Skip to main content

Genomic analysis reveals the role of integrative and conjugative elements in plant pathogenic bacteria



ICEs are mobile genetic elements found integrated into bacterial chromosomes that can excise and be transferred to a new cell. They play an important role in horizontal gene transmission and carry accessory genes that may provide interesting phenotypes for the bacteria. Here, we seek to research the presence and the role of ICEs in 300 genomes of phytopathogenic bacteria with the greatest scientific and economic impact.


Seventy-eight ICEs (45 distinct elements) were identified and characterized in chromosomes of Agrobacterium tumefaciens, Dickeya dadantii, and D. solani, Pectobacterium carotovorum and P. atrosepticum, Pseudomonas syringae, Ralstonia solanacearum Species Complex, and Xanthomonas campestris. Intriguingly, the co-occurrence of four ICEs was observed in some P. syringae strains. Moreover, we identified 31 novel elements, carrying 396 accessory genes with potential influence on virulence and fitness, such as genes coding for functions related to T3SS, cell wall degradation and resistance to heavy metals. We also present the analysis of previously reported data on the expression of cargo genes related to the virulence of P. atrosepticum ICEs, which evidences the role of these genes in the infection process of tobacco plants.


Altogether, this paper has highlighted the potential of ICEs to affect the pathogenicity and lifestyle of these phytopathogens and direct the spread of significant putative virulence genes in phytopathogenic bacteria.


Integrative and conjugative elements (ICEs) are self-transmissible mobile elements that play a central role in bacterial adaptation processes; hence, they can directly affect the evolution of their host [1, 2]. These widely distributed elements are currently found integrated into the bacterial chromosome, as they are capable of performing their excision, by recombination of direct repeat sequences (DRs) that flank the element (attachment sites), and transference by conjugation, carrying their machinery in a modular structure [3,4,5]. The main genetic modules found in ICEs include genes that encode functions related to their integration and excision from the host chromosome, conjugation, and regulation. These modules also have variable content, which leads these functions to be performed by different mechanisms from a diverse range of genes [5, 6]. ICEs often carry cargo genes, thus conferring significant phenotypes to the host cell, such as virulence, resistance to antibiotics and heavy metals that are important to bacteria fitness. For instance, ICETn43716061 discovered on Pseudomonas aeruginosa, provides resistance against carbapenem antibiotics, and ICEPm1 of Proteus mirabilis, Providencia stuartii and Morganella morgani, which carry genes that encode an adhesion protease and an iron acquisition system that contributes to the virulence of these bacteria [4, 7,8,9].

ICEs are broadly distributed in bacterial chromosomes, and some studies demonstrate their presence in plant pathogenic bacteria, which are microorganisms involved in major crop losses by host tissue invasion using virulence factors such as biofilm formation and toxins [3, 10]. For instance, different ICEs were found in strains of Pseudomonas syringae pv. actinidiae conferring resistance to heavy metals, and ICE HAI2 of Pectobacterium atrosepticum, which transmits genes that codify a biosynthetic cluster of an important virulence factor [11, 12]. Among these phytopathogenic bacteria, the most relevant were classified by Mansfield et al., in 2012, according to their scientific relevance and economic impact, in a ranking composed of Pseudomonas syringae, Ralstonia solanacearum, Agrobacterium tumefaciens, Xanthomonas oryzae pv. oryzae, Xanthomonas campestris, Xanthomonas axonopodis pv. manihotis, Erwinia amylovora, Xylella fastidiosa, Dickeya (dadantii and solani) and Pectobacterium (carotovorum and atrosepticum) [13].

A large part of pioneer studies involving ICEs was based only on phenotypes conferred by cargo genes and did not provide broader knowledge about these elements [5]. However, the development of Whole-Genome Sequencing (WGS) efforts leading to the large availability of complete genome sequences has enabled the conducting of investigation to clarify the role of ICEs in bacterial evolution [14,15,16]. Thus, here we search for ICEs integrated into 300 complete genomes of major phytopathogenic bacteria and analyze putative cargo genes and their potential role in virulence or adaptation.


The most comprehensive dataset of ICEs found integrated into the plant pathogenic bacteria genomes

We first sought to identify and analyze ICEs in the genomes of important plant pathogenic bacteria in molecular plant pathology. A total of 78 putative elements were found in nine species of phytopathogenic bacteria, including the species of D. dadantii, D. solani, P. atrosepticum, P. carotovorum, A. tumefaciens, P. syringae, X. campestris, X. fastidiosa and R. solanacearum species complex (RSSC) (Fig. 1 and Table S11). Among these elements, 45 ICEs were found to be distinct, and a greater number of ICEs were found in the genome of P. syringae (33, 20 of which were distinct elements) (Fig. 2A). There were no ICEs identified in the chromosomal sequences of X. oryzae, X. axonopodis, or E. amylovora.

Fig. 1
figure 1

Distribution of ICEs among bacterial strains. Solar explosion chart indicating the elements found in all strains. Bacterial species were arranged from the species with the largest number of elements to the species with the least number of elements and separated by color: Lilac: P. syringae; Dark blue: D. solani; Light blue: R. pseudosolanacearum; Green (from the darkest to the lightest, respectively): P. atrosepticum, X. fastidiosa, A. tumefaciens, X. campestris; Yellow: R. syzigii; Light orange: P. carotovorum; Dark orange: D. dadantii. From the inside out of the chart: The bacterial species, name of the strains, and the identified elements present in each strain. b Hierarchical organization of ICEs distribution around bacterial species, with color-coding in species as shown in the legend. The scale beside the plot shows the number of ICEs found for each species

Fig. 2
figure 2

General ICES identification results. a Bar chart of ICEs number distribution by groups of bacteria (dark blue: total elements, light blue: different elements); b Distribution chart of genome size, in bases pair, compared to the size of ICEs; c The type of Integrases found in the ICEs. d The type of Relaxase family found in the ICEs. e Bar chart of ICEs size by species f) Bar chart of GC content of the ICEs by species

The elements exhibited great variation in sequence size. The largest element ICEPsy10 was found in P. syringae with 161 kb and the smallest ICEDda2 was found in D. dadantii with 40 kb. Overall, the average size of the elements was 80 kb. The GC content ranged from 40 to 66%, which was found in ICEPat2 and ICEXfa2, respectively. The average content was 55% (Fig. 2F and Table S12). As already expected, no relationship was found between the increased size of the host genome and the presence of the elements (Fig. 2B).

Most of the elements (88%, n = 68) were found inserted in tRNA genes, whilst nine were found in other genes. Attachment sites (att) were identified in 49 ICEs; however, our search methods did not find the att sites in any elements integrated into RSSC genomes (Table S13). 58 ICEs encode the Tyr recombinase family, and 34 ICEs encode the MOBH relaxase gene (Fig. 2C, D; Table S14).

Interestingly, we found ICEs with core modular genes seen in other species. The ICEPca2 from P. carotovorum was found in the genome of Serratia plymuthica C-1 strain, and comparative analysis demonstrated that the elements share 99% nucleotide similarity (Data not shown). Also, ICEPca1 shared 82% of nucleotide identity with a novel ICE from P. aroidearum strain L6; ICEXca1 shared 88% sequence identity with a novel ICE from Xanthomonas arboricola pv. juglandis strain Xaj 417. Two ICEs from our dataset, ICEDda1 from D. dadantii and Tn4371 of R. pseudosolanacearum had been previously classified in the family Tn4371 [15, 17]. However, comparative analyses between these two elements indicated low similarity (45% of nucleotide identity).

ICEs carry genes with potential impact on the pathogenicity and lifestyle of plant pathogenic bacteria

The genes carried by the elements were also investigated and classified for their putative role. As expected, a greater number of hypothetic proteins and genes with unknown functions were identified, followed by conjugation and cargo genes, in general (Fig. 3A). Specifically, among the cargo genes, those encoding functions of oxidation–reduction processes and resistance appeared in a greater number of ORFs (open reading frames) in the elements, followed by virulence factors (Fig. 3B). Putative virulence and adaption roles were verified in most ICEs by the annotation in specific protein databases. Genes codifying virulence functions were tracked down in 28 elements, while with putative adaption, roles were spotted in 12 ICEs, among other important roles, such as metal and antibiotic resistance (Table S15). Regarding virulence, genes were also organized according to their putative function, and the most frequent class of virulence genes were genes that encode proteins translocated by Type III Secretion System (T3SS) and components of this system, followed by genes that encode hydrolytic enzymes involved in host cell wall degradation (Fig. 3C). Altogether, these two sections reveal the existence of ICEs in genomes of high-impact phytopathogenic bacteria and their likely impact on their pathogenicity and lifestyle. Now further, we will present specific results for individual bacteria species.

Fig. 3
figure 3

Putative functions of ICEs genes. a Bar chart of putative roles codified by ICEs genes separated by categories (Unsure category comprises Hypothetical protein, Domain of unknown function (DUF genes), and genes with undetermined function). b Bar chart of Cargo genes divided by putative roles. c Pie chart representing putative roles of Virulence factors carried by ICEs

ICEs in Agrobacterium tumefaciens

Initially, we investigated chromosome sequences of seventeen strains available in the NCBI database, each one of them with two chromosomes. Then, we searched for ICEs in 32 sequences of A. tumefaciens chromosomes (Table S3). Our methods allowed the identification of four novel elements in sequences of three strains: ICEAtu1 was identified in the chromosome of the strain 1D1609, ICEAtu2, and ICEAtu3, in the circular and linear chromosomes of the strain 12D1, respectively, and at last, ICEAtu4 was identified in the circular chromosome of the strain 186 (Fig. 1). These elements had a mean size of 86 kb; ICEAtu3 was the element with the largest sequence (114 kb), followed by ICEAtu4 (101 kb) and ICEAtu2 (68 kb), while ICEAtu1 was the smallest element, with 61 kb of length (Table S12). The mean GC content of the elements was 60% and ranged from 58% (ICEAtu3) to 63% (ICEAtu1). Only the elements ICEAtu2 and ICEAtu3 from the strain 12D1 presented GC content lower than the genome: 58% and 58%, respectively (Table S12). The att sites of ICEAtu3 and ICEAtu4 were identified, and regarding the integration site, both elements and ICEAtu2 are inserted in tRNA sequences, and ICEAtu1 is inserted in the guaA gene (Tables S13 and 14). The sequence alignment of the ICEs from A. tumefaciens revealed that ICEAtu2 and ICEAtu4 share 53% of nucleotide identity, mainly due to the gene clusters that represent conjugation and integration modules based on syntenic analysis (Fig. S1, S2, S3, S4, S5, S6, S7, S8, S9 and S10A).

A. tumefaciens ICEs encode proteins that may have important functions for pathogenicity, such as cysteine hydrolase and glycosidase in ICEAtu1, and Endo-1,4-beta-xylanase in ICEAtu4. Likewise, Alkene reductase and glutathione S-transferase on ICEAtu1 and universal stress protein on ICEAtu3 may have a putative role in the adaption of these bacteria. We also identified genes coding for a L.D – transpeptidase of ICEAtu3 and MBL fold metalo-hydrolase in ICEAtu4, which provides putative resistance to antibiotics (Table S15).

ICEs in Dickeya (dadantii and solani)

We search for ICEs in chromosomal sequences of thirteen Dickeya genomes, two of which are from D. dadantii, and eleven genomes belong to the D. solani species (Table S9). In those sequences, we were able to find three distinct elements, and a total of thirteen ICEs: ICEDda1 was found in the chromosomal sequence of the strain 3937 and ICEDda2, in the chromosome of the strain DSM 18,020. Interestingly, ICEDso1 was present in all strains of D. solani, hence, all investigated strains harbor ICEs (Fig. 1). Among these elements, only ICEDda1 has been cited in the literature, as an element of the Tn4371 family (Table S16) [17].

Regarding the size of those elements, ICEDda1 was the biggest element, with 74 kb, followed by ICEDso1 (48 kb), while ICEDda2 was the smallest, with 40 kb (Table S12). The GC content of all elements was lower than the content of the genomes, with a mean of 51%, so 52% were in ICEDso1, 52% in ICEDda2, and 49% in ICEDso1 (Table S12). Both ICEDda1 and ICEDso1 had their attachment sites identified and are inserted in tRNA sequences, and ICEDda2 was inserted in bamE gene (Tables S13 and 14). The comparison among these elements revealed low similarity between each other (< 50% of nucleotide identity) (Fig. 4B). However, clusters of syntenic genes were observed between all three elements, which were related to recombinase genes, some transcriptional regulators and cargo genes related to the Type VI secretion system (T6SS). Furthermore, ICEDda1 and ICEDso1 may also share their conjugation and regulation modules, since syntenic gene clusters comprise genes of type IV secretion system (T4SS) and a toxin-antitoxin system were verified (Fig. S2). Among the main cargo genes of these ICEs, we identified a putative tellurium resistance (terB) and an entry exclusion (eexN) in ICEDda1. Moreover, component genes of T6SS, hcp effectors, and tssI—vgrG with putative virulence roles were verified in all three different elements (Table S15).

Fig. 4
figure 4

Different Expression Analyses—RPKM Heatmaps: Significant genes of P. atrosapticum elements ICEPa1 and ICEPa2 (SCRI1043 isolate) in tobacco plants. a Coronafacic acid biosynthesis gene cluster carried by ICEPca1. b Cargo gene of ICEPca2 with putative Virulence role – Phospholipase D. c Relaxases of ICEPca1 and ICEPca2. Scaled expression values are color-coded, and the red color represents high expression. Abbreviation: Z1: Asymptomatic zone, Z2: Symptomatic zone

ICEs in Pectobacterium carotovorum (and atrosepticum)

Eight genomes from Pectobacterium were investigated, four from P. carotovorum (Pcc) and four from P. atrosepticum (Pca). In total, nine elements were identified, six of which were distinct ICEs (Fig. 1, Table S10). In Pcc, we found ICEPcc1 and ICEPcc2 in genomes of the strains JR1.1 and BP201601.1, respectively. We observed several co-occurrences in the genome of Pectobacterium, including two ICEs (ICEPca1 and ICEPca2) in the chromosome of SCRI1043, the ICEs (ICEPca1 and ICEPca3) in the strain JG10-08, and the elements ICEPca1 and ICEPca4 in the genome of the strain 36A. Here, we identified five novel elements for the genus, and only ICEPca1 had been previously reported [12, 18, 19] (Fig. 1, Table S16).

The Pectobacterium ICEs presented similarity between ICEPca2 and ICEPcc1 with 69,5% of nucleotide identity, while between ICEPca2 and ICEPca4, it was 68,9% (Fig. S10C). Syntenic analyses revealed that most elements appear to have similar conjugation modules (high identity), except for ICEPca1, a highly syntenic gene cluster comprising conjugation and T4SS genes, and similarity between integration genes for ICEPcc1, ICEPca2, ICEPcc2 and ICEPca4 (Fig. S3). Regarding the main cargo genes of these elements, the coronafacic acid biosynthesis cluster of ICEPca1 is well-known for the virulence in SCRI1043 isolate [12]. Genes encoding proteins with putative virulence roles were also found in ICEPca2 (Phospholipase D), ICEPca4 (Arginase family protein) and ICEPcc2 (Glutathione peroxidase). Moreover, we identified putative entry exclusion genes in ICEPca2, ICEPca4, and ICEPcc1. Lastly, genes encoding proteins that may confer antibiotic resistance were observed: MBL fold metallo-hydrolase in ICEPca3 and ICEPcc2, and mipA/ompV family protein in ICEPca4 (Table S15).

Our analysis of differential gene expression showed a higher expression of the gene cluster of coronafacic acid biosynthesis carried by ICEPca1 during the asymptomatic stage of P. atrosepticum SCRI1043 infection in tobacco, represented by a higher RPKM value in comparison with the symptomatic stage and in vitro culture (Fig. 4), as presented by [20]. Also, the expression of its putative virulence gene, phospholipase D, was verified, with the same pattern displayed by the genes of ICEPca1 and higher RPKM value in the asymptomatic stage of infection (Fig. 4). Finally, we analyzed the expression of relaxase genes carried by ICEPca1 (loci tag ECA_RS03055) and ICEPca2 (loci tag ECA_RS08300) to indicate the stage of infection where the mobilization of these elements may occur. A different pattern of results was verified, and the relaxase of ICEPca1 presented greater expression in the symptomatic stage of infection, followed by the in vitro culture, and lower expression in the asymptomatic stage (Fig. 4). The relaxase of ICEPca2 exhibited an upregulation of the expression in the in vitro culture, followed by the expression in the symptomatic phase (Fig. 4).

ICEs in Pseudomonas syringae pathovars

The greatest number of ICEs was found in the Pseudomonas pathovars, possibly due to several genomes available for the species. Twenty-eight chromosomes were investigated for ICEs, and 33 elements were found, including 20 distinct elements (Fig. 1, Table S1). Regarding the distribution of these elements in bacterial genomes, ICEPsy2 was the most common element, present in nine strains, followed by ICEPsy7, which was detected in seven strains (Fig. 1). We were able to track down seven P. syringae ICEs already cited in the literature. Therefore, this work brings thirteen novel putative elements (Table S16).

Interesting events of ICE co-occurrence have been verified in P. syringae chromosomal sequences, mainly in the strains Shaanxi_M228 and ICMP 20,586, each with four monopartite elements uncovered. Furthermore, we spotted the co-occurrence of three monopartite ICEs in genomes of CRAFRU14.08, NZ-47 and CRAFRU12.29; and two elements in MAFF212063, ICMP 18,708, ICMP 18,884 and P155 (Fig. 1). Some of those elements could be observed grouped in tandem on the chromosome sequence with the same att sites, whose arrangement was outlined in Fig. 5A. This may be the first time in literature that more than three elements are tracked down in one genome.

Fig. 5
figure 5

P. syringae ICEs. a P. syringae ICEs co-occurrence and in-tandem configuration. (White rectangles: bacterial chromosomes – small colored rectangles: ICEs, the colors represent different elements); b P. syringae ICEs identity matrix heatmap: red—high identity, purple -intermediate white—low identity

The size of P. syringae elements ranged from 30 kb in ICEPsy20 to 161 kb in ICEPsy10, with a mean of 99 kb (Table S12), and GC content means of 55%, ranging from 50 to 57% (Table S12). Attach sites of fifteen elements were identified, and all the 32 elements were integrated next to a tRNA sequence (Tables S13 and 14). Among the elements, a greater similarity was observed between ICEPsy4 and ICEPsy11, with 85% nucleotide identity followed by ICEPsy1 and ICEPsy14, with 82% of nucleotide identity (Fig. 5B). Comparative analysis of gene clusters illustrated highly syntenic ICEs in P. syringae and enabled us to separate these elements into three groups, based on clusters of syntenic genes. Group 1 comprises ICEPsy3, ICEPsy15, ICEPsy16, ICEPsy18 and ICEPsy19. These elements mostly share conjugation and integration modules, as well as a few IS sequences (Fig. S4). Group 2 is the largest and comprises ICEPsy1, ICEPsy4, ICEPsy6, ICEPsy9, ICEPsy11, ICEPsy13, ICEPsy14, ICEPsy17 and ICEPsy20; this group shares not only the conjugation and integration modules, as observed in group one, but also cargo genes encoding relevant functions, such as copper and arsenic resistance gene clusters among other cargo genes, except for ICEPsy20, the most distinct element among the P. syringae ICEs, which shares only an integrase and a maintenance gene (ardR) (Fig. S5). Finally, group 3 comprises ICEPsy2, ICEPsy5, ICEPsy7, ICEPsy10 and ICEPsy12; all elements also share the main modules (integration and conjugation). Moreover, ICEPsy2 and ICEPsy10 also had a syntenic gene cluster that contains T3SS effectors, a cellulase, a transporter gene cluster and chemotaxis gene clusters that may be involved in element regulation as other cargo genes. This comparison analysis allowed us to verify sequence differences between ICEPsy2 in the strains ICMP20586 and Shaanxi_M228, due to IS insertions in the elements (Fig. S6).

A large number of cargo genes encoding putative significant roles were identified in P. syringae ICEs, mainly copper and arsenic resistance gene clusters of ICEPsy8 and ICEPsy13, which have been described in the literature (Colombi et al., 2017b). However, here we report those gene clusters in ICEPsy1 and ICEPsy14 (Cooper and arsenic resistance), ICEPsy4 and ICEPsy11 (only Arsenic resistance). A great number of genes encoding proteins with virulence roles were found in some P. syringae elements, such as T3SS effector genes, which were found in ICEPsy2, ICEPsy5, ICEPsy7, ICEPsy9, ICEPsy10, ICEPsy12 and ICEPsy18. Cargo genes conferring putative antibiotic resistance were also identified, such as the crpP family protein, which is carried by twelve elements, and mupB of ICEPsy18. Moreover, a gene cluster encoding putative Tellurium resistance was identified in ICEPsy2 (Table S15).

ICEs in Ralstonia solanacearum species complex

The chromosome sequences of one hundred R. solanacearum strains were examined, revealing seven unique ICEs (six found in R. pseudosolanacearum genomes and one found in R. syzygii) (Fig. 1, Table S2). Most of those elements had already been described in another work of our research group [15] (Table S16), and here we report the presence of a known element (ICERps1) in two more strains, FJAT91-F1 and FJAT91-F8, and a novel element, ICERps4, detected in UW386. ICERps4 has a size of 56.3 kb, 62,4% of GC content, and is inserted in a tRNA sequence (Tables S12, S13 and S14). The alignment of the sequences revealed similarity between ICERps4 and ICERps1, ICERps2 and ICERps3, with nucleotide identity percentages of 79%, 81%, and 78%, respectively (Fig. S3D). It was illustrated with syntenic gene clusters between these elements comprising the conjugation module and other cargo genes (Fig. S7). These elements carry cargo genes that encode a putative role in bacterial adaption, such as Glutathione S-transferase as the element Tn4371 and ICERps3, and gamma-glutamylcyclotransferase carried by ICERps1. Likewise, we were able to identify genes with a putative effect on virulence, such as amidohydrolase from ICERsy1, and SDR family oxidoreductase, present in Tn4371 and ICERps3. Lastly, the ICERps1 also carries a Superoxide dismutase gene with a putative antioxidant resistance role (Table S15).

ICEs in Xanthomonas campestris pathovars

We started our research with chromosomal sequences of eighteen X. campestris strains, in which we track down two different ICEs, which are two novel elements (ICEXca1 and ICEXca2). ICEXca1 was found in the chromosomes of B100 and 3811 strains and ICEXca2 in the chromosome of CN03 (Fig. 1, Table S5). The size of the element ICEXca1 varied on the different strains: 64.1 kb in B100 and 64.5 kb in 3811. Moreover, the size of the ICEXca2 element was 83.7 kb; the GC content was 61% and 60%, respectively (Table S12). The attachment sites of the elements were described, and both were inserted in tRNA sequences (Tables S13 and S14). The elements shared low similarity, with a nucleotide identity percentage of 47% (Fig. S10E), however, they have highly syntenic gene clusters (Fig. S8). Both elements identified in X. campestris carry cargo genes encoding putative roles in virulence. In ICEXca1, we find genes encoding an aminotransferase and a lytic murein transglycosylase in ICEXca2. This element also carries two putative avirulence effector genes and cargo genes, such as Inositol hexakisphosphate, which may be related to the adaption of these bacteria (Table S15).

ICEs in Xylella fastidiosa

The analysis of chromosomes of twenty-one X. fastidiosa strains resulted in the discovery of three distinct ICEs from a total of four elements (Fig. 1, Table S8). The size of the element ranged from 88 kb in ICEXfa1 to 158 kb in ICEXfa3, and the mean GC content was 56 ranging from 54 to 66 (Table S12). The insertion of the element ICEXfa1 diverged from the others since this element was found integrated next to the ABC transporter gene; ICEXfa2 and ICEXfa3 were found integrated next to tRNA sequences. Moreover, only the attachment sites of ICEXfa2 were identified (Tables S13 and S14). So far, only ICEXfa2 in the strain Hib4 has been identified in the literature [21]. Hence, our work presents two novel elements in X. fastidiosa. The alignment analysis indicates low similarity between the elements with nucleotide identity percentage less or equal to 42% (Fig. S10F). Gene cluster comparison analyses were able to demonstrate significant syntenic groups shared by ICEXfa3 and ICEXfa1, comprising their conjugation and maintenance modules, represented by T4SS genes and a toxin-antitoxin gene cluster, in addition to other cargo genes; ICEXfa2 exhibits low similarity with the other elements in this analysis as well (Fig. S9). Cargo genes with putative roles in virulence were found in all three X. fastidiosa elements, including unidentified virulence factors that can be found in ICEXfa1 and ICEXfa3. Also, genes conferring a putative antibiotic resistance were found in both elements (MBL fold metallo-hydrolase- ICEXfa1) and (UDP-3-O-(3-hydroxymyristoyl- glucosamine N-acyltransferase—ICEXfa3). We identified genes conferring putative antioxidant resistance (Superoxide dismutase) and a putative role in adaption, such as coproporphyrinogen III oxidase in ICEXfa2. Furthermore, a putative Entry exclusion gene was identified in ICEXfa3 (Table S15).

The conservation and evolutionary history of plant-pathogen ICEs core-genes

Beyond cargo genes carried by the ICEs, we also present the conservation and evolutionary history of ICEs' core genes, which may play a role in element movement. Integrase/recombinase, relaxase, type-IV coupling proteins (T4CPs), ParA, ParB, topoisomerase III, and Single-strand DNA-binding protein (SSB) were among the most conserved core genes in our dataset (Fig. 6A). In addition, we found that ICEs from the same species have common core genes, including their presence/absence and the average of T4SS components, and those lacking the majority of the core genes may be defective elements, such as ICEPsy20 from P. syringae (Fig. 6A). P. syringae ICEs had the highest T4SS component average (22 genes set). Next, we group these core genes from putative intact elements and constructed a tree based on the concatenation of eight backbone gene alignments. The species-related ICEs were clustered into four groups on the phylogenetic tree. P. syringae ICEs, the most conserved cluster, A. tumefaciens, R. pseudosolanacearum, and a cluster including ICEs from Pectobacterium spp. and Dickeya spp. (Fig. 6B). These findings might imply that these elements have the same common origin. Nevertheless, we found clusters with different species, suggesting that the ICEs genes themselves are conserved (Fig. 6B).

Fig. 6
figure 6

ICEs core-gene conservation and evolutionary history. a Plot of eight core genes found in ICEs dataset with the number of components of T4SS grouped by species. Blue colored square indicates the presence of the gene in the element and the colorless square indicates the absence. Abbreviation for Rec, Recombinase; T4CP, type-IV coupling proteins; topo III, topoisomerase III; Single-strand DNA-binding protein (SSB). b Maximum Likelihood tree based on the eight backbone gene alignments. The General Time Reversible model and a bootstrap confidence value of 1,000 were applied to the tree. The alignment and phylogenetic analysis were done using MEGA X. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site


The limited understanding regarding ICEs has been overcome in recent years due to the increased availability of whole genome sequences [4, 5, 22]. Some studies have addressed the presence of ICEs in phytopathogenic bacteria but have not dealt in-depth. However, it is necessary to fully understand the relationship between ICEs and economically important plant pathogenic bacteria [3, 10]. Through an in-silico investigation of ICEs using 300 genomes available at NCBI, we have identified and characterized 78 putative ICEs integrated into the genomes of the top ten phytopathogenic bacteria. As expected, most ICEs were found integrated into tRNA sequences [4]. These elements encoded core modular genes, including genes that allow Integration/excision modules, conjugation, maintenance and regulation modules [4]. In general, evidence of ICEs features such as GC content indicates a slightly lower value than expected in the host genome, suggesting that these elements may have been acquired recently and probably be under selective pressure to adapt to the codon host’s codon usage [23, 24]. Some elements also carry entry exclusion genes (eexn and traG), which can avoid redundant transfer of ICEs leading to host energy savings [25, 26]

We found no ICEs in X. oryzae pv. oryzae, X. axonopodis or E. amylovora, possibly due to a bias in the software system used, since we are dealing with highly diverse elements and the number of complete genomes available for these species. However, we search for ICEs in 83 complete genomes of X. oryzae pv. oryzae and, despite its large repertoire of insertion sequences [27, 28], no ICE was found. Similarly, we investigate 100 sequences of RSSC complete genomes, 40 new genomes more than those analyzed by [15], and one novel ICE (ICERps4) was reported for RSSC. We hypothesize that the present variation of ICEs in genomes of different bacterial species may be related to a type of mechanism to control the entry of these elements into cells, which can be more or less rigorous, thus allowing or not the acquisition of ICEs by host cells.

Most of the identified elements were found to carry genes with putative functions for adaptation and virulence. Putative antibiotic resistance genes were also identified, which can be related to the ICEs maintenance module, although they have not been classified in the same way. Regarding the virulence factors found, an increased number of T3SS ORFs was observed in ICEs. This secretion system is an important virulence trait for phytobacteria that allows the translocation of effector proteins into plant cells, either by changing their metabolism or suppressing defenses [29, 30]. Furthermore, we also found genes that encode hydrolytic enzymes involved in host cell wall degradation as the second most prevalent group of virulence factors in our ICEs. Thus, our work highlights the importance of ICEs for a possible function in parasitism evolution. Conserved core genes found in the ICEs may contribute to the element’s mobility and enhance the spread of significant putative virulence genes in phytopathogenic bacteria.

In conclusion, our results suggest a putative association between ICEs and plant pathogen bacteria fitness. Our in silico study opens the doors to further experimental investigations that should be carried out to improve knowledge about the role of ICEs and their cargo genes in phytopathogenic bacteria.

Materials and methods


Three hundred complete genomes of phytopathogenic bacteria of economic and scientific impact [13] were downloaded from the National Center for Biotechnology Information (NCBI— in July 2020. The chromosome sequences in GenBank format were used to search for ICEs (Tables S1, S2, S3, S4, S5, S6, S7, S8, S9 and S10).

Identification and the delimitation of integrative and conjugative elements

To uncover sequences of ICEs in bacterial chromosomes, we resort to a method similar to that applied by Gonçalves and Santana [16]. Thus, we perform a search of the element sequences using BLASTn [31] against known ICEs deposited in the ICEberg database [32, 33], and only sequences that obtained an E-value less or equal to 10–5 and coverage more or equal to 50% were selected. We submit the nucleotide sequences of ICEs to the ICEfinder software system (, an online tool provided by ICEberg 2.0 that identifies signature features of integrative and conjugative elements as integrase gene, T4SS, and directed repeats sequences (DRs) in bacterial genomes [32, 33], OriTfinder [34] ( that identifies transfer origin sequences in bacterial chromosomes, among other features, which indicates the presence of the ICE, MOBscan ( that identifies relaxase MOB families, the CONJscan module of MacSyFinder ( that identifies conjugative systems in bacterial genomes searching for Type IV secretion systems [35]. We also execute a manual search on the sequences of complete and annotated chromosomes looking for ICEs signature genes: genes that are part of the T4SS involved in the conjugative transfer, such as tra, vir0, or trb, and integrase (int) [5]. The attachment regions (att site) that provided upper and lower boundaries of the elements were identified in ICEfinder, but when the att regions were not detected, we manually identified them using BLASTn. We initially delimited the upper bound of the element by looking for genes of integrases close to tRNAs, then, that region between these genes was selected to make the BLAST look for a repeated sequence in another position of the genome that was close to the coordinates the possible final portion of the element given by ICEfinder. ICEs were named following patterns already described [36].

The characterization of carrying genes

The annotation of protein sequence was performed using Uniprot ( [37], and Pfam ( [38] protein databases. Putative functions of accessory genes were investigated by performing a BLASTp against Pathogen-host Interactions database ( [39], Virulence Factor Database ( [32, 33] and Type III secretion system effectors database ( [40]. The parameters used to identify sequence coding proteins were: e-value less or equal to 10–5 and amino acid identity greater than 30% [15]. Subsequently, the nucleotide sequences of the identified elements were downloaded in GenBank format and analyzed using the Geneious® software system (Biomatters Ltd.) for the characterization of the excision and integration, conjugation, regulation and maintenance modules.

Differential expression analysis

The differential expression analysis was performed using RNAseq data from P. atrosepticum isolate SCRI1043 corresponding to two stages of infection in the tobacco plant (asymptomatic and symptomatic) and an in vitro culture. The data are available in NCBI BioProject (accession number PRJNA403794) [20]. The Geneious software system was used for the analysis, following the Expression Analysis tutorial with default parameters. In order to study the gene expression of the ICEs present in the genome, the element sequence was used as a reference to map the reads, and the differential expression was measured. Reads per kilobase per million (RPKM) values were plotted in GraphPad Prism version 8.4.3 to generate heatmaps.

Comparative analysis

Nucleotide sequences in fasta format of the ICEs identified were submitted to ClustalW [41] to generate Pairwise Identity Matrices for Heatmaps creation, using GraphPad Prism version 8.4.3 for Windows. The sequences were also submitted to Mauve [42] and clinker clustermap.js [43] to generate gene cluster comparison and synteny analyses. Core genes were aligned in ClustalW [44] and concatenated in Mesquite software Version 3.70 ( The maximum likelihood tree was aligned and constructed using MEGA X [45] based on the eight backbone gene alignments. The General Time Reversible model and a bootstrap confidence value of 1,000 were applied to the tree.

Availability of data and materials

The datasets analyzed for this study can be found in the article/Supplementary Material. The ICEs sequences here described were deposited in the ICEberg database.


  1. Burrus V. Mechanisms of stabilization of integrative and conjugative elements. Curr Opin Microbiol. 2017;38:44–50.

    Article  CAS  PubMed  Google Scholar 

  2. Carraro N, Burrus V. The dualistic nature of integrative and conjugative elements. Mob Genet Elements. 2015;5(6):98–102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Guglielmini, J., Quintais, L., Garcillán-Barcia, M. P., de la Cruz, F., & Rocha, E. P. C. The repertoire of ICE in prokaryotes underscores the unity, diversity, and ubiquity of conjugation. PLoS Genetics. 2011;7(8). 78(1), 138–157.

  4. Johnson CM, Grossman AD. Integrative and Conjugative Elements (ICEs): What They Do and How They Work. Annu Rev Genet. 2015;49:577–601.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Wozniak RAF, Waldor MK. Integrative and conjugative elements: mosaic mobile genetic elements enabling dynamic lateral gene flow. Nat Rev Microbiol. 2010;8(8):552–63.

    Article  CAS  PubMed  Google Scholar 

  6. Toussaint A, Merlin C. Mobile elements as a combination of functional modules. Plasmid. 2002;47(1):26–35.

    Article  CAS  PubMed  Google Scholar 

  7. Flannery EL, Antczak SM, Mobley HLT. Self-transmissibility of the integrative and conjugative element ICEPm1 between clinical isolates requires a functional integrase, relaxase, and type IV secretion system. J Bacteriol. 2011;193(16):4104–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Fonseca EL, Marin MA, Encinas F, Vicente ACP. Full characterization of the integrative and conjugative element carrying the metallo-β-lactamase blaSPM-1 and bicyclomycin bcr1 resistance genes found in the pandemic Pseudomonas aeruginosa clone SP/ST277. J Antimicrob Chemother. 2015;70(9):2547–50.

    Article  CAS  PubMed  Google Scholar 

  9. Flannery EL, Mody L, Mobley HLT. Identification of a Modular Pathogenicity Island That Is Widespread among Urease-Producing Uropathogens and Shares Features with a Diverse Group of Mobile Elements. Infection and Immunity. 2009;77(11):4887-4894.

  10. Mole BM, Baltrus DA, Dangl JL, Grant SR. Global virulence regulation networks in phytopathogenic bacteria. Trends Microbiol. 2007;15(8):363–71.

    Article  CAS  PubMed  Google Scholar 

  11. Colombi E, Straub C, Künzel S, Templeton MD, McCann HC, Rainey PB. Evolution of copper resistance in the kiwifruit pathogen Pseudomonas syringae pv actinidiae through acquisition of integrative conjugative elements and plasmids. Environ Microbiol. 2017;19(2):819–32.

    Article  CAS  PubMed  Google Scholar 

  12. Panda P, Vanga BR, Lu A, Fiers M, Fineran PC, Butler R, Armstrong K, Ronson CW, Pitman AR. Pectobacterium atrosepticum and Pectobacterium carotovorum harbor distinct, independently acquired integrative and conjugative elements encoding coronafacic acid that enhance virulence on potato stems. Front Microbiol. 2016;7:1–13.

    Article  Google Scholar 

  13. Mansfield J, Genin S, Magori S, Citovsky V, Sriariyanum M, Ronald P, Dow M, Verdier V, Beer SV, Machado MA, Toth I, Salmond G, Foster GD. Top 10 plant pathogenic bacteria in molecular plant pathology. Mol Plant Pathol. 2012;13(6):614–29.

    Article  PubMed  PubMed Central  Google Scholar 

  14. da Silva GC, Gonçalves OS, Rosa JN, França KC, Bossé JT, Santana MF, Langford PR, Bazzolli DMS. Mobile genetic elements drive antimicrobial resistance gene spread in pasteurellaceae species. Front Microbiol. 2022;12:773284.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Gonçalves OS, de Queiroz MV, Santana MF. Potential evolutionary impact of integrative and conjugative elements (ICEs) and genomic islands in the Ralstonia solanacearum species complex. Sci Rep. 2020;10(1):1–13.

    Article  CAS  Google Scholar 

  16. Gonçalves OS, Santana MF. The coexistence of monopartite integrative and conjugative elements in the genomes of Acidobacteria. Gene. 2021;777:145476.

    Article  CAS  PubMed  Google Scholar 

  17. Toussaint A, Merlin C, Monchy S, Benotmane MA, Leplae R, Mergeay M, Springael D. The biphenyl- and 4-chlorobiphenyl-catabolic transposon Tn4371, a member of a new family of genomic islands related to IncP and Ti plasmids. Appl Environ Microbiol. 2003;69(8):4837–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Bell KS, Sebaihia M, Pritchard L, Holden MTG, Hyman LJ, Holeva MC, Thomson NR, Bentley SD, Churcher LJC, Mungall K, Atkin R, Bason N, Brooks K, Chillingworth T, Clark K, Doggett J, Fraser A, Hance Z, Hauser H, Toth IK. Genome sequence of the enterobacterial phytopathogen Erwinia carotovora subsp atroseptica and characterization of virulence factors. Proc Natl Acad Sci U S A. 2004;101(30):11105–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Vanga BR, Ramakrishnan P, Butler RC, Toth IK, Ronson CW, Jacobs JME, Pitman AR. Mobilization of horizontally acquired island 2 is induced in planta in the phytopathogen Pectobacterium atrosepticum SCRI1043 and involves the putative relaxase ECA0613 and quorum sensing. Environ Microbiol. 2015;17(11):4730–44.

    Article  CAS  PubMed  Google Scholar 

  20. Gorshkov V, Gubaev R, Petrova O, Daminova A, Gogoleva N, Ageeva M, Parfirova O, Prokchorchik M, Nikolaichik Y, Gogolev Y. Transcriptome profiling helps to identify potential and true molecular switches of stealth to brute force behavior in Pectobacterium atrosepticum during systemic colonization of tobacco plants. Eur J Plant Pathol. 2018;152(4):957–76.

    Article  CAS  Google Scholar 

  21. Denancé N, Briand M, Gaborieau R, Gaillard S, Jacques MA. Identification of genetic relationships and subspecies signatures in Xylella fastidiosa. BMC Genomics. 2019;20(1):1–21.

    Article  Google Scholar 

  22. Botelho J, Schulenburg H. The Role of Integrative and Conjugative Elements in Antibiotic Resistance Evolution. Trends Microbiol. 2021;29(1):8-18.

  23. Lawrence JG, Ochman H. Molecular archaeology of the Escherichia coli genome. Proc Natl Acad Sci. 1998;95:9413–7.

    Article  CAS  Google Scholar 

  24. Marri PR, Golding GB. Gene amelioration demonstrated: the journey of nascent genes in bacteria. Genome. 2008;51:164–8.

    Article  CAS  Google Scholar 

  25. Dunny GM. A new flavor of entry exclusion in ICE elements provides a selective advantage for the element and its host. Micro Commentary. 2019;112(July):1061–5.

    Article  CAS  Google Scholar 

  26. Marrero J, Waldor MK. Determinants of entry exclusion within Eex and TraG are cytoplasmic. J Bacteriol. 2007;189(17):6469–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Cesbron S, Briand M, Essakhi S, Gironde S, Boureau T, Manceau C, Fischer-Le Saux M, Jacques MA. Comparative genomics of pathogenic and nonpathogenic strains of Xanthomonas arboricola unveil molecular and evolutionary events linked to pathoadaptation. Front Plant Sci. 2015;6:1126.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Salzberg SL, Sommer DD, Schatz MC, Phillippy AM, Rabinowicz PD, Tsuge S, Furutani A, Ochiai H, Delcher AL, Kelley D, Madupu R, Puiu D, Radune D, Shumway M, Trapnell C, Aparna G, Jha G, Pandey A, Patil PB, Bogdanove AJ. Genome sequence and rapid evolution of the rice pathogen Xanthomonas oryzae pv oryzae PXO99A. BMC Genomics. 2008;9(May):1–16.

    Article  CAS  Google Scholar 

  29. Cornelis GR, van Gijsegem F. Assembly and function of type III secretory systems. Annu Rev Microbiol. 2000;54:735–74.

    Article  CAS  Google Scholar 

  30. Alfano JR, Collmer A. TYPE III SECRETION SYSTEM EFFECTOR PROTEINS: Double Agents in Bacterial Disease and Plant Defense. Annu Rev Phytopathol. 2004;42(1):385-414.

  31. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215(3):403–10.

    Article  CAS  PubMed  Google Scholar 

  32. Liu B, Zheng D, Jin Q, Chen L, Yang J. VFDB 2019: A comparative pathogenomic platform with an interactive web interface. Nucleic Acids Res. 2019;47(D1):D687–92.

    Article  CAS  PubMed  Google Scholar 

  33. Liu M, Li X, Xie Y, Bi D, Sun J, Li J, Tai C, Deng Z, Ou HY. ICEberg 2.0: an updated database of bacterial integrative and conjugative elements. Nucleic Acids Res. 2019;47(D1):D660–5.

    Article  CAS  PubMed  Google Scholar 

  34. Li X, Xie Y, Liu M, Tai C, Sun J, Deng Z, Ou HY. OriTfinder: a web- based tool for the identification of origin of transfers in DNA sequences of bacterial mobile genetic elements. Nucleic Acids Res. 2018;46(W1):W229–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Cury J, Touchon M, Rocha EPC. Integrative and conjugative elements and their hosts: composition distribution and organization. Nucleic Acids Res. 2017;45(15):8943-8956.

  36. Burrus V, Pavlovic G, Decaris B, Guédon G. Conjugative transposons: the tip of the iceberg. Mol Microbiol. 2002;46(3):601–10.

    Article  CAS  PubMed  Google Scholar 

  37. Bateman A. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res. 2019;47(D1):D506–15.

    Article  CAS  Google Scholar 

  38. Bateman A, Coin L, Durbin R, Finn RD, Hollich V, Griffiths-Jones S, Khanna A, Marshall M, Moxon S, Sonnhammer ELL, Studholme DJ, Yeats C, Eddy SR. The Pfam protein families database. Nucleic Acids Res. 2004;32:138–41.

    Article  CAS  Google Scholar 

  39. Urban M, Cuzick A, Rutherford K, Irvine A, Pedro H, Pant R, Sadanadan V, Khamari L, Billal S, Mohanty S, Hammond-Kosack KE. PHI-base: a new interface and further additions for the multi-species pathogen-host interactions database. Nucleic AcidsResearch. 2017;45(D1):D604–10.

    Article  CAS  Google Scholar 

  40. Tay, D. M. M., Govindarajan, K. R., Khan, A. M., Ong, T. Y. R., Samad, H. M., Soh, W. W., Tong, M., Zhang, F., & Tan, T. W. T3SEdb: Data warehousing of virulence effectors secreted by the bacterial Type III Secretion System. BMC Bioinformatics. 2010;11(SUPPL. 7).

  41. Larkin MA, Blackshields G, Brown NP, Chenna R, Mcgettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG. Clustal W and Clustal X version 2.0. Bioinformatics. 2007;23(21):2947–8.

    Article  CAS  PubMed  Google Scholar 

  42. Darling ACE, Mau B, Blattner FR, Perna NT. Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Res. 2004;14(7):1394–403.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Gilchrist, C. L. M., & Chooi, Y. H. clinker & clustermap.js: Automatic generation of gene cluster comparison figures. BioRxiv. 2020

  44. Juraschek K, Borowiak M, Tausch SH, Malorny B, Käsbohrer A, Otani S, et al. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 2019;5:102.

    Article  CAS  Google Scholar 

  45. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Mol Biol Evol. 2018;35:1547–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references


This work was supported in part by the Conselho Nacional de Desenvolvimento Científico e Tecnológico-CNPq and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brazil (CAPES) – finance code 001.

Author information

Authors and Affiliations



MFS and JCSA conceived and designed the study; JCSA, OSG and ASF. collected and analysed the data; JCSA drafted the first version of the manuscript; OSG, ASF, MVQ, DMSB and MFS rafted subsequent versions of the manuscript. All authors contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Mateus Ferreira Santana.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Supplementary Table 1.

Genomes of Pseudomonas syringae analyzed in this work. Supplementary Table 2. Genomes of Ralstonia solanacearum Species complex analyzed in this work. Supplementary Table 3. Genomes of Agrobacterium tumefaciens analyzed in this work. Supplementary Table 4. Genomes of Xanhtomonas oryzae pv. oryzae analyzed in this work. Supplementary Table 5. Genomes of Xanthomonas campestris analyzed in this work. Supplementary Table 6. Genomes of Xanthomonas axonopodis analyzed in this work. Supplementary Table 7. Genomes of Erwinia amylovora analyzed in this work. Supplementary Table 8. Genomes of Xylella fastidiosa analyzed in this work. Supplementary Table 9. Genomes of Dickeya (dadantii and solani) analyzed in this work. Supplementary Table 10. Genomes of Pectobacterium carotovorum (and P. atrosepticum) analyzed in this work. Supplementary Table 11. ICEs identified in the genomes of the main phytopathogenic bacteria. Supplementary Table 12. Size and GC content of the identified elements. Supplementary Table 13. Attachment sites. Supplementary Table 14. Insertion sites, Type of Integrase and Relaxase. Supplementary Table 15. Putative significant cargo genes carried by ICEs characterized in this work. Supplementary Table 16. Elements of this work described in the literature.

Additional file 2: Supplementary Figure 1.

Gene clusters comparision of Agrobacterium tumefaciens ICEs. Supplementary Figure 2. Gene clusters comparision of Dickeya ICEs. Supplementary Figure 3. Gene clusters comparision of Pectobacterium carotovorum (and atrosepticum) ICEs. Supplementary Figure 4. Gene clusters comparision of group 1 Pseudomonas syringae ICEs. Supplementary Figure 5. Gene clusters comparision of group 2 Pseudomonas syringae ICEs. Supplementary Figure 6. Gene clusters comparision of group 3 Pseudomonas syringae ICEs. Supplementary Figure 7. Gene clusters comparision of RSSC ICEs. Supplementary Figure 9. Gene clusters comparision of Xylella fastidiosa ICEs. Supplementary Figure 10. ICEs identity matrix heatmaps.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de Assis, J.C.S., Gonçalves, O.S., Fernandes, A.S. et al. Genomic analysis reveals the role of integrative and conjugative elements in plant pathogenic bacteria. Mobile DNA 13, 19 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: