Dodds and Rathjen, 2010; Khan et al., 2016). The interaction between pathogen T3SEs and the host immune system results in an evolutionary arms race, where pathogen T3SEs evolve to avoid detection while still maintaining their role in the virulence process, and the host immune system evolves to recognize the diversity of T3SEs and their actions, while maintaining a clear distinction between self and non-self to avoid autoimmune activation.

One of the best studied arsenals of T3SEs is carried by the plant pathogenic bacterium *Pseudomonas syringae* (Lindeberg et al., 2009, 2012; Mansfield et al., 2012). *P. syringae* is a highly diverse plant pathogenic species complex responsible for a wide-range of diseases on many agronomically important crop species (Mansfield et al., 2012). While the species as a whole has a very broad host range, individual strains can only cause disease on a small range of plant hosts (Sarkar et al., 2006; Lindeberg et al., 2009; Baltrus et al., 2017; Xin et al., 2018). A growing number of *P. syringae* strains have also recently been recovered from non-agricultural habitats, including wild plants, soil, lakes, rainwater, snow, and clouds (Morris et al., 2007, 2008, 2013; Clarke et al., 2010). This expanding collection of strains and the increased availability of comparative genomics data presents unique opportunities for obtaining insight into the determinants of host specificity in *P. syringae* (Baltrus et al., 2011, 2012; O'Brien et al., 2011, 2012; Dillon et al., 2019).

*Pseudomonas syringae* T3SEs have been the focus of both fundamental and applied plant pathology research for decades, going back to some of the early work on gene-for-gene resistance and avirulence proteins (Mukherjee et al., 1966; Staskawicz et al., 1984, 1987; Keen and Staskawicz, 1988; Kobayashi et al., 1989; Keen, 1990; Jenner et al., 1991; Fillingham et al., 1992). Since then, over 1000 publications have focused on *P. syringae* T3SEs (Web of Science {"*P. syringae*" AND [avirulence OR ("type III" AND *effector*)]}, October 2018), making it one of the most comprehensively studied T3SE systems. To date a total of 66 T3SE families and 764 T3SE alleles have been cataloged in the *P. syringae* Genome Resources Homepage<fnref n="1" />. Many of these T3SE families are small, relatively conserved, and only distributed in a subset of *P. syringae* strains, while others are more diverse and distributed across the majority of sequenced *P. syringae* strains (Baltrus et al., 2011; O'Brien et al., 2011; Dillon et al., 2019). Given the irregular distribution of T3SEs among strains and their frequent association with mobile genetic elements, it has long been recognized that horizontal transfer plays an important role in the dissemination of T3SEs among strains (Kim and Alfano, 2002; Rohmer et al., 2004; Stavrinides and Guttman, 2004; Lovell et al., 2009, 2011; Godfrey et al., 2011; Neale et al., 2016). Nucleotide composition and phylogenetic analyses of a subset of T3SEs identified eleven *P. syringae* T3SE families that were acquired by recent horizontal transfer events. However, the remaining thirteen families appeared to be ancestral and vertically inherited, suggesting that pathoadaptation may also play a major role in T3SE evolution through mutations that modify the function of T3SEs (Rohmer et al., 2004; Stavrinides et al., 2006; O'Brien et al., 2011). While T3SE repertoires

are thought to be key determinants of host specificity, strains with divergent repertoires are at times capable of causing disease on the same host (Almeida et al., 2009; O'Brien et al., 2011, 2012; Lindeberg et al., 2012), signifying that we have much to learn about the ways in which T3SEs contribute to *P. syringae* virulence.

Two major issues impact our understanding of T3SE diversity in *P. syringae*; namely, sampling, and nomenclature. From a sampling perspective, the current catalog of T3SEs listed on the *P. syringae* Genome Resources Homepage were identified from approximately 120 strains that represent only a subset of the phylogroups and overall diversity in the *P. syringae* species complex. Expanding this strain collection to include more diversity, including less biased agricultural collections and more natural isolates, will undoubtedly expand our understanding of diversity within T3SE families and reveal as-yet identified families.

Nomenclature problems are certainly less interesting from a biological perspective, but are very important operationally since poor classification and naming practices can lead to substantial confusion and even spurious conclusions. Efforts to address this problem have been made in the past. Most notably, a standardized set of criteria for the identification and naming of *P. syringae* T3SEs was agreed upon by the majority of labs heavily invested in T3SE research in 2005 (Lindeberg et al., 2005). Specifically, we proposed that new T3SEs be classified into existing families using a BLASTP analysis against previously characterized T3SEs to designated families ($E < 10^{-5}$, alignment length > 60%), at which point each family would be subject to rigorous phylogenetic analyses to assign subgroups and truncations. T3SEs that did not fit into any existing families were assigned a new family designation. While the guidelines proposed by this work were widely accepted and implemented, they were not universally applied to all new candidate T3SEs for a number of reasons. Some of the problems stemmed from the inherent biological complexity found in many T3SE, which are often multidomain proteins that share similarity with multiple divergent T3SE families (Stavrinides et al., 2006; McCann and Guttman, 2008). Further, at the time of their discovery, many families also had fewer than three T3SE alleles, making robust phylogenetic analyses impossible. Regardless of the root cause, we are currently in a situation where many T3SEs are annotated without family assignment, some very similar T3SEs have been assigned to different T3SE families, and some highly divergent T3SEs are assigned to the same family based on short tracts of local similarity. This situation should be rectified in order to facilitate more comprehensive analyses of the role of T3SEs in the outcomes of host-pathogen interactions, particularly in light of the growing database of *P. syringae* genomics resources.

Here, we present an expanded catalog of T3SEs in *P. syringae* and an updated phylogenetic analysis of the diversity within each T3SE family. We identified a total of 14,613 T3SEs from 494 *P. syringae* whole-genomes that include strains from 11 of the 13 *P. syringae* species complex phylogroups. These strains allowed us to redefine evolutionarily distinct family barriers for T3SEs, examine the distribution of each family across the *P. syringae* species complex, quantify the diversity within each

<footnote n="1">¹www.pseudomonas-syringae.org/</footnote>
T3SE family, and explore how T3SEs are inherited. By expanding and diversifying the database of confirmed and predicted *P. syringae* T3SEs and placing all alleles in an appropriate phylogenetic context, these analyses will ultimately enable more comprehensive studies of the roles of individual T3SEs in pathogenicity and allow us to more effectively explore the contribution of T3SEs to host specificity.

# MATERIALS AND METHODS

## Genome Sequencing, Assembly, and Gene Identification

Four hundred and ninety-four *P. syringae* species complex strains were analyzed (**Supplementary Dataset S1**), of which 102 assemblies were obtained from public sequence databases, including NCBI/GenBank, JGI/IMG-ER, and PATRIC (Markowitz et al., 2012; Wattam et al., 2014; NCBI Resource Coordinators, 2018), and 392 strains were sequenced in house by the University of Toronto Center for the Analysis of Genome Evolution and Function (CAGEF). Two hundred and sixty-eight of these sequenced strains were provided by the International Collection of Microorganisms from Plants (ICMP). For the strains sequenced by CAGEF, DNA was isolated using the Gentra Puregene Yeast and Bacteria Kit (Qiagen, MD, United States), and purified DNA was then suspended in TE buffer and quantified with the Qubit dsDNA BR Assay Kit (ThermoFisher Scientific, NY, United States). Paired-end libraries were generated using the Illumina Nextera XT DNA Library Prep Kit following the manufacturer's instructions (Illumina, CA, United States), with 96-way multiplexed indices and an average insert size of ~400 bps. All sequencing was performed on either the Illumina MiSeq or GAIIx platform using V2 chemistry (300 cycles). Following sequencing, read quality was assessed with FastQC v0.11.5 (Andrews, 2010) and low-quality bases and adapters were trimmed using Trimmomatic v0.36 (Bolger et al., 2014) (ILLUMINACLIP: NexteraPE-PE.fa, Maximum Mismatch = 2, PE Palindrome Match = 30, Adapter Read Match = 10, Maximum Adapter Length = 8; SLIDINGWINDOW: Window Size = 4, Average Quality = 5; MENLEN = 20). All genomes were then *de novo* assembled into contigs with CLC v4.2 (Mode = fb, Distance mode = ss, Minimum Read Distance = 180, Maximum Read Distance = 250, Minimum Contig Length = 1000). Raw reads were then re-mapped to the remaining contigs using samtools v1.5 with default settings to calculate the read coverage for each contig (Li and Durbin, 2009). Any contigs with a coverage depth of less than the average contig coverage by more than two standard deviations were filtered out of the assembly. Finally, gene prediction was performed on each genome using Prodigal v2.6.3 with default settings (Hyatt et al., 2010).

## Identifying, Annotating, and Delimitation of Type III Secreted Effector Families

To characterize the effector repertoire of each of the 494 *P. syringae* strains used in this study, we first downloaded all available *P. syringae* effector, helper, and chaperone sequences

from three public databases: NCBI<fnref n="2" /> (18,120), Bean 2.0 (225) (Dong et al., 2015), and the *P. syringae* Genome Resources Homepage<fnref n="3" /> (843). Additional type III associated proteins were recovered from NCBI by querying the NCBI protein database with “type III effector,” “type III helper,” and “type III chaperone” along with “*P. Syringae*.” These were combined with all available type III secretion associated genes from the Bean 2.0 database and the *P. syringae* Genome Resources database, which were downloaded directly. Using this database of 19,188 T3SE associated sequences in *P. syringae*, we then performed an all-vs-all BLASTP analysis to ensure that all sequences that we downloaded were assigned to appropriate families, which was essential given that many of the sequences downloaded from NCBI are ambiguously labeled. Any unassigned T3SE associated gene that had significant reciprocal blast hits (*E* < 1e-24) with an assigned T3SE associated gene was assigned to the corresponding family. This strict *E*-value cutoff was chosen to avoid incorrectly assigning families to sequences based on short-tracts of similarity that are common in the *N*-terminal region of T3SEs from different families (Stavrinides et al., 2006). Sequences that had reciprocal significant hits from multiple families were assigned to the family where they had more significant hits, which means that smaller families could be dissolved into a larger family if all sequences from the two families were sufficiently similar. However, this only occurred in one case, which resulted in all HopF and HopBB sequences being assigned to the HopF/HopBB family. In sum, our final seed database of *P. syringae* T3SEs contained a total of 7,974 effector alleles from 66 independent families, 1,585 discontinued effector alleles from 6 independent families, 2,230 helper alleles from 23 independent families, and 1,569 chaperones alleles from 10 independent families. Any sequences that were not able to be assigned to an appropriate T3SE family were discarded because of the possibility that these are not true T3SE associated genes.

## Identifying and Classifying Individual Type III Secreted Effectors

We identified all putative T3SE protein sequences from the 494 *P. syringae* genomes by querying each predicted protein against the T3SE seed database using BLASTP if it passed a significance threshold of *E* < 1e-24. This resulted in the annotation of 14,613 T3SEs across the 494 *P. syringae* strains. Family names were initially assigned to these T3SEs based on the name that had been assigned to the hit in the seed database, and then later refined based on more rigorous criterion. First, we blasted each T3SE amino acid sequence against a database of all 14,613 T3SEs and retained only hits with an *E*-value of less than 1e-24 and a length that covered at least 60% of the shorter sequence. Sequences that had multiple non-contiguous hits (i.e., high-scoring segment pairs) with an *E*-value less than 1e-24 whose cumulative lengths covered at least 60% of the shorter sequence were also retained. As was the case above, the strict *E*-value cutoff prevents us from assigning significant hits between T3SE sequences that only share strong local identity, which is most commonly seen in

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

<footnote n="3">³https://pseudomonas-syringae.org</footnote>
the N-terminal secretion signal. The 60% length cutoff prevents chimeric T3SEs from linking the two unrelated T3SE families that combined to form the chimera.

Second, a final list of all T3SE pairs that shared significant hits was gathered and T3SE sequences were collectively binned based on their similarity relationships. With this method, T3SE families were built based on all-by-all pairwise similarity between T3SEs rather than the similarity between individual T3SEs and an arbitrary seed T3SE or collection of centroid T3SEs, as is the case with some clustering methods. Significantly, our approach binned all significantly similar T3SEs regardless of whether any two T3SEs were connected through direct or transitive similarity. For example, if T3SE sequence A was significantly similar to T3SE sequence B, and sequence B was significantly similar to sequence C, all three sequences would be binned together, regardless of whether there was significant similarity between sequence A and sequence C. This is important for appropriately clustering particularly diverse T3SE families, which may contain highly divergent alleles that have intermediate variants.

Finally, we assigned the same T3SE family designation to all T3SEs within each cluster based on the most commonly assigned T3SE family name that had initially been assigned to sequences within that cluster. In the majority of cases, all sequences in a single cluster had the same initially assigned T3SE family. However, for cases where there were multiple family names assigned to sequences within a single cluster, both Hop designations (i.e., HopD/HopAO) were assigned to all sequences in the cluster, with the lower designation being considered the short-form for the family. Conversely, for cases where T3SEs that had initially been assigned the same family designation formed two separate clusters, T3SEs from the larger cluster were assigned the initial family name, and T3SEs from the smaller cluster(s) were assigned a novel family name, starting with HopBO, which is the first available Hop designation. In these cases, the initial family designation of the T3SEs in the family were also kept following a forward-slash ("/") so that the source of the family was known (i.e., HopBO/HopX). Ultimately, this method allowed us to effectively delimit all T3SEs in this dataset into separate families with consistent definitions and performed considerably better at partitioning established T3SE families than standard orthology delimitation software like PorthoMCL (Tabari and Su, 2017) (**Supplementary Dataset S2**), likely because of the widespread presence of chimeric T3SEs in the *P. syringae* species complex.

We then validated our approach and assessed whether the reliance on protein queries (e.g., BLASTP) substantially increased the likelihood of missing T3SEs without predicted protein sequences due to the lack of a properly called coding sequence. To do this we examined whether we recovered all T3SEs from the well characterized repertoires of *P. syringae* strains *PtoDC3000*, *PsyB728a*, *Pph1448a*, and *PtoT1* (Cunnac et al., 2009; Xin et al., 2018). Of the 123 non-pseudogene T3SEs carried by these four strains, we only failed to identify a single T3SE; namely, AvrPto1 from *PsyB728a*. This T3SE was not identified because in this region of the chromosome an alternative coding sequence was identified on the opposite strand and the AvrPto1 region was not called as a coding region. While we can identify these

additional T3SEs by directly querying the genome assemblies with TBLASTN, this approach increases our false positive rate by pulling non-effectors via their chimeric relationships with known T3SEs and often results in the inaccurate identification of start and stop codons, which muddles downstream evolutionary analyses, Therefore, only T3SEs that were identified as coding sequences in this study were analyzed.

In order to classify short chimeric relationships between families, as illustrated in **Figure 2**, we used a similar approach to the one outlined above. Specifically, we parsed our reciprocal BLASTP results to capture hits that occurred between alleles that had been assigned to different families. Here, we used a significance cutoff of *E*-value < 1e-10, with no length limitation. All chimeric relationship are shown in **Figure 2**, with the length of each allele and their overlapping regions shown proportionally. These local relationships between alleles in distinct families were not considered in the following evolutionary analyses.

## Phylogenetic Analyses

We generated three separate phylogenetic trees in this study to ask whether core-genome diversity, pan-genome content, or effector content could effectively sort *P. syringae* strains based on their host of isolation. For the core genome tree, we clustered all protein sequences from the 494 *P. syringae* genomes used in this study into ortholog families using PorthoMCL v3 with default settings (Tabari and Su, 2017). All ortholog families that were identified in at least 95% of the *P. syringae* strains in our dataset were considered part of the soft-core genome and each of these families was independently aligned using MUSCLE v3.8.31 with default settings (Edgar, 2004). These alignments were then concatenated end-to-end using a custom python script and a maximum likelihood phylogenetic tree was constructed based on the concatenated alignment using FastTree v2.1.10 with default parameters (Price et al., 2010). For the pan-genome tree, we generated a binary presence-absence matrix for all ortholog families that were identified in more than one *P. syringae* strain. This presence-absence matrix was used to compute a distance matrix in R v3.3.1 using the "dist" function with the Euclidean distance method. The phylogenetic tree was then constructed using the "hclust" function with the complete linkage hierarchical clustering method. We used the same approach to generate the effector content tree, except the input binary presence-absence matrix contained information on the 70 effector families rather than all ortholog families that made up the *P. syringae* pan-genome.

## Estimating Pairwise *Ka*, *Ks*, and *Ka/Ks*

Evolutionary rate parameters were calculated independently for each T3SE family. First, amino acid sequences were multiple aligned with MUSCLE v3.8.31 using default settings (Edgar, 2004). Each multiple alignment was then reverse translated based on the corresponding nucleotide sequences using RevTrans v1.4 (Wernersson and Pedersen, 2003) and all pairwise *Ka* and *Ks* values were calculated for each family using the Nei-Gojobori Method, implemented by MEGA7-CC (Kumar et al., 2016). Output files were parsed using custom python scripts to convert the *Ka* and *Ks* matrices to stacked data frames with four
columns: Sequence 1 Header, Sequence 2 Header, *Ka*, and *Ks*. The alignment-wide ratio of non-synonymous to synonymous substitutions (*Ka/Ks*) was then calculated for all T3SE pairs that had both a *Ka* and a *Ks* value greater than 0 in each family. For codon-level analysis of positive selection in each family, we used Fast Unconstrained Bayesian Approximation (FUBAR) to detect signatures of positive selection in all families that were present in at least five strains with default settings (Murrell et al., 2013).

For comparisons between T3SE family evolutionary rates and core genome evolutionary rates, we converted each individual core genome family alignment that was generated with MUSCLE to a nucleotide alignment with RevTrans, then concatenated these alignments end-to-end as described above. As was the case with each T3SE family, we then calculated *Ka* and *Ks* for all possible pairs of core genomes using the Nei-Gojobori Method and parsed the output files into stacked data frames using our custom python script. The core genome data frame was then merged with each T3SE family data frame independently based on the genomes that the two T3SE sequences were from so that the evolutionary rates between these two T3SEs could be directly compared to the evolutionary rates of the corresponding core genomes.

## Gain-Loss Analysis

We used Gain Loss Mapping Engine (GLOOME) to estimate the number of gain and loss events that have occurred for each T3SE family over the course of the evolution of the *P. syringae* species complex (Cohen et al., 2010). The gain-loss analysis implemented by GLOOME integrates the presence-absence data for each gene family of interest across the phylogenetic profile to estimate the posterior expectation of gain and loss across all branches. These events are then summed to calculate the total number of gene gain and loss events that have occurred for each family across the phylogenetic tree. We performed this analysis on each T3SE family using the mixture model with variable gain/loss ratio and a gamma rate distribution. The phylogenetic tree that we used for this analysis was the concatenated core genome tree, which gives us the best estimation of the evolutionary relationships between strains, given the ample recombination known to occur within the *P. syringae* species complex (Dillon et al., 2019).

## RESULTS

In this study, we analyzed the collective type III effector repertoire of the *P. syringae* species complex using whole-genome assemblies from 494 strains representing 11 of the 13 established phylogroups and 72 distinct pathovars (**Supplementary Dataset S1**). These strains were isolated from 28 countries between 1935 and 2016, and include 62 *P. syringae* type and pathotype strains (Thakur et al., 2016). Although the majority of the strains were isolated from a diverse collection of more than 100 infected host species, we also included strains isolated from environmental reservoirs, which have been dramatically under-sampled in *P. syringae* studies (Morris et al., 2007, 2013; Mohr et al., 2008; Clarke et al., 2010; Demba Diallo et al., 2012; Monteil et al., 2013, 2016; Karasov et al., 2018). As per Dillon

et al. (Dillon et al., 2019), we designate phylogroups 1, 2, 3, 4, 5, 6, and 10 as primary phylogroups and 7, 9, 11, and 13 as secondary phylogroups (we have no representatives from phylogroups 8 or 12, although presumably they would also be secondary phylogroups) (Berge et al., 2014). The primary phylogroups are phylogenetically quite distinct from the secondary phylogroups and include all of the well-studied *P. syringae* strains. Nearly all of the primary phylogroup strains carry a canonical *P. syringae* type III secretion system and were isolated from plant hosts. In contrast, many of the strains in the secondary phylogroups do not carry a canonical *P. syringae* type III secretion system and were isolated from environmental reservoirs (e.g., soil or water).

All of the *P. syringae* genome assemblies used in this study were downloaded directly from NCBI or generated in-house by the University of Toronto Centre for the Analysis of Genome Evolution & Function using paired-end data from the Illumina GAIIx or the Illumina MiSeq platform. There was some variation in the genome sizes, contig numbers, and N50s among strains due to the fact that the majority of the genomes are *de novo* assemblies in draft format (**Supplementary Figure S1**); however, the number of coding sequences identified in each strain were largely consistent with the six finished (closed and complete) genome assemblies in our dataset. Given the large size of the *P. syringae* pan-genome, the fact that some strains have acquired large plasmids, and the relatively high frequency of horizontal gene transfer in the *P. syringae* species complex (Baltrus et al., 2011; Dillon et al., 2019), we expect there to be some variation in genome size and coding content of different strains.

## Distribution of Type III Secreted Effectors in the *P. syringae* Species Complex

To explore the distribution of T3SEs across the *P. syringae* species complex, we first identified all putative T3SEs present in each of our 494 genome assemblies using a BLASTP analysis (Altschul et al., 1997), where all protein sequences from each *P. syringae* genome were queried against a database of known *P. syringae* T3SEs obtained from the *P. syringae* Genome Resource Database<fnref n="4" />, the Bean 2.0 T3SE Database<fnref n="5" />, and the NCBI Protein Database<fnref n="6" />. In sum, we identified a total of 14,613 confirmed and putative T3SEs (**Supplementary Datasets S2–S4**), 4,636 of which were unique at the amino acid level, and 5,127 of which were unique at the nucleotide level. We consider these T3SEs to be putative because their presence within a genome does not necessarily mean that they are expressed and translocated into the host cytoplasm. Individual *P. syringae* strains in the dataset harbored between one and 53 putative T3SEs, with a mean of 29.58 ± 10.13 (SEM), highlighting considerable variation in both the composition and size of each strain's suite of T3SEs (**Figure 1**). As expected, primary phylogroup strains tended to harbor substantially more T3SEs than secondary phylogroups strains (30.55 ± 8.97 vs. 3.89 ± 1.64, respectively), which frequently do not contain a canonical T3SS (Dillon et al., 2019). However, a subset of strains from phylogroups 2 and 3, and all

<footnote n="4">⁴https://pseudomonas-syringae.org</footnote>

<footnote n="5">⁵http://systbio.cau.edu.cn/bean</footnote>

<footnote n="6">⁶https://www.ncbi.nlm.nih.gov</footnote>
<figure><img src="image_49.png" /><figcaption>**FIGURE 1** | Total number of coding T3SEs in each *P. syringae* strain, sorted by phylogroup. Closed circles represent the number of effectors in each strain, boxes show the first quartile effector count, median effector count, and third quartile effector count for the whole phylogroup, and whiskers extend to the highest and lowest effector counts in the phylogroup that are not identified as outliers ( > 1.5 times the interquartile range).</figcaption></figure>

strains from phylogroup 10 harbored fewer than 10 T3SEs, more closely mirroring secondary phylogroup strains in their T3SE content. The extensive T3SE repertoires found in most primary phylogroup strains supports the idea that these effectors play an important role in the ecological interactions of the majority of strains in this species complex.

Objective criteria are required for partitioning and classifying T3SEs prior to any study of their distribution and evolution. In 2005, an effort was made to unify the disparate classification and naming conventions applied to *P. syringae* T3SEs (Lindeberg et al., 2005). While this effort was very successful overall, the criteria have not been universally or consistently applied, resulting in some problematic families. For example, the HopK and AvrRps4 families have high similarity over the majority of their protein sequences, but are assigned to distinct families, while the HopX family contains highly divergent subfamilies that only share short tracts of local similarity.

We reassessed the relationship between all 14,613 T3SEs using a formalized protocol in order to objectively delimit families and suggest new family designations for some similar families. While the selection of the specific delimiting criteria is arbitrary and open to debate, we have elected to use a well-established protocol with fairly conservative thresholds. We identified shared similarity using a BLASTP-based pairwise reciprocal best hit approach (Altschul et al., 1997; Eisen, 2000; Daubin et al., 2002), with a stringent Expect-value acceptance threshold of $E < 1e-24$ and a length coverage cutoff of ≥60% of the shorter sequence (regardless of whether it is query or subject). It should be noted that since this approach uses BLAST it requires only local similarity between family members. Nevertheless, our stringent *E*-value and coverage thresholds select for matches that share more extensive similarity than would typically be observed when proteins only share a single domain. We feel that these criteria provide a reasonable compromise between very relaxed local similarity criteria (using default BLAST parameters) and very conservative global similarity criteria. All T3SEs that exceeded our acceptance thresholds were sorted into family bins. T3SEs

in each bin can therefore be either connected through direct similarity or transitive similarity. Finally, we assigned a primary name to all T3SEs in each bin based on the most common effector family name in that bin and included all secondary family names following a "/".

Our analysis identified 70 T3SE families and sorted T3SEs into their historical families in the majority of cases. We found that our particular delimitation criteria created T3SE family partitions with the best match to those commonly used in the literature. Unfortunately, it was impossible to find any one objective set of standards that did not require some family renaming and shuffling of alleles among families. These exceptions include merging existing effector families that shared significant local similarity (Table 1) and assigning previously named T3SEs into new families (Table 2). A number of these new families only contain a single allele, so it is likely that they are recent pseudogenes still annotated as coding sequences by Prodigal. Finally, in two cases, a subset of alleles from one T3SE family were assigned to a different family due to the extent of shared local similarity. This included the assignment of all originally designated HopS1 subfamily alleles to HopO, and the assignment of all originally designated HopX3 alleles to HopF/HopBB.

<table><caption>**TABLE 1** | T3SE Families Merged into a New Family.</caption><thead><tr><td>Families to Merge</td><td>New Family<sup>1</sup></td><td>New Family Short Form<sup>1</sup></td></tr></thead><tbody><tr><td>HopAB + HopAY</td><td>HopAB/HopAY</td><td>HopAB</td></tr><tr><td>HopAT + HopAV</td><td>HopAT/HopAV</td><td>HopAT</td></tr><tr><td>HopB + HopAC</td><td>HopB/HopAC</td><td>HopB</td></tr><tr><td>HopAO + HopD</td><td>HopD/HopAO</td><td>HopD</td></tr><tr><td>HopF + HopBB</td><td>HopF/HopBB</td><td>HopF</td></tr><tr><td>HopK + AvrRps4</td><td>HopK/AvrRps</td><td>HopK</td></tr><tr><td>HopW + HopAE</td><td>HopW/HopAE</td><td>HopW</td></tr></tbody></table>

<footnote n="1">¹New family short forms were assigned based on the first assigned Hop designation.</footnote>
<table><caption>**TABLE 2** | New T3SE Families.</caption><thead><tr><td>Old Name</td><td>New Family</td><td>New Family Short Form</td></tr></thead><tbody><tr><td>HopX2</td><td>HopBO/HopX</td><td>HopBO</td></tr><tr><td>HopZ3</td><td>HopBP/HopZ</td><td>HopBP</td></tr><tr><td>HopH3</td><td>HopBQ/HopH</td><td>HopBQ</td></tr><tr><td>HopBN1</td><td>HopBR/HopBN</td><td>HopBR</td></tr><tr><td>HopAV1</td><td>HopBS/HopAV</td><td>HopBS</td></tr><tr><td>HopAB2</td><td>HopBT/HopAB<sup>1</sup></td><td>HopBT<sup>1</sup></td></tr><tr><td>HopAB2</td><td>HopBU/HopAB<sup>1</sup></td><td>HopBU<sup>1</sup></td></tr><tr><td>HopAJ2</td><td>HopBV/HopAJ<sup>1</sup></td><td>HopBV<sup>1</sup></td></tr><tr><td>HopBH1</td><td>HopBW/HopBH<sup>1</sup></td><td>HopBW<sup>1</sup></td></tr><tr><td>HopL1</td><td>HopBX/HopL<sup>1</sup></td><td>HopBX<sup>1</sup></td></tr></tbody></table>

It is important to emphasize that the new criteria do not bin T3SEs that share less than 60% similarity across the shortest sequence. This was done to prevent families from being combined due to short chimeric relationships between a subset of the alleles in distinct families (Stavrinides et al., 2006). These relationships could be considered super-families, although the reticulated nature of these relationships makes this unwieldy. We list families that share these short regions of similarity in **Figure 2**, although it is important to recognize that some of these chimeric relationships are only found in a subset of alleles in each family.

The distribution of each of these 70 T3SE families across the *P. syringae* species complex reveals that the majority of families are present in only a small subset of *P. syringae* strains, typically from a few primary phylogroups (**Figure 3** and **Supplementary Figure S2**). Among T3SE effector families, only AvrE, HopB/HopAC, HopM, and HopAA are considered part of the soft-core genome of *P. syringae* (present in >95% of strains). This designation of core T3SE is not impacted by the inclusion or exclusion of the secondary phylogroup strains. Interestingly, three of these core families, AvrE, HopM, and HopAA are part of the conserved effector locus (CEL), a well characterized and evolutionarily conserved sequence region that is present in most *P. syringae* strains (Alfano et al., 2000; Dillon et al., 2019). The fourth CEL effector, HopN, is only present in 14.98% of strains, all of which are from phylogroup 1. HopB/HopAC emerged as a core effector family in our analysis because of the merging of HopB with the broadly distributed HopAC family, which is present in nearly all *P. syringae* strains (491/494). The significant similarity between HopB and HopAC (*E* < 1e-24) occurs across the full length of HopB (the shorter of the two). Despite the high prevalence of this family throughout the *P. syringae* species complex, very little is known about its function. It would be particularly interesting to see if there has been neofunctionalization between the shorter HopB alleles, which are generally localized between the HrpK locus protein and a 315 amino acid hypothetical protein, and the longer alleles formally classified as HopAC, localized between a nebramycin 5' synthase and a 481 amino acid hypothetical protein. While the remainder of T3SE families are also mostly present in a small

subset of strains, there is a wide distribution in the number of strains harboring individual T3SE families, further highlighting the dramatic variation in T3SE content across *P. syringae* strains (**Supplementary Figure S3**).

Following family and strain T3SE classification, we also performed hierarchical clustering using the T3SE content of each strain to determine if T3SE profiles are a good predictor of host specificity. We previously reported that in *P. syringae*, neither the core genome or gene content phylogenetic trees correlate well with the hosts from which the strains were isolated (Dillon et al., 2019). This remains true in this study, where we've updated the core and pan-genome analyses with an expanded set of strains (**Supplementary Figures S4, S5**). The T3SE content tree is not as well resolved due to the smaller number of phylogenetically informative signals in the T3SE dataset. However, we were able to largely recapitulate the established *P. syringae* phylogroups with this analysis, suggesting that more closely related strains do tend to have more similar T3SE repertoires (**Supplementary Figure S6**). We also see that the phylogroup 2, phylogroup 3, and phylogroup 10 strains that have smaller T3SE repertoires than other primary phylogroups, cluster more closely with secondary phylogroup strains in the effector content tree. However, as was the case in the core genome and gene content trees, hierarchical clustering based on effector content did not effectively separate strains based on their host of isolation. We therefore conclude that overall T3SE content is not a good predictor of host specificity.

## Diversification of Type III Secreted Effectors in the *P. syringae* Species Complex

Substantial genetic and functional diversity has been shown to exist within individual T3SE families (Lewis et al., 2014; Dillon et al., 2019). While some T3SE families are relatively small, restricted to only a subset of *P. syringae* strains, and present in only a single copy in each strain, others are found in nearly all strains, and often appear in multiple copies within a single genome (**Figure 4**). Many of the largest families, including those that are part of the core genome (AvrE, HopB/HopAC, HopM, and HopAA), are among those that are often present in multiple copies. However, we also found that some families that are present in less than half of *P. syringae* strains (e.g., HopF/HopBB, HopO, HopZ, and HopBL) frequently appear in multiple copies. While the average copy number of individual T3SEs per strain across all families is 1.30 and some families are present in copy numbers as high as six, it is important to recognize that in many cases these multi-copy effectors are not full-length T3SEs. Rather, they are partial copies derived from the same full-length allele that have been split due to the introduction of a premature stop codon (**Supplementary Dataset S2**). Therefore, at least in these cases, we think it is unlikely that both copies retain function. Nevertheless, the fact that both of these two coding sequences retain enough protein similarity to be linked to other T3SEs in the same family suggests that these disruption events either occur very commonly, or that these regions are

<footnote n="1">¹These new families only contain a single allele.</footnote>
<figure><img src="image_50.png" /><figcaption>**FIGURE 2** | Interfamily blast hits (*E* < 1e-10) that did not pass our *e*-value and/or length cut-offs for combining T3SEs into families. Each superfamily represents a cluster of families that have some overlapping sequence. Colored blocks represent the regions of the representative sequence pairs that are homologous, where the length of the blocks is proportional to the length of the homologous sequence. Black lines represent the remainder of each representative sequence that is not homologous, where the length of the lines is proportional to the length of the 5' and 3' non-homologous regions. Not all families within a superfamily need to contain a significant blast hit with all other families in the superfamily because they can be homologous to the same intermediate sequence in different regions. Short form family names are used for merged or separated families.</figcaption></figure>
<figure><img src="image_51.png" /><figcaption>**FIGURE 3** | Heat map demonstrating the proportion of strains in each phylogroup that harbor each of the T3SE families. Only four T3SE families, AvrE, HopB/HopAC, HopM, and HopAA are considered part of the soft-core *P. syringae* complex genome (present in >95% of strains). Other T3SE families are mostly sparsely distributed across the *P. syringae* species complex, with several families only being present in a few phylogroups. Short form family names are used for merged or separated families.</figcaption></figure>

<figure><img src="image_52.png" /><figcaption>**FIGURE 4** | Total number of *P. syringae* strains harboring an allele from each T3SE family. Color categories denote the copy number of each effector family in the corresponding strains. While the majority of families are mostly present in a single copy, some of the more broadly distributed families have higher copy numbers in a subset of *P. syringae* genomes. Short form family names are used for merged or separated families.</figcaption></figure>
still subject to purifying selection due to the retention of some
functional role.

To quantify the extent of genetic diversification within
each T3SE family, we aligned the amino acid sequences of
all members from each family with MUSCLE, then reverse
translated these amino acid alignments and calculated all pairwise
non-synonymous (Ka) and synonymous (Ks) substitution rates
for all pairs of alleles within each family. There was a broad
range of pairwise substitution rates in the majority of T3SE
families, which is expected given the range of divergence
times in the core-genomes of strains from different P. syringae
phylogroups (Dillon et al., 2019). The three families with the
highest non-synonymous substitution rates were HopF/HopBB,
HopAB/HopAY, and HopAT/HopAV (Figure 5A), which all
have an average Ka greater than 0.5. These families also
tended to have relatively high synonymous substitution rates,
but several other families also have Ks values that are greater
than 1.0 (Figure 5B).

While some pairwise comparisons of effector alleles did yield
a *Ka/Ks* ratio greater than 1, the predominance of purifying
selection operating in the conserved domains of these families
likely overwhelms signals of positive selection at individual
sites. Indeed, the average global pairwise *Ka/Ks* values were less
than 1 for all T3SE families (Figure 5C). Therefore, we also
analyzed the *Ka* and *Ks* on a per codon basis using FUBAR
to search for site-specific signals of positive selection in each
family (Bayes Empirical Bayes *P*-Value ≥ 0.9; *Ka/Ks* > 1) (Murrell
et al., 2013). We find that 37 out of the 64 (57.81%) T3SE
families with at least five alleles have at least one positively
selected site. The number of positively selected sites in these
families was relatively low, ranging from 1 to 17, with the
percentage of positively selected sites in a single family never
rising above 2.29% (Table 3). By comparison, we found that only
3,888/17,807 (21.83%) ortholog families from the pangenome of
*P. syringae* that were present in at least five strains demonstrated
signatures of positive selection at one or more sites (Dillon
et al., 2019), suggesting that T3SE families experience elevated
rates of positive selection. Nevertheless, these results should be
interpreted cautiously given the variable rates of recombination
and horizontal transfer among strains and the confounding
impact this can have on detecting selection (O'Reilly et al., 2008;
Betancourt et al., 2009).

Finally, to explore whether T3SE families display different
levels of diversity than core gene families carried by the same
*P. syringae* strains, we compared all pairwise *Ka* and *Ks* values
within each effector family to the pairwise *Ka* and *Ks* values for
the core genes carried in the corresponding genomes. We would
expect T3SEs and core genes to share the same *Ka* and *Ks* values
if they were evolving under the same evolutionary pressures.
Deviation from this null expectation could be due to either
differences in selective pressures, or the movement of the T3SE
via horizontal gene transfer (HGT). We find that the pairwise
*Ka* values for T3SEs are substantially higher than those of the
corresponding core genes for the majority of T3SEs (Figure 6A
and Supplementary Figure S7). This was also true for pairwise
*Ks* values, although the differences between T3SE pairs and core
genes were not as high and there were many more examples of

T3SE pairs that had lower *Ks* values than the corresponding core
genes (Figure 6B and Supplementary Figure S8).

Gene Gain and Loss of Type III
Secreted Effectors in the
*P. syringae* Species Complex

Both the patchy distribution of T3SE families across the *P. syringae* species complex and the inconsistent relationships between T3SE and core gene substitution rates suggest that HGT may be an important evolutionary force contributing to the evolution of T3SEs in the *P. syringae* species complex. Therefore, we also sought to analyze the expected number of gene gain events across the *P. syringae* phylogenetic tree in order to more accurately quantify the extent to which HGT has actively transferred T3SEs between *P. syringae* strains over the evolutionary history of the species complex. We used the Gain Loss Mapping Engine (GLOOME) to estimate the number of gain and loss events (Cohen et al., 2010; Cohen and Pupko, 2010), and found extensive evidence for HGT in several T3SE families, with some families experiencing as many as 40 HGT events over the course of the history of the *P. syringae* species complex (Figure 7). Outlier T3SE families that did not appear to have undergone much HGT in *P. syringae* include the smallest families, like HopU, HopBE, and HopBR/HopBN, and the largest families, like AvrE, HopB/HopAC, HopM, and HopAA. Smaller families were less likely to have undergone HGT because they were only identified in a subset of closely related strains, so are not expected to have been part of the *P. syringae* species complex through the majority of its evolutionary history. Larger families may experience less HGT because they are more likely to already be present in the recipient strain and therefore will quickly be lost following an HGT event. However, because GLOOME only identifies HGT events that result in the gain of a new family, we cannot be certain whether *P. syringae* genomes with multiple copies were generated by HGT or gene duplication.

An opposing evolutionary force that is also expected to have a
disproportional effect on the evolution of T3SE families is gene
loss. Specifically, loss of a given T3SE may allow a *P. syringae*
strain to infect a new host by shedding an effector that elicits the
hosts' ETI response. Indeed, we found that gene loss events were
also common in many T3SE families, with more than 50 events
estimated to have occurred in the HopAT/HopAV and HopAZ
families (Figure 7). T3SE families that experienced more gene
loss events also tended to experience more gene gain events,
as demonstrated by a strong positive correlation between gene
loss and gene gain in T3SE families (Supplementary Figure S9)
(linear regression; *F* = 140.50, *df* = 1, 68, *p* < 0.0001, *r*² = 0.67).
However, as was the case with gene gain events, we observed
few gene loses in the smallest and the largest T3SE families. For
small families, this is again likely to be the result of the fact that
they have spent less evolutionary time in the *P. syringae* species
complex. For large families, we are again blind to gene loss events
that occur in a genome that has multiple copies of the effector
prior to the loss event. Therefore, there are likely many more
T3SE losses occurring in larger families than we observe here
<figure><img src="image_53.png" /><figcaption>**FIGURE 5** | Non-synonymous substitution rates (Ka) (A), synonymous substitution rates (Ks) (B), and Ka/Ks ratio (C) for each T3SE family. All alleles in each family were aligned using MUSCLE v. 3.8 and all pairwise Ka and Ks values within each family were calculated using MEGA7 with the Nei-Gojobori Method. Boxes show the first quartile substitution rates, median substitution rates, and third quartile substitution rates for each family, and whiskers extend to the highest and lowest substitution rates in the family that are not identified as outliers (> 1.5 times the interquartile range). Average pairwise Ka, Ks, and Ka/Ks values for each family are denoted by red diamonds. Short form family names are used for merged or separated families.</figcaption></figure>

because these T3SE families tend to be present in multiple copies within the same genome.

Finally, we also observed that there is a significant positive correlation between both evolutionary rate parameters and the rates of gene gain and loss for T3SE families (Ka-Gene Gain: *F* = 8.48, df = 1, 63, *p* = 0.0050, *r*² = 0.1186; Ka-Gene Loss:

*F* = 16.15, df = 1, 63, *p* = 0.0002, *r*² = 0.2041; *Ks*-Gene Gain: *F* = 6.46, df = 1, 63, *p* = 0.0135, *r*² = 0.0930; *Ks*-Gene Loss: *F* = 7.70, df = 1, 63, *p* = 0.0072, *r*² = 0.1089) (Supplementary Figure S10). This implies that the same evolutionary forces resulting in diversification of T3SEs are also causing them to undergo elevated rates of gain or loss. However, there was
<table><caption>**TABLE 3** | Positive Selection among T3SE Families.</caption><thead><tr><th>Family</th><th>Total Number of Alleles</th><th>Number of Unique Alleles<sup>1</sup></th><th>Alignment Length (Codons)</th><th>Positively Selected Sites (N)</th><th>Positively Selected Sites (%)</th></tr></thead><tbody><tr><td>AvrA</td><td>27</td><td>12</td><td>906</td><td>1</td><td>0.11</td></tr><tr><td>AvrB</td><td>277</td><td>75</td><td>366</td><td>0</td><td>0.00</td></tr><tr><td>AvrE</td><td>608</td><td>360</td><td>2248</td><td>3</td><td>0.13</td></tr><tr><td>AvrPto</td><td>170</td><td>33</td><td>275</td><td>0</td><td>0.00</td></tr><tr><td>AvrRpm</td><td>171</td><td>39</td><td>301</td><td>0</td><td>0.00</td></tr><tr><td>AvrRpt</td><td>25</td><td>12</td><td>261</td><td>3</td><td>1.15</td></tr><tr><td>HopA</td><td>277</td><td>105</td><td>449</td><td>0</td><td>0.00</td></tr><tr><td>HopB/HopAC</td><td>770</td><td>362</td><td>2265</td><td>0</td><td>0.00</td></tr><tr><td>HopC</td><td>115</td><td>28</td><td>271</td><td>0</td><td>0.00</td></tr><tr><td>HopD/HopAO</td><td>587</td><td>228</td><td>981</td><td>0</td><td>0.00</td></tr><tr><td>HopE</td><td>103</td><td>31</td><td>274</td><td>0</td><td>0.00</td></tr><tr><td>HopF/HopBB</td><td>380</td><td>125</td><td>385</td><td>0</td><td>0.00</td></tr><tr><td>HopG</td><td>190</td><td>70</td><td>528</td><td>0</td><td>0.00</td></tr><tr><td>HopH</td><td>265</td><td>54</td><td>226</td><td>2</td><td>0.88</td></tr><tr><td>HopI</td><td>400</td><td>166</td><td>601</td><td>0</td><td>0.00</td></tr><tr><td>HopK/AvrRps</td><td>156</td><td>34</td><td>338</td><td>3</td><td>0.89</td></tr><tr><td>HopL</td><td>102</td><td>53</td><td>902</td><td>1</td><td>0.11</td></tr><tr><td>HopM</td><td>620</td><td>223</td><td>1034</td><td>2</td><td>0.19</td></tr><tr><td>HopN</td><td>74</td><td>25</td><td>350</td><td>0</td><td>0.00</td></tr><tr><td>HopQ</td><td>227</td><td>75</td><td>391</td><td>1</td><td>0.26</td></tr><tr><td>HopQ</td><td>304</td><td>86</td><td>504</td><td>3</td><td>0.60</td></tr><tr><td>HopR</td><td>424</td><td>231</td><td>2001</td><td>6</td><td>0.30</td></tr><tr><td>HopS</td><td>114</td><td>26</td><td>179</td><td>2</td><td>1.12</td></tr><tr><td>HopT</td><td>97</td><td>34</td><td>398</td><td>2</td><td>0.50</td></tr><tr><td>HopU</td><td>15</td><td>4</td><td>264</td><td>0</td><td>0.00</td></tr><tr><td>HopV</td><td>307</td><td>74</td><td>738</td><td>2</td><td>0.27</td></tr><tr><td>HopW/HopAE</td><td>618</td><td>219</td><td>1125</td><td>1</td><td>0.09</td></tr><tr><td>HopX</td><td>308</td><td>83</td><td>452</td><td>3</td><td>0.66</td></tr><tr><td>HopY</td><td>201</td><td>53</td><td>287</td><td>2</td><td>0.70</td></tr><tr><td>HopZ</td><td>396</td><td>79</td><td>771</td><td>2</td><td>0.26</td></tr><tr><td>HopAA</td><td>752</td><td>218</td><td>578</td><td>0</td><td>0.00</td></tr><tr><td>HopAB/HopAY</td><td>553</td><td>204</td><td>893</td><td>5</td><td>0.56</td></tr><tr><td>HopAD</td><td>30</td><td>12</td><td>675</td><td>5</td><td>0.74</td></tr><tr><td>HopAF</td><td>395</td><td>105</td><td>289</td><td>3</td><td>1.04</td></tr><tr><td>HopAG</td><td>347</td><td>141</td><td>742</td><td>17</td><td>2.29</td></tr><tr><td>HopAH</td><td>899</td><td>317</td><td>479</td><td>1</td><td>0.21</td></tr><tr><td>HopAI</td><td>326</td><td>110</td><td>268</td><td>1</td><td>0.37</td></tr><tr><td>HopAL</td><td>33</td><td>15</td><td>679</td><td>0</td><td>0.00</td></tr><tr><td>HopAM</td><td>54</td><td>15</td><td>281</td><td>3</td><td>1.07</td></tr><tr><td>HopAQ</td><td>26</td><td>8</td><td>98</td><td>2</td><td>2.04</td></tr><tr><td>HopAR</td><td>105</td><td>30</td><td>312</td><td>1</td><td>0.32</td></tr><tr><td>HopAS</td><td>421</td><td>164</td><td>1396</td><td>4</td><td>0.29</td></tr><tr><td>HopAT/HopAV</td><td>604</td><td>223</td><td>1858</td><td>0</td><td>0.00</td></tr><tr><td>HopAU</td><td>243</td><td>58</td><td>815</td><td>0</td><td>0.00</td></tr><tr><td>HopAW</td><td>117</td><td>18</td><td>266</td><td>1</td><td>0.38</td></tr><tr><td>HopAX</td><td>63</td><td>33</td><td>448</td><td>0</td><td>0.00</td></tr><tr><td>HopAZ</td><td>283</td><td>98</td><td>340</td><td>1</td><td>0.29</td></tr><tr><td>HopBA</td><td>43</td><td>16</td><td>239</td><td>0</td><td>0.00</td></tr><tr><td>HopBC</td><td>26</td><td>9</td><td>254</td><td>2</td><td>0.79</td></tr><tr><td>HopBD</td><td>141</td><td>50</td><td>304</td><td>3</td><td>0.99</td></tr><tr><td>HopBE</td><td>11</td><td>6</td><td>633</td><td>0</td><td>0.00</td></tr></tbody></table>

(Continued)

<table><caption>**TABLE 3** | Continued</caption><thead><tr><th>Family</th><th>Total Number of Alleles</th><th>Number of Unique Alleles<sup>1</sup></th><th>Alignment Length (Codons)</th><th>Positively Selected Sites (N)</th><th>Positively Selected Sites (%)</th></tr></thead><tbody><tr><td>HopBF</td><td>104</td><td>25</td><td>252</td><td>0</td><td>0.00</td></tr><tr><td>HopBG</td><td>13</td><td>5</td><td>134</td><td>0</td><td>0.00</td></tr><tr><td>HopBH</td><td>84</td><td>26</td><td>427</td><td>1</td><td>0.23</td></tr><tr><td>HopBI</td><td>106</td><td>31</td><td>452</td><td>2</td><td>0.44</td></tr><tr><td>HopBJ</td><td>8</td><td>6</td><td>260</td><td>0</td><td>0.00</td></tr><tr><td>HopBK</td><td>75</td><td>32</td><td>89</td><td>1</td><td>1.12</td></tr><tr><td>HopBL</td><td>94</td><td>50</td><td>819</td><td>0</td><td>0.00</td></tr><tr><td>HopBM</td><td>40</td><td>10</td><td>157</td><td>0</td><td>0.00</td></tr><tr><td>HopBN</td><td>80</td><td>20</td><td>301</td><td>1</td><td>0.33</td></tr><tr><td>HopBO/HopX</td><td>93</td><td>32</td><td>355</td><td>1</td><td>0.28</td></tr><tr><td>HopBP/HopZ</td><td>83</td><td>31</td><td>411</td><td>5</td><td>1.22</td></tr><tr><td>HopBQ/HopH</td><td>20</td><td>3</td><td>215</td><td>0</td><td>0.00</td></tr><tr><td>HopBR/HopBN</td><td>5</td><td>1</td><td>133</td><td>0</td><td>0.00</td></tr><tr><td>HopBS/HopAV</td><td>3</td><td>1</td><td>52</td><td>0</td><td>0.00</td></tr><tr><td>HopBT/HopAB</td><td>1</td><td>1</td><td>194</td><td>0</td><td>0.00</td></tr><tr><td>HopBU/HopAB</td><td>1</td><td>1</td><td>190</td><td>0</td><td>0.00</td></tr><tr><td>HopBV/HopAJ</td><td>1</td><td>1</td><td>677</td><td>0</td><td>0.00</td></tr><tr><td>HopBW/HopBH</td><td>1</td><td>1</td><td>171</td><td>0</td><td>0.00</td></tr><tr><td>HopBX/HopL</td><td>1</td><td>1</td><td>182</td><td>0</td><td>0.00</td></tr></tbody></table>

¹Unique DNA sequences.

substantial unexplained variance in these correlations, resulting in some T3SE families that have high evolutionary rates and low levels of gain and loss, and other T3SE families that have low evolutionary rates and high levels of gain and loss. These families tended to be the same for all correlations.

DISCUSSION

Bacterial T3SEs are primary virulence factors in a wide-range of plant and animal pathogens (Hueck, 1998; Desveaux et al., 2006; Zhou and Chai, 2008; Block and Alfano, 2011; Buttner, 2016; Khan et al., 2016; Hu et al., 2017; Khan et al., 2018; Xin et al., 2018). T3SEs are particularly interesting from an evolutionary perspective due to their dual and diametrically opposed roles in host-pathogen interactions. While T3SEs have evolved in order to promote bacterial fitness, usually via the suppression of host immunity or disruption of host cellular homeostasis, hosts have evolved mechanisms to recognize the presence or activity of T3SEs, and this recognition often elicits an immune response that shifts the interaction back into the host's favor. To explore the distribution and evolutionary history of *P. syringae* T3SEs and gain insight into their role in host specificity, we cataloged the T3SE repertoires of a large and diverse collection of 494 *P. syringae* isolates. These phylogenetically diverse strains allowed us to generate an expanded database of more than 14,000 putative T3SE alleles and investigate the evolutionary mechanisms through which these important molecules have enabled *P. syringae* to become one of the most globally important bacterial plant pathogens (Mansfield et al., 2012).
<figure><img src="image_54.png" /></figure>

**FIGURE 6** | Relationship between the average pairwise non-synonymous substitution rate (Ka) (A) and the average pairwise synonymous substitution rate (Ks) (B) for each effector family with the average core genome non-synonymous and synonymous substitution rates of the corresponding *P. syringae* strains. Pairwise substitution rates for all sequences within a family were estimated by reverse translating the effector family and concatenated core genome amino acid alignments, then calculating pairwise substitution rates in MEGA7 with the Nei-Gojobori Method. Each point on the scatter plot represents the average of these pairwise rates for a single family and the red dotted lines represent the null-hypothesis that the substitution rates in the effector family will be the same as the substitution rates of the core genes in the same collection of genomes.

## Expanded Database of Type III Secreted Effectors in *P. syringae*

This study increases the number of confirmed and putative T3SE alleles available in the *P. syringae* Genome Resources Database by 20-fold, resulting in a final database of 14,613 T3SE alleles from the *P. syringae* species complex, 5,127 of which are unique at the nucleotide level. Although these new, putative T3SEs all share an ancestral sequence with known T3SE families, we did not confirm expression or translocation of any of these T3SEs, so some of these coding regions may represent recently pseudogenized effectors. However, the extensive diversification that has occurred within many of these families clearly indicates that some level of functional diversification has occurred.

Consistent with our earlier analysis, we find that primary phylogroup strains harbor considerably larger repertoires of T3SEs than secondary phylogroup strains (Baltrus et al., 2011; O'Brien et al., 2011; Dudnik and Dudler, 2014; Dillon et al., 2019). We also find that a small number of primary phylogroup strains have significantly smaller effector repertoires; including phylogroup 10 strains, which were primarily isolated from non-agricultural sources similar to most secondary phylogroup strains, and the phylogroup 2 strain Psy642, which has previously been highlighted as an outlier in its T3SE content and has been characterized as non-pathogenic (Clarke et al., 2010; O'Brien et al., 2011). In general, phylogroup 2 strains have somewhat smaller T3SE repertoires and employ a greater number of phytotoxins relative to other primary phylogroup strains (Baltrus et al., 2011; O'Brien et al., 2011; Dillon et al., 2019). This may indicate that phylogroup 2 strains have evolved a different host-microbe lifestyle than other *P. syringae* primary phylogroup strains, e.g., one tending toward low virulence, epiphytic interactions, rather than high virulence, invasive pathogenesis (Hirano and Upper, 2000).

Among the 70 T3SE families that were delimited in this study, seven of the newly assigned families had fewer than five total members (HopBR/HopBN, HopBS/HopAV, HopBT/HopAB, HopBU/HopAB, HopBV/HopAJ, HopBW/HopBH, HopBX/HopL). These families all consist of alleles that were separated from a larger T3SE family during the delimitation stage of our analysis because they shared only very limited regions of local similarity with the larger family. The small size of these families suggests that they may be pseudogenes degenerating due to a lack of selective constraints. The 63 remaining families are similar to the ~60 families that have been discussed in earlier studies (Baltrus et al., 2011; Lindeberg et al., 2012). While we do merge seven families based on our delimitation analysis, seven new families have been discovered in the past 5 years (McCann et al., 2013; Hockett et al., 2014; Lam et al., 2014; Matas et al., 2014; Mucyn et al., 2014). Furthermore, our objective delimitation analysis separated HopX2 from HopX, HopZ3 from HopZ, and HopH3 from HopH, forming the HopBO/HopX, HopBP/HopZ, and HopBQ/HopH families, respectively. Despite these differences, we arrive at several similar conclusions to prior work on the distribution of individual T3SEs across *P. syringae* strains. Specifically, we find that few T3SE families are considered part of the core genome (Baltrus et al., 2011; O'Brien et al., 2011; Lindeberg et al., 2012), with only AvrE, HopB/HopAC, HopM, and HopAA being present in more than 95% of strains. Three of these families (AvrE, HopM, and HopAA) are part of the CEL, while the other CEL effector, HopN, is only present in 14.98% of *P. syringae* strains, all from phylogroup 2. This suggests that HopN arose in the CEL after the divergence of this phylogroup. Other families that have previously been characterized as core T3SEs in *P. syringae* include HopI and HopAH (Baltrus et al., 2011), which are only present in 79.76 and 89.07% of strains from our study, respectively. Neither HopB
<figure><img src="image_55.png" /><figcaption>**FIGURE 7** | Expected number of gene gain and gene loss events for each T3SE family. The posterior expectation for gain and loss events was estimated for each family on each branch of the *P. syringae* core-genome tree using GLOOME with the stochastic mapping approach. The sum of these posterior expectations across all branches yields the total expected number of events for each family. Short form family names are used for merged or separated families.</figcaption></figure>

or HopAC has been highlighted as a core T3SE in prior studies, but the HopB/HopAC family in this study was one of the largest and most broadly distributed T3SE families. Although HopB and HopAC do vary substantially in length and occur in different genomic contexts, they typically share reciprocal BLASTP hits across more than 80% of the HopB sequence with *E*-values less than 1e-24, indicating shared ancestry. The remainder of T3SE families have a considerably sparser distribution across the *P. syringae* species complex, ranging in frequency from 1.62% to 80.97%. This demonstrates that different T3SE families were likely acquired episodically throughout the evolutionary history of the *P. syringae* species complex and are subject to strong evolutionary pressures for gain and loss due to the widespread and diverse ETI surveillance system of plants (Cunnac et al., 2009; Xin et al., 2018).

Finally, we find that highly divergent combinations of T3SEs can enable *P. syringae* to infect the same host (Supplementary Figure S6). While this observation is consistent with prior studies in *P. syringae* (Baltrus et al., 2011; Lindeberg et al., 2012; O'Brien et al., 2012), it is in contrast to the convergence in T3SE repertoires that has been observed in *Xanthomonas*, another phytopathogen that employs a T3SS (Hajri et al., 2009). Importantly, this limits our ability to detect and differentiate *P. syringae* pathogens of different hosts using this fairly crude application of comparative genomics. The lack of correlation between T3SE repertoires and host specificity may be a direct result of the fact that there is substantial functional redundancy among *P. syringae* T3SEs from different families, or that certain T3SEs in combination can mask the detection of other T3SEs in a given *P. syringae* background (Cunnac et al., 2009; Cunnac et al., 2011; Lindeberg et al., 2012; Wei et al., 2018). However, it will be important moving forward to assess the true host range of a broader collection of *P. syringae* strains in order to determine whether specific T3SEs promote or suppress growth on particular hosts.

## Genetic and Functional Evolution of *P. syringae* Type III Secreted Effectors

Given the broad array of unique T3SEs that exist within the *P. syringae* species complex, mining this untapped diversity is likely to reveal a number of new functions and interactions for T3SEs in *P. syringae*. By quantifying *Ka*, *Ks*, and *Ka/Ks* for each pair of T3SE alleles in each family, we identified substantial genetic diversity in most T3SE families (Figure 5). Our codon-level analysis of positive selection also revealed that T3SE families were substantially more likely than non-T3SE families to contain positively selected sites (Table 3). Finally, we confirmed that this divergence is not simply a reflection of the immense diversity exhibited by the strains used in this study, since the divergence observed for T3SE families is consistently higher than the divergence observed across core genes (Supplementary Figures S7, S8). Elevated non-synonymous substitution rates in T3SE families implies that there may be elevated positive selection operating on these families, while elevated synonymous substitution rates show that this
elevated positive selection may extend to synonymous sites, that many T3SEs arose prior to the last common ancestor (LCA) of the *P. syringae* species complex, and/or that T3SEs undergo considerably higher rates of HGT than core genes. However, it is difficult to pinpoint the timing and strength of positive selection on T3SEs because of the confounding effects of variable rates of recombination and horizontal transfer throughout their evolutionary history.

Fast-evolving T3SEs will also provide numerous opportunities for studying Red Queen dynamics (Van Valen, 1973). Under Fluctuating Red Queen (FRQ) dynamics, fluctuating selection drives oscillations in allele frequencies at the focal genetic loci in both the pathogen and the host, resulting in rapid evolutionary change on both sides (Brockhurst et al., 2014). In the case of *P. syringae* and their plant hosts, bacterial T3SEs are the key players on the pathogen side, and plant resistance genes are the key players on the host side. These FRQ dynamics are expected to maintain high levels of within-population genetic diversity at focal loci, as we've observed in many T3SE families. The majority of T3SE families in *P. syringae* are highly divergent and display strong signatures of positive selection, likely in response to intense host-imposed selection to evade recognition (Rohmer et al., 2004; Baltrus et al., 2011; Lindeberg et al., 2012). This implies that few T3SEs are broadly unrecognized, making interactions between individual T3SEs and the corresponding plant resistance genes an excellent resource for exploring FRQ dynamics.

The highly dynamic nature of T3SE evolution is also seen in our analysis of T3SE gain and loss across the *P. syringae* phylogenetic tree. More than five gene gain events are estimated to have occurred in 52 out of the 70 T3SE families analyzed in this study, with a maximum of 41 HGT events estimated in the HopZ family. Gene loss events were even more common, with 57 out of 70 T3SE families experiencing more than five loss events and a maximum of 53 events in the HopAZ family. Earlier studies have also suggested that both gene gain and loss were quite common among T3SE families. One specific study using nucleotide composition and phylogenetics found that members from 11 out of 24 tested *P. syringae* T3SE families were recently acquired by HGT (Rohmer et al., 2004). These families included AvrA, AvrB, AvrD, AvrRpm, HopG, HopQ, HopX, HopZ, HopAB, HopAF, and HopAM (although AvrD is not a T3SE Leach and White, 1996; Mucyn et al., 2014). The T3SEs from this dataset were also highlighted by this study as undergoing considerably higher rates of gene gain and loss within the *P. syringae* species complex. Specifically, all of these T3SEs were demonstrated to have undergone at least ten gene gain events and many were among the most dynamic T3SEs in our dataset. Other studies have shown that many T3SEs are present on mobile genetic elements and that T3SEs from the same family are often found at different genomic locations (Kim and Alfano, 2002; Charity et al., 2003; Lovell et al., 2009, 2011; Godfrey et al., 2011; Neale et al., 2016), which may both promote and be a consequence of the high rates of gene gain and loss for particular T3SE families. From a selective perspective, it is also likely that host immune recognition can drive selection

for gene gain or loss (Vinatzer et al., 2006), while the functional redundancy of different T3SE families carried in the same genetic background may limit the negative impacts of the loss of such T3SEs (Kvitko et al., 2009; Cunnac et al., 2011; Wei et al., 2018). Finally, as has been previously reported (Baltrus et al., 2011), we find that there is a significant positive correlation between rates of evolution and rates of gene gain and loss (Supplementary Figure S10), suggesting that similar evolutionary forces that cause the diversification of T3SEs are contributing to the loss and gain of T3SEs. However, not all T3SEs fit this model which could reflect that T3SEs vary in their mutational robustness and/or that the genomic context of different T3SEs makes them more or less prone to HGT. In any event, the extensive gene gain and loss that occurs in the majority of T3SE families lends further support to the hypothesis that few T3SE alleles are broadly unrecognized (Baltrus et al., 2011).

Given the highly dynamic nature of T3SE evolution, we predict that there are still numerous T3SEs that will be found to elicit ETI. Most research on ETI elicitation to date has focused on a small number of T3SE families, and an even smaller number of alleles from each family (Mansfield, 2009). The immense diversification that we observe in many T3SE families points to strong selective pressures that may be explained by as-yet discovered ETI responses. If this prediction holds true, it will be particularly interesting to study T3SE families with alleles that induce different ETI responses in the same host. These patterns will help reveal how strains shift onto new hosts or break immunity in an existing host, perhaps explaining the evolutionary driving force behind new disease outbreaks.

## AUTHOR CONTRIBUTIONS

MD, DD, and DG designed the research. MD, BL, AM, and BW performed the experiments. MD and RA analyzed the data. MD and DG wrote the manuscript.

## FUNDING

This work was supported by Natural Sciences and Engineering Research Council of Canada Discovery grants (DG and DD), Canada Research Chairs in Comparative Genomics (DG) and Plant-Microbe Systems Biology (DD), and the Center for the Analysis of Genome Evolution and Function (DG and DD).

## ACKNOWLEDGMENTS

We thank all members of the Guttman and Desveaux labs for helpful discussion and valuable input on this project.

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2019.00418/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.

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# Fitness Features Involved in the Biocontrol Interaction of *Pseudomonas chlororaphis* With Host Plants: The Case Study of PcPCL1606

Eva Arrebola¹,², Sandra Tienda¹,², Carmen Vida¹,², Antonio de Vicente¹,² and Francisco M. Cazorla¹,²*

¹Departamento de Microbiología, Facultad de Ciencias, Universidad de Málaga, Málaga, Spain, ²Instituto de Hortofruticultura Subtropical y Mediterránea "La Mayora" IHSM, UMA-CSIC, Málaga, Spain

## OPEN ACCESS

**Edited by:**
Marco Scortichini,
Council for Agricultural and
Economics Research, Italy

**Reviewed by:**
Vittoria Catara,
Università degli Studi di Catania, Italy
Anastasia L. Lagopodi,
Aristotle University of Thessaloniki,
Greece
Monika Maurhofer,
ETH Zürich, Switzerland

*Correspondence:
Francisco M. Cazorla
cazorla@uma.es

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

Received: 26 November 2018

Accepted: 21 March 2019

Published: 10 April 2019

**Citation:**
Arrebola E, Tienda S, Vida C, de Vicente A and Cazorla FM (2019) Fitness Features Involved in the Biocontrol Interaction of Pseudomonas chlororaphis With Host Plants: The Case Study of PcPCL1606. *Front. Microbiol.* 10:719. doi: 10.3389/fmicb.2019.00719

The goal of this mini review is to summarize the relevant contribution of some beneficial traits to the behavior of the species *Pseudomonas chlororaphis*, and using that information, to give a practical point of view using the model biocontrol strain *P. chlororaphis* PCL1606 (PcPCL1606). Among the group of plant-beneficial rhizobacteria, *P. chlororaphis* has emerged as a plant- and soil-related bacterium that is mainly known because of its biological control of phytopathogenic fungi. Many traits have been reported to be crucial during the multitrophic interaction involving the plant, the fungal pathogen and the soil environment. To explore the different biocontrol-related traits, the biocontrol rhizobacterium PcPCL1606 has been used as a model in recent studies. This bacterium is antagonistic to many phytopathogenic fungi and displays effective biocontrol against fungal phytopathogens. Antagonistic and biocontrol activities are directly related to the production of the compound 2-hexyl, 5-propyl resorcinol (HPR), despite the production of other antifungal compounds. Furthermore, PcPCL1606 has displayed additional traits regarding its fitness in soil and plant root environments such as soil survival, efficient plant root colonization, cell-to-cell interaction or promotion of plant growth.

**Keywords:** *Pseudomonas chlororaphis*, root colonization, biocontrol, avocado, antifungals

## INTRODUCTION

Since the earliest studies, soil has been described as an infinite source of microorganisms with beneficial activities that promote plant health (Waksman and Woodruff, 1940). Inside the soil, the rhizosphere environment is considered the soil-plant root interphase where potentially beneficial rhizobacteria are established. The plant-beneficial microbial life can be actively recruited by the plant rhizosphere (Berendsen et al., 2018) and can finally result in the biological control of the disease (Babalola, 2010). These biocontrol rhizobacteria can use a wide range of mechanisms involved in the suppression of plant pathogens. A diverse range of bacterial genera, such as *Bacillus*, *Pseudomonas*, *Serratia*, *Stenotrophomonas*, and *Streptomyces*, has been commonly described as
beneficial rhizobacteria (Berg, 2009). Among them, representatives of the *Pseudomonas* genus have been commonly associated with the rhizosphere and soil habitats (Lugtenberg and Dekkers, 1999). This bacterial genus has also been widely studied due to its ability to produce antifungal compounds, compete for niche and/or nutrients on the rhizosphere, and elicit induced systemic resistance in plants (Haas and Défago, 2005). Currently, many strains belonging to the group of fluorescent *Pseudomonas* are known to enhance plant growth promotion and reduce the severity of various diseases (Ganeshan and Kumar, 2005; Mercado-Blanco and Bakker, 2007; Weller, 2007).

The *Pseudomonas fluorescens* complex is one of the most diverse bacterial groups within the *Pseudomonas* genus and comprises more than fifty validly named species and many unclassified isolates (Garrido-Sanz et al., 2017). Many strains of this complex have been isolated from plant-related environments, and several species can be considered beneficial since many are described as plant growth-promoting rhizobacteria and/or minimize the effects of phytopathogens (PGPR; Kang et al., 2006; Raaijmakers et al., 2009). The beneficial effects displayed by some bacteria result from the expression of multiple activities that act directly and indirectly inhibiting pathogen activities and promoting plant health (McSpadden, 2007). To date, a number of studies have characterized the environmental factors that affect the abundance of different pseudomonad populations below ground (Berg et al., 2002; Ownley et al., 2003; Mazzola et al., 2004; Bergsma-Vlami et al., 2005). *Pseudomonas* species most commonly reported to include plant beneficial rhizospheric strains are *Pseudomonas aureofaciens*, *Pseudomonas brassicacearum*, *Pseudomonas chlororaphis*, *P. fluorescens*, *Pseudomonas Protegens*, and *Pseudomonas putida*.

## BENEFICIAL TRAITS OF RHIZOSPHERIC *Pseudomonas chlororaphis* STRAINS

Among the beneficial *Pseudomonas* spp., *P. chlororaphis* has evolved to be a common inhabitant of the root environment of many plants. Moreover, it has been extensively reported the role of specific traits that render this bacterium able to be used as an inoculant for biofertilization, phytostimulation, and biocontrol purposes (Bloemberg and Lugtenberg, 2001).

### Subspecies of *Pseudomonas chlororaphis*

*Pseudomonas chlororaphis*, *P. aureofaciens*, and *Pseudomonas aurantiaca* were initially included in the Approved List of Bacterial Names (Skerman et al., 1980) and considered separate species in the first edition of Bergey's Manual of Systematic Bacteriology by Palleroni (1984). However, the results obtained by Peix et al. (2007) of fatty acid analysis, phenotypic characterization, 16S rRNA gene sequencing, and DNA-DNA relatedness together with the results obtained by Hilario et al. (2004) on the phylogenetic analysis of several housekeeping genes, support the reclassification of *P. aurantiaca* as a later heterotypic synonym of *P. chlororaphis*. The results

published by Peix et al. (2007) also reveal that strains of *P. aurantiaca*, *P. aureofaciens*, and *P. chlororaphis* form three clearly distinguishable groups within *P. chlororaphis* that merit the status of subspecies. Therefore, the current classification is *P. chlororaphis* subsp. *chlororaphis* subsp. nov., *P. chlororaphis* subsp. *aureofaciens* subsp nov., comb. nov. and *P. chlororaphis* subsp. *aurantiaca* subsp. nov., comb. nov. (Peix et al., 2007). Three years later, Burr et al. (2010) added a new subspecies to *P. chlororaphis* and placed it on a distinct branch within this species with the name *P. chlororaphis* subsp. *piscium* subsp. nov. The current reports of sequenced bacterial genomes of *P. chlororaphis* strains (Calderón et al., 2015; Deng et al., 2015; Town et al., 2016; Moreno-Avitia et al., 2017; Biessy et al., 2019) will help to refine the current classification of the *P. chlororaphis* group.

### Main Traits Involved in Biocontrol by *P. chlororaphis*

These aerobic, Gram-negative bacteria are associated with soil and plant roots (González-Sánchez et al., 2010; Calderón et al., 2015; Vida et al., 2017a). Typically, this species possesses plant-colonizing and antagonistic activities against soil-borne plant pathogens. Products from secondary metabolism usually mediate antagonism, and can be regulated by the GacS-GacA two component regulatory system. GacS-GacA system governs a complex signal transduction pathway, involving regulatory RNAs and translational repression (Yan et al., 2018; Jahanshah et al., 2019). Simultaneously, Quorum Sensing (QS) is a regulatory systems which is involved in the general biology performance of *P. chlororaphis*, including biofilm formation, antifungal production or exoenzyme secretion. QS is a mechanism of intercellular signaling that makes the bacterial population to act co-ordinately, based in the secretion of diffusible signal molecules (mainly acyl homoserine lactones, or AHL; Venturi, 2006). The use of OMICS and functional studies have revealed a more complex scenario, where the presence of several QS systems can coexist inside the same bacterial cell (Morohoshi et al., 2017), but also the participation of secondary metabolites (such as the antifungals phenazines and/or the resorcinol-related compounds) in final QS regulation (Selin et al., 2010; Brameyer et al., 2015).

Recent reports using OMICS techniques, have allowed a more comprehensive understanding of the potential weaponry that *P. chlororaphis* group could uses to interact with the root plant. For example, presence of different antimicrobial and insecticidal compounds, cyclic peptides, siderophores, bacteriocins, molecules involved in beneficial plant-bacteria interactions, secretions systems, antibacterial proteins, etc., (Loper et al., 2012; Chen et al., 2015; Biessy et al., 2019). Below, the most relevant are summarized (Table 1).

Phenazines are among the most copious secondary metabolites produced by fluorescent pseudomonads, and phenazine-producing microorganisms represent a ubiquitous group of antibiotic-producing bacteria in the environment (Chin-A-Woeng et al., 2000; Mavrodi et al., 2013). Phenazine
<table><caption>TABLE 1 | Summary of main compounds produced by *Pseudomonas chlororaphis* subspecies with beneficial effects in plant pathogen control.</caption><thead><tr><th>Compound</th><th>Target/beneficial effect</th><th>Subspecies<sup>1</sup></th><th>Reference strain</th><th>References</th></tr></thead><tbody><tr><td colspan="5"><strong>Antibiotics</strong></td></tr><tr><td>Phenazine 1-carboxamide</td><td>Antifungal redox-active antibiotic</td><td>Pa, Pe, Pc, Pp</td><td>PCL1391</td><td>Hernández et al., 2004</td></tr><tr><td>Phenazine 1-carboxylic acid</td><td>Antifungal redox-active antibiotic</td><td>Pc, Pp</td><td>PCL1391</td><td>Chin-A-Woeng et al., 1998</td></tr><tr><td>2-hydroxy phenazine<br>1-carboxylic acid</td><td>Fungistatic and bacteriostatic</td><td>Pa, Pe, Pc</td><td>GP72</td><td>Liu et al., 2016</td></tr><tr><td>Pyrrolnitrin</td><td>Antifungal compound</td><td>Pa, Pe, Pc</td><td>PA23</td><td>Nandi et al., 2015</td></tr><tr><td>2-hexyl, 5-propylresorcinol</td><td>Antifungal compound and signal<br>molecule</td><td>Pa, Pe, Pc</td><td>PCL1606</td><td>Cazorla et al., 2006</td></tr><tr><td>2,4-Diacetylphloroglucinol</td><td>Membrane damage, distribution of<br>mitochondria electron transport chain<br>and inhibition of V-ATPase activity.<br>Antifungal</td><td>Pc</td><td>UFB2</td><td>Deng et al., 2015</td></tr><tr><td>Rhizoxin</td><td>Antifungal</td><td>Pc</td><td>MA 342</td><td>Loper et al., 2008</td></tr><tr><td colspan="5"><strong>Insecticidal compounds</strong></td></tr><tr><td>Cyclic peptides</td><td>Insecticidal, surfactant and antagonistic<br>activity</td><td>Pc</td><td>PCL1391</td><td>Flury et al., 2017</td></tr><tr><td>Fit toxin</td><td>Insecticidal activity</td><td>Pc, Pe, Pp</td><td>PCL1606</td><td>Flury et al., 2016</td></tr><tr><td colspan="5"><strong>Siderophores</strong></td></tr><tr><td>Pyoverdine</td><td>Fe chelation and competition</td><td>Pa, Pe, Pc</td><td>D-TR133</td><td>Barelmann et al., 2003</td></tr><tr><td>Achromobactine</td><td>Fe chelation and competition</td><td>Pa, Pe, Pc</td><td>PCL1606</td><td>Calderón et al., 2015</td></tr><tr><td>Hemophore</td><td>Fe chelation</td><td>Pp</td><td>PCL1607</td><td>Biessy et al., 2019</td></tr><tr><td colspan="5"><strong>Enzymes and hormones</strong></td></tr><tr><td>Chitinase</td><td>Chitin hydrolysis enzyme and antifungal</td><td>Pc, Pe, Pp</td><td>PCL1391</td><td>Flury et al., 2016</td></tr><tr><td>Protease</td><td>Protein hydrolysis enzyme and<br>antifungal</td><td>Pa</td><td>M71</td><td>Raio et al., 2017</td></tr><tr><td>Phosphatase</td><td>Phosphorus solubilization enzyme</td><td>Pc</td><td>SZY6</td><td>Ahemad, 2015</td></tr><tr><td>ACC deaminase</td><td>Plant growth promotion</td><td>Pa, Pe, Pc, Pp</td><td>6G5</td><td>Glick, 2014</td></tr><tr><td>PQQ</td><td>Plant growth promotion</td><td>Pa, Pe, Pc</td><td>B23</td><td>Nishiyama et al., 1991</td></tr><tr><td>IAA</td><td>Plant growth promotion</td><td>Pa, Pe, Pc</td><td>O6</td><td>Kang et al., 2006</td></tr><tr><td colspan="5"><strong>Volatile</strong></td></tr><tr><td>2,3 butanediol</td><td>Elicite plant resistance</td><td>Pa, Pe, Pc</td><td>O6</td><td>Han et al., 2006</td></tr><tr><td>Hydrogen cyanide</td><td>Metalloenzymes inhibitor and antifungal</td><td>Pa, Pc, Pe, Pp</td><td>PA23</td><td>Nandi et al., 2015</td></tr><tr><td colspan="5"><strong>Hormones</strong></td></tr><tr><td>Indol acetic acid</td><td>Plant growth promotion</td><td>Pa, Pc, Pe, Pp</td><td>O6</td><td>Kang et al., 2006</td></tr></tbody></table>

Reference strains published are included. <sup>1</sup>Pa: *P. chlororaphis* subsp. aurantiaca; Pe: *P. chlororaphis* subsp. aureofaciens; Pc: *P. chlororaphis* subsp. chlororaphis; Pp: *P. chlororaphis* subsp. Piscium.

compounds are redox-active nitrogen-containing heterocyclic molecules and its beneficial role on plant biology is not limited to antibiosis against phytopathogenic microbes (Pierson and Pierson, 2010; Biessy and Filion, 2018; Biessy et al., 2019). Additional effects have been shown for this compound such as triggering induced systemic resistance in plants, reducing the expression of key pathogenicity-related genes of the phytopathogen, or its involvement in the root persistence (Biessy and Filion, 2018). In relation to the bacterial interaction with the plant root, phenazines can be crucial for biofilm formation (Selin et al., 2010). An extensive colonization of the rhizosphere is a prerequisite in efficient disease suppression by preventing pathogen form access to the root (Lugtenberg and Kamilova, 2009). The involvement of phenazines on root colonization has been strengthened because some phenazine compounds could be terminal signaling factors in the QS network of some bacteria, and are directly involved

in biofilm formation on biotic surfaces (Dietrich et al., 2006; Selin et al., 2012).

Pyrrolnitrin and the volatile compound hydrogen cyanide, are also among the additional antifungal compounds typically produced by *P. chlororaphis* strains. Pyrrolnitrin is considered a key compound for fungal biocontrol (Hill et al., 1994) and is becoming even more relevant than phenazines extending its action to eukaryotic organisms (Nandi et al., 2015; Huang et al., 2018). The same observation can be applied to the volatile compound hydrogen cyanide, which also has a broad spectrum of prokaryotic and eukaryotic targets (Nandi et al., 2017; Kang et al., 2018). The biological importance of this broad spectrum of both active compounds would be related to its typical environmental persistence, for example, allowing them to escape from predation (Nandi et al., 2017). Related to the insecticidal activity of this bacterial species, the most studied virulence factor against insects is the Fit toxin,
which is similar to Mcf1 of the entomopathogenic bacterium *Potorhabdus luminescens* (Ruffner et al., 2015). Fit mutants of *P. chlororaphis* PCL1391 further showed reduced virulence, and the residual toxicity could be assigned to the wide range of other antimicrobial compounds produced by *P. chlororaphis* (previously listed) or cyclic lipopetides (Flury et al., 2017).

About Clps, these compounds can be involved in many biological functions, such as motility, biofilm formation, protection against predators and antagonism (De Souza et al., 2003; Raaijmakers et al., 2010). Clps produced by plants-beneficial bacteria were found to induce plant resistance and to contribute to plant protection against root pathogenic fungi (Olorunleke et al., 2015). But interestingly, Clps were demonstrated to be further insect pathogenicity factor in *P. chlororaphis* strains (Flury et al., 2016, 2017).

The production of exoenzymes has also been described to have a role in biocontrol activity (Haran et al., 1996). Enzymes such as chitinases, lipases or proteases have a broad distribution among the soil bacterial community and are probably related to general metabolism, but also inhibit the pathogen (degrading some cell structures) and stimulate plant growth by providing additional resources from the degradative activity (Vida et al., 2017a). Remarkably, *P. chlororaphis* strains can produce 1-aminocyclopropane-1-carboxylate (ACC) deaminase (Nadeem et al., 2007), which is an enzyme produced by plant-associated bacteria that decrease the ethylene levels and protect the plant from its effect, which results in a general beneficial activity (Glick, 2014). In addition, the production of the biofertilizer hormone indole-3-acetic acid (IAA) has also been reported for *P. chlororaphis* strains (Dimkpa et al., 2012), and its production is important in microbe-microbe and microbe-plant signaling, and can also results in an promotion of plant growth (Kang et al., 2006).

Other compounds can also have an important role for *P. chlororaphis*, such as the production of siderophores, which can be considered as a general beneficial activity, at least, for all the soil-related *Pseudomonas* spp. (Zhang and Rainey, 2013). These molecules are secondary metabolites involved in iron quelation. The most known is pyoverdine, a water-soluble fluorescent pigment produced by fluorescent *Pseudomonas* species (Barelmann et al., 2003). However, the recent comparative genomic studies of *P. chlororaphis* genomes, revealed the putative presence of various secondary siderophores, such as achromobactine and hemophore (Biessy et al., 2019).

# THE BENEFICIAL RHIZOBACTERIUM *Pseudomonas chlororaphis* PCL1606 (PcPCL1606) AS A MODEL

In order to find potential bacterial biocontrol agents against the avocado white root rot caused by *Rosellinia necatrix*, a collection of bacterial isolates belonging to the genera *Bacillus* and *Pseudomonas* were isolated from avocado rhizosphere (Cazorla et al., 2006, 2007; Pliego et al., 2011). Interestingly, a number of *P. chlororaphis* were consistently isolated from avocado roots (Cazorla et al., 2006). The management of this crop

could enhance this presence on avocado roots of *P. chlororaphis* isolates, since it has been reported that application of organic amendments can enhance the presence of specific groups of beneficial microbes, including antagonistic *P. chlororaphis* (Vida et al., 2016).

# PcPCL1606 as a Biological Control Agent

Nearly all the *P. chlororaphis* isolated from avocado roots were antagonistic and produced a broad range of antimicrobials including phenazines. Among them, the strain PcPCL1606 do not produce phenazines; otherwise produce proteases, lipases and the antifungal metabolite 2-hexyl 5-propylresorcinol (HPR; **Figure 1**). Another unusual characteristic of this strain is the absence of plant growth promotion in the assayed plant models; however, siderophore production and phosphorous solubilization were detected (among other PGPR-related traits; Vida et al., 2017a). This strain displayed strong antagonism to many phytopathogenic fungi and showed biocontrol of crown and root rot of tomato, caused by *Fusarium oxysporum* f. sp. *radicis-lycopersici* and avocado white root, caused by *R. necatrix* (Cazorla et al., 2006; González-Sánchez et al., 2013). Effectiveness of biocontrol was directly related to the compound HPR (Cazorla et al., 2006; Calderón et al., 2013). HPR production was led by three biosynthetic genes located in a cluster (*darA*, *darB*, and *darC*) followed by two independent regulatory genes (*darS* and *darR*; Nowak-Thompson et al., 2003; Calderón et al., 2013). Further experiments revealed that HPR production was also under transcriptional regulation of the GacS-GacA two-component regulatory system, as previously described for other antifungal antibiotics (Haas and Keel, 2003), and also modulated by different growth parameters such as temperature, pH and the presence of salts in the medium (Calderón et al., 2014a).

# Main Features of PcPCL1606 Involved in Pathogen and Plant Interaction

PcPCL1606 showed strong antifungal activity (Figure 1), and HPR production was the main determinant in the antagonistic and biocontrol phenotypes (Calderón et al., 2013). In addition to HPR, other antifungals can be produced by PcPCL1606, such as pyrrolnitrin (PRN) or hydrogen cyanide (HCN), as well as several exoenzymes such as proteases, chitinases or phosphatases (Vida et al., 2017a). Nevertheless, HPR is more than a powerful compound against pathogenic fungi in the soil and could have additional roles. It has been reported that some alkylresorcinols (to which the compound HPR belongs) can behave as quorum sensing-like signal molecules in the genus *Potorhabdus* (Brameyer et al., 2015), and for this, could have a similar role in HPR-producing *P. chlororaphis* strains. Thus, additional HPR-dependent traits, which are different from antagonism, could have an essential role in the beneficial effects of PcPCL1606 on the plant, such as the root colonization or the biofilm formation (Calderón et al., 2014b, 2019).

Related to the possibility to physically exclude the pathogen from the plant root habitat (Figure 1), biological processes, such as biofilm formation or chemotaxis, are crucial for the PcPCL1606. PcPCL1606 is strongly attracted to the avocado
<figure><img src="image_57.png" /><figcaption>**FIGURE 1** | Current knowledge of the strategies displayed during the multitrophic interactions with plants and fungal pathogens by the model rhizobacterial biocontrol strain PcPCL1606. The main strategies involved in the interaction (yellow circles) included cell-to-cell interaction, beneficial interaction with plants, exclusion, antibiotic production and signal interference. The different strategies can enhance a second one (double-ended blue arrows).</figcaption></figure>

root exudates by chemotactic processes (Polonio et al., 2017). As a result of this attraction, PcPCL1606 efficiently colonizes avocado roots (González-Sánchez et al., 2010) and can be found forming a biofilm on avocado root surfaces, located in the same area where *R. necatrix* can be found during the early stages of infection (Calderón et al., 2014b). Moreover, two bacteriocins (R-tailocins 1 and 2), recently described in PcPCL1606 would contribute to better competition against other rhizosphere-associated bacteria (Dorosky et al., 2017). However, PcPCL1606 bacterial cells also displayed a direct chemotaxis to fungal exudates and finally showed a direct contact with the fungal hyphae of *R. necatrix*. This cell-to-cell contact causes an increase in stress symptoms on the hyphae, among others, by the direct release of antifungal substances, which lead to an accelerated ageing process in the hyphae and hyphal death (Calderón et al., 2014b; Moore-Landecker, 1996). Moreover, the root colonization ability and biofilm

formation of the wild-type strain was also related to HPR production, and the absence of HPR resulted in reduced root colonization levels and no biofilm formation by PcPCL1606 (Calderón et al., 2014b, 2019).

To obtain insight into the features of PcPCL1606, its complete genome sequencing was completed. Phylogenetic studies clustered this strain into the *P. chlororaphis* clade which is placed into the fluorescent *Pseudomonas* complex, however, as previously mentioned, PcPCL1606 it is not a typical *P. chlororaphis* strain (Biessy et al., 2019). Thus, phylogenetic analysis revealed clear differences with the genomes of other biocontrol *P. chlororaphis*, such as PcPCL1601 or PcPCL1607, also isolated from avocado root (Calderón et al., 2015; Vida et al., 2017b; Biessy et al., 2019). Analysis of PcPCL1606 genome confirmed a lack of phenazine biosynthetic genes, cyclic lipopeptides that are related to the surfactant and insecticidal properties, which are typical for *P. chlororaphis*
(Raaijmakers et al., 2006). However, PcPCL1606 exhibits a
complete Fit toxin (fit) cluster (Calderón et al., 2015).

FUTURES PROJECTS AND RESEARCH

The future of *P. chlororaphis* as biocontrol agent is very
promising. *P. chlororaphis* is ubiquitous in the environment,
lacks known toxic or allergenic properties, and has a history
of safe use in agriculture and in food and feed crops.
*P. chlororaphis* is considered non-pathogenic to humans,
wildlife or the environment according to the United States
Environmental Protection Agency (EPA), and commercial
products based on *P. chlororaphis* strains are already available.
For example, Cedomon® (*P. chlororaphis*, BioAgri AB, Sweden),
Spot-Less® (*P. aureofaciens* Tx-1, Turf Science Laboratories,
Carlsbad, United States) or AtEze® (*P. chlororaphis* 63-28, Turf
Science Laboratories, Carlsbad, United States) are based on
*P. chlororaphis* strains, but many other products are already
present in the market based on other *Pseudomonas* spp. These
facts pointed out to a promising future for the use of biocontrol
agents belonging to the specie *P. chlororaphis*.

Regarding the model bacterium PcPCL1606, studies
revealed that PcPCL1606, as well as other *P. chlororaphis*
isolates from avocado roots, displayed high persistence and
reached a population density that was enough to reduce

disease (González-Sánchez et al., 2013). Under commercial
greenhouse conditions, applications of PcPCL1606 cells resulted
in biocontrol against *R. necatrix*. Moreover, some other
*P. chlororaphis* isolates from avocado roots, that have different
beneficial traits (such as phenazine production or plant growth
promotion), could also provide plant protection. These finding
suggest that a promising approach to improve *P. chlororaphis*
based biocontrol would be to develop consortia which combine
strains with complementary traits resulting in more stable or
even enhanced beneficial effects on plants.

AUTHOR CONTRIBUTIONS

EA and FC designed the review content. EA, ST, CV, AV, and
FC wrote the manuscript. All authors read and approved the
final manuscript.

FUNDING

This research was supported by the Spanish Plan Nacional I +
D + I. Grant AGL2017-83368-C2-1-R and partially supported by
the European Union (FEDER). CV and ST were supported by a
grant from FPI, Ministerio de Ciencia e Innovación, Spain.

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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.

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# Xanthomonas citri pv. viticola
Affecting Grapevine in Brazil:
Emergence of a Successful
Monomorphic Pathogen

Marisa A. S. V. Ferreira¹*, Sophie Bonneau², Martial Briand², Sophie Cesbron², Perrine Portier², Armelle Darrasse², Marco A. S. Gama³, Maria Angélica G. Barbosa⁴, Rosa de L. R. Mariano³, Elineide B. Souza³ and Marie-Agnès Jacques²*

¹Departamento de Fitopatologia, Universidade de Brasília, Brasília, Brazil, ²IRHS, INRA, AGROCAMPUS-Ouest, SFR4207 QUASAV, Université d'Angers, Beaucouzé, France, ³Laboratório de Fitobacteriologia, Departamento de Agronomia, Universidade Federal Rural de Pernambuco, Recife, Brazil, ⁴Embrapa Semiarido, Petrolina, Brazil

## OPEN ACCESS

**Edited by:**
Giorgio Gambino,
Institute for Sustainable Plant
Protection, Italian National Research
Council (IPSP-CNR), Italy

**Reviewed by:**
Sang-Wook Han,
Chung-Ang University, South Korea
Fabiano Sillo,
University of Turin, Italy

*Correspondence:
Marisa A. S. V. Ferreira
marisavf@unb.br
Marie-Agnès Jacques
marie-agnes.jacques@inra.fr

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

**Received:** 29 November 2018

**Accepted:** 29 March 2019

**Published:** 18 April 2019

**Citation:**
Ferreira MASV, Bonneau S, Briand M, Cesbron S, Portier P, Darrasse A, Gama MAS, Barbosa MAG, Mariano RdLR, Souza EB and Jacques M-A (2019) *Xanthomonas citri pv. viticola Affecting Grapevine in Brazil: Emergence of a Successful Monomorphic Pathogen*. *Front. Plant Sci.* 10:489. doi: 10.3389/fpls.2019.00489

The pathovar *viticola* of *Xanthomonas citri* causes bacterial canker of grapevine. This disease was first recorded in India in 1972, and later in Brazil in 1998, where its distribution is currently restricted to the northeastern region. A multilocus sequence analysis (MLSA) based on seven housekeeping genes and a multilocus variable number of tandem repeat analysis (MLVA) with eight loci were performed in order to assess the genetic relatedness among strains from India and Brazil. Strains isolated in India from three related pathovars affecting Vitaceae species and pathogenic strains isolated from *Amaranthus* sp. found in bacterial canker-infected vineyards in Brazil were also included. MLSA revealed lack of diversity in all seven genes and grouped grapevine and *Amaranthus* strains in a monophyletic group in *X. citri*. The VNTR (variable number of tandem repeat) typing scheme conducted on 107 strains detected 101 haplotypes. The total number of alleles per locus ranged from 5 to 12. A minimum spanning tree (MST) showed that Brazilian strains were clearly separated from Indian strains, which showed unique alleles at three loci. The two strains isolated from symptomatic *Amaranthus* sp. presented unique alleles at two loci. STRUCTURE analyses revealed three groups congruent with MST and a fourth group with strains from India and Brazil. Admixture among populations were observed in all groups. MST, STRUCTURE and e-BURST analyses showed that the strains collected in 1998 belong to two distinct groups, with predicted founder genotypes from two different vineyards in the same region. This suggest that one introduction of grape planting materials contaminated with genetically distinct strains took place, which was followed by pathogen adaptation. Genome sequencing of one Brazilian strain confirmed typical attributes of pathogenic xanthomonads and allowed the design of a complementary VNTR typing scheme dedicated to *X. citri* pv. *viticola* that will allow further epidemiological survey of this genetically monomorphic pathovar.

**Keywords:** MLVA, MLSA, *Vitis vinifera*, grapevine bacterial canker, *Xanthomonas campestris* pv. *viticola*
INTRODUCTION

Xanthomonas citri pv. viticola, the causal agent of grapevine bacterial canker, was first described in India as Pseudomonas viticola sp. nov. (Nayudu, 1972). For many years, its occurrence was restricted to India and regarded as a disease of secondary importance until outbreaks in the late 1980's (Chand and Kishun, 1990). In 1998, a new disease was reported affecting vines of Vitis vinifera cultivar Red Globe in the irrigated areas of the São Francisco River valley in Pernambuco and Bahia states, northeastern Brazil. This region accounts for a significant percentage of table grape production in Brazil. Disease symptoms were leaf spots and cankers observed on stems, twigs and petioles. The causal agent was identified through biochemical and pathogenicity tests as Xanthomonas campestris pv. viticola. Additionally, rep-PCR fingerprinting analysis of strains collected in Brazil showed highly similar profiles to the Indian pathotype strain (NCPPB 2475) (Trindade et al., 2005). Infected grapevines were later detected in other states in Brazil (Halfeld-Vieira and Nechet, 2006; Rodrigues Neto et al., 2011), and eradication procedures were adopted since the pathogen is of quarantine significance and subjected to regulatory measures. Besides India and Brazil, the pathogen has been reported in Africa in 2005 (Midha and Patil, 2014). The pathogen may disseminate by infected propagating material and an association with seeds and berries was demonstrated suggesting systemic colonization and spread (Tostes et al., 2014). Natural hosts of pathovar viticola are V. vinifera varieties. Nayudu (1972) also reported natural infection of Azadirachta indica (neem, Meliaceae) and Phyllanthus maderaspatensis (Euphorbiaceae), which may represent alternative sources of inoculum for infection of grapevines. Plants in the Anacardiaceae family, such as mango tree (Mangifera indica) have also been described as potential hosts through inoculation (Chand and Kishun, 1990). In Brazil, some weed species belonging to the genera Alternanthera, Amaranthus, Glycine, and Senna have been identified as potential alternative hosts as well (Peixoto et al., 2007).

Diagnosis of grapevine bacterial canker is based on symptom observation followed by bacterial isolation and identification tools, including induction of a hypersensitive reaction (HR) on tomato leaves, pathogenicity tests on susceptible varieties, serology with polyclonal antibodies and/or molecular identification tests based on PCR (Trindade et al., 2005, 2007; Gama et al., 2018). Primers have been designed on partial sequences of the *hrp* cluster that differentiate Xanthomonas strains at both pathovar and species levels (Leite et al., 1994) and were shown to be useful for detection and identification of pathovar *viticola* in culture and plant tissue (Trindade et al., 2007).

The pathovar *viticola*, a non-pigmented xanthomonad, has been referred as *Xanthomonas campestris sensu lato* since it was not included in the *Xanthomonas* reclassification study of Vauterin et al. (1995). Sequence analysis of the housekeeping gene gyrase B (*gyrB*) for over 200 xanthomonads, including 67 poorly characterized pathovars of *X. campestris*, placed the pathotype strain from India and three pathovars associated

with hosts formerly classified in the genus *Vitis*, in the *X. citri* subsp. *citri* clade (Parkinson et al., 2009), along with several members of group 9.5 of *X. axonopodis*, such as pathovars *citri*, *glycines*, and *mangiferaeindicae* (Ah-You et al., 2009; Mhedbi-Hajri et al., 2013). Coherently, it was recently included in the newly proposed *X. citri* species that encompasses the so-called 9.5 and 9.6 groups (Rademaker et al., 2005; Constantin et al., 2016). A taxonomic reposition as *X. citri* pv. *viticola* comb. nov. has been proposed (Gama et al., 2018). In addition, phylogenomic analysis revealed that several pathovars, including pathovar *viticola*, form a monophyletic cluster and belong to one species, *X. citri* (Bansal et al., 2017).

Multilocus variable number of tandem repeats analysis (MLVA) is a high-resolution method for monitoring epidemics and assessing population structure and diversity for many bacterial species. A typical variable number of tandem repeats (VNTR) locus shows large range of copy numbers even among highly related bacterial strains (Jackson, 2010). MLVA has been used as a typing tool in outbreaks of numerous human and animal pathogens, but also in food microbiology such as the winemaking process (Claisse and Lonvaud-Funel, 2012). For human pathogens of medical interest, it has been regarded as a powerful tool for outbreak detection and source tracing in several European countries (Lindstedt et al., 2013). Resources for discovery of polymorphic loci such as VNTR databases are available for free access (Chang et al., 2007). For plant associated bacteria, several MLVA schemes have been described for important pathogens including several species and pathovars of Xanthomonas spp. such as *X. citri* pv. *citri* (Bui Thi Ngoc et al., 2009; Pruvost et al., 2014; Leduc et al., 2015); *X. oryzae* (Poulin et al., 2015); *X. arboricola* (Cesbron et al., 2014; Essakhi et al., 2015; López-Soriano et al., 2016); *X. fragariae* (Gétaz et al., 2018); and *X. axonopodis* pv. *manihotis* (Arrieta-Ortiz et al., 2013). VNTR typing has been recognized as the best tool to type recently emerged bacteria with limited genetic diversity and to better understand their patterns of long-distance dissemination (Bühlmann et al., 2013; Cunty et al., 2015; Nakato et al., 2018).

The objectives of this study were to assess the genetic relatedness among *Xanthomonas citri* pv. *viticola* strains from India and Brazil, related pathovars (pv. *vitiscarnosae*, *vitistrifoliae*, *vitiswoodrowii*) affecting other host plants in the family Vitaceae and three pathogenic strains from *Amaranthus* sp. collected close to bacterial canker-infected grapevines in Brazil. We conducted the characterization of pathovar *viticola* strains based on a concatenated sequence of seven housekeeping genes (MLSA) to allow comparisons with strains from other pathovars. A MLVA typing scheme with eight VNTR loci derived from *X. citri* pv. *citri* was validated with 107 strains of pathovar *viticola* and used to assess the genetic structure of this pathovar in Brazil. Genome sequencing of one Brazilian strain confirmed typical attributes of pathogenic xanthomonads and allowed the design of a complementary VNTR typing scheme dedicated to *X. citri* pv. *viticola* that will allow further epidemiological survey of this genetically monomorphic pathovar.
# MATERIALS AND METHODS

## Bacterial Strains

A collection of 102 strains isolated from grapevine (*Vitis vinifera*) and three strains isolated from symptomatic *Amaranthus* sp. plants growing in bacterial canker-infected vineyards in Brazil were used in this study (Table 1). These strains were isolated over a period of 14 years (1998–2012). The pathovar *viticola* pathotype strain from India, two other Indian strains from grapevine (*V. vinifera*) and the pathotype strains (CFBP 7658, CFBP 7659, and CFBP 7657) of the three pathovars affecting other species in the Vitaceae family (*vitiscarnosae*, *vitistrifoliae*, and *vitiswoodrowii*, respectively) were also included in this study. These six strains were isolated in India from 1951 to 1972 (Table 1). The strains isolated from grapevine plants in Brazil were previously identified by PCR with specific primers targeting a 240 bp-sequence of the *hrcN* (*hrpB*) gene (Trindade et al., 2007) and tested for hypersensitive response (HR) induction on tomato and/or pathogenicity on a susceptible grapevine cultivar.

All strains were recovered on LPGA medium (yeast extract 7 g liter⁻<fnref n="1" />; peptone 7 g liter⁻<fnref n="1" />; glucose 7 g liter⁻<fnref n="1" />; agar 15 g liter⁻<fnref n="1" />, pH 7.2) and transferred to 10% TSA medium (1.7 g liter⁻<fnref n="1" /> tryptone, 0.3 g liter⁻<fnref n="1" /> soybean peptone, 0.25 g liter⁻<fnref n="1" /> glucose, 0.5 g liter⁻<fnref n="1" /> NaCl, 0.5 g liter⁻<fnref n="1" /> K₂HPO₄, and 15 g liter⁻<fnref n="1" /> agar). Cells were grown at 28°C for 24 h. For long term storage strains were preserved and frozen in 40% glycerol at -80°C. DNA was obtained from 1 × 10⁷ CFU ml⁻<fnref n="1" /> bacterial cell suspensions with a heating step at 94°C for 10 min before the amplification program.

## Multilocus Sequencing Analysis (MLSA)

Two strains from India (CFBP 7660 and CFBP 7691) and a subcollection of 26 strains from the 105-strain collection from Brazil were selected to represent the diversity in terms of year, host, and geographical origin. PCR amplifications of portions of seven housekeeping genes [atpD: ATP synthase-beta chain, dnaK: encoding the 70-kDa heat shock protein, efp: elongation factor P, fyuA coding a transmembrane protein (Ton-B dependent transporter), glnA: glutamine synthetase I, gyrB: DNA gyrase subunit B, and rpoD: RNA polymerase sigma 70 factor] were carried out with the primers designed by Mhedbi-Hajri et al. (2013), except for *gyrB* from which a 904-bp portion was amplified with the forward primer *XgyrB1F* (ACGAGTACAACCCGGACAA) and the reverse primer *XgyrB1R* (CCCATCARGGTGCTGAAGAT) (Young et al., 2008).

PCR amplifications were performed in a 25 µl-reaction containing 1X Go Taq Buffer (Promega), 200 µM dNTPs, 0.5 µM of each primer, 0.375 U of Go Taq Polymerase, and 5 µl of boiled bacterial cell suspension. Amplification program was carried out in a PE 9600 thermocycler (Applied Biosystems) with an initial denaturation at 94°C for 5 min, 35 cycles of denaturation at 94°C for 30 s, annealing at 60°C for 30 s (or 62°C for *efp*), extension for 1 min at 72°C, and a final extension at 72°C for 7 min. Quality and yield of PCR products were checked by loading 5 µl of the reaction in 1% agarose gels in 1 x Tris acetate EDTA (TAE)

followed by staining with ethidium bromide. PCR products (20 µl) from each strain/gene combination were sequenced with reverse and forward primers at Genoscreen (Lille, France). Sequences obtained from forward and reverse primers were assembled and edited using GENEIOUS Pro 4.8.5 (Biomatters, New Zealand). Consensus sequences were generated, and codon-based multiple alignments were obtained using CLUSTALW (Thompson et al., 1994) application in BioEDIT (Hall, 1999) with default parameters. Initial phylogenetic analyses were performed on individual *rpoD* and *gyrB* sequences for comparisons with sequences from *Xanthomonas* (type and pathotype strains) from the CFBP/PhyloSearch tool database<fnref n="1" /> using the Neighbor Joining (NJ) method available in MEGA 5.05 (Tamura et al., 2007). As the concatenated data sets were identical for all 27 strains tested, we selected the sequences from the pathotype strain (CFBP 7660) for comparisons with DNA sequences of 131 strains of *X. axonopodis* representing 21 pathovars (Mhedbi-Hajri et al., 2013) from all six Rademaker's genetic groups (Rademaker et al., 2005). Phylogenetic analysis was performed for each gene individually and on the concatenated data set. Concatenated alignments of the seven-genes sequences displayed in alphabetic order were generated in GENEIOUS to a final sequence of 4,759 bp (1–738 for *atpD*, 739–1485 for *dnaK*, 1486–1832 for *efp*, 1833–2473 for *fyuA*, 2474–3352 for *glnA*, 3353–4054 for *gyrB*, and 4055–4759 for *rpoD*). Separate and concatenated trees were constructed by NJ and maximum-likelihood (ML) reconstruction methods. For the latter, the model of nucleotide substitution was estimated with hierarchical likelihood ratio test (hLRT) and the Akaike Information Criterion (AICc) to select the best model from 56 candidate models, using Modeltest 3.7 in PAUP (Swofford, 2002). Phylogenetic trees were obtained by the PhyML method and *Xanthomonas campestris* pv. *campestris* strain CFBP5241 (ATCC 33913) was used to root the tree as it is more distantly related from the other xanthomonads (*X. citri* and related species). The SH test (Shimodaira and Hasegawa, 1999) from the DNAml program in PHYLIP (Felsenstein, 1989) was performed to test whether the ML tree topology based on each separate gene fell within the same confidence limits. For both NJ and ML trees, bootstrap analyses were performed with 1,000 replications and the trees were generated with MEGA 5.05.

## HR Induction and Pathogenicity Tests on *Vitis vinifera*

Upon isolation from plant material, strains were tested for induction of HR on tomato (*Solanum lycopersicum* "Santa Clara") by leaf infiltration of a 1 × 10⁹ CFU ml⁻<fnref n="1" /> bacterial suspension in sterile distilled water. Pathogenicity of isolated strains was confirmed following infiltration of *V. vinifera* cv. Red Globe leaves with a bacterial suspension at 1 × 10⁸ CFU ml⁻<fnref n="1" />. Bacterial suspension (100 µL⁻<fnref n="1" />) was infiltrated into four points of the abaxial surface of the leaves with the aid of a hypodermic syringe without needle. These qualitative tests were conducted with two replicates per isolate. Inoculated plants were maintained in a greenhouse at 28°C and the pathogen was reisolated from typical lesions 7–10 days after inoculation.

<footnote n="1">¹http://147.99.127.226/pub/cfbp/user_tool.php</footnote>
<table><caption>TABLE 1 | Xanthomonas strains used in this study.</caption><thead><tr><th>Strain</th><th>Other collections</th><th>Host cultivar</th><th>Country of origin</th><th>Location<sup>a</sup></th><th>Year of isolation</th><th>Pathogenicity</th><th>HR tomato</th><th>PCR<sup>b</sup></th></tr></thead><tbody><tr><td>CFBP 7660</td><td>NCPPB 2475, LMG 965, ICMP 3351</td><td>Anab-e-Shahi</td><td>India</td><td>Andhra Pradesh</td><td>1969</td><td>+</td><td>+</td><td>+</td></tr><tr><td>CFBP 7691</td><td>NCPPB 2614, LMG 966, ICMP 3865</td><td>na<sup>c</sup></td><td>India</td><td>na</td><td>1972</td><td>nd<sup>d</sup></td><td>nd</td><td>nd</td></tr><tr><td>CFBP 7694</td><td>NCPPB 3642</td><td>na</td><td>India</td><td>na</td><td>1990<sup>e</sup></td><td>—</td><td>nd</td><td>nd</td></tr><tr><td>CFBP 5869</td><td>IBSBF 1385</td><td>Italia</td><td>Brazil</td><td>Teresina, PI</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>CFBP 7675</td><td>ICMP 13704, IBSBF 1376</td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>nd</td><td>nd</td><td>nd</td></tr><tr><td>CFBP 7676</td><td>ICMP13706, IBSBF 1386</td><td>Ribier</td><td>Brazil</td><td>Teresina, PI</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>CFBP7764</td><td>P1S6</td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>+</td><td>+</td><td>+</td></tr><tr><td>482</td><td>IBSBF 2598</td><td></td><td>Brazil</td><td>Boa Vista, RR</td><td>2006</td><td>+</td><td>nd</td><td>+</td></tr><tr><td>4562</td><td>IBSBF 1507</td><td></td><td>Brazil</td><td>Petrolina, PE</td><td>1999</td><td>+</td><td>nd</td><td>+</td></tr><tr><td>1184</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1186</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1187</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1189</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1191</td><td></td><td>Italia</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1192</td><td></td><td>Italia</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1193</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1194</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1195</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>1998</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1205</td><td></td><td>Italia</td><td>Brazil</td><td>Sobradinho, BA</td><td>2000</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1226</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2001</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1299</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Juazeiro, BA</td><td>2004</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1303</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2005</td><td>nd</td><td>+</td><td>+</td></tr><tr><td>1307</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2005</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1309</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2005</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1315</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2005</td><td>+</td><td>+</td><td>+</td></tr><tr><td>1316</td><td></td><td>Red Globe</td><td>Brazil</td><td>Juazeiro, BA</td><td>2005</td><td>nd</td><td>+</td><td>+</td></tr><tr><td>1318</td><td></td><td>BRS Morena</td><td>Brazil</td><td>na</td><td>2006</td><td>+</td><td>+</td><td>+</td></tr><tr><td>4779B</td><td></td><td>Red Globe</td><td>Brazil</td><td>Cianorte, PR</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>A2</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2010</td><td>+</td><td>+</td><td>+</td></tr><tr><td>A11</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2010</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>A12</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2010</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>AR1</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>+</td><td>+</td></tr><tr><td>AR2</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>TR1</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>TR3</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>+</td><td>+</td></tr><tr><td>P1S5</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>P1S9</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>+</td><td>+</td></tr><tr><td>P1S12</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>P1S16</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>P2S1</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>P2S2</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>+</td><td>nd</td><td>+</td></tr><tr><td>P2S4</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>+</td><td>+</td><td>+</td></tr><tr><td>P2S6</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>+</td><td>+</td></tr><tr><td>P2S7</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>RS2</td><td></td><td>Red Globe</td><td>Brazil</td><td>Curaça, BA</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>RS6</td><td></td><td>Red Globe</td><td>Brazil</td><td>Curaça, BA</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>RS8</td><td></td><td>Red Globe</td><td>Brazil</td><td>Curaça, BA</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>RS10</td><td></td><td>Red Globe</td><td>Brazil</td><td>Curaça, BA</td><td>2012</td><td>nd</td><td>nd</td><td>+</td></tr><tr><td>RS11</td><td></td><td>Red Globe</td><td>Brazil</td><td>Curaça, BA</td><td>2012</td><td>nd</td><td>+</td><td>+</td></tr><tr><td>XCV005</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2008</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV008</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2008</td><td>+</td><td>+</td><td>+</td></tr></tbody></table>

(Continued)
<table><caption>TABLE 1 | Continued</caption><thead><tr><th>Strain</th><th>Other collections</th><th>Host cultivar</th><th>Country of origin</th><th>Location<sup>a</sup></th><th>Year of isolation</th><th>Pathogenicity</th><th>HR tomato</th><th>PCR<sup>b</sup></th></tr></thead><tbody><tr><td>XCV009</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2008</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV013</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV015</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV021</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV026</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV028</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV033</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV034</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV039</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV040</td><td></td><td>Italia</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV044</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Juazeiro, BA</td><td>2009</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV045</td><td></td><td>Crimson</td><td>Brazil</td><td>Juazeiro, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV047</td><td></td><td>Italia</td><td>Brazil</td><td>Juazeiro, BA</td><td>2009</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV050</td><td></td><td>na</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV052</td><td></td><td>Sugraone</td><td>Brazil</td><td>Casa Nova, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV054</td><td></td><td>Sugraone</td><td>Brazil</td><td>Casa Nova, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV056</td><td></td><td>Sugraone</td><td>Brazil</td><td>Casa Nova, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV065</td><td></td><td>Italia</td><td>Brazil</td><td>Casa Nova, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV068</td><td></td><td>Red Globe</td><td>Brazil</td><td>Casa Nova, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV070</td><td></td><td>Benitaka</td><td>Brazil</td><td>Casa Nova, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV071</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV076</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV079</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV080</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV081</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Casa Nova, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV090</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Juazeiro, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV091</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Juazeiro, BA</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV112</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV114</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV116</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV117</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV119</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV124</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2009</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV129</td><td></td><td>Sugraone</td><td>Brazil</td><td>Juazeiro, BA</td><td>2010</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV133</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2010</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV137</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Casa Nova, BA</td><td>2010</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV143</td><td></td><td>Red Globe</td><td>Brazil</td><td>Petrolina, PE</td><td>2010</td><td>+</td><td>-</td><td>+</td></tr><tr><td>XCV153</td><td></td><td>Red Globe</td><td>Brazil</td><td>Casa Nova, BA</td><td>2010</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV154</td><td></td><td>Red Globe</td><td>Brazil</td><td>Casa Nova, BA</td><td>2010</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV171</td><td></td><td>Sugra18</td><td>Brazil</td><td>Petrolina, PE</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV176</td><td></td><td>Red Globe</td><td>Brazil</td><td>Juazeiro, BA</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV178</td><td></td><td>Sugraone</td><td>Brazil</td><td>Casa Nova, BA</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV179</td><td></td><td>Benitaka</td><td>Brazil</td><td>Casa Nova, BA</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV181</td><td></td><td>Red Globe</td><td>Brazil</td><td>Juazeiro, BA</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV191</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Juazeiro, BA</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV192</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Juazeiro, BA</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV200</td><td></td><td>Red Globe</td><td>Brazil</td><td>Juazeiro, BA</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV201</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV202</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV203</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV204</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr></tbody></table>

(Continued)
<table><caption>**TABLE 1** | Continued</caption><thead><tr><th>Strain</th><th>Other collections</th><th>Host cultivar</th><th>Country of origin</th><th>Location<sup>a</sup></th><th>Year of isolation</th><th>Pathogenicity</th><th>HR tomato</th><th>PCR<sup>b</sup></th></tr></thead><tbody><tr><td>XCV207</td><td></td><td>Thompson Seedless</td><td>Brazil</td><td>Petrolina, PE</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV208</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>XCV210</td><td></td><td>Sugraone</td><td>Brazil</td><td>Petrolina, PE</td><td>2011</td><td>+</td><td>+</td><td>+</td></tr><tr><td>Am-1</td><td></td><td>Amaranthus sp.</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>+</td><td>+</td><td>+</td></tr><tr><td>Am-2</td><td></td><td>Amaranthus sp.</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>+</td><td>+</td></tr><tr><td>Am-3</td><td></td><td>Amaranthus sp.</td><td>Brazil</td><td>Petrolina, PE</td><td>2012</td><td>nd</td><td>+</td><td>+</td></tr></tbody></table>

The three pathotype strains (CFBP 7657, 7658, and 7659) were tested on 90-day-old *V. vinifera* plants cv. Sauvignon under controlled conditions (28°C, 98% RH, photoperiod of 16 h). Two methods of inoculation were employed: leaf infiltration (two spots per leaf) with 200 µl of a 1 × 10⁷ CFU ml⁻¹ suspension and deposition of 25 µl of a 1 × 10⁸ CFU ml⁻¹ suspension on the stems at three points after wounding with a needle. Two plants and six leaves per plant were inoculated with each strain. Plants were kept at 100% humidity for 48 h and were evaluated for symptom development until 35 days after inoculation. Three additional plants each were inoculated with pathovar *viticola* strains from India, CFBP 7660 and CFBP 7694, and one Brazilian strain (CFBP 7764) as positive controls. One plant was inoculated with water and kept as a negative control. All inoculation tests were carried out following quarantine procedures at IRHS, France. The assay was evaluated qualitatively, by scoring presence or absence of necrotic symptoms during 35 days. Isolations from inoculated leaves and stems were attempted 35 days after inoculation and colony growth was recorded after 48–72 h on 100% TSA medium.

## Selection of VNTR Loci for MLVA

Bacterial suspensions of each strain were prepared at 1 × 10⁷ CFU ml⁻¹ and were boiled at 95°C for 10 min before PCR. Aliquots of boiled cells were kept at -20°C. Primers for amplification of 14 VNTR loci from *X. citri* pv. *citri* (Bui Thi Ngoc et al., 2009) were tested with five strains of pathovar *viticola* and strain 306 of pathovar *citri*. Reaction mix contained 1X GoTaq Flexi buffer (Promega), 1.5 or 3.0 mM MgCl₂, 62.5 µM each dNTP, 0.125 µM of each primer, 0.25 U of GoTaq Flexi DNA polymerase and 1 µl of bacterial cells suspension. Conditions for amplification were as follows: 95°C for 5 min followed by 32 cycles of 95°C for 30 s; 60, 64 or 68°C, depending on the primer set, for 30 s and 72°C for 30 s and a final extension at 72°C for 10 min. PCR products were separated on 2.5% agarose gels in 1X Tris acetate EDTA buffer (TAE) and visualized after ethidium-bromide staining. When poor amplification occurred, PCR was optimized by testing different MgCl₂ concentrations (1.5 and 3.0 mM) and annealing temperatures (60, 64, 68°C). VNTR loci were selected based on reproducibility (amplicons of same size produced in different PCR runs) and polymorphism detection among pathovar *viticola* strains, verified by gel electrophoresis.

## VNTR Genotyping

Eight VNTR loci were selected and the forward primers were tagged with one of four fluorescent dyes, 6-FAM, VIC, NED or PET (Eurofins MWG/Operon). Primer pairs were combined in four duplexes, with the respective annealing temperature, as follows: XL-1 FAM and XL-4 VIC, 64°C; XL-13 NED and XL-15 PET, 60°C; XL-3 FAM and XL-5 PET, 64°C; XL-6 NED and XL-8 VIC, 68°C.

PCR products (1 µl of products marked with 6-FAM, VIC or NED; and 2 µl of products marked with PET) were diluted in ultrapure water to a final volume of 32 µl. An aliquot of 2.4 µl was mixed with 0.15 µl of the GeneScan™ 500 LIZ™ size standard (Applied Biosystems) and 9.35 µl formamide in a 96-well tray, followed by denaturation at 94°C for 10 min in a thermocycler. Capillary electrophoresis was conducted in the ABI3130 sequencer using the GeneMapper application. Chromatograms were visualized with PeakScanner™ software v. 1.0 (Applied Biosystems). Fragment sizes were estimated and converted into copy number for each VNTR. To confirm the copy number for each VNTR locus, PCR products of strains CFBP 7660 and CFBP 7764 were sequenced at Genoscreen. Sequences were edited with GENEIOUS and the search tools were used to detect the tandem repeat sequences.

## Stability Test

In order to test the stability of the pathovar *viticola* VNTR types after successive culture transfers, four distinct strains were tested: three pathovar *viticola* strains (CFBP 7660, 7764, and 5869) and *X. axonopodis* pv. *citri* strain 306. A starter bacterial cell suspension (1 × 10⁸ CFU ml⁻¹) was prepared and 50 µl were transferred to 5 ml 10% TS liquid media. After 24 h growth at 28°C, a new aliquot of 50 µl was transferred to a new tube. This procedure was repeated every 24 h for 4 days. At each day, a bacterial suspension of 1 × 10⁷ CFU ml⁻¹ was prepared from each culture and tested for the eight VNTR makers. Serial dilutions and colony counts were performed on 10% TSA after 48 h to assess the number of generations from the starter culture.

## Analyzing VNTR Data

The VNTR data obtained from 107 strains of pathovar *viticola* were analyzed with BioNumerics (version 6.5, Applied Maths, Sint-Martens-Latem, Belgium). The copy numbers for each VNTR were used as character data and submitted to cluster

<footnote><sup>a</sup>States in Brazil: PE, Pernambuco; BA, Bahia; PI, Piaui; PR, Paraná; RR, Roraima; <sup>b</sup>PCR with specific primers targeting a 240 bp-sequence of the hrcN gene (Trindade et al., 2007); <sup>c</sup>na, information not available; <sup>d</sup>not determined; <sup>e</sup>year added to NCPPB.</footnote>
analysis. A minimum spanning tree (MST) was generated. This
tool creates a tree that connects all strains in such way that the
summed distance of all branches is minimized. Clonal complexes
were designed using BioNumerics. The Bayesian clustering
approach was used to infer population structure and assign
individuals to groups characterized by distinct allele frequencies
(Pritchard et al., 2000). It was implemented in the software
structure 2.3.4. The method estimates a probability of ancestry
for each individual from each of the groups. Individuals are
assigned to one cluster or jointly to two or more clusters if their
genotypes indicate that they were admixed. Twenty independent
runs of structure were performed by setting the number of
subpopulations or groups (K) from 1 to 10, with 10,000 burn-
in replicates and a run length of 20,000 replicates to decide which
value of K best fits the data (Evanno et al., 2005). Clustering of
isolates of pathovar *viticola* was evaluated for the inferred number
of groups. Structure was run using the admixture model without
prior population information, which assumes correlated allele
frequencies for our MLVA data. The founder genotype, which
is the one from which most single locus variants (SLV) arose
(Feil et al., 2004; Spratt et al., 2004) was identified using eBURST
v3². The discriminatory power of MLVA was calculated using an
online tool<fnref n="3" />.

CFBP 7764 Genome Sequencing and
*in silico* Design of New VNTRs

The genome of *Xanthomonas citri* pv. *viticola* strain CFBP 7764 was sequenced using the Illumina HiSeq 2000 platform (Genoscreen, France). The genomic sequence of another *X. citri* pv. *viticola* strain, LMG 965, already published (GCA_000723725.1) (Midha and Patil, 2014) was used for comparison. Annotation of both genomes was performed using EuGene-PP (Sallet et al., 2014). The genome sequences were mined to search CDSs encoding functions of interest for xanthomonads. A set of almost 1800 CDSs identified mostly in xanthomonads, but also in various pathogenic bacterial genera (*Xanthomonas*, *Pseudomonas*, *Ralstonia*, *Erwinia*, *Escherichia*, *Salmonella*) was used to screen for homologs of these proteins using tBLASTN (identity higher than 80% on at least 80% of CDS length). Genes encoding proteins involved in chemotaxis, motility, lipopolysaccharide and exopolysaccharide biosynthesis, TonB-dependent transporters (TBDTs), two-component systems (TCSs), the different secretion systems (T1SS, T2SS, T3SS, T4SS, T6SS) and their effectors, fibrillar and afibrillar adhesins, and insertion sequences (ISs) belonging to different families were included in this list. Furthermore, reciprocal tBLASTN (identity higher than 80% on at least 80% of CDS length) were performed between the 4,572 and 4,233 CDSs that were predicted in CFBP 7764 and LMG 965 genomes, respectively.

Tandem repeats finder web tool (Benson, 1999) was used to
search Variable Number of Tandem Repeats (VNTRs) in the
genome of CFBP 7764. Selected VNTRs have at least two copies
with period size shorter than 100 nucleotides and a percentage of
matches of at least 95% between the different copies. VNTRs were

then checked on LMG 965 genome and only VNTRs that had a
different number of copies within both genomes were selected.
Primers conserved in both strains were designed in the 500 bp-
flanking regions using Primer3 web site (Untergasser et al., 2012)
in order to amplify DNA fragments with a final size between 100
and 350 bp to be compatible with the use of the ABI3130 capillary
electrophoresis sequencer.

Nucleotide Sequence
Accession Numbers

The GenBank accession numbers for the partial sequences of
the grapevine strain CFBP 7764 and the *Amaranthus* strain
Am-1, used in this study are, respectively: for *atpD* MH171285
and MH171286; for *dnaK* MH171287 and MH171288; for *efp*
MH171289 and MH171290; for *fyuA* MH171291 and MH171292;
for *glnA* MH171293 and MH171294; for *gyrB* MH171295 and
MH171296; and for *rpoD* MH171297 and MH171298.

Accession Number

The whole-genome shotgun sequence of *Xanthomonas citri* pv. *viticola* strain CFBP 7764 has been deposited in GenBank under accession no. PPHE00000000.

RESULTS

Xanthomonas Strains Causing Grapevine
Bacterial Canker in Brazil Belong to
*X. citri* pv. *viticola* and Are Monomorphic
Based on MLSA

Neighbor Joining tree-based phylogeny determined from *rpoD* and *gyrB* concatenated sequences alignments showed the relatedness among types and pathotypes of 15 *Xanthomonas* species and 27 strains of pathovar *viticola* and strains of the three other pathovars affecting plants in the Vitaceae family (Figure 1). All pathovar *viticola* strains (Table 1) had identical sequences for both gene sequences, including the Brazilian and Indian strains and two strains from *Amaranthus* sp. These strains, as well as those from the related pathovars affecting Vitaceae species from India, were assigned to the newly described *X. citri* species that encompasses the previously described 9.5 and 9.6 groups. The pathovar *viticola* strains were all distinct from these other pathovars. Based on housekeeping gene sequences, the closest relative to pathovar *viticola* is pathovar *vitistrifoliae*.

Sequences of all seven genes were identical for all strains
collected from grapevine and from *Amaranthus*. Therefore, only
one sequence type was used for comparisons with 131 gene
sequences from *X. axonopodis* pathovars from Mhedbi-Hajri
et al. (2013) and sequences from the three Vitaceae-associated
pathotypes. ML (Figure 2) and NJ trees were constructed based
on the 4,759 bp concatenated sequences of the seven genes.
Both trees showed congruent assignments for most pathovars
according to Rademaker's genetic groups 9.1-9.6, except for
pathovars alfalfae and allii from the 9.2 group. ML trees showed
higher bootstrap values compared to the NJ trees. Both methods
assigned the pathovar *viticola* and the other related pathovars

<footnote n="2">²http://eburst.mlst.net/</footnote>

<footnote n="3">³http://insilico.ehu.es/mini_tools/discriminatory_power/index.php</footnote>
<figure><img src="image_59.png" /><figcaption>**FIGURE 1** | Neighbor-joining tree based on concatenated partial sequences of gyrB and rpoD of 28 strains of pathovar *viticola* and 15 type strains of most *Xanthomonas* species. Bootstrap values (1,000 replicates) are shown at each node. The 28 strains include 24 strains isolated in Brazil from bacterial canker-infected grapevines, two (Am-1 and Am-3) from *Amaranthus* plants grown in the vicinity of grapevines, and two strains from India (CFBP 7660 and CFPB 7691). CFBP 7660 is the pathotype strain of *X. citri* pv. *viticola*.</figcaption></figure>

to the 9.5 clade. The SH test performed on the ML trees showed that for five genes the concatenated tree topology was congruent with each individual gene tree, except for *glnA* and

*rpoD* (Supplementary Table S1). For these two genes, different positions of pathovars in the 9.1 and 9.2 groups were evident, suggesting occurrence of recombination events.
<figure><img src="image_60.png" /></figure>

**FIGURE 2** | Maximum likelihood tree of 131 *Xanthomonas* strains based on the 4,759 bp concatenated sequences of *atpD*, *dnaK*, *efp*, *fyuA*, *glnA*, *gyrB*, and *rpoD*. Tree was constructed with PhyML and the bootstrap values higher than 50 (1,000 replicates) are shown at each node. Sequences of the pathotype strain (CFBP 7660) of *X. citri* *pv. viticola* were compared to sequences of 131 strains formerly assigned to *X. axonopodis* representing 21 pathovars (Mhedbi-Hajri et al., 2013) and all six Rademaker's genetic groups 9.1-9.6 (Rademaker et al., 2005). Correspondence between Rademaker's groups and the four *Xanthomonas* species (according to Constantin et al., 2016) are indicated. *Xanthomonas campestris* *pv. campestris* strain CFBP 5241 (ATCC 33913) was included as outgroup.
<figure><img src="image_61.png" /></figure>

<table><thead><tr><th rowspan="2">B Strain</th><th colspan="2">leaf</th><th colspan="2">stem</th></tr><tr><th>symptom</th><th>isolation</th><th>symptom</th><th>isolation</th></tr></thead><tbody><tr><td>CFBP 7660 <i>X. citri</i> pv. viticola</td><td>++</td><td>+</td><td>++</td><td>+</td></tr><tr><td>CFBP 7764 <i>X. citri</i> pv. viticola</td><td>++</td><td>+</td><td>++</td><td>+</td></tr><tr><td>CFBP 7658 <i>X. citri</i> pv. vitiscarnosae</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>CFBP 7659 <i>X. citri</i> pv. vitistrifoliae</td><td>-</td><td>+</td><td>+</td><td>+</td></tr><tr><td>CFBP 7657 <i>X. citri</i> pv. vitiswoodrowii</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>CFBP 7694 <i>X. hortorum</i></td><td>-</td><td>+</td><td>-</td><td>-</td></tr><tr><td>Control (water)</td><td>-</td><td>-</td><td>-</td><td>-</td></tr></tbody></table>

**FIGURE 3** | Pathogenicity test on *Vitis vinifera* cultivar Sauvignon carried out by leaf and stem inoculations with *Xanthomonas* strains. (A) Symptoms 35 days after inoculation of: CFBP 7764 on leaf and stem (a,b); CFBP 7657 (c), CFBP 7658 (d), CFBP 7659 (e) and negative control at 21 days after infiltration (f). (B) Symptom development was recorded as (+) necrosis at the point of infiltration; (++) necrosis at the point of infiltration followed by multiple necrotic spots on the leaves and leaf veins, or development of canker-like lesions on the stems; strain CFBP 7694 was received as *X. campestris* pv. *viticola*, but is related to *X. hortorum* according to gyrB and rpoD sequencing (as shown in **Figure 1**). Scale bar = 1.0 cm.

Based on MLSA the four pathovars affecting distinct species in the family Vitaceae were distinct from each other, while still belonging to *X. citri*, more precisely to the 9.5 Rademaker's group (Figure 2). Pathovars *vitistrifoliae* and *viticola* fell into one clade supported by high bootstrap values. On the other hand, pathovar *vitiswoodrowii* fell into a different clade, closest to pathovar bilvae. These three strains from India are reported as non-pathogenic on *V. vinifera*. However, due to the differences in their phylogenetic positions (Figure 2) we tested them for pathogenicity on *V. vinifera*, cv. Sauvignon. These pathogenicity tests confirmed the non-host status of *V. vinifera* only for pathovar *vitiswoodrowii*. Symptoms developed on stems of plants inoculated with pathovars *vitiscarnosae* and *vitistrifoliae*. For pathovar *vitiscarnosae*, necrotic spots at the point of infiltration also developed on leaves (Figure 3A). After 35 days, the

bacterium was isolated from both leaves and stems of all plants, but isolations were unsuccessful from plants inoculated with pathovar *vitiswoodrowii*. While symptoms incited by these two pathovars were mild and did not progress beyond the point of infiltration, the plants inoculated with pathovar *viticola* strains CFBP 7660 and 7764 showed more severe symptoms. Besides leaf perforation, several spots appeared on the leaf veins and in interveinal areas of the leaf that gradually enlarged becoming necrotic. Grape leaves inoculated with pathovar *vitistrifoliae* did not show any symptoms, but the isolation was positive, yielding pure colonies of the bacterium (Figure 3B).

It should be noticed that strain CFBP 7694 (NCPPB 3642), received as *Xanthomonas campestris* pv. *viticola*, was assigned to the *X. hortorum* clade, and for this reason it was not included in the MLVA study. In contrast to all pathovar *viticola* strains, which are non-pigmented, CFBP 7694 was a yellow-pigmented strain isolated in India and added to NCPPB in 1990. Due to its atypical characteristics, this strain was also tested for pathogenicity on grapevine plants. The pathogenicity test showed that it is not pathogenic on this host. This strain was identified as *X. hortorum*, according to gyrB and rpoD sequence analysis (Figure 1). No symptoms were observed on leaves or stems 35 days after inoculation. However, bacterial colonies were isolated from inoculated leaves, suggesting that this strain can survive in grape leaves (Figure 3B).

## VNTR Markers From *X. citri* pv. *citri* Have Sufficient Resolution to Detect Diversity in Pathovar *viticola*

Out of 14 VNTR loci from *X. citri* pv. *citri* (Bui Thi Ngoc et al., 2009), 13 were PCR-amplified from DNA of pathovar *viticola* strains. Primers for marker XL-2 did not produce any visible fragments on agarose gels. Using a subset of five pathovar *viticola* strains and strain 306 of *X. axonopodis* pv. *citri*, polymorphism was observed with eight markers (Table 2). The stability of these markers was checked *in vitro* after 32 generations for four strains, three pathovar *viticola* strains (CFBP 7660, 7764 and 5869) and *X. axonopodis* pv. *citri* strain 306. No variation in fragment sizes was observed throughout the experiment. Hence, all eight markers remained stable after 32 generations of these four strains.

<table><caption>**TABLE 2** | Number of alleles, range of repeat numbers, strain frequency for each dominant allele and allelic diversity for the eight VNTR loci tested on 107 pathovar *viticola* strains.</caption><thead><tr><th>Locus</th><th>Number of alleles</th><th>Range of repeat numbers</th><th>Dominant allele and strain frequency (%)</th><th>Simpson's diversity index</th></tr></thead><tbody><tr><td>XL 1</td><td>12</td><td>5-19</td><td>13 (29.9)</td><td>80.5</td></tr><tr><td>XL 4</td><td>11</td><td>5-16</td><td>11 (33.3)</td><td>80.8</td></tr><tr><td>XL 13</td><td>5</td><td>4-10</td><td>7 (85.0)</td><td>26.6</td></tr><tr><td>XL 15</td><td>8</td><td>3-11</td><td>10 (77.6)</td><td>39.0</td></tr><tr><td>XL 3</td><td>12</td><td>6-18</td><td>11 (27.1)</td><td>86.7</td></tr><tr><td>XL 8</td><td>5</td><td>4-13</td><td>5 (88.8)</td><td>19.3</td></tr><tr><td>XL 6</td><td>12</td><td>8-29</td><td>24 (30.8)</td><td>80.3</td></tr><tr><td>XL 5</td><td>7</td><td>6-13</td><td>7 (52.3)</td><td>64.1</td></tr></tbody></table>