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Article

Beyond the Basics: Taxonomic Classification and Pathogenomics in Recently Discovered Dickeya dadantii Isolates

by
Mateus Sudario Pereira
1,
Diego Lucas Neres Rodrigues
1,
Juan Carlos Ariute
1,
Douglas Vinícius Dias Carneiro
1,
Pedro Alexandre Sodrzeieski
1,
Marco Aurélio Siqueira Gama
2,
Elineide Barbosa de Souza
2,
Vasco Azevedo
3,
Bertram Brenig
4,
Ana Maria Benko-Iseppon
5 and
Flavia Figueira Aburjaile
1,*
1
Preventive Veterinary Medicine Department, Veterinary School, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Minas Gerais, Brazil
2
Department of Agronomy, Universidade Federal Rural de Pernambuco, Recife 52171-900, Pernambuco, Brazil
3
Genetics, Ecology and Evolution Department, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Minas Gerais, Brazil
4
Institute of Veterinary Medicine, University Göttingen, 37077 Göttingen, Germany
5
Genetics Department, Universidade Federal de Pernambuco, Recife 50740-600, Pernambuco, Brazil
*
Author to whom correspondence should be addressed.
Taxonomy 2024, 4(4), 696-712; https://doi.org/10.3390/taxonomy4040036
Submission received: 23 May 2024 / Revised: 11 September 2024 / Accepted: 18 September 2024 / Published: 30 September 2024
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Abstract

:
The genus Dickeya consists of Gram-negative bacteria capable of causing soft rot symptoms in plants, which involves tissue breakdown, particularly in storage organs such as tubers, rhizomes, and bulbs. These bacteria are ranked among the top ten most relevant phytopathogens and seriously threaten economically valuable crops and ornamental plants. This study employs a genomic analysis approach to taxonomically classify and characterize the resistome and virulome of two new strains, CCRMP144 and CCRMP250, identified as Dickeya dadantii. These strains were found to be the causative agents of soft rot symptoms in chili pepper (Capsicum spp.) and lettuce (Lactuca sativa), respectively, in the northeastern region of Brazil. The methodology employed in silico techniques, including tetra correlation search (TCS) and Average Nucleotide Identity (ANI) analysis, in association with a phylogenomic tree inference. TCS and ANI analysis showed that the studied strains belong to the Dickeya dadantii species. The phylogenomic analysis grouped the studied strains in the D. dadantii clade. The genomic characterization demonstrates 68 virulence genes, 54 resistances of biocide and heavy metal genes, and 23 antibiotic resistance genes. As far as we know, this is the first genomic study with Brazilian D. dadantii strains. This study demonstrates the efficacy to taxonomic classification and provides insights into the pathogenesis, host range, and adaptability of these strains which are crucial for the development of more effective management and control strategies for soft rot diseases.

1. Introduction

Bacteria belonging to the Dickeya genus are Gram-negative, facultative anaerobes that possess peritrichous flagella and are usually motile. These microorganisms are also mesophilic fermenters, capable of reducing nitrate to nitrite and are primarily phytopathogens causing soft rot in their hosts [1]. Phytopathogens of the family Pectobacteriaceae, which includes the genus Dickeya, can remain asymptomatic for several generations, making disease control difficult [2]. Dickeya species have a global distribution and can infect a wide range of hosts, encompassing economically important crops such as potato (Solanum tuberosum), rice (Oryza sativa), maize (Zea mays), pineapple (Ananas comosus), banana (Musa spp.), and even orchids such as Vanda (Vanda spp.) and vanilla (Vanilla planifolia) [3]. While most isolates come from infected plants, they can also be found in aquatic ecosystems, in aerosols washed by rain, on contaminated machinery, and at harvest [2].
After undergoing multiple reclassifications, Samson et al. (2005) [1] classified members of Pectobacterium chrysanthemi (formerly known as Erwinia chrysanthemi) into the genus Dickeya. Initially, six species were classified: Dickeya chrysanthemi, Dickeya dadantii, Dickeya dianthicola, Dickeya dieffenbachiae (now a subspecies of D. dadantii [4]), Dickeya paradisiaca (reclassified as Musicola paradisiaca [5]), and Dickeya zeae. As documented by the National Center for Biotechnology Information (NCBI), a total of twelve species of this genus have been identified until April 2023, including Dickeya aquatica, Dickeya chrysanthemi, Dickeya dadantii, Dickeya dianthicola, Dickeya fangzhongdai, Dickeya lacustris, Dickeya oryzae, Dickeya parazeae, Dickeya poaceiphila, Dickeya solani, Dickeya undicola, and Dickeya zeae [6].
This pathology is characterized by the liquefaction of plant tissues, particularly storage organs such as tubers, rhizomes, and bulbs, often leading to the death of the plant. The main mechanism of soft rot is caused by plant cell wall degrading enzymes, mainly pectate lyases, which hydrolyze pectin, a heteropolysaccharide found between the middle lamella and the primary cell wall of plants [3]. They spend most of their parasitic life in the apoplasts of their hosts [7]. However, they have also been found on leaves where they can live as epiphytes [7]. Soft rot bacteria can infect other plants through wounds and natural openings such as stomata [2]. Infection can be transmitted to nearby plants through processes involving contaminated water or equipment, which can occur during activities such as plant propagation, transport, and storage [7].
The devastating effects of SRP are particularly evident during outbreaks, such as the one in 2014, which severely impacted potato crops across the United States and several other countries [8]. The Brazilian Agricultural Research Corporation (EMBRAPA) reports that the disease is more prevalent during harvest periods that coincide with hot and rainy seasons [9]. The aggressiveness of SRP increases at temperatures above 25 °C due to the stability of pectinolytic activity at temperatures close to 30 °C [10], making it a major threat to tropical countries such as Brazil. These factors have contributed to making Dickeya one of the ten most important phytopathogenic bacteria [11].
The genus Dickeya has been the subject of relatively few studies, with fewer than 200 genomes available at NCBI at the time of this research. This study aims to perform a taxogenomic classification of two new Dickeya isolates, CCRMP144 and CCRMP250, obtained from infected chili pepper (Capsicum annuum) and lettuce (Lactuca sativa), respectively, in the state of Pernambuco, northeastern Brazil. Furthermore, it seeks to characterize their set of virulence factors (virulome) and the set of genes that confer resistance to antibiotics or other antimicrobial agents (resistome). By elucidating their virulome and resistome, this research aims to establish a foundation for more targeted and efficient strategies to manage this pathogen and safeguard global agricultural production.

2. Materials and Methods

2.1. Isolation, Genomes Database, and Sequencing Data

This study employed a dataset consisting of 199 genomes (see Table S10), which included two newly isolated strains. The first strain, CCRMP144, was derived from infected sweet pepper (Capsicum annuum) in the city of Chã Grande (8.23255 S, 35.4619 W), while the second strain, CCRMP250, was obtained from infected lettuce (Lactuca sativa) in Vitória de Santo Antão (8.1263 S, 35.3075 W), both obtained in the state of Pernambuco, Brazil.
The bacterium was selectively isolated by transferring rotting tissue onto a healthy bell pepper fruit using a sterilized stick [12]. After incubating the fruit in a humid chamber for 24 h, the bacteria were directly transferred from the lesions to petri dishes containing CPG medium (1 g of hydrolyzed casein, 10 g of peptone, 10 g of glucose, 18 g of agar, and sterile distilled water (SDW) to a final volume of 1000 mL). In this medium, young colonies of pectobacteria, (after 24 h), exhibited a “broken glass” appearance when observed under a stereoscope with oblique lighting [13]. Furthermore, the strains were tested for pathogenicity on hosts including cabbage leaves, bell pepper fruits, potato tubers, and Chinese cabbage leaves. Six samples of each host were inoculated with 10 μL of a cell suspension (107 CFU/mL). After 24 to 48 h of incubation at 28 °C in a humid chamber, typical soft rot symptoms were observed, and the strains were successfully re-isolated from symptomatic zucchini fruits, thereby completing Koch’s postulates. The isolates were then preserved in SDW, lyophilized, and stored in the Rosa Mariano Culture Collection (CCRM) of the Phytobacteriology Laboratory (LAFIBAC) at the Federal Rural University of Pernambuco (UFRPE) [14].
After that, the DNA was extracted with the MiniPrep kit for bacterial genomic DNA extraction (Axygen Biosciences, Union City, CA, USA), following the manufacturer’s recommendations. The DNA was quantified by Nanodrop and then submitted to library preparation. The sequencing was conducted on the Hi-Seq 2500 platform (Illumina, San Diego, CA, USA) using a paired-end library of 2 × 150 bp. Furthermore, the remaining 197 genomes were obtained from the public genome repository of the National Center for Biotechnology (NCBI) [6]. All available genomes (until 18 April 2023) were used to create the database.

2.2. Quality Control, Assembly, and Annotation

Sequencing quality was evaluated using the FastQC tool (v0.11.9) [15]. Adapters were removed from CCRMP144 and CCRMP250 strains using AdapterRemoval v2.3.3 software [16] with default values. Finally, the genomes were assembled using the Unicycler tool (v.0.4.8) [17] with default settings.
To ensure assembly quality, QUAST software was utilized with default parameters [18]. The assembled sequences were deposited in the National Center for Biotechnology Information (NCBI) database under the following BioProject ID: PRJNA1010767. Furthermore, BUSCO v5.2.2 [19] analyzed a total of 199 genomes, including the two new isolates and NCPPB 898 and DSM 18020, which are two distinct designations of the type strain. The compiled data were compared with the enterobacterales_odb10 database. Assemblies with four or fewer missing genes (99.09% completeness or higher) were then selected for the main database. To avoid any annotation bias [20], all the genomes that successfully passed the completeness test underwent annotation via Rapid Prokaryotic Genome Annotation (PROKKA v.14.6) with default parameters [21]. All subsequent analyses were based on the resulting files generated by Prokka.

2.3. Taxonomic Classification

Species identification was achieved through a multi-step pipeline. First, the isolates went through a tetra correlation search (TCS) using the JSpeciesWS [22] to provide initial insights into phylogenomics while concurrently imposing minimal computational processing demands because it is alignment free [23].
Subsequently, we performed an Average Nucleotide Identity (ANI) using the MUMmer alignment method (ANIm) of pyANI (0.2.12) with a stringent threshold of >95%. The MUMmer algorithm was chosen for its computational efficiency over ANIb [24]. Finally, a phylogenetic tree was constructed from the genome dataset using the hybrid methodology gene method implemented by OrthoFinder (2.5.4) [25]. We used the whole dataset of genomes along with an outgroup of Pectobacterium atrosepticum (strain 21a) that was included to serve as the root for the phylogenetic analysis. This process was performed by using MSA (Multiple Sequence Alignment) algorithm for gene tree inference and default settings. The MSA method was selected rather than the default dendroBLAST, due to its superior accuracy, which is achieved through the use of maximum likelihood [26]. To visualize the genomic tree, we utilized the iTOL and the FigTree platforms [27,28].

2.4. Pan Analyses

Pan analyses were conducted using PanviTa [29] with the D. dadantii genomes. The software uses DIAMOND-BLASTp to align the predicted proteome with the CARD [30], BacMet [31], and VFDB [32] databases filtering the results based on the specified identity and coverage parameters, set at 70% identity and 70% coverage by default parameters.

3. Results

3.1. Quality Control and Standardization of the Dataset

After the trimming processes, a total of 15283716 sequences were found for CCRMP144 and 12017356 for CCRMP250. Quality control revealed that the N50 values for CCRMP144 and CCRMP250 were high, at 162961 and 187352, respectively, indicating that at least 50% of the nucleotides are located in contigs of that size or larger. As expected for high-quality assemblies, the L50 values were as low as 10 for CCRMP144 and 8 for CCRMP250. In addition, the GC content and genome size were consistent with the predicted values for the reference 3937 strain [33]. Additional information is provided in Table S1.
The sequenced genomes of CCRMP144 and CCRMP250 were deposited in the NCBI with the following accession numbers (JAVIJR000000000 and JAVIJQ000000000), respectively. From the initial 199 genomes analyzed (Table S3), 13 were excluded for not meeting the minimum completeness threshold of four or fewer missing genes, as assessed by BUSCO (Table S2). Of these excluded genomes, nine belonged to D. dadantii. The remaining 186 genomes, including two newly identified isolates, met the 99.09% completeness standard (four or fewer missing genes), as detailed in Table S3. All genomes were annotated by Prokka tool.

3.2. Taxogenomics of the Species and Its Evolutionary Relationships

3.2.1. First Insights into CCRMP144 and CCRMP250 Isolates

The clipping of the proximity identification analysis of strains CCRMP144 and CCRMP250 with other strains is shown in Table 1. It shows a Z-score of 100% between the isolates and a significant proximity between them and the 13 other strains of the Dickeya genus. Detailed tetra correlation search results are presented in Table S4 for strain CCRMP144 and Table S5 for strain CCRMP250.
Table 1 shows that the strains studied were part of the genus Dickeya, but with several related species. This study continued with an ANI analysis between the two strains and the other strains in Table S3. The heatmap with the results of the ANI analysis is shown in Figure S1. The respective values from Figure S1 are also shown in Table S6. The main collapsed values between the species are shown in Table 2.
Table 2 shows that strains CCRMP144 and CCRMP250 are present in the cluster of D. dadantii strains, with percentage identity values above 95%. The analysis showed 10 different clusters (Figure S1). Respective to each species present in the analysis, it was observed that the D. dadantii group was distinctly separated from other species, in contrast to the species of the D. zeae complex, D. zeae, D. oryzae, and D. parazeae, which are shown in two different groups. Both isolates are presented within the D. dadantii species.

3.2.2. Orthologue Analysis of CCRMP144 and CCRMP250 Isolates

After statistical similarity analysis by ANI, phylogenomic analysis followed. Figure 1 illustrates the phylogenomic tree which used the presence of orthologous genes as a metric. Monophyletic clades were collapsed into a single branch referring to the species. Figure S2 shows the complete phylogenomic tree.
The tree shows convergent results with Figure S1. Strains CCRMP144 and CCRMP250 are present in the same clade of D. dadantii strains. These results indicate that the strains can be classified as D. dadanti. Most of the clades are monophyletic, with clear separations between species. However, the phylogenomic tree also revealed the presence of the D. zeae complex, characterized by non-monophyletic clades in which several species share the same branch.

3.3. Analysis of Shared Genes Reveals the Pathogenic Potential of the Species

3.3.1. Virulome

The D. dadantii virulome consists of 68 genes. These genes are involved in various processes, including motility, effector delivery systems, immune modulation, regulation, adherence, antimicrobial activity/competitive advantage, and biofilm production as shown in Figure 2.
The functions of the identified genes were analyzed using a pan-virulome approach, which revealed that they predominantly encode motility, effector delivery systems, and immune modulation genes. These functions, along with the nutritional/metabolic factor, pre-sense accessory genes. The nutritional/metabolic factor is the only function that is not present in the main genome. The clustermap showing the presence and absence of the genes between the two strains studied and the rest of D. dadantii is shown in Figure 3.
The vgrG2 and hcp1 genes, which are accessory genes in the pangenomic analysis, were identified. The other accessory genes are not present in the two strains, with the atsS and tufA virulence genes being present in most of the strains. In the core genome, the product = “VirK/YbjX family protein” was manually found in both strains. The complete list of virulence genes and their respective mechanisms and products are shown in Table S7.

3.3.2. Resistome: Heavy Metal and Biocide Genes

A total of 54 genes were found in the BacMet database. The resistome profiles of the isolates showed the presence of all the core genes. Notably, the analysis also revealed the presence of the exclusive genes, the arsR and sdeB, as shown in Figure 4 (the full list of genes, their products, and functions can be found in Table S8).
The heavy metals and biocides presented in Figure 5 facilitate the visualization of the amount of resistance genes and their respective compounds in a pan-resistome point of view.
The genes identified provide complete resistance to 15 different heavy metals. Of all metals analyzed, only lead does not have a core gene related to its resistance. Arsenic, cobalt, zinc, iron, and magnesium are the compounds with the most coverage genes present in the analysis (over 5). The unique genes found cover zinc, tellurium, cadmium, lead, cobalt, and nickel.

3.3.3. Resistome: Antibiotic Resistance Genes

The search for antibiotic resistance genes revealed the presence of 23 genes in the CARD database (Figure 6). Notably, most of the resistome is comprised 16 core genes involved in antibiotic efflux mechanisms (Figure S3). In addition to the presence of all the core genes, the analysis identified the presence of the exclusive gene oqxB in both isolates. The full list of antibiotic resistance genes, together with their corresponding resistance mechanisms and drug classes, is given in Table S9.
Figure 7 shows a wide range of different antibiotic classes, 19 in total. Most of the antibiotics are covered by core genes. Only the antibiotic nitrofuran had only one accessory gene. The classes of antibiotic that stand out in terms of the number of resistance genes are fluoroquinolones, peptides, aminocoumarin, aminoglycoside, penam and tetracycline. The fluoroquinolone, glycylcycline, tetracycline, diaminopyrimidine, and nitrofuran classes have one accessory gene each.

4. Discussion

4.1. Evolutive and Taxonomic Aspects of Dickeya spp.

The TCS results demonstrate a high degree of correlation (≥0.99) between the isolates and all other related species, with a particularly strong correlation observed with D. dadantii (Tables S1 and S2). This indicates a significant degree of similarity in their oligonucleotide composition. This observation suggests a close evolutionary relationship or that the genomes in question may belong to the same species.
The ANI results (Table 1) indicate that both isolates exhibited ANI values of ≥95% with all other D. dadantii strains. Moreover, the phylogenomic analysis produced a tree with distinct clusters that closely align with TCS and ANI results, as well as with findings from other studies on Dickeya species [34,35,36]. The clear clustering of CCRMP144 and CCRMP250 into well-defined branches provides strong support for their classification within the D. dadantii species.
However, several D. zeae, D. oryzae, and D. parazeae strains exhibited unexpected placements, indicating distinctive evolutionary pathways. These results highlighted a controversial issue of nomenclature within the D. zeae complex. This problem has been highlighted by the investigation carried out by Hugouvieux-Cotte-Pattat, N. and Van Gijsegem, F., 2021 [37]. These findings suggest that the taxonomy of this complex remains unresolved, as evidenced by the high prevalence of misclassifications. In particular, the strain D. zeae Dze_A586-S18-A17 forms a monophyletic clade with D. parazeae strains Dpa_Ech586 and Dpa_S31 (Figure 1 and Figure S2), with ANI values of 98.71% and 98.74%, respectively, while still showing ANI levels of >95% with most D. zeae strains (Dze_A661-S21-A17, Dze_BRIP64263, Dze_CE1, Dze_JZL7, Dze_MK19, Dze_MS_2014, Dze_MS_2018, Dze_MS1, MS2, Dze_NCPPB2538, Dze_NCPPB3532, and Dze_PL65) as presented in Table S6. Similarly, all the D. oryzae strains form a separated clade with the D. zeae strains Dze_ZJU1202, Dze_EC1, Dze_DZ2Q, Dze_WH1, Dze_EC2, Dze_A5272, Dze_NCPPB3531, and Dze_A5410 as shown in Figure 1 and Figure S2. These results indicate that these species may not be accurately classified, highlighting the need for a more robust taxonomic reassessment.

4.2. Virulome and Resistome: Navigating Pathogenic Landscapes

4.2.1. Dickeya dadantii Virulome

The virulome analysis of Dickeya dadantii reveals a wide range set of genes that contribute to its pathogenicity, highlighting the complex interplay of various virulence factors. For instance, the core virulome includes a suite of flagellar biosynthesis and chemotaxis genes (e.g., fliA, fliG, flhA, and cheA) (Figure 3 and Table S7), which are crucial for the assembly and function of the flagellum in many bacteria [38,39,40,41], including Dickeya dadantii, which was also found to be essential for the manifestation of various bacterial phenotypes, including biofilm formation in culture, bacterial adherence to plant tissue, and even the expression of pectate lyase activity [42]. The presence of these genes (Figure 2) corroborates with the hypothesis that active movement is crucial for the successful establishment of infection as previously described [43].
The prevalence of Type VI secretion system (T6SS) components, such as vipA, vipB, and vgrG2, further highlights the role of this complex in effector delivery. The T6SSs have the capacity to inject proteins into both eukaryotic cells and Gram-negative bacteria [44], which may indicate that the role of T6SS in D. dadantii extends beyond interbacterial interactions. Indeed, studies have indicated that they may also play a role in host–bacteria interactions in other phytopathogens [45,46].
Furthermore, both isolates were found to be missing two virulence genes (atsS and tufA) that are commonly present in the majority of the strains (Figure 3). The atsS protein functions as a component of the Type VI secretion system, which in Pseudomonas aeruginosa facilitates the delivery of effector molecules between bacterial cells [47]. The tufA product is the elongation factor thermal unstable Tu (EF-Tu), which is one of the most frequently occurring proteins found in bacteria. Various functions have been reported in the literature, including significant virulence factors such as adhesion to extracellular matrix components of the host [48]. It is important to note that antimicrobial resistance and virulence can have a negative or positive relationship and are not two independent characteristics; for example, in uropathogenic strains of E. coli, the acquisition of antibiotic resistance can induce the loss of virulence factors and biofilm formation [49]. The absence of these genes could also be explained by the fact that bacteria adjust their gene expression to optimize survival and growth in certain environments, resulting in variable or conditional gene expression, but further research is needed to establish the impact of the absence of these genes on virulence, given the detection of these isolates causing symptoms [50].
It is noteworthy that pectinases play a crucial role in the virulence of D. dadantii and are secreted through a Type-II secretion system [51]. Several genes are involved in the process of pectin degradation. These genes could not be found by the pan analyses as they are not present in the VFDB. However, the annotated genomes of the isolates identified the presence of pectin-degradation-related genes. Of the eight endo-pectate lyase genes identified in D. dadantii, only four were found in both isolates: pelA, pelC, pelE, and pelL. Additionally, two genes encoding exo-pectate lyases (pelX and pelW) were identified, which cleave pectin using a β-elimination mechanism that relies on calcium as a divalent cation cofactor 4. Furthermore, the presence of genes (pemA and pemB) whose products are pectin methylesterases (PME) was identified. These enzymes modify pectin enzymes by hydrolyzing the glycosidic bonds of pectic substances [52]. The presence of genes encoding pectin-degrading proteins was expected as they are required for the successful pathogenesis of soft rot bacteria [7,53].
Overall, the presented virulome analysis provides valuable insights into the pathogenic strategies of D. dadantii, emphasizing the crucial roles of motility, secretion systems, and regulatory networks in its virulence. The identification of both core, accessory, and exclusive virulence genes also suggests potential targets for future studies aimed at developing targeted control strategies against this pathogen.

4.2.2. Dickeya dadantii: Heavy Metal, Biocide, and Antibiotics Resistance Profile

The core genes, which are present across all bacterial isolates, are of fundamental importance with regard to survival and adaptation. Among these, genes involved in metal transport and homeostasis, such as the corA gene, play a pivotal role in regulating the uptake and balance of essential metals, including magnesium, nickel, and cobalt. Similarly, they are also involved in the virulence of other soft rot bacteria [54]. It is plausible that these genes are also involved in the virulence of D. dadantii. Additionally, the core genes encoding multidrug resistance efflux pumps, such as acrB and mdtB (Table S8), illustrate the bacteria’s broad-spectrum defense mechanisms. These efflux systems are capable of expelling a diverse range of toxic compounds, including heavy metals such as zinc, copper, tungstate, and antibiotics [55].
Moreover, the heavy metal and biocide resistance profile indicated the presence of a few genes that were exclusive to the isolates, the arsR and sdeB (Figure 4). The arsR gene is linked to bacterial resistance to arsenic and is commonly present in human pathogenic bacteria. Arsenic is a notable global environmental pollutant, which has various sources such as household and industrial discharges, as well as natural occurrences in both aquatic and terrestrial ecosystems. In addition to its bioaccumulate and carcinogenic properties, its environmental impact is also intensified by its widespread use in pesticides, semiconductors, medicinal applications, and pigments [56]. In pseudomonas, this gene encodes a repressor that controls the expression of the ars operon [57] Notably, the gene asrB gene was also identified in strains Dda_DSM18020, Dda_CZ1501, and Dda_ICMP9290 (Figure 4), being the heavy metal with the highest number of related genes as shown in Figure 5. The presence of an additional gene associated with arsenic resistance in both isolates may be attributed to the soil type from which they were extracted, which may have a higher arsenic concentration. The second exclusive gene identified in the isolate’s repertoire was sdeB, which is related to resistance to a broad range of antimicrobial agents and disinfectants as shown in Table S8. The same gene in Serratia marcescens functions as a multidrug efflux protein within the sdeAB-tolC efflux system, conferring resistance to antibiotic substances such as fluoroquinolones [58,59]. While the link between the resistome and the pathogenesis process of D. dadantii may not be completely elucidated, in some cases efflux pumps may also have a role in competition and host specificity. For example, the isolates’ exclusive gene sdeB (Figure 4) participates in the extrusion of the antimicrobial plant chemical berberine [60]. In this context, the significant number of core genes linked to antibiotic efflux (Figure S3) could potentially confer resistance to defensive chemicals produced by plants.
Furthermore, the findings from the CARD database indicate that resistance genes are linked to various major antibiotic classes, including macrolides, aminoglycosides, fluoroquinolones, and tetracyclines, and are predominantly situated within the core genome (Figure 7). The presence of these genes in both core and accessory categories suggests that while the primary mechanisms of resistance are well conserved, there is also some variability that could be associated with the adaptation to specific environmental pressures or hosts [61], which is evidenced by the presence of the Bado_rpoB_RIF and oqxB genes in their resistome (Figure 6). While further studies are necessary to confirm whether the presence of both genes can confer resistance to the associated classes of antibiotics, detergents, and disinfectants (Table S9), in some cases like the oqxB gene, only its overexpression is already enough to provide resistance [62]. Interestingly, some antibiotic classes, such as nitrofuran, are exclusively represented by the accessory gene, oqxB, which is present only in the CCRMP144 and CCRMP250 strains, indicating a more sporadic distribution that may reflect more recent or localized acquisitions of resistance. The sporadic presence of the oqxB gene in the isolates may be attributed to horizontal gene transfer events that have not yet become fixed within the bacterial populations. However, further research is necessary to verify the specific mechanisms by which these isolates acquired the oqxB gene and to investigate their ecological implications within D. dadantii.

5. Conclusions

This study represents a pioneering effort in the investigation of D. dadantii isolates from Brazil where research on this pathogen has been limited. This study is one of the first to use an in silico methodology for the taxonomic classification and characterization of virulence and resistance-associated genes in the Brazilian context. Our study has successfully taxonomically classified the isolates, characterized their phylogenetic relationships as well, and delved into their virulome and resistome profiles. The virulence and resistance factors were mapped, providing an understanding of the pathogenic potential of these isolates in comparison with all other described D. dadantii strains. The identification and characterization of specific virulence and resistance genes can facilitate targeted approaches and offer promising directions for the development of soft rot-resistant crops or the development of innovative control strategies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/taxonomy4040036/s1, Figure S1: Average Nucleotide Identity of the 186 Dickeya genomes; Figure S2: Phylogenomic tree with all 186 Dickeya genomes; Figure S3: Pan-resistome of antibiotic resistance mechanisms; Table S1: reference of the 199 Dickeya genomes; Table S2: Quast parameters for assembly quality control of studied strains; Table S3: Strains removed from dataset; Table S4: Origin and reference for strains used in this study; Table S5: Tetra correlation search and Z-score for the CCRMP144; Table S6: Tetra correlation search and Z-score for the CCRMP250; Table S7: ANI percentage identities; Table S8: Dickeya dadantii virulence genes; Table S9: Dickeya dadantii biocide and heavy metals resistance genes; Table S10: Dickeya dadantii antibiotic resistance genes.

Author Contributions

Conceptualization, A.M.B.-I. and F.F.A.; methodology, A.M.B.-I. and F.F.A.; formal analysis M.S.P., D.L.N.R., P.A.S. and J.C.A.; resources, A.M.B.-I., B.B., V.A. and F.F.A.; data curation, M.S.P., D.L.N.R., J.C.A., D.V.D.C. and P.A.S.; writing—original draft preparation, M.S.P., D.V.D.C. and P.A.S.; writing—review and editing, M.S.P., D.L.N.R., J.C.A., D.V.D.C., P.A.S., M.A.S.G., E.B.d.S. and F.F.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by UFMG/REITORIA/PRPQ/FUNDO FUNDEP 01/2022 (No. 30201*18) and prize awarded by L’ORÉAL-UNESCO-ABC Para Mulheres na Ciência 2023—Life Sciences category.

Data Availability Statement

All data and materials used are available in this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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Taxonomy 04 00036 g001
Figure 1. Collapsed phylogenomic tree inference using orthologues. Rooted maximum likelihood phylogeny of the 186 Dickeya strains. Monophyletic clades of D. fangzhongdai, D. dianthicola, D. solani, and D. chrysanthemi were collapsed into single species branch. Each species is denoted by a distinct color. The Pectobacterium atrosepticum (Pat_21A) was used as an outgroup. The strains CCRMP144 and CCRMP250 are highlighted in yellow.
Figure 1. Collapsed phylogenomic tree inference using orthologues. Rooted maximum likelihood phylogeny of the 186 Dickeya strains. Monophyletic clades of D. fangzhongdai, D. dianthicola, D. solani, and D. chrysanthemi were collapsed into single species branch. Each species is denoted by a distinct color. The Pectobacterium atrosepticum (Pat_21A) was used as an outgroup. The strains CCRMP144 and CCRMP250 are highlighted in yellow.
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Figure 2. Bar chart showing the pan-virulome and its associated mechanisms. The x-axis represents the different mechanisms, while the y-axis represents the number of genes. The bars are color coded to distinguish among core, accessory, and exclusive gene categories.
Figure 2. Bar chart showing the pan-virulome and its associated mechanisms. The x-axis represents the different mechanisms, while the y-axis represents the number of genes. The bars are color coded to distinguish among core, accessory, and exclusive gene categories.
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Figure 3. Clustermap indicating the presence of virulence genes in D. dadantii compared to the Virulence Factor Database (VFDB) database. The x-axis represents the genes found, while the y-axis represents the D. dadantii strains. The color gradient serves to highlight the identity level.
Figure 3. Clustermap indicating the presence of virulence genes in D. dadantii compared to the Virulence Factor Database (VFDB) database. The x-axis represents the genes found, while the y-axis represents the D. dadantii strains. The color gradient serves to highlight the identity level.
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Figure 4. Clustermap indicating the heavy metal and biocide resistance genes between D. dadantii against BacMet database. The x-axis represents the heavy metal and biocide resistance genes, while the y-axis represents the D. dadantii strains. The color gradient serves to highlight the identity level.
Figure 4. Clustermap indicating the heavy metal and biocide resistance genes between D. dadantii against BacMet database. The x-axis represents the heavy metal and biocide resistance genes, while the y-axis represents the D. dadantii strains. The color gradient serves to highlight the identity level.
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Figure 5. Bar chart showing heavy metal compounds from a pan-resistome perspective. The x-axis represents the different heavy metals, while the y-axis represents the number of genes found within the genus. The bar colors blue, orange, and green represent core, accessory, and exclusive, respectively.
Figure 5. Bar chart showing heavy metal compounds from a pan-resistome perspective. The x-axis represents the different heavy metals, while the y-axis represents the number of genes found within the genus. The bar colors blue, orange, and green represent core, accessory, and exclusive, respectively.
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Figure 6. Clustermap illustrating the presence of antibiotic resistance genes in D. dadantii compared to the CARD database. The x-axis represents antibiotic resistance genes, while the y-axis represents the D. dadantii strains. The color gradient serves to highlight the identity level.
Figure 6. Clustermap illustrating the presence of antibiotic resistance genes in D. dadantii compared to the CARD database. The x-axis represents antibiotic resistance genes, while the y-axis represents the D. dadantii strains. The color gradient serves to highlight the identity level.
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Figure 7. Bar chart showing a pan-resistome perspective of the drug classes. The x-axis represents the different drug classes, while the y-axis represents the number of genes found within the genus. The bar colors blue, orange, and green represent core, accessory, and exclusive, respectively.
Figure 7. Bar chart showing a pan-resistome perspective of the drug classes. The x-axis represents the different drug classes, while the y-axis represents the number of genes found within the genus. The bar colors blue, orange, and green represent core, accessory, and exclusive, respectively.
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Table 1. A cross-section of tetra correlation search values with the two strains studied. Showing the nearby species, strains referring to the species, the family to which they belong, and the Z-score of the two strains.
Table 1. A cross-section of tetra correlation search values with the two strains studied. Showing the nearby species, strains referring to the species, the family to which they belong, and the Z-score of the two strains.
SpeciesStrainFamilyZ-Score CCRMP144Z-Score CCRMP250
Dickeya spp. CCRMP144 Pectobacteriaceae1 1
Dickeya spp. CCRMP250 Pectobacteriaceae1 1
Dickeya dadantii3937 Pectobacteriaceae0.99980 0.99980
Dickeya dadantii subsp. dieffenbachiaeNCPPB 2976 Pectobacteriaceae0.99966 0.99965
Dickeya fangzhongdaiM005 Pectobacteriaceae0.99905 0.99904
Dickeya fangzhongdaiM074 Pectobacteriaceae0.99903 0.99903
Dickeya fangzhongdaiND14b Pectobacteriaceae0.99903 0.99903
Dickeya fangzhongdaiCGMCC1.15464 Pectobacteriaceae0.99894 0.99894
Dickeya fangzhongdaiDSM101947 Pectobacteriaceae0.99893 0.99893
Dickeya solaniDs0432-1 Pectobacteriaceae0.99887 0.99887
Dickeya solaniIPO2222 Pectobacteriaceae0.99881 0.99881
Dickeya solaniIPO2222 Pectobacteriaceae0.99879 0.99879
Dickeya dianthicolaNCPPB453 Pectobacteriaceae0.99681 0.99682
Table 2. Average ANI values per species compared to the strains studied. The strains have been collapsed by species and the values are mirrored.
Table 2. Average ANI values per species compared to the strains studied. The strains have been collapsed by species and the values are mirrored.
StrainsCCRMP144CCRMP250D. dadantiiD. solaniD. fangzhongdaiD. dianthicolaD. undicolaD. chrysanthemiD. poaceiphilaD. zeaeD. parazeaeD. oryzaeD. lacustris
CCRMP1441.000
CCRMP2501.0001.000
D. dadantii0.9760.9761.000
D. solani0.9420.9420.9421.000
D. fangzhongdai0.9250.9250.9250.9271.000
D. dianthicola0.9220.9220.9220.9220.9221.000
D. undicola0.8960.8960.8930.8960.9180.8931.000
D. chrysanthemi0.8810.8810.8800.8770.8770.8800.8661.000
D. poaceiphila0.8720.8720.8730.8710.8730.8740.8630.8721.000
D. zeae0.8650.8650.8640.8630.8640.8650.8590.8730.8701.000
D. parazeae0.8650.8650.8650.8630.8640.8660.8590.8740.8700.9551.000
D. oryzae0.8640.8640.8730.8620.8630.8660.8600.8720.8710.9570.9451.000
D. lacustris0.8490.8480.8480.8450.8470.8480.8450.8510.8480.8500.8520.8501.000
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Pereira, M.S.; Rodrigues, D.L.N.; Ariute, J.C.; Carneiro, D.V.D.; Sodrzeieski, P.A.; Gama, M.A.S.; de Souza, E.B.; Azevedo, V.; Brenig, B.; Benko-Iseppon, A.M.; et al. Beyond the Basics: Taxonomic Classification and Pathogenomics in Recently Discovered Dickeya dadantii Isolates. Taxonomy 2024, 4, 696-712. https://doi.org/10.3390/taxonomy4040036

AMA Style

Pereira MS, Rodrigues DLN, Ariute JC, Carneiro DVD, Sodrzeieski PA, Gama MAS, de Souza EB, Azevedo V, Brenig B, Benko-Iseppon AM, et al. Beyond the Basics: Taxonomic Classification and Pathogenomics in Recently Discovered Dickeya dadantii Isolates. Taxonomy. 2024; 4(4):696-712. https://doi.org/10.3390/taxonomy4040036

Chicago/Turabian Style

Pereira, Mateus Sudario, Diego Lucas Neres Rodrigues, Juan Carlos Ariute, Douglas Vinícius Dias Carneiro, Pedro Alexandre Sodrzeieski, Marco Aurélio Siqueira Gama, Elineide Barbosa de Souza, Vasco Azevedo, Bertram Brenig, Ana Maria Benko-Iseppon, and et al. 2024. "Beyond the Basics: Taxonomic Classification and Pathogenomics in Recently Discovered Dickeya dadantii Isolates" Taxonomy 4, no. 4: 696-712. https://doi.org/10.3390/taxonomy4040036

APA Style

Pereira, M. S., Rodrigues, D. L. N., Ariute, J. C., Carneiro, D. V. D., Sodrzeieski, P. A., Gama, M. A. S., de Souza, E. B., Azevedo, V., Brenig, B., Benko-Iseppon, A. M., & Aburjaile, F. F. (2024). Beyond the Basics: Taxonomic Classification and Pathogenomics in Recently Discovered Dickeya dadantii Isolates. Taxonomy, 4(4), 696-712. https://doi.org/10.3390/taxonomy4040036

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