensive genome sequence analysis of the devastating tobacco bacterial phytopathogen Ralstonia solanacearum strain FJ1003. Front. Genet. 2022, 13, 966092. [Google Scholar] [CrossRef]
  50. Sharma, P.; Johnson, M.A.; Mazloom, R.; Allen, C.; Heath, L.S.; Lowe-Power, T.M.; Vinatzer, B.A. Meta-analysis of the Ralstonia solanacearum species complex (RSSC) based on comparative evolutionary genomics and reverse ecology. Microb. Genom. 2022, 8, 000791. [Google Scholar] [CrossRef]
  51. Geng, R.; Cheng, L.; Cao, C.; Liu, Z.; Liu, D.; Xiao, Z.; Wu, X.; Huang, Z.; Feng, Q.; Luo, C.; et al. Comprehensive analysis reveals the genetic and pathogenic diversity of Ralstonia solanacearum species complex and benefits its taxonomic classification. Front. Microbiol. 2022, 13, 854792. [Google Scholar] [CrossRef]
  52. Fraser-Liggett, C.M. Insights on biology and evolution from microbial genome sequencing. Genome Res. 2005, 15, 1603–1610. [Google Scholar] [CrossRef]
Genes 15 01473 g001
Figure 1. Colony appearance (A) and cellular morphology (B) of R. solanacearum MLY91.
Figure 1. Colony appearance (A) and cellular morphology (B) of R. solanacearum MLY91.
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Figure 2. Circle graphs of the R. solanacearum MLY102 chromosome (A) and giant plasmid (B).
Figure 2. Circle graphs of the R. solanacearum MLY102 chromosome (A) and giant plasmid (B).
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Figure 3. Distribution of gene lengths of R. solanacearum MLY102.
Figure 3. Distribution of gene lengths of R. solanacearum MLY102.
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Figure 4. Functional classification of genes in R. solanacearum MLY102. (A): COG function classification; (B): GO function classification; (C): KEGG function classification.
Figure 4. Functional classification of genes in R. solanacearum MLY102. (A): COG function classification; (B): GO function classification; (C): KEGG function classification.
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Figure 5. Heatmap of average nucleotide identity (ANI) between eleven strains of R. solanacearum.
Figure 5. Heatmap of average nucleotide identity (ANI) between eleven strains of R. solanacearum.
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Figure 6. Heatmap of dispensable genes (A), Venn diagram of the pan gene set (B) and statistics of the number of homologous genes in the gene families (C) of R. solanacearum MLY102 and the reference strains.
Figure 6. Heatmap of dispensable genes (A), Venn diagram of the pan gene set (B) and statistics of the number of homologous genes in the gene families (C) of R. solanacearum MLY102 and the reference strains.
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Figure 7. Phylogenetic trees of R. solanacearum MLY102 and reference strains based on core pan (A) and gene family (B) results.
Figure 7. Phylogenetic trees of R. solanacearum MLY102 and reference strains based on core pan (A) and gene family (B) results.
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Table 1. Biochemical characteristics of R. solanacearum MLY102.
Table 1. Biochemical characteristics of R. solanacearum MLY102.
Well No.TestsResultsWell No.TestsResultsWell No.TestsResults
2APPA-21BXYL-41AGLU-
3AOD-22BAIap-42SUCT+
4PyrA-23ProA+43NAGA-
5IARL-26LIP-44AGAL-
7dCEL-27PLE-45PHOS-
9BGAL-29TyrA+46GlyA-
10H2S-31URE+47ODC-
11BNAG-32dSOR+48LDC-
12AGLTp-32dMNE-53IHISa-
13dGLU+33SAC+56CMT-
14GGT-34dTAG-57BGUR-
15OFF-35dTRE+58O129R-
17BGLU-36CIT+59GGAA-
18dMAL-37MNT-61IMLTa-
19dMAN-395KG-62ELLM-
20dMNE-40ILATk-64ILATa-
GN CardIncubation time: 7.25 h
“+” indicates that the bacterium is capable of producing a certain reaction or possessing a certain characteristic under certain conditions; “-” indicates that the bacterium is unable to produce a reaction or does not possess a characteristic under certain conditions.
Table 2. Genomic characterization of the non-coding RNA (ncRNA) R. solanacearum MLY102.
Table 2. Genomic characterization of the non-coding RNA (ncRNA) R. solanacearum MLY102.
TypeNumberAverage Length (bp)Size (bp)
tRNA6179.884873
5 s_rRNA4112448
16 s_rRNA415246096
23 s_rRNA4287711,508
sRNA2275.271656
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Lin, G.; Gao, J.; Zou, J.; Li, D.; Cui, Y.; Liu, Y.; Kong, L.; Liu, S. Whole-Genome Sequence and Characterization of Ralstonia solanacearum MLY102 Isolated from Infected Tobacco Stalks. Genes 2024, 15, 1473. https://doi.org/10.3390/genes15111473

AMA Style

Lin G, Gao J, Zou J, Li D, Cui Y, Liu Y, Kong L, Liu S. Whole-Genome Sequence and Characterization of Ralstonia solanacearum MLY102 Isolated from Infected Tobacco Stalks. Genes. 2024; 15(11):1473. https://doi.org/10.3390/genes15111473

Chicago/Turabian Style

Lin, Guan, Juntao Gao, Junxian Zou, Denghui Li, Yu Cui, Yong Liu, Lingxue Kong, and Shiwang Liu. 2024. "Whole-Genome Sequence and Characterization of Ralstonia solanacearum MLY102 Isolated from Infected Tobacco Stalks" Genes 15, no. 11: 1473. https://doi.org/10.3390/genes15111473

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