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Article

High-Quality Complete Genome Resource for Dickeya dadantii Type Strain DSM 18020 via PacBio Sequencing

by
Yi Cheng
1,2,
Jianping Xu
3,
Zhiqiang Song
2,
Wenting Li
2,
Jiayang Li
2,
Zhecheng Xu
2,
Fengming Chen
1,*,
Huajiao Qiu
1,2,* and
Tuhong Wang
2,*
1
Hunan Provincial Key Laboratory of the Traditional Chinese Medicine Agricultural Biogenomics, Changsha Medical University, Changsha 410219, China
2
Institute of Bast Fiber Crops and Center of Southern Economic Crops, Chinese Academy of Agricultural Sciences, Changsha 410205, China
3
Department of Biology, McMaster University, Hamilton, ON L8S 4K1, Canada
*
Authors to whom correspondence should be addressed.
Agronomy 2024, 14(7), 1342; https://doi.org/10.3390/agronomy14071342
Submission received: 20 May 2024 / Revised: 12 June 2024 / Accepted: 14 June 2024 / Published: 21 June 2024
(This article belongs to the Special Issue Advanced Research on Diagnosis and Biological Control of Crop Diseases)
Browse Figures
Versions Notes

Abstract

:
Dickeya dadantii is a common pathogen of bacterial soft rot on a wide range of plants, including several crops. In this study, we present the complete genome sequence of the D. dadantii type strain DSM18020T. The genome was assembled using PacBio technology, resulting in a 4,997,541 bp circular chromosome with a G+C content of 56.5%. Our sequence analyses predicted 4277 protein-encoding genes, including several associated with known bacterial virulence factors and secondary metabolites. Comparative genomics analysis between Dickeya revealed that the category of ‘metabolism’ is the most important in both the core and accessory genomes, while the category of ‘information storage and processing’ is the most dominant in unique genomes. These findings will not only help us to understand the pathogenic mechanisms of D. dadantii DSM18020T, but also provide us with useful information for new control strategies against this phytopathogen.

1. Introduction

Bacterial soft rot, caused by the Dickeya bacteria, result in significant economic losses in a wide range of crops and ornamentals [1,2,3,4]. The genus Dickeya is one of the ten most bacterial pathogens [5] and belongs to the family Pectobacteriaceae of the order Enterobacterales. The genus was first defined in 2005 based on six species [6], and since then it has been expanded to include twelve species. Each of the species in the genus Dickeya is capable of causing disease in at least 35% of angiosperm, causing significant losses in crop yield and food safety [7]. Dickeya dadantii is the causal agent of bacterial soft rot diseases of numerous plants, including orchids, peppers, potatoes, tomatoes, onions, rice, sugarcane and maize [8,9,10,11]. Strain DSM18020T, which is also known as D. dadantii CFBP 1269, NCPPB 898 or LMG 25991, represents the type strain of this species. The original isolation of this strain occurred in 1960 from a diseased Pelargonium capitatum (rose geranium, a common garden flower) in Comoros [3,12,13,14]. However, this species has since been identified in many plants and geographical locations across the globe [15].
The traditional bacterial identification methods are inadequate for distinguishing between different species of the Dickeya genus due to their high degree of homology [16]. The use of whole-genome sequence information as a taxonomic tool is becoming increasingly prevalent in bacterial taxonomy, supplanting other commonly used methods, such as the 16S rRNA sequence-based method [17]. The type stain represents a fundamental aspect of taxonomic, phylogenetic, and functional studies [18]. Nevertheless, there is a paucity of data regarding the complete genome of D. dadantii DSM 18020T.
The growing availability of complete bacterial genomes has facilitated a deeper understanding of bacterial evolution and has played a pivotal role in the comparison of complete bacterial genomes and the discovery of gene clusters. In order to gain a more profound comprehension of the pathogenic mechanism of D. dadantii, DSM18020T was selected for genome sequencing. In this report, we present the results of sequencing the complete genome of D. dadantii type strain DSM 18020 using PacBio RS II single-molecule real-time (SMRT) sequencing technology. In addition, a genome-wide analysis was conducted to identify secondary metabolite gene clusters, with the results being with those of other Dickeya spp. by the Bacterial Pangenome Analysis Tool (BPGA) [19].

2. Materials and Methods

2.1. D. dadantii Strain, Growth Conditions, and Genomic DNA Isolation

The D. dadantii type strain DSM18020 (D. dadantii strain CFBP 1269) was obtained from the Leibniz Institute DSMZ-German Collection of Microorganisms (Braunschweig, Germany). The strain was cultivated in LB broth (tryptone 10.0 g/L, yeast extract 5.0 g/L, NaCl 10.0 g/L) at 37 °C with vigorous shaking and its genomic DNA was extracted. The genomic DNA was extracted from the cells collected from the liquid culture using the Promega bacterial DNA kit (Promega Corporation, Madison, WI, USA) in accordance with the manufacturer’s instructions. The quality of the extracted DNA was determined using a NanoDrop 2500 spectrophotometer (Thermo Scientific, Waltham, MA, USA).

2.2. Genomic Sequencing, Assembly and Annotation

The complete genome was sequenced on the PacBio RS II platform using single-molecular, real-time (SMRT) technology. Following read filtering and adapter trimming, the genome was assembled de novo using SMRT Analysis 2.3.0 and the HGAP assembly protocol [20,21,22].
Genome sequence annotation, including predicted protein-coding genes, transfer RNAs (tRNAs), and ribosomal RNAs (rRNAs), was performed using the prokaryotic genome annotation pipeline of the National Center for Biotechnology Information (NCBI, https://www.ncbi.nlm.nih.gov/, accessed on 5 June 2018). The Clusters of Orthologous Groups (COGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and non-redundant databases (NR) were employed to functionally classify all scored open reading frames (ORFs) [23]. Antibiotic resistance genes were predicted using the CARD database (Version 1.1.3) [24]. Virulence genes were predicted by comparing the assembled genome sequence with the bacterial Virulence Factor Database (VFDB) (Version 2016.03) [25]. The secreted proteins were predicted using SignalP v4.1 (http://www.cbs.dtu.dk/services/SignalP, accessed on 5 June 2018). The repetitive genomic sequences were annotated using RepeatMasker v4.0.7 (http://www.repeatmasker.org/, accessed on 5 June 2018). The Carbohydrate-Active enZymes (CAZy) database (http://www.cazy.org/, accessed on 5 June 2018) was employed to analyze carbohydrate-active enzymes. The Transmembrane Hidden Markov Model TMHMM v2.0 (http://www.cbs.dtu.dk/services/TMHMM/, accessed on 5 June 2018) was utilized to predict the presence of transmembrane proteins.

2.3. Phylogenetic Analysis and Genome Comparisons

Average nucleotide identities (ANI) and DNA-DNA hybridization (dDDH) analyses were conducted utilizing the OrthoANI algorithm and the Genome-to-Genome Distance Calculator (GGDC) 3.0 with the formula 2 (accessed on 9 June 2024), respectively [26,27]. Phylogenetic trees were constructed using the Reference Sequence Alignment Phylogeny builder (REALPHY, http://realphy.unibas.ch, accessed on 9 June 2024) [28] and the Type (strain) Genome Server (TYGS, https://tygs.dsmz.de/, accessed on 13 May 2024) [29]. For secondary metabolite gene cluster analysis, antiSMASH 7.1.0, NapDoS2, NP.searcher, BAGEL4, and PRISM4 were used [30,31,32,33,34]. The pan-genome BPGA1.3 was used to evaluate the Core-Pan plot, COGs, and KEGG in the genome data employed in this investigation [19]. These genome datasets are listed in Table S1 and were downloaded from NCBI.

2.4. Accession Number

The complete genome of D. dadantii type strain DSM18020 has been submitted to the GenBank database under the accession number CP023467. This is the inaugural version of the genome sequence, as described in this paper.

3. Results

3.1. Genome Sequencing and Assembly Results

The complete genome sequence of strain DSM18020T was obtained from 63,801 high-quality reads, comprising 469,783,300 base pairs (bp) with an average length of 7363 bp/nt, via PacBio sequencing. The sequencing reads were assembled using the HGAP algorithm (Table 1) [35]. The assembled genome is composed of a single circular chromosome (Figure 1), with a length of 4,997,541 bp and an average coverage of 94.0-fold. The G+C content of the chromosome is 56.5%. A total of 4277 protein-coding genes were predicted, along with 75 tRNAs, 22 rRNAs, and 73 pseudogenes. Furthermore, 14 genomic islands were identified, with a total length of 360,924 bp and an average length of 25,780 bp, which contain 414 associated CDS. However, no plasmid was found in this strain (Table 1).

3.2. Genome Annotation

A total of 5476 ORFs and 4455 genes were identified by comparing the sequence data with various databases. A total of 4645 (84.8%), 3905 (71.3%), 4497 (82.1%), and 4944 (90.3%) ORFs were successfully annotated in the COG, GO, KEGG, and NR databases, respectively (Figure S1). Of the 4277 predicted protein-coding genes, 3554 functional genes of the DSM 10820T genome were categorized using the COG database. Many of the genes were categorized as belonging to general function prediction only (388 genes), the biosynthesis, transport, and catabolism of secondary metabolites (314 genes), transport and metabolism of inorganic ions (299 genes), transport and metabolism of lipids (291 genes), transport and metabolism of coenzymes (280 genes), and transport and metabolism of carbohydrates (267 genes) are among the processes that have been identified. Of the 4277 protein-coding genes, 3023 were linked to 185 different KEGG pathways. Carbohydrate-active enzyme predictions include 6 carbohydrate-binding modules, 11 auxiliary activities, 18 polysaccharide lyases, 35 glycosyl transferases, and 54 glycoside hydrolases (Table S2).
A comparison with the VFDB core database revealed that 563 exhibited significant similarity to known bacterial virulence factors. The analysis identified 19 genes associated with the type III secretion system, 1 gene associated with the type IV secretion system, 23 genes associated with the type VI secretion system, and 41 genes associated with flagella (Table S3). Furthermore, the breakdown of plant cell wall pectin plays a crucial role in the virulence of the plant pathogen Dickeya dadantii. In this genome, we predicted 20 genes associated with pectin degradation (Table 2). Additionally, by comparing the CARD database, 36 genes involved in drug resistance were identified. Furthermore, secondary metabolite gene clusters were identified utilizing the antiSMASH7.1.0 software, resulting in the annotation of 10 secondary metabolite gene clusters. The major secondary metabolite synthesis gene clusters were NRPS gene clusters. One of the identified gene clusters exhibited showed 100% similarity to the trichrysobactin biosynthesis gene cluster (BGC0002414), while another showed 60% similarity to the minimycin biosynthesis gene cluster (BGC0000375). Furthermore, the strain was shown to possess additional unique gene clusters for the synthesis of cyanobactin, NI-siderophore, and isocyanide, among others (Table 3). Furthermore, the DSM 18020T genome was analyzed using NapDoS, NP.searcher, PRISM, and BAGEL4 to identify secondary products and gene clusters. The results demonstrated the identification of gene clusters in the genome, as follows: epothilone, fatty acid, leinamycin, virginiamycin, and kirromycin synthesis. The BAGEL tool was used to identify two gene clusters, AOI_01 and AOI_02, in the genome. AOI_01 contains a plethora of enzymes, including ATP-binding proteins, esterases, phosphoribulose kinases, cAMP-activated global transcriptional regulators, glycosyl hydrolases, and others. The AOI_02 gene cluster contains a plethora of crucial genes, including multiple replication-associated recombinant proteins, esterases, Tat proofreading chaperone proteins, transcriptional activators, formate acetyltransferases, and ribosomal protein S12 methyl-sulfotransferase cofactor YcaO (Table S4).

3.3. A High-Quality Genome

The strain DSM 18020T is a Gram-negative, motile, rod-shaped, facultative anaerobic bacterium that exhibits necrotrophic characteristics [10]. Its length is approximately 2 µm, while its width is 0.75 µm. It was isolated from a diseased Pelargonium capitatum in Comoros in 1960. A previous study reported the draft genome sequence of this strain (=D. dadantii 898, accession number: CM001976.1) [36]. However, the genome was sequenced using the 454 sequencing technique, had a low read depth (19.0× coverage), and incomplete assembly with 52 contigs. The N50 was 191.3 kb, and the genome size for this strain was estimated at 4.9 Mb, containing 4261 protein-coding genes. It is noteworthy that within the genus Dickeya, most genetic and virulence studies have been conducted on D. dadantii 3937, which was isolated from African violet (Saintpaulia ionantha). Glasner et al. (2011) [37] also published the genome sequence of D. dadantii 3937. The complete circular chromosome of D. dadantii 3937 is 4,922,802 bp in length with a GC content of 57%. A total of 4543 protein-coding genes, 22 rRNA genes, 75 tRNA genes, and 20 non-coding RNA genes have been predicted or identified. Table 4 presents additional genome annotation statistics for this strain and 3937. The data indicate that our sequenced genome has a higher quantity of data, superior coverage, and a greater number of predicted genes. This suggests that our results are of superior quality.

3.4. Phylogenetic Analysis of DSM 18020T Based on Whole-Genome Sequences

The evolutionary relationships obtained by studying only a single or a few genes are not a reliable indicator of the taxonomic status and evolutionary relationships of Dickeya. In order to understand the taxonomy, genetic background, and evolutionary history of Dickeya more accurately, it is necessary to conduct evolutionary analyses based on whole-genome sequences. Therefore, a genetic diversity analysis of the all-available D. dadantii strains based on complete sequence was conducted using the REALPHY tool (http://realphy.unibas.ch, accessed on 9 June 2024). The complete genome sequences of the 27 Dickeya strains and 3 Enterobacterales strains were submitted to the online REALPHY pipeline in FASTQ format and the whole-genome DNA sequences were submitted to the TYGS (https://tygs.dsmz.de, accessed on 13 May 2024). The results demonstrated that all D. dadantii strains exhibited a high degree of similarity and clustered together in close proximity to D. solani type strain IPO 2222. All D. dadantii strains were subdivided into two subbranches, D. dadantii subsp. dieffenbachiae NCPPB 2976, D. dadantii S3−1, D. dadantii A622−S1−A17, and D. dadantii FZ06 cluster together as one branch, and the others clustered into one branch (Figure 2 and Figure S2). Similar to the phylogenetic analyses, the ANI and dDDH analyses showed that D. dadantii subsp. dieffenbachiae NCPPB 2976 exhibited >96% ANI and >70% dDDH values with D. dadantii S3−1, D. dadantii A622−S1−A17, and D. dadantii FZ06 (Figure S3).

3.5. Comparative Analysis of DSM 18020T with Other Dickeya spp.

To elucidate the genome characteristics and distinctions between the DSM 18020T in this study and Dickeya species in the database, we conducted a pan-genome analysis of the 14 type strains. Overall, Dickeya exhibited an open pan-genome, with the emergence of novel genes as more sequenced genomes are incorporated into the analysis. Furthermore, analysis of the core genome revealed a reduction in the number of shared genes with the addition of more input genomes (Figure 3).
COG analyses revealed that the core and accessory genes were predominantly involved in metabolism processes, while unique genes were also implicated in information storage and processing (Figure 4A,C). KEGG comparative analyses demonstrated that these genes were primarily responsible for fundamental functions such as metabolism and environmental information processing (Figure 4B). In particular, the core genes exhibited a significant association with essential functions, including metabolism, genetic information processing, and replication. As shown in Figure 4D, accessory genes are more involved in carbohydrate metabolism and signal transduction, whereas unique genes exhibit a diverse distribution with a notable representation in human disease pathways and xenobiotic metabolism.
Despite the ANI and dDDH values between D. dadantii DSM 18020T and 3937 being 98.4% and 85.4% (Distance = 0.0172, Prob. DDH = 93.9), respectively, D. dadantii 3937 is the reference genome for the species that has been widely used as a model system for molecular biology studies of the species. A comparative analysis was therefore conducted of these two strains.
The genome of D. dadantii DSM 18020T exhibited high synteny with that of D. dadantii 3937, indicating a high degree of homology (Figure S3A). COG and KEGG analyses demonstrated that the majority of the proteins could be classified into known COG functional categories and core metabolic pathways, with only a few COG categories and KEGG pathways exhibiting differences in their distribution between the two genomes (Figure S4B,C). This indicates that the two genomes exhibit extensive functional similarities and exhibit minimal differences in their adaptive evolution in the environment. Secondary gene cluster analysis revealed the similarities and differences in the composition and arrangement of gene clusters between the two genomes. In addition to some shared gene clusters, there are three unique gene clusters (Cluster 4, 5, 7) associated with bacteriocin and NRPS that were identified in DSM 18020T (Figure S4D). These findings help us understand the diversity and complexity of the two genomes at the gene level.

4. Discussion

The members of the Dickeya genus are responsible for the soft rot of plants, including food crops, economic crops, and horticultural crops during the growing season [38,39,40]. They can also cause the occurrence of soft rot diseases after fruit and vegetable harvest [2,41]. In this study, we conducted a deep sequencing of the D. dadantii type strain 18020. Compared with the earlier draft genome sequencing results [36], the genomic data of this study are more extensive in terms of data volume and coverage. It is predicted that the strain contains 4277 protein-coding genes, which is 885 more ORFs than the previously released version.
The appearance of soft rot disease symptoms is a consequence of the secretion of plant cell wall-degrading enzymes (PCDE) by Dickeya spp. to degrade plant cell walls [42,43], such as pectinases, polygalacturonases, cellulases, and proteases. One of the most important exoenzymes among these enzymes are pectinases which degrade the pectin of plant cell walls and may cause soft rot symptoms [44,45,46]. A previous study identified several virulence factors (VFs) of soft rot pathogens, including the type II secretion system, the type III secretion system, the type IV secretion system, and the type VI secretion system [44]. However, the pathogenic mechanism of soft rot is still unknown in many aspects. The genomic data obtained from the D. dadantii DSM 18020T strain were analyzed, and it was predicted that this strain contained 20 pectin-related genes, which is more than the number of genes previously reported [47]. This is important for further analysis of the pathogenic mechanism of this strain.
In comparison to genome-wide evolutionary analyses, phylogenetic analyses based on 16S or genes are often found to be misleading in species. Consequently, in this study, we employed the REALPHY and TYGS methods, which are two commonly utilized techniques for constructing genome-wide evolutionary trees. The results demonstrated that D. dadantii was classified into two groups, with D. dadantii subsp. dieffenbachiae NCPPB 2976, D. dadantii S3−1, D. dadantii A622−S1−A17, and D. dadantii FZ06 clustered into one branch individually. However, further analyses combined with DDH and ANI indicated that D. dadantii subsp. dieffenbachiae NCPPB 2976 is distinct from the strain A622−S1−A17, FZ06, and S3−1 with 96.8−98.5 ANI values and 73% dDDH values. This raises the possibility of an additional D. dadantii subspecies including strains S3-1, FZ06, and A622-S1-A17 (Figure S3) [4].
Pan-genome analysis has been used to assess genome diversity, genome dynamics, species evolution, pathogenesis, and other features of microorganisms [48,49]. In our investigation, the unique genes of each strain show a balanced distribution across different functions, highlighting their potential roles in specialized processes, and are widely distributed and associated with functions such as human disease pathways and xenobiotic metabolism. The core genes are significantly associated with essential functions such as translation and metabolism, whereas accessory genes are more involved in signal transduction and cell wall biogenesis.
The complete genome sequence of pathogenic bacteria provides a new understanding of the pathogenesis of soft rot through comparative genomics [50]. For example, the comparative analyses of complete genomes predict the 10 pectinase enzymes in D. solani type strain IPP 2222 [51]. Zhou et al. [44] presented a comparative analysis of the conservation and evolution of virulence factors in soft rot pathogens, comparing the complete genome information of D. zeae EC1 with four available complete genome sequences of the closely related Dickeya species. To date, D. dadantii 3937 has been the subject of extensive study within this species. When compared with D. dadantii 3937, DSM 18020T exhibits numerous similarities, yet it also possesses a unique three-gene cluster. The RiPP-like bacteriocins are synthesized in a trans-AT type I polyketide manner, with tolaasin I/tolaasin F cyclic lipopeptides also present. However, further studies are required to elucidate their biological activities, mechanisms of action, and their potential applications. Additionally, the role of these biosynthetic gene clusters in this strain warrants further investigation.

5. Conclusions

The complete genome sequence of pathogenic bacteria provides a new understanding of bacterial classification and the pathogenesis of soft rot through comparative genomics. Here, we have obtained the complete genome sequence of D. dadantii type strain DSM 18020, which consists of a circular chromosome of 4,997,541 bp with a G+C content of 56.5%. The complete genome comprises 4277 protein-coding genes, 22 rRNA, and 75 tRNA. Of these, 563 genes are potentially associated with virulence factors (VFs) that contribute to soft rot of host plants. Secondary metabolite gene cluster analysis showed that DSM 18020 has ten biosynthetic gene clusters, of which seven are shared with D. dadantii 3937 and three are unique to it. Comparative genomics analysis between Dickeya revealed that “metabolism” constituted the largest category within both the core and accessory genomes, while “information storage and processing” was predominant in unique genomes. This study contributes to our understanding of the classification and pathogenic mechanism of DSM 18020T. The results of whole-genome sequencing permit the undertaking of more detailed studies on molecular genetics, pathogenic mechanisms, and drug screening.

Supplementary Materials

Supplementary data associated with this article can be found online at https://www.mdpi.com/article/10.3390/agronomy14071342/s1, Figure S1: D. dadantii DSM18020T gene annotation. (A) COGs, (B) GO, (C), KEGG, Figure S2: Phylogeny of Dickeya strains constructed on TYGS using FastME based on Genome BLAST Distance Phylogeny (GBDP), Figure S3: The Average Nucleotide Identity (ANI) values and DDH values of strains in Figure 2 based on whole-genome sequences, Figure S4. Genome-wide differential analysis of D. dadantii DSM 18020T and 3937. (A) synteny analysis, (B) COGs, (C) KEGG, (D) gene clusters, Table S1: List of Dickeya genomes used in this study, Table S2: Carbohydrate-active enzymes, Table S3: Selected core virulence genes in the D. dadantii DSM 18020T genome, Table S4: Genome mining of secondary metabolites of D. dadantii DSM 18020T.

Author Contributions

Y.C. was responsible for the data analysis, validation, and design. J.X., W.L., J.L., Z.X. and Z.S. contributed to the literature search, prepared a draft of the manuscript and figures, and finalized the manuscript. T.W., H.Q. and F.C. provided the analytical platform and participated in the design, data analysis, and proofreading of the paper. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Hunan Province and the Science and Technology Innovation Program of Hunan Province (2023JJ40085), Hunan Provincial Department of Education general project (22B0894 and 22C0674), ESI Discipline Special Project of Changsha Medical University (2022CYY023 and 2022CYY006), Agricultural Science and Technology Innovation Program (CAAS–ASTIP–IBFC), and Key R&D projects in Hunan Province (2022NK2052).

Data Availability Statement

The complete genome of D. dadantii type strain DSM18020 has been deposited to the GenBank under the accession number CP023467 (BioProject: PRJNA407418; BioSample: SAMN07653240).

Conflicts of Interest

The authors declare that they have no conflicts of interest.

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Agronomy 14 01342 g001
Figure 1. Circular chromosome of D. dadantii DSM18020T genome generated by Circos v0.64 (http://circos.ca/, accessed on 5 June 2018). Circles display from outside to inside: (1) genome position in Mb; (2,3) coding genes on + and-stands, correspondingly; (4) rRNA and tRNA; (5) GC content. Above the average is red and below is blue; (6) GC skew.
Figure 1. Circular chromosome of D. dadantii DSM18020T genome generated by Circos v0.64 (http://circos.ca/, accessed on 5 June 2018). Circles display from outside to inside: (1) genome position in Mb; (2,3) coding genes on + and-stands, correspondingly; (4) rRNA and tRNA; (5) GC content. Above the average is red and below is blue; (6) GC skew.
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Figure 2. Phylogeny of Dickeya strains constructed on REALPHY using PhyML 3.1 based on complete sequence.
Figure 2. Phylogeny of Dickeya strains constructed on REALPHY using PhyML 3.1 based on complete sequence.
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Figure 3. The evolution of pan-, core, and singleton genomes depends on the number of selected Dickeya strains.
Figure 3. The evolution of pan-, core, and singleton genomes depends on the number of selected Dickeya strains.
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Figure 4. COGs in the core, accessory, and unique genomes and KEGG analysis of 14 Dickeya strains: (A) COGs’ distribution; (B) KEGG distribution; (C) COGs’ functions; (D) KEGG pathways and their functions.
Figure 4. COGs in the core, accessory, and unique genomes and KEGG analysis of 14 Dickeya strains: (A) COGs’ distribution; (B) KEGG distribution; (C) COGs’ functions; (D) KEGG pathways and their functions.
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Table 1. D. dadantii DSM18020T genome statistics.
Table 1. D. dadantii DSM18020T genome statistics.
AttributeValueSoft/Database
Total reads number63,801/
Total bases (bp) 469,783,300/
Largest (bp)44,699/
Average length (bp)7363/
Genome size (bp)4,997,541/
DNA scaffolds1/
Interpersed repeat116RepeatMasker
Tandem repeat136Tandem Repeats Finder v4.07b
DNA coding (bp)4,261,959/
DNA G+C (%)56.5Bowtie2 v2.29
Gene/genome (%)85.28/
Total genes4455/
Total CDS4426Glimmer v3.02, GeneMarkS, Prodigal
Protein-coding genes4277Pfam v31.0
RNA genes105tRNAscan-SE v2.0, Barrnap, Infernal
Pseudo genes73Pseudofinder
Genes with function prediction3240COGs, GO, KEGG, NR, Pfam, Swiss-prot
Genes assigned to COGs3554Eggnog v4.5.1
No. of CAZyme genes154CAZy v6
Genomic islands14Islander v1.2
Genes with signal peptides1167SignalP v4.1
Genes with transmembrane helices1177Tmhmm v2.0
CRISPR repeats11Minced v3
Table 2. Pectin-degrading enzymes produced by Dickeya dadantii DSM 18020T.
Table 2. Pectin-degrading enzymes produced by Dickeya dadantii DSM 18020T.
StartEndStrandGene Length (bp)NR DescriptionNCBI Accession Number
2,103,0872,102,881-207pectin methylesteraseWP_071604523.1
2,660,1452,659,813-333pectin degradation protein kdgFWP_013318064.1
2,669,9212,670,619+699pectin acetylesteraseWP_013318072.1
3,644,4593646,147+1689pectin acetylesteraseWP_038912610.1
3,646,2323647,332+1101pectinesterase AWP_038901807.1
641,951642,985+1035pectate lyaseWP_013316284.1
2,304,5282,305,847+1320pectate lyaseWP_013317754.1
2,601,0102,603,740+1731pectate lyaseWP_038911228.1
2,662,5102,664,141+1632pectate lyaseWP_038911249.1
2,969,7772,969,517-261pectate lyaseWP_236616663.1
3,195,4913,194,214-1278pectate lyaseWP_038911484.1
3,496,6223,497,656+1035pectate lyaseWP_038911625.1
3,639,8683,641,046+1179pectate lyaseWP_038911695.1
3,641,5013,642,592+1092pectate lyaseWP_038901804.1
3,643,2353,644,413+1179pectate lyaseWP_038901806.1
4,487,2394,488,139+901pectate lyaseWP_013319745.1
4,488,9104,490,034+1125pectate lyaseWP_013319746.1
4,490,1874,491,464+1278pectate lyaseWP_038902797.1
4,941,1914,940,799-393pectate lyaseWP_050570305.1
4,943,0034,941,177-1827pectate lyaseWP_050570305.1
Forward chain: +, reverse chain: -.
Table 3. Results of antiSMASH analysis of D. dadantii DSM 18020T.
Table 3. Results of antiSMASH analysis of D. dadantii DSM 18020T.
RegionTypeStartEndMost Similar Known Cluster Similarity
Cluster 1NRPS-like, hserlactone85,823149,802minimycinNRP + saccharide60%
Cluster 2isocyanide1,121,8501,163,613
Cluster 3NI-siderophore1,702,8271,740,012
Cluster 4T1PKS, NRPS1,832,5211,955,354N-myristoyl-D-asparagine/cis-7-tetradecenoyl-D-asparagine/(R)-N1-((S)-5-oxohexan-2-yl)-2-tetradecanamidosuccin-amideNRP + polyketide:modu-lar type I polyketide + polyketide:trans-AT type I polyketide13%
Cluster 5RiPP-like1,972,1251,983,156
Cluster 6thiopeptide2,245,3732,271,871O-antigensaccharide14%
Cluster 7NRPS, trans-AT PKS3,183,9253,260,793tolaasin I/tolaasin FNRP:lipopeptide40%
Cluster 8NRP-metallo-phore, NRPS3,414,9843,472,341trichrysobactin/cyclic trichrysobactin/chrysob-actin/dichrysobactinNRP100%
Cluster 9betalactone4,167,2044,190,994bonnevillamide D/bonnevillamide ENRP6%
Cluster 10cyanobactin4,468,6904,490,651
Table 4. Comparative genomic information of strains DSM 18020T, 898, and 3937 of Dickeya dadantii.
Table 4. Comparative genomic information of strains DSM 18020T, 898, and 3937 of Dickeya dadantii.
Genome Assembly CharacteristicsD. dadantii DSM 18020D. dadantii 898D. dadantii 3937
Accession numberCP023467AOOE00000000CP002038
LevelComplete genomeDraft genomeComplete genome
Number of chromosomes111
Number of scaffolds1121
Number of contigs1521
Genome coverage94.0X19.0X-
Genome size (Mb)4.9984.9384.923
Contig N50 (bp)4,997,541191,2824,922,802
Scaffold N50 (bp)4,997,5414,829,4434,922,802
GC content (%)56.556.556.5
ORF54764591-
Total number of genes445544434429
Proteins427742614242
Pesudo genes73107 79
rRNA22722
tRNA756275
Other RNA8620
Sequencing technologyPacBio454
Assembly methodHGAP3 v. Sep-2015Newbler v. 2.5.3; MINIMUS v. 2.0.8Celera assembler;
SeqMan II
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Cheng, Y.; Xu, J.; Song, Z.; Li, W.; Li, J.; Xu, Z.; Chen, F.; Qiu, H.; Wang, T. High-Quality Complete Genome Resource for Dickeya dadantii Type Strain DSM 18020 via PacBio Sequencing. Agronomy 2024, 14, 1342. https://doi.org/10.3390/agronomy14071342

AMA Style

Cheng Y, Xu J, Song Z, Li W, Li J, Xu Z, Chen F, Qiu H, Wang T. High-Quality Complete Genome Resource for Dickeya dadantii Type Strain DSM 18020 via PacBio Sequencing. Agronomy. 2024; 14(7):1342. https://doi.org/10.3390/agronomy14071342

Chicago/Turabian Style

Cheng, Yi, Jianping Xu, Zhiqiang Song, Wenting Li, Jiayang Li, Zhecheng Xu, Fengming Chen, Huajiao Qiu, and Tuhong Wang. 2024. "High-Quality Complete Genome Resource for Dickeya dadantii Type Strain DSM 18020 via PacBio Sequencing" Agronomy 14, no. 7: 1342. https://doi.org/10.3390/agronomy14071342

APA Style

Cheng, Y., Xu, J., Song, Z., Li, W., Li, J., Xu, Z., Chen, F., Qiu, H., & Wang, T. (2024). High-Quality Complete Genome Resource for Dickeya dadantii Type Strain DSM 18020 via PacBio Sequencing. Agronomy, 14(7), 1342. https://doi.org/10.3390/agronomy14071342

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