<figure><img src="image_62.png" /><figcaption>**FIGURE 4** | Minimum spanning trees of 107 *Xanthomonas citri* pv. *viticola* strains, comprising 105 Brazilian strains and two strains from India (CFBP 7660 and 7691), based on MLVA with 8 VNTR markers. The circles represent a MLVA type. The types that are connected by a thick solid line differed by 1 VNTR locus; MLVA types connected by thin solid lines differed by 2-3 VNTR loci, and the types that differed by 4 or more loci are connected by dashed and dotted lines. (A) The gray zone represents clonal complexes comprising MLVA types that differ from one another by one locus, (B) the gray zone groups types that differ by one or two loci.</figcaption></figure>

MLVA Typing Revealed Diversity in the
Pathogen Population From Brazil

In a collection of 107 pathovar *viticola* strains, the number
of alleles ranged from 5 to 12 and the copy numbers of
the repeat sequences ranged from 3 to 29. Four VNTR loci
were the most diverse (diversity indexes over 80%): XL-1, -
4, -3, and -6. The other four revealed less diversity in the
collection. For example, for XL-8, 95 strains (88.8%) presented
the same allele (Table 2). A total of 101 haplotypes were detected,
but none of them was overrepresented in this set of strains.
The discriminatory power of the MLVA was calculated and it
showed a level of discrimination of 0.9563 for 107 typed strains.
A MST based on repeat copy numbers shows the relationships
among 107 strains in relation to the year of isolation and a
subdivision in several clusters (Figure 4). The VNTR markers
clearly separated the two Indian strains from the Brazilian
strains. These strains from India, isolated in 1969 and 1972,
had unique alleles at three loci (XL-4, -8, and -5) and differ
from each other by one mismatch at locus XL-1. Three larger
clonal complexes composed by strains that differed by only one
VNTR were detected in the Brazilian set of strains. Two of these
complexes contained older strains, which were isolated in 1998,

the year of the first disease outbreak in Brazil. Bayesian clustering
was performed in Structure supporting four groups (K = 4).
Analysis of these groups revealed one population with greater
admixture containing the Indian strains, two groups containing
isolates from 1998 to 2012 and one group with isolates from
2006 to 2012 with overlapping (Figure 5). The E-burst algorithm
identified also three clusters of related genotypes, and several
singletons (Figure 6). The predicted founders for the three
clusters are strains 1193, 1194 and 54. Strains 1193 and 1194
were both isolated from Red Globe vines in 1998 in Petrolina,
state of Pernambuco, but from two different vineyards. However,
when grouping the strains that shared identical alleles at 6 or 7
loci, one single large clonal complex appeared (Figures 4B, 6).
The predicted founder of this larger complex was strain 1194
from which the larger number of single and double locus
variants emerged.

The two strains (4779B and 482) that were more geogra-
phically distant (i.e., detected in the states of Parana, south of
Brazil, and Roraima, northwest of Brazil, respectively) had unique
alleles at loci XL-6 and XL-1, respectively. Several strains appear
as singletons not belonging to the three major clonal comp-
lexes (eBURST and MST), for example, strain 26 (Figure 4A).
<figure><img src="image_63.png" /></figure>

**FIGURE 5** | STRUCTURE outputs for a test panel of 107 strains of *Xanthomonas citri* pv. *viticola*. Best K, the true value for number of clusters, was selected using the Evanno method (Evanno et al., 2005). Colors represent groups identifiable by Bayesian clustering.

<figure><img src="image_64.png" /></figure>

**FIGURE 6** | E-BURST network based on eight VNTR markers showing single locus variants (thick dark lines) and double locus variants (light blue lines) in a collection of 107 *Xanthomonas citri* pv. *viticola* strains, comprising 105 Brazilian strains and two strains from India (CFBP 7660 and 7691). The predicted founders of each clonal complex (strains 1193, 1194 and 54) are indicated with colored solid circles. The colors correspond to their groups in the Structure analysis (Figure 5).

This strain has one unique allele at locus XL-15 and it is also unique as far as to its collection site. It was collected in 2009 in the same municipality (Petrolina) as most others, but it is the only strain in the collection from one specific grape-producing area.

Regarding the host of isolation, the three strains from *Amaranthus* (Am-1, Am-2, and Am-3) had three distinct MLVA profiles and those were not identical to any of the strains collected from grapevines in the same area, in the same year (P1S5, P1S6, P1S9, P1S12, and P1S16). Strain Am-1, for example, had different copy numbers for 3 VNTRs compared to strains P1S5 and P1S16, that share the same MLVA type. Only one VNTR locus (XL 13) was monomorphic among the three Amaranthus and the five grape strains collected in the same area and year. Interestingly strain Am-3 and the founder genotype of one of the clonal complexes (strain 1194) were identical in 7 loci (Figure 4).

CFBP 7764 Genome Features Are Typical
of Plant Pathogenic Xanthomonads

Strain CFBP 7764 was chosen for whole genome sequencing
analysis because it was isolated in Brazil with a time lapse of
more than 40 years compared to the Indian pathotype strain.
Shotgun sequencing yielded 8,390,830 100-bp paired-end reads

with an insert size of 250 bp. A combination of Velvet (Zerbino
and Birney, 2008), SOAPdenovo, and SOAP Gapcloser (Luo et al.,
2012) yielded 76 contigs (N50, 592,828 bp), with the largest
contig being 791,586 bp, for a total assembly size of 5,311,793 bp.
Genomic sequence of this strain CFBP 7764 showed a typical
*Xanthomonas* gene content (Alegria et al., 2005; Potnis et al.,
2011). The genes encoding the main secretion systems described
in Gram-negative bacteria were detected in the genome of strain
CFBP 7764. Genes encoding at least two T1SSs and two more
putative T1SSs were identified. Genes encoding proteins involved
in Tat and Sec pathways, in two complete T2SSs (Xcs and
Xps) and 77 putative T2-secreted cell wall degrading enzymes
were predicted. The hrp cluster encoding the T3SS-Hrp2 family
and 17 T3E-genes (*avrBs2*, *xopA*, *xopAE*, *xopAI*, *xopAQ*, *xopB*,
*xopC2*, *xopE1*, *xopE3*, *xopK*, *xopL*, *xopN*, *xopP*, *xopQ*, *xopV*, *xopX*,
*and xopZI*), a T4SS gene cluster similar to the chromosomic
cluster of Xac306 (Alegria et al., 2005), and a single T6SS cluster
belonging to the group 3 (Potnis et al., 2011) were predicted.
Strain CFBP 7764 is fully equipped with genes necessary to sense
and move in its environment, to protect itself, and to acquire
nutrients, through a complete flagellar system, at least 25 MCPs
(methyl-accepting chemotaxis proteins), complete type I and
type IV pili, several T5SS, including *fhaB*, *fhaC*, *shlB*, and *yapH*,
xanthan biosynthesis and near seventy TBDTs. At least, almost 120 genes encoding TCSs could be involved in the detection and the response to environmental signals. Comparison of the genomic sequences of the two strains of *X. citri* pv. *viticola* did not show any differences in all these functions. The draft quality of the genome sequences did not allow an exhaustive analysis of IS content. It was however possible to observe some diversity between both strains. CFBB 7764 harbored partial sequences homologous to ISXac2 and ISXc8 from IS3 family that were not detected in LMG 965 sequence. Reciprocally, LMG 965 had sequences homologous to IS1477 from IS5 family that was not detected in CFBB 7764 (Supplementary Table S2).

As in strain LMG 965, the xanthomonadine biosynthesis gene cluster showed a truncated gene that can explain the white aspect of the colonies, in contrast to the yellow colonies of most species of the genus *Xanthomonas* (Midha and Patil, 2014). Comparison based on reciprocal tBLASTNs of the genomic sequences of CFBP 7764 and LMG 965 revealed 26 CDSs predicted in LMG 965 genome that had no orthologs in CFBP 7764, most of them were probably on a 16 Kb plasmid in LMG 965. Conversely, 233 CDSs predicted in CFBP 7764 genome had no orthologs in LMG 965 (Supplementary Tables S2, S3). These CDSs were distributed in several clusters, corresponding to almost 15 whole contigs of various sizes (between 64.4 and 0.8 Kb). Around 100 of these 233 CDSs had no orthologs in NCBI nr database. Most of the remaining CDSs had orthologs in plasmid sequences, such as plasmid pB07007 of *X. hortorum* strain B07-007, plasmid C of *X. citri* pv. fuscans strain 4834R, plasmid pICMP7383.2 of *X. gardneri*, and plasmid pH3.1 of *X. euvesicatoria* pv. perforans strain LH3. Apart from numerous CDSs encoding proteins involved in conjugation, these putative plasmids carried CDSs encoding functions such as toxin-antitoxin, restriction and anti-restriction proteins, multidrug efflux systems and copper resistance genes (Supplementary Table S3). A copLAB gene cluster has hence been evidenced in CFBP 7764.

## Availability of Epidemiological Contrasted Genome Sequences to Design New VNTRs

The eight VNTRs used in this study were initially developed for *X. citri* pv. *citri* (Bui Thi Ngoc et al., 2009). These VNTRs were found within the two genomes of *X. citri* pv. *viticola* strains, being, however, slightly divergent (Supplementary Tables S4, S5). All VNTRs had a 7-nucleotide repeat motif and were distributed among six different contigs in both genomes. Genome mining showed that five of these eight VNTRs (XL3, XL 4, XL5, XL 8, and XL15) have different repeat numbers in these two strains isolated at a 43-year interval in different continents (Supplementary Table S4). Except for XL 5 and XL6, the numbers of repeats and number of loci with different copy numbers between the two strains were greater in the experiments (amplicon sequencing) than in the genome mining-based prediction. This was due to degenerated repeats that were not taken into account in the prediction using the Tandem Repeats Finder tool. Taking the opportunity of having these two genome sequences, we designed a set of 32 new VNTRs

(Table 3). VNTRs were selected based on a repetition number higher than two, a length shorter than 100 bp, a high motif conservation within the VNTR (95%) and different repetition numbers between the two genome sequences. This VNTR scheme included repeats with motifs varying from three to 16 nucleotides and covering 11 different contigs, in particular five and nine VNTRS were designed in the two large contigs from CFBP 7764 (G102 and G103) that were not targeted with the *X. citri* pv. *citri* VNTR scheme, giving a wider representation of the entire genome sequence.

## DISCUSSION

Although it was first described in 1972, the emergence of *X. citri* pv. *viticola* as a grapevine pathogen is relatively recent with outbreaks in India (1990) and Brazil (1998). Analysis of a Brazilian collection of strains showed that this pathovar lacks genetic diversity in seven housekeeping genes and confirms its status as a monophyletic pathovar of *X. citri* species. Further knowledge of the diversity of this pathogen was possible through a MLVA scheme with eight VNTR loci which allowed a better understanding of the genetic structure of the Brazilian strains.

Primers for amplification of VNTR loci in bacterial plant pathogens have been designed from draft or complete genome sequences (Arrieta-Ortiz et al., 2013; Cesbron et al., 2014; Cunty et al., 2015; Poulin et al., 2015) or from genomes of close relatives (Pruvost et al., 2011). VNTR markers developed from a specific pathovar genome can be successfully used for genotyping other pathovars belonging to the same species, as shown for *X. arboricola* pv. *pruni* and related pathovars (Cesbron et al., 2014). For pathovar *viticola*, the genome sequence of the reference strain was not available at the beginning of this study, consequently VNTR markers designed for the citrus canker pathogen *X. citri* pv. *citri* (*Xanthomonas axonopodis* pv. *citri*) were tested. Pathovar *citri* is phylogenetically related to pathovar *viticola* based on *gyr* B sequences (Parkinson et al., 2009) and sequences from other housekeeping genes (Gama et al., 2018; this study). A closer relationship between these two pathovars had been previously demonstrated by whole-cell fatty acid methyl esters (FAMEs) following a comprehensive study of 975 xanthomonads strains (Yang et al., 1993). In fact, diseases caused by both pathovars, *viticola* and *citri*, were first noted in India and recent whole genome comparisons confirm that the two pathovars are members of the same species but with different host specificity (Midha and Patil, 2014; Bansal et al., 2017).

Eight out of 14 VNTR markers described for pathovar *citri*, were polymorphic for pathovar *viticola*. Six out of these eight markers can also reveal polymorphism among strains from the pathovars *mangiferaeindicae* and *malvacearum* (Bui Thi Ngoc et al., 2009), which also belong to the rep-PCR group 9.5 (Rademaker et al., 2005; Mhedbi-Hajri et al., 2013). Both pathovars have been included in the newly described *X. citri* species (Constantin et al., 2016).

Compared to other methods for deciphering population structures and diversity, MLVA has much higher resolution, and can be applied to human pathogens that lack diversity
<table><caption>TABLE 3 | VNTR scheme designed based on CFBP 7764 and LMG 965 genome sequences.</caption><thead><tr><th colspan="4">VNTR</th><th colspan="2">CFBP7764</th><th colspan="2">LMG 965</th></tr><tr><th>Name</th><th>Repeat sequence</th><th>Period size</th><th>Left primer</th><th>Right primer</th><th>Copy number</th><th>Amplicon size</th><th>Copy number</th><th>Amplicon size</th></tr></thead><tbody><tr><td>7764V1</td><td>GCTGTC</td><td>6</td><td>caattcagtcaggcgattt</td><td>tagaaaaacgtcgcgcatc</td><td>12.5</td><td>323</td><td>6.5</td><td>326</td></tr><tr><td>7764V2</td><td>TcGGGAA</td><td>7</td><td>aagacgttgacgccaaaag</td><td>ttagcgagcaccgtaaggac</td><td>7.4</td><td>305</td><td>8.4</td><td>351</td></tr><tr><td>7764V3</td><td>GCAACGG</td><td>7</td><td>cctatcgacggtccgtttta</td><td>cccttcctccttccaaact</td><td>4.6</td><td>268</td><td>5.4</td><td>275</td></tr><tr><td>7764V4</td><td>CATCGCCCAA</td><td>10</td><td>gacggtgtttcgggaatg</td><td>cggcacctatctggcatatc</td><td>2.9</td><td>300</td><td>1.8</td><td>290</td></tr><tr><td>7764V5</td><td>TCGGGAA</td><td>7</td><td>catcaggtagcggtgagag</td><td>tggaatacatcacagcgacaac</td><td>6.4</td><td>308</td><td>5.3</td><td>301</td></tr><tr><td>7764V6</td><td>TgGGGAA</td><td>7</td><td>atacaggtgcccgaaggttt</td><td>aagcgcacatggcaataag</td><td>8.1</td><td>296</td><td>6</td><td>282</td></tr><tr><td>7764V7</td><td>CTTCTG</td><td>6</td><td>gtaaggaaagcggcctcac</td><td>gtgtgtgagcgtcagaaagg</td><td>6.3</td><td>311</td><td>4.8</td><td>302</td></tr><tr><td>7764V8</td><td>GAATCGG</td><td>7</td><td>caacaggccgagagatcatt</td><td>ccgtacactccggttctgag</td><td>5</td><td>297</td><td>7</td><td>311</td></tr><tr><td>7764V9</td><td>GCCCCATCGCAT</td><td>11</td><td>gtcgtacgggtatgcaagtg</td><td>atggattttgctgctgtgtg</td><td>6.5</td><td>312</td><td>4.5</td><td>290</td></tr><tr><td>7764V10</td><td>GCCAAT</td><td>6</td><td>gggattcgggattttgctaac</td><td>gagctgagttgaccgtggag</td><td>4.8</td><td>300</td><td>5.8</td><td>306</td></tr><tr><td>7764V11</td><td>GCG</td><td>3</td><td>aacacctgacccttcgatca</td><td>cggatgcagcagatggac</td><td>12.3</td><td>291</td><td>11.3</td><td>288</td></tr><tr><td>7764V12</td><td>ATTCCCc</td><td>7</td><td>aatcgggaatggagaaaaagc</td><td>cggccactacgccacctat</td><td>13.9</td><td>296</td><td>16.9</td><td>317</td></tr><tr><td>7764V13</td><td>GTGGCA</td><td>6</td><td>aggtcatcgtgccgtcttc</td><td>gtaaccccatcgcctacaag</td><td>4.3</td><td>293</td><td>5.3</td><td>299</td></tr><tr><td>7764V14</td><td>GTGTTG</td><td>6</td><td>gctgtggtgatgtttgctttt</td><td>tccactcacaactgcacagc</td><td>11</td><td>301</td><td>9</td><td>289</td></tr><tr><td>7764V15</td><td>GAATCGG</td><td>7</td><td>gatggcgttcgaataacctg</td><td>ccaggatcaggaggtctacag</td><td>6</td><td>315</td><td>5</td><td>308</td></tr><tr><td>7764V16</td><td>GGGCTGC</td><td>7</td><td>gttcggacatccaccgtatc</td><td>ggcggctagttctttgtcag</td><td>7.3</td><td>271</td><td>5.3</td><td>257</td></tr><tr><td>7764V17</td><td>CCCGAAT</td><td>7</td><td>agttgtacaaggcgcgctaa</td><td>ttgctgaagcagcaggatag</td><td>10.7</td><td>296</td><td>5.7</td><td>261</td></tr><tr><td>7764V18</td><td>TCGTGAA</td><td>7</td><td>ttgtcatcgtggaagtttcc</td><td>cggagagacgttgggtaaga</td><td>7.4</td><td>302</td><td>8.4</td><td>309</td></tr><tr><td>7764V19</td><td>ATTCCCG</td><td>7</td><td>ccggttatctggtcaacga</td><td>gcctggtcgttgatatagcc</td><td>4.9</td><td>300</td><td>5.9</td><td>307</td></tr><tr><td>7764V20</td><td>GCGAGAT</td><td>7</td><td>ggtgctgactggttgaaggt</td><td>gggtcaactgcacatcggtat</td><td>3.6</td><td>315</td><td>2.4</td><td>308</td></tr><tr><td>7764V21</td><td>GGGAAGC</td><td>7</td><td>gcaättgagggcccgttagat</td><td>cagcacgttgtggttggat</td><td>6.1</td><td>294</td><td>7.1</td><td>301</td></tr><tr><td>7764V22</td><td>TGTAGA</td><td>6</td><td>ccttcagtcgtccatacct</td><td>gagatcggtcgggtgatg</td><td>6.3</td><td>336</td><td>8.3</td><td>348</td></tr><tr><td>7764V23</td><td>ACGCATC</td><td>7</td><td>gccgagtgaccgaaaacg</td><td>cagcagtcccaacacgaac</td><td>4</td><td>311</td><td>5</td><td>318</td></tr><tr><td>7764V24</td><td>AATCGGa</td><td>7</td><td>gtgcaatcggttgaaatgc</td><td>accttgccgctgtattacga</td><td>4.7</td><td>321</td><td>13.7</td><td>384</td></tr><tr><td>7764V25</td><td>GGCAGAA</td><td>7</td><td>tacagatcggtgcgagcag</td><td>gtggtcagtcgcgcctaaatc</td><td>4.7</td><td>313</td><td>2.6</td><td>299</td></tr><tr><td>7764V26</td><td>GCACCATCGCCACAAC</td><td>16</td><td>tacagacgtggcgggtgtat</td><td>gatgacatggaaacgcaaaa</td><td>5.2</td><td>297</td><td>6.2</td><td>312</td></tr><tr><td>7764V27</td><td>GCACCG</td><td>6</td><td>atcggctcggtcgtatt</td><td>gctatcgcaaaactggatcgt</td><td>8.5</td><td>298</td><td>6.5</td><td>286</td></tr><tr><td>7764V28</td><td>tTCCCGA</td><td>7</td><td>gctcaggaacgttgaaagcat</td><td>atccgctgatcatcgtc</td><td>8</td><td>291</td><td>10</td><td>305</td></tr><tr><td>7764V29</td><td>CGTCGATCCCCG</td><td>12</td><td>tgaatcaggtccacatgagc</td><td>caccacgtcgtactccactg</td><td>2.2</td><td>326</td><td>1.1</td><td>314</td></tr><tr><td>7764V30</td><td>CGTTGTG</td><td>7</td><td>gtgtcggtggacgtggaat</td><td>ctctgtgcactgcggtaatg</td><td>8.4</td><td>301</td><td>13.4</td><td>336</td></tr><tr><td>7764V31</td><td>TTTCCGA</td><td>7</td><td>gcvccacaaacaacaaaag</td><td>gtcgcagctgttcaagaat</td><td>13.3</td><td>266</td><td>9.3</td><td>238</td></tr><tr><td>7764V32</td><td>CCGAATC</td><td>7</td><td>gacgctgctagaatgacagc</td><td>tgagtcaggcggatcttctt</td><td>5.1</td><td>298</td><td>6.1</td><td>305</td></tr></tbody></table>

in housekeeping genes, i.e., monomorphic (Achtman, 2008). Among plant pathogens examples of monomorphic pathogens are *Pseudomonas syringae* pv. *actinidae* biovar 3 (Cunty et al., 2015) and X. citri pv. citri (Pruvost et al., 2014; Leduc et al., 2015). In a similar way, MLSA approach lacks resolution to distinguish among strains of pathovar *viticola*. Strains from India and Brazil were identical in all seven genes. Four (dnaK, fyuA, gyrB, and rpoD) out of these seven loci were also used in the MLSA scheme proposed by Young et al. (2008) for species differentiation in Xanthomonas. Consequently, the VNTR markers were chosen to help us gain some insight and an overview of the genetic structure of pathovar *viticola* strains isolated in Brazil since the 1998 outbreak and to understand how these strains are linked to the Indian strains. The MLVA scheme with eight loci proved to be efficient tool for discriminating strains that had identical housekeeping genes sequences (Figure 4). Even though strains isolated in the same year, in the same location and from the same cultivar (many isolated from Red Globe vines) are

overrepresented in the collection, MLVA had enough resolution to distinguish strains from the same area, strains from a weed host and grapevine, and to distinguish most Brazilian strains from the strains from India.

Grapevine bacterial canker is a disease with limited distribution around the globe. It was reported from India more than 40 years ago, but only in the last 20–25 years, it gained economic importance. Serious disease outbreaks occurred in India in the late 1980’s and were linked to increases in the area cultivated with the susceptible seedless cultivars (Chand and Kishun, 1990). The reported yield losses in severely infected vineyards were up to 60 or 80%. In 1998, the disease was first noted in Brazil affecting mostly seedless varieties. Currently, regarded as a quarantine pest in Brazil, control measures based on surveillance and eradication have been adopted (Naue et al., 2014). The detection of infected plants in other states and regions in the country (Halfeld-Vieira and Nechet, 2006;
Rodrigues Neto et al., 2011) reveals pathogen spread by asymptomatic propagating material, which leads ultimately to eradication procedures. In the state of São Paulo, approximately 4,700 plants were destroyed due to a disease outbreak in 2009 (Rodrigues Neto et al., 2011).

A possible introduction event associated with propagating material originating from India has been hypothesized to explain the emergence of this disease in Brazil (Rodrigues Neto et al., 2011). This event should have taken place at least 3 years before the disease outbreak in 1998, since the first symptoms were observed on young vines up to 3 years of age. The lack of sequence variation in seven housekeeping genes among Brazilian and Indian strains shows that, globally, it is a monomorphic pathogen. A genetically monomorphic pathogen may arise from a strong reduction in the population size of the ancestors of the existing strains due to a recent bottleneck (Achtman, 2008). Housekeeping genes encodes essential metabolic enzymes for species survival, thus they may undergo strong purifying selection, as demonstrated for most phylotypes of the plant pathogen *Ralstonia solanacearum* (Castillo and Greenberg, 2007).

A panel of eight polymorphic VNTR markers derived from *X. citri* pv. *citri* was developed for *X. citri* pv. *viticola* and showed genetic diversity in a set of 105 strains from Brazil. The high discriminatory power of MLVA revealed patterns of genetic diversity nor detected by previous studies with rep-PCR (Trindade et al., 2005; Gama et al., 2018). MST and Structure analyses identified three congruent major genetic groups in the Brazilian collection. The epidemic-related strains from 1998 were separated in two groups while the two strains from India were clustered. A fourth group (red) detected by Structure (Figure 5) was not clearly understood as it groups the two strains from India with 23 strains from Brazil that were, mostly, not connected to the major MST clonal complexes and appear as singletons. Furthermore, admixture among populations was observed (Figure 5).

Some strains found in the same field, from the same grape cultivar and year of collection shared the same haplotype (P1S5 and P1S16; 1193 and 1195). However, same haplotypes were also shared by strains collected from neighboring states (CFBP 7676 and 1192; 191 and 119), which suggests dissemination by the planting or grafting of symptomless contaminated plant material. That would also explain the disease outbreaks in two more distant states in the country (Paraná, in the southeast and Roraima, in the north region).

Most Brazilian strains are members of three larger clonal complexes (Figure 4A). The predicted founder genotypes of two clonal complexes are strains 1194 and 1193 which were isolated in 1998 from Red Globe vines. These strains are not linked to the two Indian strains isolated in 1969 and in 1972. The fact that the Brazilian strains from 1998 belong to two distinct clonal complexes suggests that the 1998 outbreak of grapevine bacterial canker in Brazil probably occurred through one introduction event of two distinct grapevine planting materials contaminated with genetically distinct strains. The development of the irrigation projects in the São Francisco River valley in Brazil started in the 1970's and the introduction and

exchange of propagating material of different grape varieties occurred over time.

The lack of a more diverse and recent collection from India did not allow us to draw conclusions about the events that lead to the emergence of this pathogen in Brazil. We hypothesize that the 1998 outbreak-related strains from Brazil are probably epidemiologically linked to the strains that caused the severe disease outbreaks in India in the late 1980's (Chand and Kishun, 1990) which were highly aggressive on seedless varieties, but not linked to the ancient strains (1969/1972) as shown by the results.

The environment where conditions are variable may favor the existence of more genetically diverse populations, from which new crop strains emerge, often as highly virulent clones (Goss et al., 2013). Alternative hosts harboring potential sources of inoculum may contribute to amplify the diversity observed in Brazil. In Brazil, xanthomonads-like bacteria have been isolated from several weeds growing in the vicinity of vineyards. Their pathogenicity was confirmed in the original host and in Red Globe grapevines (Peixoto et al., 2007). In the present study we provide further evidence on the identification of three *Amaranthus* strains, collected in a Red Globe area in 2012. Pathogenicity of these strains on grapevine was confirmed. Based on MLSA these strains have 100% identity to the grape strains, confirming the potential of pathovar *viticola* to survive and infect weeds such as *Amaranthus* sp. as alternative hosts. Neem is often employed as windbreaks in vineyards in Brazil and has been described as a natural host in India (Nayudu, 1972). Mango is also grown in the same region in Brazil and can develop symptoms upon inoculation with pathovar *viticola* (Chand and Kishun, 1990). However, natural populations of pathovar *viticola* infecting neem or mango have never been reported. Isolations from neem have been unsuccessful (Peixoto et al., 2007) and whether pathovar *viticola* strains can survive epiphytically and/or infect mango under natural conditions remains unknown.

Genome mining revealed that strain CFBP 7764 had all genes necessary to a *Xanthomonas* strain to sense and move in its environment, to protect itself, and to acquire nutrients. Presence of the different types of secretion systems (T1SS to T6SS) and their numerous effectors confirmed the pathogenic nature of strain CFBP 7764. Comparison of the genomic sequences of the two strains of *X. citri* pv. *viticola* did not show any differences in all these functions but revealed differences mostly in plasmid content. Indeed, the presence of sequences that matched with one or several plasmids was detected in strain CFBP 7764, and the sequences had no orthologs in LMG 965; reciprocally the sequences from one plasmid of LMG 965 had no orthologs in CFBP 7764. However, the sequencing technology used did not allow to obtain a sufficiently high-quality sequence to properly assemble the putative plasmids. Plasmids allow phytopathogenic bacteria to maintain a dynamic, flexible genome and possible advantage in host-pathogen and other environmental interactions (Sundin, 2007).

We proposed a new VNTR scheme, based on the analysis of genomic sequences of two strains representing epidemics from India and Brazil. This scheme could complete the previously proposed *X. citri* pv. *citri* VNTR scheme. Indeed, the VNTRs from the newly proposed scheme were chosen
specifically to have different copy numbers between the two sequenced strains in order to enhance the probability to have variable loci in Brazilian vs. Indian strain collections. This scheme encompasses a majority of VNTRs with a short repeat motif (≤7) that should be particularly well suited for epidemiologically related strains as previously mentioned (Pruvost et al., 2014). Furthermore, we designed some VNTRs with a longer repeat motif (up to 16), all together that should allow epidemiological surveys at various scales, with shorter repeat motifs being suited for small to medium spatio-temporal scales and larger ones for global surveillance (Poulin et al., 2015). This study is the first step toward a MLVA scheme suitable for assessing the genetic structure of pathovar *viticola*, which may help to identify inoculum sources and understand how this pathogen disseminated at both local and intercontinental scales. Comparing population diversity of this bacterial pathogen in its native area (India) and invaded regions in Brazil, may contribute to our knowledge of how bacterial plant pathogens emerge and adapt in new environments. Furthermore, the recent availability of two complete genome sequences of pathovar *viticola* (this study, Lima et al., 2017) will improve our understanding of genome diversity and the relationships among strains from different geographical origins.

## CONCLUSION

In this study, we used sequences of housekeeping genes to confirm the taxonomic status of strains pathogenic on grapevine and *Amaranthus* as members of *Xanthomonas citri* pv. *viticola*. We demonstrated that pathovar *viticola* is a well-defined and monophyletic pathovar, distinct from three other pathovars from India, that affect plants in the Vitaceae family. Based on MLSA, Brazilian strains do not differ from two ancient strains from India. In contrast, eight polymorphic VNTR markers allowed us to assess the genetic structure of the pathogen in Brazil and suggested one introduction event of two genetically distinct groups of strains that lead to adaptation of this pathogen in the country. MLVA showed that Brazilian strains from 1998 and the two ancient Indian strains are not epidemiologically linked. Whole genome comparisons between two strains from India and Brazil, collected within a gap of 43 years revealed new VNTR

markers that could be useful to assess diversity at various scales. Our results provided novel information and insights into how this pathogen emerged in Brazil. Validation of this method with a larger collection of strains, especially from India, could be subject of future studies. This is the first report of a MLVA scheme for rapidly assessing diversity in this plant pathogen.

## AUTHOR CONTRIBUTIONS

MF and M-AJ conceived and designed the study. MF and SB performed the multilocus sequencing analysis. AD and MB performed the genome analysis. PP, MG, MAB, ES, and RM contributed with strain collection, characterization and pathogenicity tests. MF and SC designed and performed the VNTR analysis. MF, M-AJ, AD, and SC wrote and critically reviewed the manuscript. All authors read and approved the final manuscript.

## FUNDING

Capes-MEC (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Ministério da Educação), Brazil, provided financial support for MF.

## ACKNOWLEDGMENTS

We would like to thank Karine Durand, Jacky Guillaumes, and Geraldine Taghouti for their technical assistance. We would also like to thank Muriel Bahut and the ANAN platform from SFR Quasav for VNTR sequencings, and CIRM-CFBP (https://www6.inra.fr/cirm_eng/CFBP-Plant-Associated-Bacteria) for strain preservation and supply.

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2019.00489/full#supplementary-material

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**Conflict of Interest Statement:** 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.

Copyright © 2019 Ferreira, Bonneau, Briand, Cesbron, Portier, Darrasse, Gama, Barbosa, Mariano, Souza and Jacques. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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# A Pathovar of *Xanthomonas oryzae* Infecting Wild Grasses Provides Insight Into the Evolution of Pathogenicity in Rice Agroecosystems

## OPEN ACCESS

**Edited by:**

Dawn Arnold,
University of the West of England,
United Kingdom

**Reviewed by:**

Gongyou Chen,
Shanghai Jiao Tong University, China
David J. Studholme,
University of Exeter, United Kingdom

**\*Correspondence:**

Valérie Verdier
valerie.verdier@ird.fr

Jan E. Leach

Jan.Leach@colostate.edu

† These authors have contributed equally to this work

**Specialty section:**

This article was submitted to Plant Microbe Interactions, a section of the journal Frontiers in Plant Science

Received: 21 December 2018

Accepted: 02 April 2019

Published: 30 April 2019

**Citation:**

Lang JM, Pérez-Quintero AL, Koebnik R, DuCharme E, Sarra S, Doucoure H, Keita I, Ziegle J, Jacobs JM, Oliva R, Koita O, Szurek B, Verdier V and Leach JE (2019) A Pathovar of Xanthomonas oryzae Infecting Wild Grasses Provides Insight Into the Evolution of Pathogenicity in Rice Agroecosystems. *Front. Plant Sci.* 10:507. doi: 10.3389/fpls.2019.00507

Jillian M. Lang<fnref n="1" />,<fnref n="2" />†, Alvaro L. Pérez-Quintero<fnref n="1" />,<fnref n="2" />†, Ralf Koebnik<fnref n="2" />, Elysa DuCharme<fnref n="1" />, Soungalo Sarra³, Hinda Doucoure⁴, Ibrahim Keita⁴, Janet Ziegle⁵, Jonathan M. Jacobs<fnref n="1" />,<fnref n="2" />,⁶, Ricardo Oliva⁷, Ousmane Koita⁴, Boris Szurek<fnref n="2" />, Valérie Verdier<fnref n="1" />,<fnref n="2" />* and Jan E. Leach<fnref n="1" />*

*Xanthomonas oryzae* (Xo) are globally important rice pathogens. Virulent lineages from Africa and Asia and less virulent strains from the United States have been well characterized. *Xanthomonas campestris* pv. *leersiae* (Xcl), first described in 1957, causes bacterial streak on the perennial grass, *Leersia hexandra*, and is a close relative of Xo. *L. hexandra*, a member of the Poaceae, is highly similar to rice phylogenetically, is globally ubiquitous around rice paddies, and is a reservoir of pathogenic Xo. We used long read, single molecule real time (SMRT) genome sequences of five strains of Xcl from Burkina Faso, China, Mali, and Uganda to determine the genetic relatedness of this organism with Xo. Novel transcription activator-like effectors (TALEs) were discovered in all five strains of Xcl. Predicted TALE target sequences were identified in the *Leersia perrieri* genome and compared to rice susceptibility gene homologs. Pathogenicity screening on *L. hexandra* and diverse rice cultivars confirmed that Xcl are able to colonize rice and produce weak but not progressive symptoms. Overall, based on average nucleotide identity (ANI), type III (T3) effector repertoires, and disease phenotype, we propose to rename Xcl to X. oryzae pv. *leersiae* (Xol) and use this parallel system to improve understanding of the evolution of bacterial pathogenicity in rice agroecosystems.

**Keywords:** Xanthomonas oryzae, transcription activator-like effectors (TALEs), agroecosystem, cutgrass, rice

<footnote n="1">¹ Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO, United States,</footnote>

<footnote n="2">² IRD, Cirad, Univ. Montpellier, IPME, Montpellier, France, ³ Centre Régional de Recherche Agronomique de Niono, Institut d’Economie Rural, Bamako, Mali, ⁴ Laboratoire de Biologie Moléculaire Appliquée, Université des Sciences Techniques et Technologiques de Bamako, Bamako, Mali, ⁵ Pacific Biosciences, Menlo Park, CA, United States, ⁶ Department of Plant Pathology, Infectious Disease Institute, Ohio State University, Columbus, OH, United States, ⁷ International Rice Research Institute, Los Baños, Philippines</footnote>
# INTRODUCTION

Rice is a staple crop for more than half the world. Severe rice diseases, such as bacterial leaf streak (BLS) caused by *Xanthomonas oryzae* pv. *oryzicola* (*Xoc*) and bacterial blight (BB), caused by *X. o.* pv. *oryzae* (*Xoo*), are increasing in prevalence in parts of Asia and sub-Saharan Africa and cause significant yield losses. In Asia, perennial weeds are considered an important source of primary pathogen inoculum for these two diseases (Ou, 1985; Mew, 1987).

Southern cutgrass (*Leersia hexandra* Swartz) is a common grass found in the southern United States, South America, Africa, and Asia. It is a member of the Poaceae family and is closely related to rice, but diverged from *Oryza* approximately 14 mya (Guo and Ge, 2005). *L. hexandra* is an invasive species that frequently grows along rivers and canals surrounding rice paddies. Because of its close relationship to *Oryza* spp., *Leersia* spp. are included as outgroups in phylogenetic studies. Recent genome investigations of *Leersia perrieri*, a cutgrass found in Madagascar, were done to compare repetitive elements and transposable elements among *Oryza* sp. and to uncover orthologs of the important submergence tolerance gene, *SUB1* (Copetti, 2013; Copetti et al., 2015; dos Santos et al., 2017). One-third of the *L. perrieri* genome was found to consist of repeats. The high amount of newly discovered repeats (35%) indicates that the *L. perrieri* genome is evolving rapidly relative to the *Oryza* genus (Copetti, 2013).

Early reports of phytoremediation by *L. hexandra* showed this grass' capacity to sequester Cr, Cu, and Ni, and it has now been proposed as a tool in wastewater treatment (Liu et al., 2011; Wang et al., 2012; You et al., 2013). Interestingly, this and other grasses in this genus, such as *Leersia sayanuka*, *Leersia oryzoides*, and *Leersia japonica*, are susceptible to *Xoo* (Noda and Yamamoto, 2008) and can serve as reservoirs for inoculum. *Xoo* strains isolated from symptomless *L. hexandra* cause BB symptoms in rice, and, in artificially inoculated weed plants, *Xoo* multiplied without evidence of disease (Gonzalez et al., 1991) implicating this grass as an alternative host for the pathogen. These and other findings reinforce that effective integrated management of crop diseases must incorporate knowledge of pathogen interactions with weedy species.

The species *Xo* is highly diverse, and is represented by distinct lineages of *Xoo* from Asia and Africa, *Xoc* from Asia and Africa, and strains not assigned as a pathovar from the United States, *Xo* (Gonzalez et al., 2007; Triplett et al., 2011; Hajri et al., 2012; Poulin et al., 2015; Triplett and Leach, 2016). The term pathovar is used to refer to a strain or set of strains with the same or similar characteristics, differentiated at infrasubspecific level from other strains of the same species or subspecies on the basis of distinctive pathogenicity to one or more plant hosts<fnref n="1" />. Poulin et al. (2015) used multi-locus variable-number tandem-repeat analysis (MLVA) to investigate genetic structures of microbial populations (Zhao et al., 2012; Poulin et al., 2015), and suggested that *Xoo* and *Xoc* from Africa had a common Asian ancestor; this conclusion was based on the fact that the allelic richness,

or number of alleles, was significantly less in these populations. However, further analyses on an extensively sampled set of isolates are needed to confirm this ancestral hypothesis.

*Xanthomonas* spp. inject effector proteins into plant host cells to elicit disease via a type-III (T3) secretion system (White et al., 2009). These proteins can confer pathogenicity and/or dictate host specificity (Jacques et al., 2016). *Xanthomonas* spp. are most notable for production of transcription activator-like effectors (TALEs). TALEs influence host gene expression by directly binding to specific sequences [effector binding elements (EBEs)] in the target promoter as dictated by repeat-variable di-residues (RVDs) at the 12 and 13 amino acid position in the central repeat region (CRR) (Boch et al., 2009; Moscou and Bogdanove, 2009; White et al., 2009; Bogdanove and Voytas, 2011). The CRR contains different numbers of repeats, each with 33–35 amino acids. TALEs may enhance diseases by targeting susceptibility (S) genes, or may trigger a resistance response through activation of an “executor” resistance gene (R) expression (Boch et al., 2014; Hutin et al., 2015).

The presence of TALE effectors is variable in the genus (Jacques et al., 2016). *Xoo* contain nine to 20 TALEs while *Xoc* can contain up to 29. US *Xo* do not contain any TALEs, and due to this absence, have been employed as a tool to study TALE effector biology in rice (Ryba-White et al., 1995; Verdier et al., 2012). New sequencing technologies and predictive algorithms have accelerated the characterization of TALEs and their host gene targets. In particular, long read, single molecule real time (SMRT) sequencing (Pacific Biosciences, Menlo Park, CA, United States) has enabled the rapid assembly of TALE sequences that are otherwise laborious to capture due to their highly repetitive structure (Eid et al., 2009; Booher et al., 2015; Wilkins et al., 2015; Grau et al., 2016; Peng et al., 2016; Quibod et al., 2016; Tran et al., 2018). Collectively, TALE repertoires (TALomes) encoding polymorphic groups that have contrasted abilities to induce susceptibility target genes potentially underlie host adaptation at a small evolutionary scale (Doucouré et al., 2018). The *Xo* group has clearly undergone significant evolution influenced by geography, environment, and host, and TALomes can provide critical insight into how these events occur.

*Xanthomonas campestris* pv. *leersiae* (*Xcl*), a pathogen of *L. hexandra*, was previously shown to group distinctly from *Xo* by host range and phylogenetic analysis (Fang et al., 1957; Parkinson et al., 2009). However, using a multi-locus sequence alignment (MLSA) analysis Triplett et al. (2011) showed that *Xcl* strain NCPPB4346, which was isolated from southern cutgrass in China, groups within the *Xo* cluster, yet it could not be assigned to any described pathovar. A more recently isolated strain, BAI23 from weeds in Burkina Faso, showed high sequence similarity with *Xcl* NCPPB4346 based on a MLSA analysis as well as the presence of TALEs (Wonni et al., 2014). Together, the two strains form a distinct genetic cluster within *X. oryzae*.

Prediction algorithms based on the TALE's specific RVD pattern and their corresponding degenerate DNA code has facilitated identification of plant target genes whose promoters contain EBEs for TALE binding (Doyle et al., 2012; Grau et al., 2013, 2016; Pérez-Quintero et al., 2013; Booher and Bogdanove, 2014; Yang et al., 2014). Many *S* genes are transporters

<footnote n="1">¹www.isppweb.org/about_tppb_naming.asp</footnote>
(sugar or sulfate) or transcription factors and upon induction facilitate bacterial colonization and symptom development (Hutin et al., 2015; Tran et al., 2018). Although a large body of work is available on TALEs from *Xoo* and *Xoc*, no information has been reported on the TALEs from *Xcl*, how they compare to those in other *X. oryzae*, and the nature of their predicted targets within *Leersia* spp. In this study, we used comparative genomics, identification of T3 effectors, TALomes, and disease phenotyping to characterize *Xcl*. We used gene target prediction algorithms to identify potential *Xcl* TALE gene targets in draft *Leersia* genome sequences. Finally, we provide evidence to support renaming *Xcl* to *X. oryzae* pv. *leersiae* (Fang et al., 1957) and will refer to this organism as *Xol* throughout this work.

# MATERIALS AND METHODS

## Bacterial Strains and Plant Varieties

Bacterial strains included in this study are listed in Table 1. Bacteria were cultured on peptone sucrose agar (PSA) at 28°C for plant inoculations. Genomic DNA for sequencing was isolated from *Xol* strains BAI23, BB 151-3, BB 156-2, NCPPB4346, and NJ 6.1.1 grown for 48 h on nutrient agar at 28°C (Lang et al., 2014; Wonnii et al., 2014). Barley (*Hordeum vulgare* L. cultivar Morex), wheat (*Triticum aestivum* cv. Chinese Spring) and tobacco (*Nicotiana tabacum*) were grown in a growth chamber at 22°C, 50% relative humidity, and 16 h of light. Rice (*Oryza sativa*) varieties included in pathogenicity assays were Azucena, Carolina Gold, Cypress, IR64, and Nipponbare.

Southern cutgrass (*L. hexandra*) was collected in Texas, United States, and seed was propagated at Colorado State University. The seed was scarified then germinated in porous ceramic silica (Greens Grade, Profile Products, LLC, Buffalo Grove, IL, United States) and 0.5x Hoagland's solution with the following modifications: 2.5 mM KNO₃, 1 mM MgSO₄, 3 mM KH₂PO₄, 2.5 Ca(NO₃)₂, 0.05 mM FeSO₄, and 0.1 mM (Na)₂EDTA (Hoagland and Arnon, 1950). Seed was incubated in a petri dish in the dark for 8 days, then in the light for 30 days at 28°C. Germinated seeds were transplanted into 1-gallon pots with equal parts Greens Grade and ProMix BX (ProMix, Quakertown, PA, United States), and grown in a greenhouse (27 ± 1°C, 16 h day length, and 80-85% relative humidity). Additional plants were obtained from the two mother plants via rhizome propagation. Propagation began 30 days after planting with subsequent propagation every week to allow time for new growth. To promote root growth, plants were placed in the dark for 24 h.

## Pathogenicity Assays

Rice varieties were inoculated at 4-5 week-old with suspensions ($10^8$ CFU mL⁻¹) of bacterial strains listed in Table 1. Bacterial suspensions were both infiltrated into the intercellular spaces of rice leaves on either side of the main vein with a needleless syringe and inoculated by leaf clipping as described (Kauffman et al., 1973; Reimers and Leach, 1991). Two leaves were inoculated on each of three to six separate plants; water was included as a negative control. The entire experiment was conducted

twice. Lesions were measured at 12 days post inoculation (dpi), and bacterial numbers *in planta* were quantified as previously described (Verdier et al., 2012).

## Molecular Diagnostics

To test relationships of *Xol* to *Xo* (Notomi et al., 2000; Triplett et al., 2011; Wonnii et al., 2014), a diagnostic multiplex and loop mediated isothermal amplification (LAMP) PCR were used (Lang et al., 2010, 2014; Wonnii et al., 2014). Previously described universal US *Xo* primers were also tested to differentiate *Xol* from this novel US clade within the species (Triplett et al., 2011). UniqPrimer was employed to compare draft *Xol* genomes (BAI23 and NCPPB4346) and generate primers specific to *Xol* as previously described (Ash et al., 2014; Lang et al., 2014, 2017; Juanillas et al., 2018). Specificity was validated by screening *Xol* primers against diverse pools of bacterial genomic DNA (Table 1). Primers, expected product size, and optimal annealing temperatures are listed in Supplementary Table S1.

## Genome Sequencing and Assembly

Long read, SMRT sequencing (PacBio, Menlo Park, CA, United States) data were generated for five *Xol* strains and for the *Xo* strain X11-5A, to be used as an outgroup. DNA for SMRT sequencing was isolated by culturing strains on nutrient agar for 48 h then using the Genomic DNA buffer set and Genomic-tips according manufacturer instructions (Qiagen, Valencia, CA, United States). SMRT sequence was assembled using HGAP v4 (PacBio, Menlo Park, CA, United States). Genomes were circularized using circulator (Hunt et al., 2015). Assemblies and raw data have been deposited in NCBI (BioProject IDs PRJNA522807 and PRJNA522811; BioSample accessions SAMN03862116, SAMN02469650, SAMN10956066-68, SAMN10956070; raw sequencing files SRX5417793-98; Assembly accessions CP036251-56). Assembly CP036251 (X11-5A) replaces draft assembly GCF000212755.1 and assembly CP036253 (NCPPB4346) replaces draft assembly GCF001276975.1 (also in Bioproject PRJNA257008). Accessions for all genomes used in this study are listed in Supplementary Table S2.

## Phylogenomics and
Bioinformatic Analyses

In addition to the five *Xol* sequenced strains, all completely sequenced *X. oryzae* genomes were obtained from the NCBI to be used for comparisons, as well as representative genomes from other *Xanthomonas* species. All genomes and accessions can be found in Supplementary Table S2.

Average nucleotide identity (ANI) values were obtained using the ANI-matrix script from the enveomics collection (v1.3) (Rodriguez-R and Konstantinidis, 2016). Parsimony trees based on pan-genome SNPs were obtained using KSNP (v3.0) (Gardner et al., 2015). Multi-locus sequence analysis was made by identifying 33 housekeeping genes in all genome using Amphora2 (Wu and Scott, 2012). Concatenated amino acid sequences of these genes were then aligned using MUSCLE (v3.8.31) (Edgar, 2004), and neighbor-joining
<table><caption>TABLE 1 | Bacterial strains used in phenotyping and molecular diagnostics.</caption><thead><tr><th rowspan="2">Species</th><th rowspan="2">Strain</th><th rowspan="2">Origin</th><th rowspan="2">Host</th><th rowspan="2">Reference or source</th><th colspan="2">Response to diagnostic primer set</th></tr><tr><th>Xol5</th><th>Xol7</th></tr></thead><tbody><tr><td>Burkholderia andropogonis</td><td>3549</td><td></td><td>Zea mays</td><td>L.E. Claflin</td><td>—</td><td>—</td></tr><tr><td>Escherichia coli</td><td>DH5α</td><td></td><td></td><td></td><td>—</td><td>—</td></tr><tr><td>Pseudomonas fuscovaginae</td><td>SE-1</td><td>Philippines</td><td>Oryza sativa</td><td>G. Ash</td><td>—</td><td>—</td></tr><tr><td>P. syringae pv. syringae</td><td>M108</td><td>United States</td><td>Solanum lycopersicum</td><td>H.F. Schwartz</td><td>—</td><td>—</td></tr><tr><td>Xanthomonas sp.</td><td>M136</td><td>Mali</td><td>O. sativa</td><td>V. Verdier</td><td>—</td><td>—</td></tr><tr><td>Xanthomonas sp.</td><td>SHU100</td><td>Philippines</td><td>O. sativa seed</td><td>C.M. Vera Cruz</td><td>—</td><td>—</td></tr><tr><td>X. campestris pv. alfalfae</td><td>KX-1</td><td>United States</td><td></td><td>L.E. Claflin</td><td>—</td><td>—</td></tr><tr><td>X. c. pv. campestris</td><td>X1910</td><td>United States</td><td>Brassica oleracea</td><td>N. Dunlop</td><td>—</td><td>—</td></tr><tr><td>X. c. pv. pelargonii</td><td>X5</td><td>United States</td><td>Geranium sp.</td><td>L.E. Claflin</td><td>—</td><td>—</td></tr><tr><td>X. euvesicatoria</td><td>85-10</td><td>United States</td><td>Capsicum frutescens</td><td>A. Bogdanove</td><td>—</td><td>—</td></tr><tr><td>X. euvesicatoria</td><td>O177</td><td>United States</td><td>Allium cepa</td><td>H.F. Schwartz</td><td>—</td><td>—</td></tr><tr><td>X. oryzae</td><td>X11-5A<sup>a</sup></td><td>United States</td><td>O. sativa</td><td>Triplett et al., 2011</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. leersiae</td><td>BAI23<sup>a</sup></td><td>Burkina Faso</td><td>Weeds</td><td>V. Verdier, Wonnii et al., 2014</td><td>+</td><td>+</td></tr><tr><td>X. o. pv. leersiae</td><td>BB 151-3</td><td>Uganda</td><td>O. sativa</td><td>B. Yang, R. Oliva, G. Onaga</td><td>+</td><td>+</td></tr><tr><td>X. o. pv. leersiae</td><td>BB 156-2</td><td>Uganda</td><td>O. sativa</td><td>B. Yang, R. Oliva, G. Onaga</td><td>+</td><td>+</td></tr><tr><td>X. o. pv. leersiae</td><td>NCPPB4346<sup>a</sup></td><td>China</td><td>Leersia hexandra</td><td>Triplett et al., 2011; Wonnii et al., 2014</td><td>+</td><td>+</td></tr><tr><td>X. o. pv. leersiae</td><td>NJ 6.1.1</td><td>Mali</td><td>L. hexandra</td><td>This study</td><td>+</td><td>+</td></tr><tr><td>X. o. pv. oryzae</td><td>A3857</td><td>India</td><td>O. sativa</td><td>J.E. Leach</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzae</td><td>BAI3<sup>a</sup></td><td>Burkina Faso</td><td>O. sativa</td><td>V. Verdier</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzae</td><td>MAI1</td><td>Mali</td><td>O. sativa</td><td>V. Verdier</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzae</td><td>NAI8</td><td>Niger</td><td>O. sativa</td><td>V. Verdier</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzae</td><td>PXO86</td><td>Philippines</td><td>O. sativa</td><td>C.M. Vera Cruz</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzae</td><td>PXO99<sup>Aa</sup></td><td>Philippines</td><td>O. sativa</td><td>J.E. Leach</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzae</td><td>Xoo4</td><td>Thailand</td><td>O. sativa</td><td>J.E. Leach</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzae</td><td>Xoo199</td><td>Korea</td><td>O. sativa</td><td>S.H. Choi</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzicola</td><td>BLS98</td><td>Philippines</td><td>O. sativa</td><td>C.M. Vera Cruz</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzicola</td><td>BLS105</td><td>Philippines</td><td>O. sativa</td><td>C.M. Vera Cruz</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzicola</td><td>BLS256<sup>a</sup></td><td>Philippines</td><td>O. sativa</td><td>A. Bogdanove</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzicola</td><td>BLS305</td><td>Philippines</td><td>O. sativa</td><td>C.M. Vera Cruz</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzicola</td><td>MAI4</td><td>Mali</td><td>O. sativa</td><td>V. Verdier</td><td>—</td><td>—</td></tr><tr><td>X. o. pv. oryzicola</td><td>MAI10<sup>a</sup></td><td>Mali</td><td>O. sativa</td><td>V. Verdier</td><td>—</td><td>—</td></tr><tr><td>X. translucens</td><td>LH2-1</td><td>United States</td><td>L. hexandra</td><td>This study</td><td>—</td><td>—</td></tr><tr><td>X. t. pv. cerealis</td><td>NCPPB1944</td><td>United States</td><td>Bromus inermis</td><td>V. Verdier</td><td>—</td><td>—</td></tr><tr><td>X. t. pv. phleipratensis</td><td>PDDCC5744</td><td>United States</td><td>Phleum pretense</td><td>C. Stevens</td><td>—</td><td>—</td></tr><tr><td>X. t. pv. translucens</td><td>B76</td><td>United States</td><td>Hordeum vulgare</td><td>N. Tisserat</td><td>—</td><td>—</td></tr><tr><td>X. t. pv. translucens</td><td>NCPPB2389</td><td>India</td><td>H. vulgare</td><td>C. Bragard</td><td>—</td><td>—</td></tr><tr><td>X. t. pv. translucens</td><td>UPB787</td><td>Paraguay</td><td>H. vulgare</td><td>C. Bragard</td><td>—</td><td>—</td></tr><tr><td>X. t. pv. undulosa</td><td>UPB513</td><td>Mexico</td><td>T. aestivum</td><td>C. Bragard</td><td>—</td><td>—</td></tr></tbody></table>

bootstrapped trees were generated using functions (dist.ml; model = "Blosum62", NJ, bootstrap.pml) of the R package phangorn (v2.4.0) (Schliep, 2011).

Automated annotation of proteins used in this manuscript for all genomes was made using Prokka (v1.14-dev) (Seemann, 2014), annotation for public versions available in the NCBI was made with the NCBI Prokaryotic Genome Annotation Pipeline (PGAP). Groups of orthologs and trees based on

presence/absence of ortholog genes were generated using OrthoFinder (v 2.2.6) (Emms and Kelly, 2015). Dotplots of whole genome alignments were obtained using Gepard (v. 1.4, using word length 100) (Krumsiek et al., 2007). Genome duplications were then quantified using minimap (v.1) (Li, 2016) as implemented in minidot<fnref n="2" /> (parameters = -g 1000 -k 50

<footnote><sup>a</sup>Strains tested for pathogenicity to Oryza sativa and Leersia hexandra.</footnote>

<footnote n="2">²https://github.com/thackl/minidot</footnote>
—w 5 —L 100). Colinear gene regions were identified using DAGChainer (Haas et al., 2004) (parameters = —E 1e-20 —s —g 2000 —x 200 —A 4) using the blast results from orthofinder as inputs. Insertion sequences (ISs) were identified using ISEScan (v1.6) (Xie and Tang, 2017).

Non-TALE T3 effectors were identified by BLASTP (v. 2.6.0+, results were filtered keeping hits with -evalue < 0.0001, > 0% identity in >40% the query length) (Boratyn et al., 2013) of consensus effectors sequences obtained from http://xanthomonas.org/ against the protein sequences obtained using Prokka. TALE sequences were extracted from each genome using in-house Perl scripts<fnref n="3" />. Neighbor joining trees were generated from concatenated nucleotide TALE N and C terminal sequences, alignments were made using MUSCLE (Edgar, 2004) and trees were generated using functions (dist.ml; model = “JC”, NJ, bootstrap.pml) of the phangorn (v2.4.0) (Schliep, 2011).

Transcription activator-like effector repeat sequences were aligned using DisTAL v1.2 (Pérez-Quintero et al., 2015) and neighbor joining trees were generated based on DisTAL genetic distances using the R package ape (Paradis et al., 2004). TALE groups were defined using the function cutree in R (height = 4.8) on the DisTAL tree. Predictions for TALE binding sites were made using Talvez on the promoters (–1 kb upstream of the translation start site) of annotated genes in the *L. perrieri* (v1.4) and *O. sativa* cv. Nipponbare (v. MSU7) as previously described (Pérez-Quintero et al., 2013).

# RESULTS

## Xol Is Pathogenic to Rice and Southern Cutgrass

To better understand the biology of Xol, we established a host range by screening for pathogenicity on rice and southern cutgrass (*L. hexandra*) using different inoculation techniques. Relative to the virulent Philippine *Xoc* strain BLS256, the *Xol* strains were less aggressive to rice, and caused less expansive water-soaked leaf streaking on several rice varieties. *Xol* BAI23 was more aggressive than NCPPB4346 on rice varieties Cypress and IR64, and caused more disease than the US *Xo* strain X11-5A on Azucena. Rice variety Carolina Gold was resistant to *Xol*, exhibiting a hypersensitive response and no lesion expansion after infiltration. Both *Xol* strains caused longer lesions on southern cutgrass than *Xo*, but were not as aggressive as *Xoc* BLS256 on rice. *Xo* produced water-soaked spots at the point of infiltration that did not expand on southern cutgrass (Figure 1).

After clip inoculations, lesions caused by Xol did not expand on rice or southern cutgrass, unlike those caused by the vascular pathogen Xoo (Supplementary Figure S1). When infiltrated into leaves, populations of Xol were equivalent to Xoc BLS256 and Xo X11-5A on rice cvs. Nipponbare or Azucena after 72 hpi (Figure 2). On southern cutgrass, their native host, Xol grew to a significantly higher population than Xo X11-5A. Xol did not cause disease on wheat or barley (Supplementary Figure S2). Phenotyping *Nicotiana* species can serve as a screen for the ability

of microbes, particularly *Xanthomonas* spp., to elicit a non-host resistance response (Gonzalez et al., 2007). *Xol* caused minor chlorosis, but not water soaking nor a hypersensitive response, when infiltrated into *N. tabacum*, similar to the phenotype caused by *Xoo* PXO99A and *Xoc* BLS256 while *Xoo* BAI3 and *Xo* US 11-5A caused a strong hypersensitive response at the site of infiltration on *N. tabacum* similar to prior reports (Gonzalez et al., 2007) (Supplementary Figure S2).

Our studies show that Xol is pathogenic to southern cutgrass and mildly pathogenic on diverse varieties of rice, but does not cause disease on barley or wheat, and that some rice varieties exhibit resistance to Xol. After inoculation, Xol causes symptoms on rice that are most similar to Xoc, i.e., expanding lesions when introduced into the intercellular spaces (leaf infiltration) and no spreading lesions when introduced into the xylem vessels (clipping).

## X. campestris pv. leersiae Belongs to the X. oryzae Species and Is Phylogenetically Close to Xoc

Amplification of Xol DNA with primers specific for Xo but not Xoc, Xoo, or US Xo suggested that Xol were related to X. oryzae, but distinct from other Xo pathovars (Lang et al., 2010; Triplett et al., 2011) (Supplementary Figure S3). We then used SMRT sequencing technology to derive complete genomes of five available Xol strains from China (NCPPB4346), Burkina Faso (BAI23), Mali (NJ611), and Uganda (BB151-3 and BB156-2). We calculated pairwise ANI among these and all fully sequenced *X. oryzae* genomes (Rodriguez-R and Konstantinidis, 2016). This analysis showed that Xol strains were 99–100% identical to one another, and were 97–99% identical to US Xo, Xoc, and Xoo. Xol were most similar to Xoc (~98.5%). They were 76–91% similar to other *Xanthomonas* species. *X. vasicola* was the next most similar *Xanthomonas* species to *oryzae*, sharing 91% ANI with Xol and all Xo (Figure 3). We generated parsimony phylogenetic trees based on pan-genome SNPs using kSNP3 (Gardner et al., 2015), which showed again that Xol strains were closely related to Xoc (Figure 3). Neighbor-joining trees generated based on MLSA and on presence/absence of ortholog families showed similar groupings, although the placement of African Xoo in the tree was variable (Figure 3 and Supplementary Figure S4).

These combined data indicate that our sequenced strains are more closely related to Xo than other *Xanthomonas* species and therefore, combined with previously reported MLSA data (Triplett et al., 2011; Wonni et al., 2014), we recommend that the formal taxonomic placement of Xcl be included in the species "oryzae." Further biological support for this shift from host range and effector repertoires is described below.

To avoid misidentification of Xol as a Xoc or Xoo in future studies, genomes were compared to identify regions of specificity to base diagnostic primer design with UniqPrimer (Juanillas et al., 2018). Two primer sets were validated for specificity against over 30 closely and distantly related bacteria (Supplementary Table S1). Both primer sets consistently amplified only control Xol strains and did not amplify any other bacterial strain tested (Table 1).

<footnote n="3">³https://github.com/alperezq/experimenTAL</footnote>
<figure><img src="image_66.png" /></figure>

**FIGURE 1** | *X. oryzae* (campestris) pv. *leersiae* (Xcl) and *X. oryzae* cause water soaking on reciprocal hosts, but virulence is highest on original host. Phenotypes and quantitative lesion lengths caused by *Xanthomonas oryzae* (Xo) X11-5A, *X. o. pv. oryzicola* (Xoc) BLS256 and *X. o. pv. leersiae* NCPPB4346 on **(A,C)** diverse rice varieties and **(B,C)** wild *Leersia hexandra* were measured 12 days post infiltration inoculation. An asterisk denotes a significant difference between strains on each variety (*p* ≤ 0.05). Error bars represent ± SD.

## Rice Associated *X. oryzae* Show High Genome Plasticity Compared to *X. oryzae* pv. *leersiae*

We generated dotplots to visualize pairwise whole genome alignments to further compare the genomes of *X. oryzae* strains. These alignments showed several genome rearrangements between the different *Xol* strains with respect to each other and to other *X. oryzae* groups. Curiously, we noticed that self-alignments of genomes of pathovars *oryzae* and *oryzicola* overall showed more genomic duplication than those of *Xol* (**Figure 4A**). To quantify this, we identified colinear regions within each genome that showed these possible genomic duplication events are present in different frequencies in each *X. oryzae* lineage; and that they are more frequent in *Xoc* and Asian *Xoo*, and less frequent in *Xol* and African *Xoo* (**Figure 4B**). Notably, all *X. oryzae* examined exhibited overall more genomic duplications than other *Xanthomonas* species (**Figure 4B**).

We also identified colinear arrangements of homologous genes within each genome, meaning genome duplications that involve multiple genes, and again, these were more frequent in *Xoc* and *Xoo* than in *Xol* (**Figure 4C**). Since some of these duplications may be mediated by duplicative transposition we annotated and quantified insertion sequences (ISs) in the

different *X. oryzae* genomes, which indeed revealed a higher frequency of IS in the groups with higher amounts of duplicated regions (**Figure 4**). The distribution of IS families was overall similar among *X. oryzae*, with *Xol*'s most resembling the distribution of African *Xoo* (**Figure 4E**).

## Non-TAL T3E Repertoires of *Xol* Are Similar to *Xoc*

Computational prediction of T3E among annotated proteins in each genome revealed that the *Xol* T3E repertoire resembles more closely that of *Xoc*. Nonetheless, some features are unique to *Xol*, specifically all *Xol* strains possess a *xopD* gene that is absent in all other *Xo* genomes. *XopAH* is also present in all *Xol* strains and is shared only by two *Xoc* strains. On the other hand, *Xol* strains lack *xopO* which is present in all *Xoc* strains, and some *Xol* strains seem to lack the otherwise universal effectors *xopW* and *xopK* (**Supplementary Figure S5**).

## *Xol* Strains Have Distinct TALE Repertoires With Some Similarities to African *Xoo*

Previous Southern blot analyses using conserved TALE probes predicted that *Xol* BAI23 and NCPPB4346 had five and four
<figure><img src="image_67.png" /><figcaption>**FIGURE 2** | *X. oryzae* pv. *leersiae* can grow and colonize rice as effectively as rice pathogens and rice pathogens can colonize *Leersia hexandra* as effectively as *X. oryzae* pv. *leersiae*. Bacterial population growth in leaves of rice varieties Nipponbare and Azucena and *L. hexandra* inoculated with *X. oryzae* X11-5A, *X. oryzae* pv. *oryzicola* BLS256, and *X. oryzae* pv. *leersiae* NCPPB4346 were quantified at 0 and 72 h post inoculation (hpi). Population sizes were measured in a 5 cm leaf segment infiltrated with each strain. Error bars represent ± SD of six independent leaves, and letters denote treatments significantly different from one another on each variety (p ≤ 0.05).</figcaption></figure>

<figure><img src="image_68.png" /><figcaption>**FIGURE 3** | *X. oryzae* pv. *leersiae* (*Xo*) is a member of *X. oryzae* (*Xo*) and is closely related to *X. oryzae* pv. *oryzicola* (*Xoc*). The heatmap shows pairwise average nucleotide identity (ANI) values between fully sequenced *X. oryzae* genomes. (Left) Consensus parsimony tree generated with based on shared pangenome SNPs, numbers in gray indicate node support as outputed by kSNP3, heatmap rows are ordered according to this tree. (Top) MLSA neighbor-joining tree based on concatenated alignments of 33 housekeeping genes, numbers in gray indicate bootstrap support for branches, and heatmap columns are ordered according to this tree. *X. oryzae* pv. *oryzae* is abbreviated as *Xoo* and *X. vasicola* pv. *vasculorum* as *Xvv*. All species abbreviations are followed by strain name.</figcaption></figure>
<figure><img src="image_69.png" /><figcaption>**FIGURE 4** | *X. oryzae* pv. *leersiae* genomes show generally less plasticity than other *X. oryzae* genomes but more than other *Xanthomonas*. (A) Dotplots showing pairwise whole genome alignments between representative genomes of each *X. oryzae* group, blue squares highlight self-alignments showing high amounts of duplication and rearrangements in *X. oryzae* pv. *oryzicola* and pv. *oryzae* when compared to *X. oryzae* pv. *leersiae*. (B) Boxplot showing total duplicated nucleotide sequences (at least 100 bp) in self-alignments of whole genomes for each group, each dot represents the total regions detected for one strain aligned to itself. (C) Gene duplication involving at least four co-linear genes were identified based on alignments of annotated proteins in a genome against itself, boxplot shows total duplication events detected for each strain. (D) Total number of insertion sequences (ISs) identified in genomes of each group. (E) Distribution of IS families identified within each group, percentages are calculated based on the average of each family in all strains analyzed for each group.</figcaption></figure>

TALEs, respectively (Wonni et al., 2014). However, Southern blot analysis cannot resolve TALEs that are close in size. We found in our whole genome sequences that *Xol* strains contained 12 or 13 TALEs each, which is more than the nine TALEs per genome found in African *Xoo*, and less than what is commonly found in *Xoc* (22–29 TALEs) and Asian *Xoo* (13–20 TALEs). No truncated TALEs were identified in any *Xol* genome. As previously reported, no TAL effectors were found in the *Xo* strain X11-5A (Ryba-White et al., 1995; Triplett et al., 2011).

Phylogenetic trees based on the N and C termini of *X. oryzae* TALEs showed that *Xol* TALEs form a distinct group, but seem to be close to African *Xoo* TALEs, despite the overall genomic similarities with *Xoc* (Supplementary Figure S6). We also constructed trees based on similarities in the CRR of using DisTAL, which grouped *Xol* and African *Xoo* together in a subgroup that also includes *Xoc* (Figure 5A). We used the DisTAL tree to define TALE groups based on repeat region similarities, *Xol* TALEs were classified in 12 groups (Figure 5B).
A

<figure><img src="image_70.png" /></figure>

B

<figure><img src="image_71.png" /></figure>

C

<figure><img src="image_72.png" /></figure>

**FIGURE 5** | TALEs from *X. oryzae* pv. *leersiae* are unique and closely related to African *X. oryzae* pv. *oryzae* TALEs. (A) neighbor-joining tree based on TALE repeat arrangement alignments obtained using DisTAL. Each point represents a single TALE. (B) TALEs were classified in group according to the DisTAL tree, the heatmap shows presence/absence of each TALE group in *X. oryzae* strains, darker colors indicate multiple TALs from one group found in one strain. Tree to the left indicates average DisTAL distance between repeat arrangements for each TALE group. Top trees show hierarchical clustering of each *X. oryzae* group based on the presence/absence pattern of TALE groups. (C) Dotplots shows pairwise distance between all TALE repeat arrangements from each strain as calculated with DisTAL, each dot represents a pair of TALEs within one genome.

One of the groups contained TALEs from *Xoc* and *Xol* strains, while all the others were exclusive to *Xol*. Of these, seven groups were present in all five *Xol* strains. One of these groups, present in the four African *Xol* strains, contains the RVD combination “TI” which has not been previously reported in other species.

All *Xol* strains contained at least two TALEs that were classified within the same group, that is, within each *Xol* genome there are at least two TALEs with nearly identical repeat arrangements (Figure 5B). By examining pairwise genetic distances between the repeat regions of TALEs, we saw that TALEs from *Xol* are on average more similar to each other than TALEs within other *X. oryzae* groups, indicating that they are possibly less diversified and/or more redundant (Figure 5C).

## *Xol* TALE Targets in Cutgrass and Rice Are Different From *Xoc* and *Xoo* Targets

Talvez (Pérez-Quintero et al., 2013) was used to predict host targets for each TALE in our dataset in the promoters of annotated genes in the *L. perrieri* (v1.4) and *O. sativa* (vMSU7) genomes. We identified ortholog pairs between both genomes using reciprocal BLAST. Comparisons of the predictions between both genomes for *Xol* TALEs revealed very few cases where an ortholog pair was predicted to be a target in both genomes (Supplementary Figure S7), and highlighted that the promoters (and thus the targeted genes) in these two hosts are very different.

We then compared predictions for all *Xol* lineages in both genomes and calculated the overlap between predictions for each
<figure><img src="image_73.png" /><figcaption>**FIGURE 6** | TALEs from *X. oryzae* pv. *leersiae* (Xol) are predicted to target distinct genes from other *X. oryzae* [Xo, *X. oryzae* pv. *oryzae* (Xoo), *X. oryzae* pv. *oryzicola* (Xoc)] strains. Predictions for binding sites were made for each TALE in the promoters (~1 kb) of annotated genes in the *L. perrieri* and *O. sativa* genomes, top 200 predicted targets for each TALE were kept, and predictions were aggregated for each strain. For each pair of strains, the overlap of predictions was calculated as the number of common genes predicted as TALE targets in both strains divided by the total genes predicted as targets in either strain, times 200 (intersect × 2 × 100/union). The lower left triangle part of the heatmap shows percentage of shared targets in the *L. perrieri* genome for each pair of strains, and the upper right shows shared targets in the *O. sativa* genome. Trees at the top and left show hierarchical clustering based on stard targets in each genome. Accession numbers for genomes used in this analysis are available in **Supplementary Table S2**.</figcaption></figure>

strain. As a result, we saw that each *X. oryzae* group has a distinct group of predicted targets with relatively little overlap with other groups. In the case of *Xol*, the highest overlap was found with predictions for *Xoc* TALEs (10–11% shared predicted targets) (**Figure 6**). Given the differences in the genomes of their hosts and that *Xol* TALEs have unique repeat sequences, we expect their targets to be likewise unique. Additionally, we looked for orthologs of known susceptibility (*S*) genes targeted by *Xoc* or *Xoo* TALEs (e.g., SWEETs, OsSULTR3;6) and queried whether they were among the top predictions for *Xol* TALEs. No known *Xoc* or *Xoo* target homolog was found. It is, however, possible, that while not targeting the direct orthologs of these *S*

genes, *Xol* TALEs may be inducing similar functions, since the predicted targets contain genes annotated with similar functions to known *S* genes including sulfate transporters, nodulins and various families of transcription factors (**Supplementary Table S3**). Expression data and further experiments are necessary to effectively identify the biological mechanisms of these TALEs.

DISCUSSION

*Xanthomonas oryzae* pv. *leersiae*, which has been isolated from the pervasive weed species *L. hexandra* surrounding rice paddies
(Fang et al., 1957; Wonni et al., 2014), was historically grouped as a distinct species and pathovar (Vauterin et al., 1995; Triplett et al., 2011; Wonni et al., 2014). We compared pathogenicity of multiple strains on diverse cereal hosts and complete genomes of five *Xol* strains from Burkina Faso, China, Mali, and Uganda. Similar to *Xoc*, *Xol* strains caused water soaked lesions on rice and *L. hexandra*, but were not virulent to wheat and barley. ANI is a widely accepted baseline beyond DNA-DNA hybridization for taxonomic placement of prokaryotes into a species, not a pathovar, at a threshold of >95-96% (Konstantinidis and Tiedje, 2005; Goris et al., 2007; Richter and Rossello-Mora, 2009; Kim et al., 2014; Bull and Koike, 2015). In phylogenetic analyses, these five *Xol* strains, representing geographic and temporal diversity, grouped more closely with *Xo* pathovars than other members of this genus, and were above a species delineation threshold in ANI analyses. Therefore, we propose re-naming these strains from *Xcl* to *Xol* (Fang et al., 1957) comb. nov.

*Xanthomonas oryzae* pv. *leersiae* colonize and cause water-soaking on rice leaves, but the southern cutgrass isolates are not as aggressive as *Xo* isolated from rice. The lesions caused by *Xol* were phenotypically similar to rice BLS caused by *Xoc* and these strains did not cause disease when introduced into rice or southern cutgrass by leaf-clipping. Thus, we suggest that *Xol* are not systemic pathogens, and are more like *Xoc* than the systemic relative *Xoo*.

T3Es, as important contributors to bacterial pathogenicity, may define host range, and can also inform lineages and evolutionary relationships among different populations of related bacteria (Arlat et al., 1991; Hajri et al., 2012; Wonni et al., 2014; Schwartz et al., 2015). Studies in *X. oryzae* have shown that different lineages are shaped by T3E repertoires and reflect phenotypic adaptation to their agroecosystems (Hajri et al., 2012; Quibod et al., 2016). Likewise, this study sought to uncover similarities between *Xo* and *Xol* effector repertoires that could further inform their evolutionary lineage. Out of a set of previously defined core effectors for *X. oryzae* [*avrBs2*, *avrBs3* (*TALEs*), *xopL*, *xopN*, *xopP*, *xopQ*, *xopV*, *xopW*, *xopY*, *xopAA*, *xopAB*, *xopAE*, and *xopF1*) (Hajri et al., 2012), *Xol* strains contain all except *xopW*, which is absent in three of the five strains. Although present in strains BAI23 and NJ611, *xopW* contains a large IS. This IS most likely prevented its amplification in previous studies (Wonni et al., 2014). Interestingly, this same IS was identified in other African *Xoc* strains, consistent with a shared evolutionary origin with *Xol* (Hajri et al., 2012). On the other hand, *xopD* is present in *Xol* but absent in other *X. oryzae*. XopD is a SUMO protease mimic that suppresses host defense responses during *Xanthomonas euvesicatoria* infection (Kim et al., 2008, 2013). In addition to *Xol*, *xopD* is predicted to be present in *X. campestris* pv. *campestris*, *X. euvesicatoria*, and *Acidovorax citrulli*<fnref n="4" />. Absence in other *Xo* suggests an independent acquisition by *Xol*. Conversely, loss of this effector at some time by *Xoo* or *Xoc* could have occurred, but further validation of these hypotheses is necessary. Since it is not known what level of virulence, and/or host specificity any T3E conveys for *Xol*, future work should include functional validations.

We also assessed TALE diversity in *Xol* strains, using genomic assemblies based on long reads generated using SMRT sequencing. While according to phenotyping, phylogenomics, and non-TALE Type III effector repertoires, *Xol* most closely resembles *Xoc*, the *Xol* TALE sequences more closely resemble African *Xoo*. *Xol* and African *Xoo* also possess, on average, smaller TALomes (TALEs per genome) than *Xoc* or Asian *Xoo*. Furthermore, their TALEs also have less diverse repeat arrangements as evidenced by shorter genetic distances in pairwise TALE repeat alignments. A possible explanation for this feature is that TALEs from *Xol* and African *Xoo* more closely resemble the ancestral TALE repertoire for the group and have not undergone the extensive diversification found in *Xoc* and Asian *Xoo*. A hypovirulent strain of *Xoc* was isolated from rice in the Yunnan province of China that also contains nine TALEs. This strain was used in heterologous expression assays to determine targets and function of Tal7 (Cai et al., 2017). Unfortunately, the TALome of this strain is unavailable at this time and it is unclear if this strain is related to the *Xol* strains characterized in this study.

The expansion of *Xoc* and *Xoo* TALomes is curious since many of the TALEs they carry seem not to be required for virulence and some may even have redundant functions (Pérez-Quintero et al., 2013; Cernadas et al., 2014). Given their repetitive nature and a general tendency toward homogenization of repeats, TALEs have been proposed as being selected for evolvability, that is, selected for their ability to quickly recombine (Schandry et al., 2016). Having an expanded TALome would further allow frequent recombination and generation of new TALE variants, as reflected in bigger evolutionary distances between repeat arrangements. This selection of a bigger TALome has been proposed to be driven by extensive breeding for resistance in the host plant (Schandry et al., 2018). When exposed to a resistant host population, a pathogen population can benefit from carrying a heterogeneous and redundant set of effectors, since preexisting isolates harboring a set advantageous for the new conditions would then be selected, in what has been proposed as a type of evolutionary “bet-hedging” strategy (Win et al., 2012). It is then possible that *Xoc* and Asian *Xoo* have historically encountered more resistance, possibly related to domestication of its primary host, than *Xol* and African *Xoo*, leading to a selection for expanded TALomes.

At least two resistance genes (*Xa1* and *Xo1*) in *O. sativa* specifically recognize TALEs (Ji et al., 2016; Triplett et al., 2016), and *Xoc* and *Xoo* seem to have benefited from their expanded TALomes by selecting TALE variants (iTALEs or truncTALEs) that can specifically suppress resistance mediated by these genes (Ji et al., 2016; Read et al., 2016). Meanwhile *Xol* infecting *L. hexandra*, as African *Xoo* originally infecting *Oryza glaberrima* (Gonzalez et al., 2007), may have never encountered similar resistance in its host, and thus lacks these TALE variants and cannot cause disease on varieties carrying *Xo1* (Figure 1).

TALome expansion may have been accompanied by, or be a consequence of, higher genome plasticity in the *X. oryzae* clade as evidenced by a high amount of genome and gene duplication and a high frequency of IS elements, these measures being generally lower in *Xol*. Within the clade, differences

<footnote n="4">⁴www.xanthomonas.org</footnote>
may be once more related to resistance in the host, with the
more plastic genomes (Asian Xoo) matching more variable host
populations. The requirement of plastic genomes in the clade
as a whole has been hypothesized to be a consequence of rice
cultivation through millennia (Salzberg et al., 2008; Bogdanove
and Voytas, 2011), and suggest the ancestor of the clade faced
an already variable population. Which then raises the question
of where Xol falls within this scenario of adaptation to a
cultivated crop?

Rice and southern cutgrass are closely related members of the Poaceae. Leersia species are often used as an outgroup in phylogenetic and, most recently, genomic investigations (Copetti et al., 2015). Evidence of genome duplication events and defense response genes shared by rice and Leersia species has been reported (Jacquemin et al., 2009; Xiao et al., 2009). It is plausible that based on their genetic and evolutionary relatedness that respective pathogens of Oryza and Leersia evolved independently. The US strains of Xo, which do not contain intact TALEs, could have been progenitors of other Xo pathovars, having acquired TALEs over time to enhance virulence on rice or Leersia spp. (Triplett et al., 2011). Significant trade between the United States, Africa, and Asia could allow for movement of strains across continents. However, it is not clear if Xol is currently present in the United States, despite early reports of L. hexandra being an alternate host for Xoo (Gonzalez et al., 1991). Alternatively, this system may represent a sympatric scenario where Xoo, Xoc, Xo, and Xol all lived in the same habitat, providing the opportunity to exchange genetic material and to adapt to their respective host while maintaining basic homology (Jacques et al., 2016). In this scenario, given its similar infection biology and overall similarities to Xoc, Xol may be a specialized subgroup originating from a Xoc-like population able to colonize southern cutgrass, or vice versa.

How specifically adapted Xol strains are to either L. hexandra
or rice remains a fascinating question, since Xol could
potentially represent an emerging pathogen for rice. Here
we have shown that Xol can, to some extent, infect rice, and
two of the isolates sequenced in this work were originally
recovered from symptomatic rice leaves in a field (BB 151-
3 and BB 156-2). To get insights into host adaptation, we
attempted to predict targets for Xol TALEs in L. hexandra
using L. perrieri, the only available genome from the genus,
as proxy and O. sativa. Overall, the predictions indicate
that Xol TALEs induce different sets of genes than other
X. oryzae, and that different genes are induced in rice and
Leersia sp. given that relatively few orthologues are predicted
as targets in both genomes. Of particular interest, given the
phenotypic similarities with Xoc, is the predicted targeting
of genes annotated as sulfate transporters. Four genes in
the L. perrieri genome corresponding to orthologs of sulfate
transporters from rice (LOC_Os03g09940, LOC_Os03g09970,
LOC_Os03g09980, and LOC_Os09g06499) were predicted
to be targeted by TALEs from at least one Xol strain with
high prediction scores (Supplementary Table S3). The
primary virulence target of Tal2g from Xoc is OsSULTR3;6
which is a member of the sulfate transporter family 3

(Takahashi et al., 2011; Cernadas et al., 2014). It is feasible
that the TALEs targeting sulfate transporters in *Leersia* mirror
the virulence function of Tal2g. However, transcriptomic
data and further biological validation are required since it
is still possible that the few-shared genes in the predictions
are true targets and similar functions are required for
virulence in both hosts.

CONCLUSION

In summary, we propose Xol, which was isolated from rice
and southern cutgrass (L. hexandra), a weedy grass closely
related to rice, as a new member of the X. oryzae species.
Genomic analysis and disease phenotyping on various
hosts demonstrated the close relationship of Xol to the
rice pathogens Xoo and Xoc. T3E and TALE content of
the Xol indicated that this group of organisms uses similar
virulence mechanisms to the rice pathogens. While weeds
such as southern cutgrass are not agronomic crops, they
are competitors for resources and potential reservoirs of
pathogen inoculum, they are important in management
considerations for rice growers. Interfering in any agroecosystem
requires comprehensive consideration. Certain Leersia sp.
are used as banker plants for the critically important rice
brown plant hopper (Zheng et al., 2017), therefore integrated
management of weeds surrounding rice paddies will require
prospecting and balance of all possible pests. The fact that
they harbor a pathogen group that can also impact rice
emphasizes that, in general, more attention should be focused
to the surrounding ecosystem in rice production and more
broadly in any crop rotation as a general management
strategy. Research contributing toward understanding the
Xol/rice/southern cutgrass pathosystem will be significant for all
rice-producing countries.

AUTHOR CONTRIBUTIONS

JML, AP-Q, RK, BS, VV, and JEL conceived and designed experiments. JML, AP-Q, RK, ED, and JJ performed the experiments. SS, HD, IK, RO, OK, and VV collected and provided new Xol strains. JML, AP-Q, RK, and JZ analyzed the data. RK, RO, OK, BS, VV, and JEL provided resources and supervision. JML, AP-Q, BS, VV, and JEL developed the manuscript.

FUNDING

This research was supported by a Marie Curie IOF Fellowship (EU Grant PIOF-GA-2009-235457 to VV); the Embassy of France in the United States, Office of Science and Technology – STEM Chateaubriand Fellowship Program (to JML); USDA NIFA Postdoctoral Fellowship Award No. 2016-04706 (to JJ); USDA’s National Institute of Food and Agriculture, award # 2018-67013-28490 (to JJ, JML, and JEL); and by IRD JEAI Coana (to SS and OK).
ACKNOWLEDGMENTS

We are grateful to Dr. Geoffrey Onaga for strain collection
in Uganda; Dr. Bing Yang for Xol BB 151-3 and BB 156-2
genome sequence; and Emily Luna for technical support. We
thank Drs. Mathilde Hutin, Céline Pesce, Sébastian Cunnac, and
Tuan T. Tran for seed, constructive discussions, and technical
support and Dr. Young-Ki Jo for providing *Leersia hexandra*.
This article is based upon work from COST Action CA16107

EuroXanth, supported by COST (European Cooperation in
Science and Technology).

SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online
at: https://www.frontiersin.org/articles/10.3389/fpls.2019.00507/
full#supplementary-material

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**Conflict of Interest Statement:** 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.

Copyright © 2019 Lang. Pérez-Quintero, Koebnik, DuCharme, Sarra, Doucoure, Keita, Ziegle, Jacobs, Oliva, Koita, Szurek, Verdier and Leach. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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# *Pseudomonas syringae* pv. *syringae*
Associated With Mango Trees, a
Particular Pathogen Within the
"Hodgepodge" of the *Pseudomonas*
*syringae* Complex

José A. Gutiérrez-Barranquero, Francisco M. Cazorla and Antonio de Vicente*

Departamento de Microbiología, Facultad de Ciencias, Universidad de Málaga, Instituto de Hortofruticultura Subtropical y Mediterránea "La Mayora" (IHSM-UMA-CSIC), Málaga, Spain

The *Pseudomonas syringae* complex comprises different genetic groups that include strains from both agricultural and environmental habitats. This complex group has been used for decades as a “hodgepodge,” including many taxonomically related species. More than 60 pathovars of *P. syringae* have been described based on distinct host ranges and disease symptoms they cause. These pathovars cause disease relying on an array of virulence mechanisms. However, *P. syringae* pv. *syringae* (Pss) is the most polyphagous bacterium in the *P. syringae* complex, based on its wide host range, that primarily affects woody and herbaceous host plants. In early 1990s, bacterial apical necrosis (BAN) of mango trees, a critical disease elicited by Pss in Southern Spain was described for the first time. Pss exhibits important epiphytic traits and virulence factors, which may promote its survival and pathogenicity in mango trees and in other plant hosts. Over more than two decades, Pss strains isolated from mango trees have been comprehensively investigated to elucidate the mechanisms that governs their epiphytic and pathogenic lifestyles. In particular, the vast majority of Pss strains isolated from mango trees produce an antimetabolite toxin, called mangotoxin, whose leading role in virulence has been clearly demonstrated. Moreover, phenotypic, genetic and phylogenetic approaches support that Pss strains producers of BAN symptoms on mango trees all belong to a single phylotype within phylogroup 2, are adapted to the mango host, and produce mangotoxin. Remarkably, a genome sequencing project of the Pss model strain UMAF0158 revealed the presence of other factors that may play major roles in its different lifestyles, such as the presence of two different type III secretion systems, two type VI secretion systems and an operon for cellulose biosynthesis. The role of cellulose in increasing mango leaf colonization and biofilm formation, and impairing virulence of Pss, suggests that cellulose may play a pivotal role with regards to the balance of its different lifestyles. In addition, 62-kb plasmids belonging to the pPT23A-family of plasmids (PFPs) have been strongly associated with Pss strains that inhabit mango trees. Further, complete sequence and comparative genomic analyses revealed major roles of PFPs in detoxification of copper compounds and ultraviolet

## OPEN ACCESS

**Edited by:**
Olivier Pruvost,
UMR Peuplements Végétaux et
Bio-Agresseurs en Milieu
Tropical (CIRAD), France

**Reviewed by:**
Boris Alexander Vinatzer,
Virginia Tech, United States
Cindy E. Morris,
INRA Centre Provence-Alpes-Côte
d'Azur, France

*Correspondence:
Antonio de Vicente
adevicente@uma.es

**Specialty section:**
This article was submitted to
Plant Microbe Interactions,
a section of the journal
Frontiers in Plant Science

Received: 18 December 2018

Accepted: 15 April 2019

Published: 08 May 2019

**Citation:**
Gutiérrez-Barranquero JA, Cazorla FM and de Vicente A (2019) *Pseudomonas syringae* pv. *syringae* Associated With Mango Trees, a Particular Pathogen Within the "Hodgepodge" of the *Pseudomonas syringae* Complex. *Front. Plant Sci.* 10:570. doi: 10.3389/fpls.2019.00570
radiation resistance, both improving the epiphytic lifestyle of Pss on mango surfaces. Hence, in this review we summarize the research that has been conducted on Pss by our research group to elucidate the molecular mechanisms that underpin the epiphytic and pathogenic lifestyle on mango trees. Finally, future directions in this particular plant-pathogen story are discussed.

**Keywords:** *Pseudomonas syringae* pv. *syringae*, mango tree, epiphytic fitness, virulence strategies, mangotoxin, pPT23A family plasmid, ultraviolet radiation and copper resistance

## Pseudomonas syringae pv. syringae
STRAINS ISOLATED FROM MANGO TREES BELONG TO A SINGLE PHYLOTYPE AND HAVE FEATURES DISTINGUISHING THEM FROM THE REST OF THE *Pseudomonas syringae* COMPLEX

Pseudomonas syringae complex has been traditionally used as a taxonomic hodgepodge that currently includes 15 recognized bacterial species and more than 60 different pathovars of the sensu stricto species P. syringae (Gomila et al., 2017). The taxonomy of the P. syringae complex has been widely discussed over the last 40 years, yet still remains a controversial group. The classification of this group is defined based on host range and symptomatology, dividing P. syringae species into pathogenic varieties known as pathovars (Dye et al., 1980; Young, 2010). The pathovar-based classification is widely accepted even today, but does not reveal the genetic relationships between pathovars. Initial genomic studies were based on DNA-DNA hybridization methods (Palleroni et al., 1972; Pecknold and Grogan, 1973; Denny et al., 1988; Gardan et al., 1992; Janse et al., 1996). Gardan et al. (1999) described nine discrete genomospecies classification groups that have been widely accepted until recently. Phylogenetic approaches based on multilocus sequence typing analysis (MLST) have had a significant impact on P. syringae classification (Sarkar and Guttman, 2004; Hwang et al., 2005; Almeida et al., 2010; Bull et al., 2011; Berge et al., 2014). Although the classification proposed by Berge et al. (2014) is generally accepted, a recent study using comparative genomics of the whole genome sequences of this species proposed the delineation of phylogenomic P. syringae complex and confirmed, as one might expect, that a high proportion of strains were misclassified (Gomila et al., 2017). Significantly, different P. syringae strains isolated from different sources (i.e., snow, irrigation water, and a diseased crop) have been identified as belonging to the same evolutionary lineage (Monteil et al., 2016). This fact suggests that the evolutionary history of the plant pathogen P. syringae is linked to the water cycle, which promoted the colonization of agricultural and non-agricultural habitats (Morris et al., 2008).

Pseudomonas syringae species possess a great diversity of virulence factors, such as a type III secretion system (T3SS) and its effector repertoires, toxic compounds, exopolysaccharides, ice nucleation activity, cell-wall-degrading enzymes and plant hormones, that make it the model phytopathogenic bacterium

for understanding plant-pathogen interactions. Additionally, adaptation mechanisms to its plant hosts and microbial evolution have more recently become of great interest to many research groups (Xin et al., 2018). In particular, Pseudomonas syringae pv. syringae (Pss), has been described as the most polyphagous bacterium into the P. syringae complex due to its broad host range (Kennelly et al., 2007). Pss strains isolated from mango trees were identified as the causative agent of bacterial apical necrosis (BAN) disease of mango trees, which is the most limiting factor for mango crop in the Mediterranean region (Cazorla et al., 1998). A novel antimetabolite toxin called "mangotoxin" was reported to be intimately associated with all Pss strains isolated from mango trees, and with a few Pss strains from other hosts (Arrebola et al., 2003). The presence of different variants of copper resistance genes, as well as ultraviolet resistance determinants, were found to be associated with 62-kb plasmids belonging to the pPT23A family plasmids (PFPs) (Cazorla et al., 2002, 2008; Gutiérrez-Barranquero et al., 2013b). In addition, several studies have attempted to unravel the biosynthesis pathway and the regulatory mechanisms of mangotoxin production (Arrebola et al., 2007; Arrebola et al., 2012; Carrión et al., 2012, 2014). A molecular evolutionary approach using mangotoxin biosynthetic operon gene cluster, revealed that this operon was specifically distributed within the P. syringae Genomospecies 1, and which was acquired only once during evolution (Carrión et al., 2013). Moreover, a diversity survey of Pss strains isolated from mango trees was performed using phenotypic, genetic and phylogenetic approaches based on MLST analysis (Gutiérrez-Barranquero et al., 2013a) in order to understand the epidemiology of BAN disease. This study strongly indicated that Pss isolated from mango trees were forming a single phylotype inside the Pss species, characterized mainly by its adaptation to the mango host and by the production of mangotoxin. Subsequently, and due to the genome sequencing project of the model strain Pss UMAF0158 (Martínez-García et al., 2015), a gene cluster involved in the production of cellulose was discovered (Arrebola et al., 2015). This study demonstrated that cellulose was an important exopolysaccharide (EPS) to attach to the mango surface that could also act as a switch modulating the transition from epiphytic to pathogenic phases of Pss on the mango host. Finally, a PFPs sequencing project determined the importance of the 62-kb plasmids in improving the epiphytic survival of Pss strains isolated from mango trees (Gutiérrez-Barranquero et al., 2017a).

Therefore, this review summarizes the work that has been conducted on Pss strains isolated from mango trees over more than two decades of research. This phytopathogenic bacterium has arisen as a particular pathogen developing important features
that modulate their epiphytic and pathogenic lifestyle phases on the mango tree surface.

## Pseudomonas syringae pv. syringae, THE CAUSAL AGENT OF BACTERIAL APICAL NECROSIS OF MANGO TREES

Mango crops (Mangifera indica L.) are present in many tropical and subtropical regions and represent one of the most important subtropical fruit crops distributed worldwide (Galán-Saúco, 2015). This crop was established in Southern Spain in Malaga in the early 1980s. The pace of the planting of this crop was relatively high over the last few years, expanding from 800 hectares (ha) in 2004 to 4500 ha in 2016 in Spain, of which more than 2,000 ha are in full production (Gutiérrez-Barranquero et al., 2017b). Very recent data claim that there are more than 6,000 ha, of which more than 3,000 are currently in full production, which would break the historical record of more than 30,000 tons of mango fruit harvested (Anonymous, 2018) August. Thus, the mango crop has been considered one of the most promising crops in Southern Spain, mainly in the tropical coastal areas of Malaga and Granada. As new crops are deployed in new regions, there might be spill-over effects and the emergence of new diseases. The commercial viability of this crop has been threatened by different bacterial and fungal plant pathogens (Bradbury, 1986; Gagnevin and Pruvost, 2001; Gutiérrez-Barranquero et al., 2019). In Southern Spain, the fungal pathogen Fusarium mangiferae which causes mango malformation disease (Crespo et al., 2012) and Pss the causal agent of BAN disease (Cazorla et al., 1998) are the most severe phytopathogens causing important economic losses. The main symptomatology associated with BAN disease, the isolation and identification of Pss as the causal agent of BAN disease, and the control methods specifically tested to limit and prevent Pss infections are discussed in detail below.

## BAN Disease Symptomatology

The mango crop develops well at temperatures between 20 and 25°C, reaching a dormancy period when the temperature is below 15°C (Samson, 1986; Galán-Saúco, 2015). Thus, cool temperatures and wet periods play an important role in favoring the development of BAN symptoms, which has also been described in other infections caused by P. syringae in other woody hosts (Kennelly et al., 2007). Rain or dew are essential for inoculum dissemination to other buds and leaves, and wind exposure facilitates BAN development by causing microinjuries (Cazorla et al., 1998). BAN disease on mango trees is characterized by rapidly expanding necrotic spots on buds and leaves from October-November. January-February are the coolest and rainiest months in Southern Spain, giving rise to the highest incidence of necrotic symptoms, which is consistent with the period with the largest Pss population on mango trees (Cazorla et al., 1998). Additionally, at this time the symptoms can extend from buds through the leaf petiole to reach the leaves and stems. Typically, lesions on leaves start as interveinal, angular, water-soaked spots that may coalesce, becoming black and slightly raised. Importantly, favorable weather conditions

for the pathogen that are maintained throughout the winter and even into the spring season can promote the appearance of wood necrosis on branches to such a degree that, in extreme cases, this can lead to the death of the tree. These symptoms are quite similar to those described for blossom blast of pear and stone fruits (English et al., 1980). Additionally, a white milky gum exudate can also be observed. Necrotic symptoms affecting flower panicles are less frequently observed but can become very apparent in years with severe attacks. These symptoms cause the most severe economic losses due to decreases in fruit yield (Cazorla et al., 1998). The typical symptoms of BAN disease of mango trees are summarized in **Figure 1**.

## Unraveling the Causative Agent of BAN Disease

The phytopathogenic bacterium *P. syringae* has the ability to survive as an epiphyte on plant surfaces. During its epiphytic phase, *P. syringae* has to cope with different abiotic factors by using different mechanisms (Sundin and Jacobs, 1999; Yu et al.,

<figure><img src="image_75.png" /><figcaption>**FIGURE 1** | Typical symptoms of bacterial apical necrosis (BAN) disease on mango trees. (A) Healthy mango tree. (B) Mango tree affected by BAN disease. (C) Healthy mango apical bud. (D) Typical gum exudates on mango apical bud. (E) Initial necrotic spots on mango apical bud. (F) Severe necrosis of mango apical bud. (G) Necrotic symptoms progression from apical bud to leaves through the petiole. (H) Dead mango apical bud and surrounded leaves. (I) Flower panicles. Yellow arrow: healthy mango flower panicle; red arrow: necrosis on mango flower panicle.</figcaption></figure>
1999; L window and B randl, 2003), which allow it to achieve large
population sizes before starting an infection process (Hirano and
Upper, 2000). Although *P. syringae* can elicit disease symptoms
in a wide variety of woody and herbaceous plants, *P. syringae*
has been considered a weak pathogen because the infection
process on their plant hosts can be strongly improved by
frost damage or mechanical injury. Thus, *P. syringae* can elicit
disease outbreaks in temperate regions distributed worldwide
in important crops, causing significant yield losses (Kennelly
et al., 2007). Since the early 1990s, necrotic symptoms have
been observed in apical buds, leaves and stems in mango
trees in Southern Spain and Portugal (Cazorla et al., 1998). In
years with severe attacks, which correlate with cool and wet
winters, necrotic symptoms were more evident in the mango tree
canopy and could cause a reduction of 30-50% in mango fruit
production (Gutiérrez-Barranquero et al., 2012). Preliminary
isolation from the edge of necrotic tissues of mango trees revealed
that over 90% of bacterial isolates recovered were fluorescent
Pseudomonas. Similar necrotic symptoms have been reported
in many other woody hosts infected by Pss, such as peaches
(Endert and Ritchie, 1984), citrus (Mirik et al., 2005; Ivanović
et al., 2017), cherry (Sundin et al., 1989; Wenneker et al.,
2013), almond (Lindow and Connell, 1984), apple (Mansvelt
and Hattingh, 1986; Gasic et al., 2018) and pear (Montesinos
and Vilardell, 1991; Xu et al., 2008). Different biochemical and
physiological characteristics suggested the tentative identification
of *P. syringae*. Furthermore, the presence of ice nucleation activity
(INA), a virulence trait well-documented in *P. syringae* to be used
by the bacterium to cause micro-wounds on the plant surface
to provide an entry way to the plant (Hirano and Upper, 1995;
Hwang et al., 2005), was found in bacterial isolates following
a protocol previously described by Cazorla et al. (1995). The
production of lipodepsipeptidic toxins typically associated with
*P. syringae*, such as syringomycin and syringopeptins, were
also confirmed in bacterial isolates from mango (Gross and
DeVay, 1977; Ballio et al., 1991; Arrebola et al., 2003). All the
results obtained conclusively confirmed that the bacterial isolates
associated with necrotic symptoms in mango trees belonged to
the *P. syringae* species (Cazorla et al., 1992, 1998). *P. syringae* is a
highly heterogeneous species comprising more than 60 pathovars
(Young, 2010). To determine which pathovar was the causal
agent of necrotic symptoms, different pathogenicity tests were
performed in tomato and lilac plants, immature lemon and pear
fruits, and bean pods (Lelliott and Stead, 1987). All *P. syringae*
strains assayed induced typical symptoms in all plant hosts of Pss.
Once the bacterial strains associated with necrotic symptoms in
mango trees were identified, a pathogenicity test in adult mango
plants was carried out in order to fulfill Koch's postulates. Two
different experiments under field conditions were performed
using 2-year-old mango plants growing in pots. Buds and stems
were inoculated with 10 µl of bacterial suspensions using a
microsyringe. Necrotic symptoms developed in the inoculated
mango trees, and the incidence and severity of necrotic symptoms
that occurred in each experiment (i.e., different years) were
different, indicating the importance of the weather conditions
in symptom development, as has been previously observed
for *P. syringae* in other hosts (Hirano and Upper, 2000). The

subsequent re-isolation from the necrotic lesions artificially
reproduced in mango tissues and the subsequent identification
confirmed that Pss was the causal agent of bacterial apical
necrosis (BAN) of mangos (Cazorla et al., 1998).

Therefore, the life cycle of Pss on mango trees is clearly
divided first, in an epiphytic phase, in which Pss has to survive
and grow under harsh environmental conditions, and second, in
a pathogenic phase to produce BAN symptomatology. In both
phases, different genetic traits are expressed to either, improve
survival or to enhance an infection process (Figure 2).

Control Options for BAN Disease

Management of woody plant diseases caused by *P. syringae*,
and particularly those provoked by Pss, are a major concern
for growers worldwide due to the broad host range. Sprays
of copper compounds have been used for decades as standard
bactericides to combat many bacterial diseases, but their use
is subject to a number of constraints (Kennelly et al., 2007).
The most common treatment for controlling BAN disease in
Southern Spain is the spraying of a copper compound with
a film-forming mode of action known as Bordeaux mixture
(BM). However, different copper-based compounds fail to protect
against BAN. Unfortunately, continuous treatments with copper
sprays can lead to many problems. The efficacy of copper
treatments for the control of bacterial diseases is often limited,
largely due to the selection of copper-resistant strains; this
has previously been described for Pss strains isolated from
mango trees (Cazorla et al., 2002). Another serious problem
associated with the excessive usage of copper is that copper is
a major heavy metal contaminant that accumulates in soil from
different sources (Wang, 1997; Xiong, 1998; Kabata-Pendias,
2001). Copper has demonstrated toxicity to roots and young
shoots and leaves (Kairu et al., 1985; Alva and Graham, 1991;
Iannotta et al., 2007), and has sustained bioaccumulation effects
(Xiong and Wang, 2005). Finally, the European Union has
introduced legislation limiting the use of copper compounds in
regulation No. 473/2002 (Anonymous, 2002). For all of these
reasons, there has been an urgent need expressed by growers
and extension services to search for alternative treatments to
copper compounds that may be effective for the control of
BAN disease. In this context, Cazorla et al. (2006) evaluated the
capacity of several different control treatments to cope with BAN
disease in mango crops. In addition, the mechanisms of action
of the different treatments were examined, analyzing their effect
on Pss population levels. The treatments assayed in this work
included BM, fosetyl-Al, gibberellic acid, acibenzolar-S-methyl,
silicon gel (soluble potassium silicate 34%) and combined
treatments (Cazorla et al., 2006). Interestingly, treatments
reduced symptoms but did not reduce the size of the pathogen
population, suggesting a non-bactericidal mode of action of
these compounds. After evaluation of the different treatments,
this study concluded that the best treatment to control BAN
disease was conventional copper-based treatment BM. However,
there were promising effects showed by other assayed treatments
against BAN disease, indicating that a few of them could be
interesting alternatives to traditional chemical control (Cazorla
et al., 2006). The silicon gel was highly relevant, because its
<figure><img src="image_76.png" /></figure>

**FIGURE 2** | The life cycle of *Pseudomonas syringae* pv. *syringae* on mango trees. (A) Epiphytic phase of *P. syringae* pv. *syringae* on mango trees is developing mainly in spring/summer seasons, where high temperature and high UV radiation are present. At population level, *P. syringae* pv. *syringae* is present mainly on the buds and leaves surfaces forming microcolonies (1), that will subsequently form a mature biofilm with the biosynthesis of an extracellular matrix (2). At single cell level, *rulAB* operon encoded by 62-kb PFP plasmid involved in resistance to UV radiation, and wss operon present at the chromosome and involved in the biosynthesis of cellulose, are both highly expressed. On the contrary, *copABCD* operon encoded by 62-kb PFP plasmid involved in copper resistance, and *mbo* operon located at the chromosome and involved in mangotoxin biosynthesis, are less expressed. (B) Pathogenic phase of *P. syringae* pv. *syringae* on mango trees arise primarily in autumn/winter seasons, where low temperatures, low UV radiation and high rainfall are present. At population level, the infection process on mango leaves and buds is the following: (3) epiphytic survival and biofilm formation; (4) biofilm disassembly and bacterial migration; (5) ice nucleation activity to damage mango surfaces; (6) bacterial entry into cells by microinjuries; (7) Bacterial entry into cells through stomata; (8) Release of phytotoxins; and (9) Release of type III effectors by using the type III secretion system. At single cell level, firstly, *copABCD* operon involved in detoxification of copper compounds is highly expressed in response to copper treatment applications by farmers. Then, all genes that encode virulence factors are highly expressed (Mangotoxin, lipodepsipeptidic toxins and type III secretion system and its effectors) to elicit the typical BAN disease symptoms.
reduction of necrotic symptoms in apical buds was similar to the levels obtained with BM; it also has potential for use in organic farming.

Due to the limitations concerning the use of copper compounds, together with the increasing demand for organic crops, have led to in-depth analysis of different alternative treatments to combat plant diseases. Particularly, Gutiérrez-Barranquero et al. (2012) performed a study where they analyzed different alternative treatments, including the silicon gel that previously showed potential to control BAN disease. In this study after different scale trials (small, semi-commercial, and commercial), confirmed the efficacy of silicon gel to control BAN disease, reducing the occurrence of necrotic symptoms at a similar level to the conventional treatment BM. Moreover, mango growers directly observed the effectiveness of silicon gel, and thus, this treatment has been registered for commercial use in mango crops in Spain as a phytostrengthenner compatible with organic farming (Gutiérrez-Barranquero et al., 2012). Interestingly, silicon gel failed to reduce the bacterial population in mango tress, suggesting a film-forming mode of action acting as a physical barrier to avoid the entry of the pathogen, as it was previously reported for BM (Becerra, 1995). A similar mode of action has been previously described for silicon protective effects in other plant hosts against fungal and bacterial pathogens (Diogo and Wydra, 2007; Guével et al., 2007; Sun et al., 2010). However, other putative modes of action for silicon gel cannot be ruled out, as might be the induction of systemic resistance (ISR) (Bélanger et al., 2003; Rodrigues et al., 2003; Rodgers-Gray and Shaw, 2004; Fauteux et al., 2005) and to enhance cell wall lignification (Kim et al., 2002).

## EPIPHYTIC FITNESS DETERMINANTS: IMPROVING SURVIVAL OF *P. syringae* pv. *syringae* ON MANGO SURFACES

Plant surfaces are hostile and dynamic environments for plant-associated bacteria due to rapidly changing climatic conditions (Lindow and Brandl, 2003). *P. syringae* is an epiphytic bacterium and an opportunistic plant pathogen that needs to survive on plant surfaces (Hirano and Upper, 2000). Before initiating infection, *P. syringae* has to face environmental abiotic stressors via different survival mechanisms (Sundin and Jacobs, 1999; Yu et al., 1999; Lindow and Brandl, 2003). The life cycle of Pss on mango plant surfaces (as depicted in **Figure 2**) involves an epiphytic phase mainly during the spring and summer seasons, that subsequently leads to an infection process during the autumn and winter seasons, when the weather conditions are favorable for the disease development (Cazorla et al., 1998).

*Pseudomonas syringae* pv. *syringae* isolated from mango trees has therefore developed different strategies to survive on the mango plant surface. Where present, the 62 Kb PFP plasmids exhibit a key role (Cazorla et al., 2002, 2008; Arrebola et al., 2009; Gutiérrez-Barranquero et al., 2013b, 2017a). Recently, other important genes located on the chromosomal genetic material have been described as having a primary role in adhesion

and subsequent biofilm formation on mango plant surfaces (Arrebola et al., 2015).

## Copper and Ultraviolet Resistance Genes Mainly Encoded by PFP Plasmids Are Essential for Epiphytic Survival on Mango Tree Surfaces

Plasmids have been reported to be one of the most important sources for bacterial evolution, due to their ability to acquire foreign DNA and be rapidly transmitted among bacteria via the horizontal gene transfer process (Vivian et al., 2001; Norman et al., 2009). Plasmids are part of the flexible genome and represent a portion of the genome that does not contribute to basic survival functions. However, plasmids encompass important genes that can improve the ecological fitness of their bacterial hosts (Medini et al., 2005; Sundin, 2007) and improve virulence mechanisms (Jackson et al., 1999; Arnold et al., 2001). The PFPs are a family of native plasmids that appear to be indigenous to *P. syringae*. All PFP plasmids share a major replication protein, gene *repA* (Sesma et al., 1998, 2000). Apart from specific genes involved in self-maintenance and replication processes of PFPs, different genes implicated in virulence and/or ecological fitness are encoded. In particular, copper- and ultraviolet radiation-resistance genes are two of the most widely distributed genes in this family of plasmids, which play a fundamental role in epiphytic survival (Sundin, 2007).

As mentioned previously, the use of copper compounds has been strongly associated with agriculture (Lamichhane et al., 2018). The extensive use of copper by growers led to an increase in the dosage and frequency of applications, giving rise to the emergence of copper-resistant strains, a concerning issue that is very common among plant pathogenic bacteria, such as *P. syringae* (Sundin et al., 1989; Andersen et al., 1991; Sundin and Bender, 1993; Scheck and Pscheidt, 1998). In Southern Spain, different copper compounds have been largely used to control BAN disease in mango trees, as well as other plant diseases. This suggests that the selection of copper-resistant strains could be a major reason for further control failures with copper bactericides. The *copABCD* operon is the most common genetic determinant associated with copper resistance in *P. syringae* and has been reportedly associated with conjugative native PFP plasmids (Bender and Cooksey, 1986; Cooksey, 1987; Lim and Cooksey, 1993; Sundin and Bender, 1996). The *copABCD* operon encoded by a 35-kb plasmid from *P. syringae* pv. *tomato* was the first of these genes to be sequenced (Mellano and Cooksey, 1988). Based on this background, a study was performed to analyze the role of the *copABCD* operon in copper treatment tolerance, as well as its association with PFP plasmids in Pss strains isolated from mango trees (Cazorla et al., 2002). The presence of the *copABCD* operon and its association with PFPs plasmids was further analyzed. Over 75% of the copper-resistant strains, harbored 62-kb plasmids that showed a hybridization signal by Southern blot analysis with the *copABCD* probe obtained from *P. syringae* pv. *tomato* PT23 (Bender and Cooksey, 1987). The *copABCD* operon is also encoded, albeit to a lesser extent, in the chromosome, as well as in 120- and 45-kb plasmids. This observation suggested that
different variants of copper resistance determinants could be found in Pss mango populations, as has previously been reported in other Pss populations (Sundin and Bender, 1993; Rogers et al., 1994). These data were also supported by 62-kb plasmids restriction profiles, identifying different restriction profiles in both copper-resistant and copper-sensitive plasmids. Moreover, in order to determine whether those plasmids were conjugative and also the main determinants of copper resistance, mating experiments proved that those plasmids were conjugative and were involved in the copper resistance phenotype. The presence of copper-resistant conjugative plasmids could be considered the main cause of control strategy failures when treating with copper bactericides. Thus, field experiments where copper treatments were applied to mango trees once per month, from September to June, were analyzed to assess the emergence of copper-resistant strains. It was clearly demonstrated that excessive usage of copper in mango trees to control BAN disease promoted an increase in copper-resistant strains, which could be mainly due to the ability of these plasmids with be transmitted by conjugative processes (Cazorla et al., 2002).

Subsequently, based on a PFPs sequencing project that included strains that harbored different variants of copper-resistance determinants (Gutiérrez-Barranquero et al., 2017a), it was shown that the presence of a novel genetic structure in Pss UMAF0081 strain isolated from mango increased copper-resistance phenotypes. This novel genetic structure encoded the *cusCBA* genes (detoxifying monovalent cations of silver and copper) and *copG*, a putative metal-transporting P-type ATPase, both inserted within the *copABCD* operon (Gutiérrez-Barranquero et al., 2013b). Furthermore, the novel genetic structure was found in another strain of Pss analyzed in this study (Pss 6-9 strain isolated from sweet cherry), and was also present in another two strains from the database that belonged to different pathovars (ATCC1128 pv. *tabaci* and NCPPB1108 pv. *tomato*). This structure encompassed 15 genes that were more than 17 kb in size, according to data that was recently updated (Gutiérrez-Barranquero et al., 2017a). To determine whether those extra genes were responsible for the increase in copper resistance, the minimal inhibitory concentrations of copper and other heavy metals were investigated. A collection of Pss strains isolated from mangos and others hosts, two strains from different pathovars, a transconjugant strain obtained previously (Cazorla et al., 2002, FF5-km + 62-kb 0081 plasmid), and two Pss FF5 transformants that harbored *copG* and *cusCBA* were independently evaluated. It was observed that the transconjugant strain showed the same MIC value for copper as the original 0081 strain; the transformed strains also had increased their MIC values in comparison with the copper-sensitive parental FF5 strain (Sundin and Bender, 1993). A growth curve performed in minimal medium supplemented with 0.8 mM of copper sulfate clearly demonstrated that *copG* and *cusCBA* were responsible for the increase in copper resistance. The role of *cusCBA* in detoxifying heavy metals has been previously reported in *Cupriavidus metallidurans* (Mergeay et al., 2003; Von Rozycki and Nies, 2009), *Escherichia coli* (Franke et al., 2003) and *Pseudomonas putida* KT2440 (Cánovas et al., 2003; Leedjärv et al., 2008). Finally, qRT-PCR experiments were

performed to analyze the expression profiles of *copG* and *cusA* in the presence or absence of 0.8 mM copper sulfate. The results showed that the expression levels of *cusA* and *copG* increased 13- and 100-fold, respectively, in the presence of copper, and the expression of *cusA* was 3-fold higher than *copG*. These results confirmed the previous results obtained in the MIC and growth curve experiments, supporting the hypothesis that the novel rearrangement of three different genetic determinants into a conjugative plasmid increases copper resistance in *P. syringae* (Gutiérrez-Barranquero et al., 2013b). Thus, the presence of different copper-resistance structures associated primarily with 62-Kb PFPs plasmids has been demonstrated in Pss strains isolated from mango trees. However, little is known concerning the dynamics of maintenance or preference of the different types of 62-kb plasmids in Pss mango populations.

UV radiation affects bacterial communities that are intimately associated with plant surfaces; to overcome this growth-limiting environmental stress, different mechanisms have been developed (Beattie and L window, 1995; Sundin and Jacobs, 1999; Jacobs and Sundin, 2001). Among the different mechanisms described for avoiding UV damage, the presence of DNA repair mechanisms, such as *rulAB* operon encoded by PFP plasmids, are the most relevant in Pss (Sundin et al., 1996; Sesma et al., 1998; Sundin and Murillo, 1999; Sundin et al., 2000). In Southern Spain, mango crops are exposed to high UV radiation, especially in the spring and summer seasons. These highly restrictive solar radiation conditions suggest that a similar *rulAB*-like operon could play an indispensable role in the epiphytic survival of Pss associated with mango trees. As noted above, there was a high incidence of 62-kb plasmids associated with Pss isolated from mango trees that belong to the PFP family, which were also strongly associated with copper resistance phenotype (Cazorla et al., 2002). In this sense, Cazorla et al. (2008) analyzed the presence of the *rulAB*-like operon and its role in UV radiation tolerance in the 62-Kb PFP plasmids. Over 62% of the strains analyzed harbored a 62-kb plasmid. Additionally, it was observed that the Pss strains harboring 62-kb plasmids, rather than those lacking plasmids or having a different plasmid, were more tolerant to UVC exposure and were able to maintain higher population levels *in vitro*. However, the UVC wavelengths do not naturally reach the earth's surface; thus, its impact on ecological fitness is low (Kim and Sundin, 2000). Subsequently, two different exposures conditions of UVA+B (high irradiation and similar radiation in a summer day in Southern Spain) were tested, and in both conditions, the role of plasmids in UVA+B tolerance was demonstrated. This result reinforced the importance of 62-kb plasmids in epiphytic survival of Pss isolated from mango trees in Southern Spain. Finally, the role of 62-kb plasmids in UV tolerance was tested *in vivo* on mango leaf surfaces, evaluating different conditions (leaves in sunny and shady areas, and adaxial and abaxial parts of the leaves). Once again, a greater surviving population of Pss was observed in the strains harboring 62-kb PFP plasmids, although this difference was only notable in the adaxial side of leaves exposed to direct sunlight radiation (Cazorla et al., 2008). Therefore, it has been clearly demonstrated the *rulAB+* Pss strains shown an advantage regarding their epiphytical fitness, and thus this operon plays a relevant role in
growth and dispersion of Pss on mango surfaces during its harsh epiphytic phase suffered in Southern Spain. This competitive advantage may be promoting the selection and the dispersion of these plasmids among the mango microbiome.

## Cellulose Production Modulates the Epiphytic and Pathogenic Lifestyle of *Pseudomonas syringae* pv. *syringae* on Mango Surfaces

Exopolysaccharides (EPS) have been reported to play essential roles in plant colonization and epiphytic survival of plant-associated bacteria (Pfeilmeier et al., 2016), including *P. syringae* (Yu et al., 1999). Different EPS have been associated with different functions of *P. syringae* during the epiphytic phase on the plant surface, as well as with its pathogenic lifestyle. Alginate is one of the most-studied EPS in *P. syringae*, and its involvement in osmotic stress tolerance, epiphytic survival, and virulence has been well-established (Yu et al., 1999; Freeman et al., 2013). Although the role of alginate and levan are not directly related to biofilm formation (Laue et al., 2006), their role in the initial stages of adhesion prior to biofilm development cannot be ignored (Yu et al., 1999). In addition, the putative role of levan as a nutrient source in mature biofilms, as well as its activity as a barrier blocking the recognition by the plant during pathogenesis, have been proposed (Kasapis et al., 1994; Laue et al., 2006). Cellulose is an important EPS that is well-documented in many bacterial species (Römling and Galperin, 2015). It is an integral part of extracellular matrix components of biofilms, mainly in environmental and pathogenic *Pseudomonas* (Ude et al., 2006; Römling et al., 2013). It is noteworthy that cellulose also exhibits major roles in the modulation of virulence mechanisms in both human and plant pathogenic bacteria (Römling et al., 2013). Based on a "genome mining" approach using the complete genome sequence of the model strain Pss UMAF0158 (Martínez-García et al., 2015), an orthologous gene cluster to the operon *wss* of *Pseudomonas fluorescens* SBW25 involved in cellulose biosynthesis was identified in the chromosome (Rainey and Travisano, 1998; Spiers et al., 2002). This gene cluster is organized as an operon, and encompasses 14,642 bp that encodes nine genes with putative functions associated with cellulose production and acetylation. Additionally, the evolutionary history of this gene cluster revealed that it was present in both pathogenic and non-pathogenic *Pseudomonas*. In addition, the flanking regions of the cellulose gene cluster were consistent between Pss UMAF0158 and other *P. syringae* cellulose-producing strains, suggesting an identical chromosome location.

Epiphytic colonization by *P. fluorescens* SBW25 and its survival on plant surfaces is primarily due to cellulose overproduction by the *wss* operon (Gal et al., 2003; Spiers et al., 2003). The role of cellulose in biofilm formation of *P. syringae* pv. *tomato* DC300 has also been shown (Pérez-Mendoza et al., 2014). To determine the role of cellulose in the lifecycle of Pss isolated from mangos, insertional mutants in the biosynthetic genes of the *wss* cluster, *wssB* and *wssE* (Römling, 2002), were constructed and proved to be impaired

in cellulose production. Furthermore, a cellulose-overproducing strain was obtained via the transformation of Pss UMAF0158 with plasmid pVS61-WsR19 that contained *wspR19* from *P. fluorescens* SBW25 (Ude et al., 2006). Scanning electronic microscopy on mango buds and tomato leaves revealed the formation of microcolonies of the wild-type and overproducing strains immersed in the extracellular matrix, but not for the cellulose-defective mutants. Furthermore, adhesion experiments on mango leaves revealed that the amount of bacteria recovered were higher in the wild-type and overproducing strains, in respect to the *wss* mutants. In contrast, although growth curves on minimal medium for the different strains exhibited similar patterns, the incidence (number of necrotic points developed) and the severity (necrotic area developed) on tomato leaflets were higher in the *wss* mutants, lower in the wild-type, and practically abolished in the cellulose overproducing strain. The competitive index approach analysis supported these results, showing that the competitiveness of the overproducing strain was decreased during the plant infection experiments (Arrebola et al., 2015). It is evident that cellulose plays a primary dual role between epiphytic and pathogenic lifestyle of Pss on mango tree surfaces, which suggests that this trait is maintained on Pss mango populations for mango leaf and bud colonization and adaptation. Mechanisms of the regulation of cellulose biosynthesis by Pss isolated from mango trees has not yet been determined, but some clues have been discovered in related *Pseudomonas*. The second messenger c-di-GMP controls cellulose biosynthesis in *P. fluorescens* SBW25 (Spiers et al., 2002) and regulates the switch between the static and motile phases in many different bacterial species (Römling et al., 2013). More recently, the transcriptional regulator AmrZ has been reported to be a key regulator in the biosynthesis of cellulose in *P. syringae* pv. *tomato* DC3000 (Prada-Ramírez et al., 2016). The regulon of the AmrZ transcriptional regulator includes putative c-di-GMP proteins such as AdcA and MorA; thus, AmrZ could be directly involved in cellulose biosynthesis by modulating the available pool of c-di-GMP.

## VIRULENCE FACTORS ASSOCIATED WITH *Pseudomonas syringae* pv. *syringae* STRAINS ISOLATED FROM MANGO TREES

As described by Salmond (1994), a virulence factor could be any molecule present on the bacterial cell surface or released from the cell that could influence the growth of the pathogen in plants, enhancing infection and subsequent disease development. Plant pathogenic bacteria have developed many different and specific virulence strategies to infect successfully their plant hosts. The identification, characterization and dissection of the modes of action of different virulence factors is complex, despite the efforts of many research groups (Mansfield et al., 2012; Pfeilmeier et al., 2016). Whereas the traits that confer *P. syringae* pathogenicity are numerous and well-studied, the mechanisms underlying susceptibility of mango are unknown. The lack of balance in our understanding of the mechanisms involved (well understood
for the pathogen, poorly understood for the host) make us to focus in the role of the pathogen during the interaction with the host. *P. syringae*, in particular, and Pss strains isolated from mango specifically, shows a broad and sophisticated armament of different virulence factors (Ichinose et al., 2013), among which bacterial toxins are one of the most studied in depth.

## Bacterial Toxins

Bacterial toxins are important virulence factors of *P. syringae* (Mitchell, 1991) and have been described to be involved in the development of chlorotic and necrotic disease symptoms in its plant hosts (Volksch and Weingart, 1998; Scholz-Schroeder et al., 2001). Lipodepsipeptidic toxins, such as syringomycins and syringopeptins, have been strongly associated with several pathovars of *P. syringae* and are mainly related with the production of necrotic symptoms (Gross and DeVay, 1977; Ballio et al., 1991; Adetuyi et al., 1995; Vassilev et al., 1996; Bender et al., 1999; Scholz-Schroeder et al., 2001). Pss strains isolated from mango trees were found to produce syringomycin by using growth inhibition tests toward *Geotrichum candidum* (Gross and DeVay, 1977) and *Rhodotorula pilimanae* (Iacobellis et al., 1992), and the detection of a specific gene involved in its biosynthesis was done by a PCR protocol (Sorensen et al., 1998). In addition, Pss strains isolated from mango trees were also found to produce syringopeptins by using a grown inhibition bioassay of *Bacillus megaterium* (Lavermicocca et al., 1997). Another group of important toxins described in several pathovars of *P. syringae* are the so-called "antimetabolite toxins." This group of toxins blocks the function of enzymes involved in the biosynthetic pathways of crucial amino acids, as well as the biosynthesis of polyamine (Bender et al., 1999; Arrebola et al., 2011a,b). These toxins produce chlorotic symptoms in plant tissue due to the accumulation of different intermediates (Patil et al., 1972; Turner and Debbage, 1982; Bachmann et al., 1998). The best-known antimetabolite toxins produced by different pathovars of *P. syringae* are tabtoxin, phaseolotoxin, and the recently identified mangotoxin (Arrebola et al., 2003). Mangotoxin was initially identified to be produced mainly by Pss strains isolated from mango trees, although its production was also reported in a few Pss strains from other hosts (Arrebola et al., 2003). The biosynthesis pathway of mangotoxin, its regulation, and the role that this toxin plays in the different lifestyles of Pss-mango interactions are discussed extensively in the next section.

## MANGOTOXIN, AN ANTIMETABOLITE TOXIN MAINLY ASSOCIATED WITH *P. syringae* pv. *syringae* STRAINS ISOLATED FROM MANGO TREES

Mangotoxin is the most recent antimetabolite toxin discovered and was first described to be mainly produced by Pss strains isolated from mango trees. This toxin was called "mangotoxin" due to the plant host (mango tree) from which most of the Pss strains mangotoxin producers were isolated (Arrebola et al.,

2003). As mentioned above, antimetabolite toxins block enzymes functions involved in the biosynthetic pathways of crucial amino acids and the biosynthesis of polyamine (Bender et al., 1999; Arrebola et al., 2011a,b). The toxic activity of mangotoxin is reversed by the addition of ornithine, and thus, its target enzyme was identified as ornithine N-acetyl transferase (OAT) (Arrebola et al., 2003). In **Figure 3A**, a schematic representation of the arginine-glutamine and polyamine biosynthesis pathways shows the target enzymes of the different antimetabolite toxins including mangotoxin. In order to decipher the chemical structure of mangotoxin a physicochemical characterization was performed initially using cell-free filtrates revealing that mangotoxin is a small secreted molecule of a hydrophilic nature smaller than 3 kDa in size, extremely resistant to high pH and high temperature, but sensitive to protease treatments. The analysis of a Tn5 defective mutant in mangotoxin production (UMAF0158-3aE10) and the wild-type strain Pss UMAF0158 by using High-performance liquid chromatography (HPLC), revealed a specific peak associated with mangotoxin activity (Arrebola et al., 2003). Another chemical separation techniques such hydrophilic interaction liquid chromatography (HILIC) and ion Exchange chromatography (FPLC) have been also applied to decode the mangotoxin structure (data not published). However, the efforts conducted to unravel the chemical structure of mangotoxin have been in vain to date, largely due to its high chemical instability.

To understand the molecular basis of mangotoxin production, three mutants impaired in mangotoxin production obtained from a genomic library (Pss UMAF0158-3γH1, -6γF6, and -5αC5) that displayed growth characteristics and production of lipodepsipeptidic toxins similar to wild-type strain UMAF0158 (Arrebola et al., 2007) were studied in depth. The insertion in the mutant UMAF0158-6γF6 was located in a DNA region that showed high similarity with an non-ribosomal peptide synthetase (NRPS) present in Pss B728a, *P. syringae* pv. *tomato* DC3000 and *P. syringae* pv. *phaseolicola* 1448A. This orf called *mgoA* gene has a size of 3447 bp, and the amino acids sequence of this protein was composed of an activation module with conserved domains typical for NRPS (Stein and Vater, 1996; Marahiel et al., 1997). The role of *mgoA* in virulence of Pss was demonstrated in tomato leaflets, showing this mutant a lower disease incidence than the wild-type. Therefore, the NRPS gene *mgoA* was confirmed to be involved in mangotoxin biosynthesis and, also, in virulence (Arrebola et al., 2007). Furthermore, three additional genes were detected together with the *mgoA* gene and were designated *mgoB*, *mgoC*, *mgoA*, and *mgoD*, in accordance with the mangotoxin generating operon. Insertional mutants in *mgoC*, *mgoA*, and *mgoD*, had altered mangotoxin production. Additionally, by using RT-PCR all *mgo* genes were co-transcribed together, forming a single polycistronic mRNA and thus forming an operon. Complementation experiments with the *mgo* operon restored the ability of the mutants to produce mangotoxin, and therefore, these results confirmed strongly that the *mgo* operon was necessary for mangotoxin production (Arrebola et al., 2007, 2012). The *mgo* operon has been found to be well-distributed in the majority of *Pseudomonas* species, including different pathovars of *P. syringae* (Lindeberg et al., 2008; Vallet-Gely et al.,
<figure><img src="image_77.png" /></figure>

**FIGURE 3** | Enzymatic target of mangotoxin and its biosynthesis regulation. (A) Representative scheme of the arginine-glutamine and polyamine biosynthesis pathways. The enzymatic targets of the different antimetabolite toxins, including mangotoxin, and the different pathovars involved in the production of the different antimetabolite toxins are depicted. OAT, ornithine N-acetyltransferase; OCT, ornithine carbamoyltransferase; ODC, ornithine decarboxylase, and GS, glutamine synthetase. Orange box: pathovars positives for the presence of *mbo* genes and positives for mangotoxin production; red box: pathovar positive for the presence of *mbo* genes, but negative for mangotoxin production; dotted lines box: pathovars positive for the presence of *mbo* genes, but not experimentally tested for mangotoxin production. (B) Mangotoxin biosynthesis regulation model. GacS/GacA two-component regulatory system regulates directly or indirectly the transcription of the *mgo* operon. *Mgo* operon could synthesize a positive regulator (signal molecule) to activate the *mbo* operon transcription. The *mbo* operon produces mangotoxin, which acts primarily as a virulence factor, although, other functions have been described.

2010). A homologous gene cluster to the *mgo* operon, *pvf*, has been proposed to be encoded in *Pseudomonas entomophila* as a regulator of virulence factors (Vallet-Gely et al., 2010). Recently, the family of pyrazine N-oxides (PNOs), including a novel dihydropyrazine N,N'-dioxide metabolite, were identified to be

produced by the *pvf* gene cluster in *P. entomophila*, suggesting that these molecules could be involved in *Pseudomonas* signaling and virulence (Kretsch et al., 2018). In addition, fragin biosynthesis, the main antifungal compound produced by *Burkholderia cenocepacia* H111 is under the control of valdiazen,
a novel quorum-sensing signaling molecule produced by a gene cluster homologous to the *mgo* and *pvf* operons (Jenul et al., 2018). Although the structure of the putative signaling molecule produced by the *mgo* operon in Pss isolated from mango trees remains unknown, its function as a regulator of biosynthesis of mangotoxin, and likely other secondary metabolites, is quite feasible.

Interestingly, another two Tn5 mutants abolished in mangotoxin production (UMAF01585aC5 and UMAF0158-4βA2), and thus, affected in virulence (tested in virulence assay in tomato leaflets) were studied in depth because they did not show homology with the genome sequences of Pss B728a, *P. syringae* pv. *tomato* DC3000 or *P. syringae* pv. *phaseolicola* 1448A. The involvement of mangotoxin in the epiphytic survival of Pss strains isolated from mango was demonstrated by Arrebola et al. (2009). Epiphytic survival experiments on tomato leaflets revealed that there was no difference between the wild-type Pss UMAF0158 and both mutants. Nevertheless, when the bacteria were co-inoculated together the wild-type with each of the mutants individually a slight but significant decrease was observed in the mutants, and the difference reached almost one order of magnitude. Thus, in addition to its virulence function, mangotoxin could also play a role in improving the ecological fitness of Pss strains isolated from mango trees. Furthermore, the screening of both mutant insertions in the genomic library showed that both were in a cluster of six genes present in wild-type strain Pss UMAF0158 and not in Pss B728a, *P. syringae* pv. *tomato* DC3000 or *P. syringae* pv. *phaseolicola* 1448A. Complementation experiments restored the ability of both mutants to produce mangotoxin (Carrión et al., 2012). These six genes were named *mboA*, *B*, *C*, *D*, *E*, and *F* in accordance with the *mangotoxin biosynthetic* operon and experiments based on RT-PCR and Northern blot analysis confirmed that these six genes were co-transcribed as a single polycistronic mRNA molecule confirming that these genes were forming an operon. Furthermore, site directed insertional mutations performed in each gene have shown a complete abolition of mangotoxin production in *mboA*, *B*, *C*, and *D* gene mutants and altered phenotypes in *mboE* and *F* gene mutants. Transformation experiments with pLAC-AF (pBBR1-MCS5 + mboA-F), a plasmid that contains the six *mbo* genes in different non-producing *Pseudomonas* strain genetic backgrounds, resulted in mangotoxin producers. Therefore, all experiments strongly confirmed that the *mbo* genes were essential for full production of mangotoxin.

Unambiguously, Carrión et al. (2014) demonstrated that the regulation of mangotoxin production was under the control of both *gacS/gacA* and *mgo* genes and additionally, that *mgo* genes were regulated by *gacS/gacA* genes. Tn5 mutants that were all defective in mangotoxin production (*mgoA* mutant, *mboD* mutant, *mboB* mutant, *gacS* mutant, and *gacA* mutant) were used to unravel the regulation of the mangotoxin biosynthetic pathway. Transcriptional analysis by qRT-PCR showed that expression levels of the *mboA*, *C*, and *E* genes were significantly lower in the *gacA* and *mgoA* mutants than in the wild-type; however, the *mgo* and *mbo* mutants did not affect the transcription levels of the *gacS/gacA* genes. These results

suggested that the *gacS/gacA* system controls the regulation of both *mgo* and *mbo* operons and downstream the *mgo* operon controlled the regulation of the *mbo* operon, and thus controlling the mangotoxin production. Promoter fusion experiments using the *mbo* promoter showed high levels of β-galactosidase activity in the wild-type, whereas the expression was significantly lower in *mgoA*, *gacA*, and *gacS* mutants, supporting the results obtained previously. Taken together, a model for the regulation of mangotoxin production has been proposed (Figure 3B) (Carrión et al., 2014). In this model, it is proposed that *mgo* molecules could serve as signaling molecules, as has been previously described in similar bacteria, and may be involved in the regulation of other virulence traits in Pss strains isolated from mango trees. Moreover, other functions in addition to virulence have been described for mangotoxin, and its putative role as a signaling molecule has been hypothesized.

A diversity survey using different approaches (genetic, phenotypic, and phylogenetic) showed that Pss strains isolated from mango trees formed a single phylotype into the pathovar syringae associated with the mango host, producers of mangotoxin and distributed worldwide in areas where mango is grown and BAN is a relevant disease (Gutiérrez-Barranquero et al., 2013a). Despite of Pss strains isolated from mango are more similar among them in comparison with other Pss isolated from others hosts and other pathovars, phenotypic (including virulence degree) and genetic variability has been observed (Gutiérrez-Barranquero et al., 2013a). Then, in order to determine the evolutionary history of the *mbo* operon, a phylogenetic analysis using the housekeeping genes *rpoD* and *gyrB* grouped all strains belonging to the Genomospecies 1 together but separated in three different clusters. Two of these clusters were associated with the presence of the *mbo* operon (Carrión et al., 2013). Group I *mbo+* was mainly composed of strains from the pathovar syringae, mainly isolated from woody hosts, but predominantly from mango trees, group which correspond with the single phylotype of Pss strains associated with mango trees described by Gutiérrez-Barranquero et al. (2013a). Group II *mbo+* was composed of five different pathovars of *P. syringae* isolated from herbaceous and woody plants (aptata, avellanae, japonica, pisi, and syringae) and group III mainly composed by the pathovar syringae that was negative for the presence of *mbo* genes. Interestingly, group III (the group that lacked the *mbo* operon) diverged before the separation of groups I and II. These results suggested that the *mbo* operon was acquired by groups I and II in only one or two acquisition events after their separation from group III. Thus, this work strongly suggested that the *mbo* operon was horizontally acquired only once during the evolution of the *P. syringae* complex shown to be specifically distributed within the *P. syringae* Genomospecies 1 (Carrión et al., 2013). In the last few years, the databases have suffered a veritable explosion regarding the number of *P. syringae* genome sequences available (Baltrus et al., 2011; Thakur et al., 2016), which also contributed to a novel classification of the *P. syringae* complex in 13 different phylogroups (Berge et al., 2014). A more in depth phylogenetic analysis has been performed including 150 strains of the *P. syringae* complex belonging to the phylogenetic groups
1, 2, 3, 4, 5, 6, 7, and 11 (Figure 4). Inside the phylogenetic group 2, where the Pss strains isolated from mango are present, it is possible to observe the differentiation of three main groups, similar to those previously reported by Carrión et al. (2013). Group I mbo+ was mostly composed of pathovar syringae, mainly isolated from mango trees, corresponding with the single phylotype described. Group II mbo+ was composed of the 5 pathovars previously identified in this group. However, this new analysis included two more pathovars into this group (pathovar atrofaciens and coryli). Finally, a third group was composed mainly by the pathovar syringae that was negative for the presence of *mbo* genes. This new phylogenetic analysis confirms the previous assumption that Pss strains isolated from mango are forming a single phylotype inside the Genospecies1-phylogenetic group 2.

## Ice Nucleation Activity

*Pseudomonas syringae* infections tend to be favored by cool and wet conditions due to its ability to induce ice nuclei formation at warm, subfreezing temperatures (−2 to −4°C) (L window et al., 1982; Hirano and Upper, 1995). Ice nucleation activity (INA), is considered an important virulence factor wide spread throughout *P. syringae* complex that plays a major role in the early stages of infections causing wounds that can facilitate disease particularly

in woody plant species (L window et al., 1982; O’Brien and L window, 1988; Hwang et al., 2005; Lamichhane et al., 2014). In this sense, Cazorla et al. (1995) developed a simple and alternative multiple-tube test that showed an increase in detection sensitivity of active ice nuclei forming bacteria relative to the traditional drop-freezing methods (L window et al., 1978). This method revealed that all Pss strains isolated from mango trees were positive for INA detection. Although the INA virulence factor could be important at the initial stages of BAN development, the low probability of occurrence of frost in mango-producing areas makes its role in virulence largely anecdotal.

## Type III Secretion System

The most-studied and well-characterized virulence factor associated with *P. syringae* is the T3SS (Lindeberg et al., 2012). The T3SS is a complex nanomolecular machinery used by *P. syringae* and many other plant and animal pathogens to inject effector proteins into host plant cells to subvert the plant immune system and induce disease development (Lindeberg et al., 2012). While the T3SS is the most-studied virulence factor in *P. syringae*-plant interactions (Collmer et al., 2000; Oh et al., 2010; Cunnac et al., 2011; Lo et al., 2017), the role that this secretion system might play in the development of BAN disease has not been examined in depth to date. At this stage, a

<figure><img src="image_78.png" /><figcaption>**FIGURE 4** | Multilocus sequence typing analysis of strains belonging to the *P. syringae* complex. (A) The neighbor-joining tree was constructed with combined partial sequences of *rpoD* and *gyrB* housekeeping genes using MEGA 7 software. Bootstrap values (1,000 repetitions) are shown on branches and evolutionary distances are in units of nucleotide substitutions per site. One hundred and fifty strains belonging to the phylogenetic groups 1, 2, 3, 4, 5, 6, 7, and 11 of the *P. syringae* complex are depicted in the circular phylogenetic tree. Marked in blue are represented the strains belonging to the phylogenetic group 2, where the *P. syringae* pv. *syringae* strains isolated from mango are found. (B) Exclusive representation of the phylogenetic group 2. Three main groups are defined regarding the presence or not of the *mbo* genes necessary for mangotoxin production. The topology was similar among phylogenetic trees produced by the maximum-parsimony and maximum-likelihood methods. **Supplementary Table S1** provides the phylogenetic groups, the host of isolation and the accession numbers of the DNA sequences used for each strain represented in this phylogenetic analysis.</figcaption></figure>
genome sequencing project performed on the Pss model strain isolated from mango trees, UMAF0158, revealed the presence of two different T3SSs (Martínez-García et al., 2015). The first T3SS (T3SS-1) is similar to the Hrp-1 T3SS family (Egan et al., 2014) found in different pathovars of *P. syringae* (Lindeberg et al., 2012) and represents the canonical T3SS widely distributed in pathogenic *P. syringae* strains (Block and Alfano, 2011; Lindeberg et al., 2012). Pss strains isolated from mango trees were able to induce a hypersensitivity response (HR) in tobacco plants (Cazorla et al., 1998). The capability of *P. syringae* to provoke a HR in non-host plants is dependent on a functional T3SS (Huang et al., 1992). Thus, in Pss UMAF0158, a simple deletion mutant constructed in the *hrpL* gene (UMAF0158Δ*hrpL*) (an alternative sigma factor that binds to the hrp box promoter sequence of the T3SS genes that upregulates their expression) confirmed the involvement of T3SS-1 in HR development (Martínez-García et al., 2015). The role of this particular T3SS in overall virulence has been widely recorded in Pss B728a, *P. syringae* pv. *tomato* DC3000, and many others (Schechter et al., 2006; Vinatzer et al., 2006; Kvitko et al., 2009; Lee et al., 2012).

Additionally, bioinformatics analysis highlighted the presence of an additional T3SS (called T3SS-2) in the chromosome of Pss UMAF0158 (Martínez-García et al., 2015) that was also found in different strains from different pathovars (Reinhardt et al., 2009; Studholme et al., 2009; Clarke et al., 2010; Matas et al., 2014). This T3SS-2 shows high similarity to the rhizobial-like T3SS Rhc of the Rhizobiales family (Gazi et al., 2012; Egan et al., 2014). A typical *hrp* box promoter regulatory sequences of the

HrpL regulon found preceding the genes of the typical T3SS (Fouts et al., 2002) was missed in the T3SS-2. As it has been demonstrated in other *P. syringae* strains, the T3SS-2 is dispensable for pathogenicity, although a possible role in plant surface colonization or interaction with insects cannot be ruled out (Lindgren et al., 1986; Clarke et al., 2010; Pérez-Martínez et al., 2010; Silby et al., 2011). Different specific mutants in the T3SS-1, T3SS-2, and in combination in both systems constructed in Pss UMAF0158 did not revealed the function of the T3SS-2 in Pss isolated from mango trees, which remains unknown to date (Martínez-García et al., 2015).

Due to the release of the Plant-bacteria Interaction FActors Resource (PIFAR), an open-access web-based resource for genetic factors involved in bacterial interactions with plant-hosts<fnref n="1" /> (Martínez-García et al., 2016), the detection of type 3 effectors (T3Es) has become more accurate than the method previously selected to identify T3Es in Pss UMAF0158 (Martínez-García et al., 2015). By using PIFAR tool, 15 putative T3Es have been identified in Pss UMAF0158, 4 T3Es more than the 11 previously identified. A Venn diagram analysis of the core T3Es, comparing the Pss UMAF0158 genome with the genome sequencing of three Pss strains (B728a, HS191, and B301D) and *P. syringae* Cit7 all belonging to Genomospecies 1 (Gardan et al., 1999) and Phylogenetic Group 2 (Berge et al., 2014), has been performed (**Figure 5A**). In addition, the presence or absence of the different T3Es present in these four strains are

<figure><img src="image_79.png" /></figure>

<footnote n="1">¹http://bacterial-virulence-factors.cbgp.upm.es/PIFAR</footnote>
depicted (Figure 5B). *hopA1*, *hopAX1*, *hopAZ1*, and *hopBK1* are the unique T3Es shared by Pss UMAF0158 with several other strains (Ps Cit7 and Pss HS191). On the other hand, *hopA1*, *hopAX1*, and *hopBK1* have been found in other pathovars of *P. syringae* belonging to different phylogroups (Berge et al., 2014). Remarkably, the effector *hopAX1* appears to be mainly associated with a few strains of different pathovars all belonging to the Genomospecies 1-Phylogenetic Group 2 (pv. *aptata*, pv. *pisi*, pv. *aceris*, and pv. *syringae*). Dillion et al. (2019) have recently described the high-specificity of *hopAX1* T3E in the Phylogenetic Group 2.

## *P. syringae* pv. *syringae* STRAINS ISOLATED FROM MANGO TREES IN THE GENOMIC ERA

High-Throughput Sequencing technologies (HTS) has had a large impact on plant pathology and other research areas. In recent years, there has been substantial growth regarding genome sequencing of bacterial plant pathogens (Studholme et al., 2011) that can provide a strong basis for a better understanding of plant-microbe interactions that 1 day will contribute to the eradication of plant diseases. *P. syringae* is the model plant pathogen par excellence most often used worldwide to dissect plant-pathogen interactions (Baltrus et al., 2017). From the first genome sequenced of the model strain *P. syringae* pv. *tomato* DC 3000, the current landscape has changed markedly, with many groups interested in *P. syringae* comparative genomics and evolution (Lovell et al., 2009; Green et al., 2010; Baltrus et al., 2011; McCann et al., 2013; Thakur et al., 2016; Hulin et al., 2018). Currently, the complete genome sequences of 29 *P. syringae* strains, along with more than 400 draft genome sequences, are included in the NCBI database<fnref n="2" />,<fnref n="3" />. To date, there is only one complete genome sequenced of Pss strains isolated from mango trees (chromosome + 62-kb PFP plasmid), which was performed in the model strain Pss UMAF0158 (Martínez-García et al., 2015). This work revealed a high degree of conservation with other *Pseudomonas* from the *P. syringae* complex; however, different genetic factors were identified for their potential involvement in the epiphytic or pathogenic lifestyle, and these factors have been described in depth in this review. Among these factors, the most important were the presence of the *mbo* operon (mangotoxin biosynthetic operon), the presence of the *wss* operon (operon involved in cellulose biosynthesis), the additional type III-like rhizobial secretion system, the additional type VI secretion system, and a particular T3E repertoire.

Recently, a PFP sequencing project that includes 4 62-kb PFP plasmids from different strains of Pss strains isolated from mango trees was carried out (Gutiérrez-Barranquero et al., 2017a). In this work, it was revealed that the main functions of 62-kb plasmids of Pss strains isolated from mango trees were related to the increase in UV radiation and copper treatment tolerance. The

backbone of the different plasmids regarding the genes involved in the maintenance, replication and conjugation was similar and showed a high degree of synteny. Interestingly, these plasmids were included in the previously described subgroup B (Ma et al., 2007), sharing more than the *repA* gene (replicase gene shared by all PFPs plasmids; Sundin, 2007). In addition, a novel genetic structure likely related to a cell-to-cell communication signaling system appeared in those plasmids upstream of the type IV secretion system, suggesting that the conjugation process could be under the regulation of this signaling mechanism (Gutiérrez-Barranquero et al., 2017a). On the other hand, there is a relatively low degree of homology in remaining genes found in each 62-kb PFP plasmids.

## CONCLUDING REMARKS AND FUTURE DIRECTIONS

The enormous efforts that have been carried out over the last two decades have led us to gain more in-depth understanding of the *P. syringae* pv. *syringae*-mango host interactions. Pss causes important economic losses in mango crop production in the Mediterranean region. Pss strains isolated from mango trees form a single phylotype within the pathovar syringae and exhibit important factors that contribute to the epiphytic-pathogenic phase establishment on the mango plant, revealing a deep interaction between the pathogenic microbe and the host plant. It is worthy to note that the traits in *P. syringae* that are involved in pathogenic and epiphytic lifestyles have been studied in depth, but particularly, the mechanisms underlying the association of Pss with the mango host are little known. Thus, the major traits analyzed in depth in this review would help Pss to interact successfully with mango trees, but some of them are also useful in the interaction of other *P. syringae* strains with other plant hosts. Mangotoxin is the main virulence factor of this particular group of bacteria, and although much attention has been paid to it, the structure of this toxic molecule remains elusive. In addition, the possible role of mangotoxin as a signaling molecule modulating specific gene expression has been hypothesized. Further experiments are currently being carried out to confirm this hypothesis. Additionally, another important virulence factor not well-studied is the T3SS. In Pss isolated from mango trees, an extra copy of the T3SS is present. However, despite the efforts made, its role in the ecology of Pss remains unknown. Another relevant factor recently discovered in Pss strains isolated from mango trees is the presence of a cellulose biosynthetic gene cluster. The cellulose gene cluster has been described as involved in adhesion and biofilm formation development in Pss on the mango leaf surfaces. This gene cluster is only present in a few strains of *P. syringae* but is present in all Pss strains isolated from mango trees, suggesting that it is a crucial factor in the adaptation to the mango host. Its role in modulating epiphytic and pathogenic phases on mango surfaces has also been addressed. In addition, 62-kb PFP plasmids have been shown to play a key role in epiphytic survival of Pss on mangos, harboring UV and copper resistance determinants, among others. This

<footnote n="2">²https://www.ncbi.nlm.nih.gov/genome/185</footnote>

<footnote n="3">³https://www.ncbi.nlm.nih.gov/genome/2253</footnote>