The ecological genetics of Pseudomonas syringae from kiwifruit leaves
=====================================================================

* Christina Straub
* Elena Colombi
* Li Li
* Hongwen Huang
* Matthew D. Templeton
* Honour C. McCann
* Paul B. Rainey

## SUMMARY

Interactions between commensal microbes and invading pathogens are understudied, despite their likely effects on pathogen population structure and infection processes. We describe the population structure and genetic diversity of a broad range of co-occurring *Pseudomonas syringae* isolated from infected and uninfected kiwifruit during an outbreak of bleeding canker disease caused by *P. syringae* pv. *actinidiae* (*Psa*) in New Zealand. Overall population structure was clonal and affected by ecological factors including infection status and cultivar. Most isolates are members of a new clade in phylogroup 3 (PG3a), also present on kiwifruit leaves in China and Japan. Stability of the polymorphism between pathogenic *Psa* and commensal *P. syringae* PG3a isolated from the same leaf was tested using reciprocal invasion from rare assays *in vitro* and in planta. *P. syringae* G33C (PG3a) inhibited *Psa* NZ54, while the presence of *Psa* NZ54 enhanced the growth of *P. syringae* G33C. This effect could not be attributed to virulence activity encoded by the Type 3 secretion system of *Psa*. Together our data contribute toward the development of an ecological perspective on the genetic structure of pathogen populations.

**ORIGINALITY-SIGNIFICANT STATEMENT** Bacterial pathogen populations are often studied with little consideration of co-occurring microbes and yet interactions between pathogens and commensals can affect both population structure and disease progression. A fine-scale sampling of commensals present on kiwifruit leaves during an outbreak of bleeding canker disease caused by *P. syringae* pv. *actinidiae* reveals a clonal population structure. A new clade of non-pathogenic *P. syringae* (PG3a) appears to be associated with kiwifruit on a global scale. The presence of PG3a on kiwifruit has significant effects on the outcome of infection by *P. syringae* pv. *actinidiae*. This emphasises the value of studying the effect of co-occurring bacteria on pathogen-plant interactions.

## INTRODUCTION

Kiwifruit (*Actinidia* spp.) cultivation is challenged by outbreaks of the bacterial pathogen *Pseudomonas syringae* pv. *actinidiae* (*Psa*) – the causative agent of bleeding canker disease. The latest outbreak was first reported in Italy in 2008 (Balestra et al., 2008) before spreading rapidly through most kiwifruit growing regions of the world (Abelleira et al., 2011; Everett et al., 2011; Koh et al., 2012; Zhao et al., 2013; Sawada, 2015), arriving in New Zealand in 2010 (Everett et al., 2011).

As a pathogen, *Psa* faces the challenge of colonising diverse environments before proliferating in the apoplast and vascular tissues. Colonisation of leaf surfaces prior to invasion is a key infection stage (Wilson and Lindow, 1994; Wilson et al., 1999; Monier and Lindow, 2003; Pfeilmeier et al., 2016). On the leaf surface *Psa* is likely to encounter and interact with a diverse range of plant-colonising bacteria (Hirano and Upper, 2000; Lindow and Brandl, 2003). Physical proximity increases the likelihood of competitive interactions affecting disease outcomes (Lindow and Brandl, 2003; Hibbing et al., 2010) and increases the probability of horizontal gene transfer (Sawada et al., 1999; Polz et al., 2013; Colombi et al., 2017).

The local context and the scale of sampling bacterial populations is particularly important, as it can have an impact on genetic structure (Istock et al., 1992; Souza et al., 1992; Haubold and Rainey, 1996; Spratt and Maiden, 1999). A study by Istock et al. (1992) made a particularly persuasive case by showing that *sampling Bacillus subtilis* at the local level (instead of pooled collections) contradicted the common view of its clonal population structure. Similar lessons regarding the scale of sampling have come from studying *P. syringae* populations with a range of structures reported depending upon whether or not environmental isolates are included (Sarkar and Guttman, 2004; Monteil et al., 2013).

Bacterial interactions are context-dependent, ranging from synergistic to antagonistic, and may have both local and global effects on the plant host (Stubbendieck et al., 2016). Antagonistic or competitive interactions between microbes may be direct or indirect, resulting in the inhibition of growth or even killing (Lindow, 1986; Völksch and May, 2001; Berlec, 2012; Hockett et al., 2015; Nakahara et al., 2016). Synergistic interactions occur when multiple types cooperate to cause disease (Singer, 2010; Lamichhane and Venturi, 2015). For example, *P. savastanoi* pv. *savastanoi*, causative agent of olive knot disease, interacts with non-pathogenic endophytes *Erwinia* sp. and sp. in cankers, enhancing the severity of disease (Marchi et al., 2006; Moretti et al., 2011; Buonaurio et al., 2015). Synergistic interactions can also be exploitative: bacteria lacking virulence factors can reap benefits from co-existing pathogenic isolates (Young, 1974; Hirano et al., 1999; Macho et al., 2007; Rufián et al., 2017).

*P. syringae* is a common member of the phyllosphere (defined as the aerial part of a plant (Vorholt, 2012)) and engages in both commensal and pathogenic interactions with plants (Hirano and Upper, 2000; Mohr et al., 2008). The diversity and population structure of *P. syringae* has been investigated using both multilocus sequence typing (MLST) and genome sequence analysis of pathogenic isolates collected from diseased plants (Sarkar and Guttman, 2004; Hwang et al.,2005; Baltrus et al., 2011; McCann et al., 2013, 2017; Fujikawa and Sawada, 2016; Nowell et al., 2016). Studies have also explored the structure of *P. syringae* populations from environmental reservoirs beyond standard host plants (Morris et al., 2008; Monteil et al., 2013, 2014, 2016). However, the genetic structure of specific pathovar populations from the phyllosphere of specific host plants have rarely been studied in the context of co-occurring *P. syringae* types.

Here we describe the population structure of the *P. syringae* species complex inhabiting the kiwifruit phyllosphere during an outbreak of bleeding canker disease in New Zealand. Using an MLST scheme, we reveal a largely clonal population structure, but show that genetic diversity is significantly affected by ecological factors such as infection status and cultivar. We identified members of four *P. syringae* phylogroups (PG1, PG2, PG3 and PG5) and recovered a new monophyletic clade within PG3 (PG3a) that is associated with kiwifruit in different kiwifruit-growing regions of the world. Investigations into the ecological interactions between a representative of this new clade and *Psa* show that PG3a restricts *Psa* proliferation, while *Psa* facilitates growth of PG3a.

## RESULTS

### Phyllosphere diversity of *Pseudomonas syringae*

Four housekeeping genes (*gapA, gyrB, gltA, rpoD*) were sequenced for each of 148 *P. syringae* isolated from two varieties of kiwifruit (‘Hayward’ and ‘Hort16A’) in both uninfected and *Psa*-infected orchards. Rarefaction analysis indicates saturation of the sampling effort (Figure S1). The infected ‘Hayward’ orchard displayed the highest α-diversity (D=0.904), while the uninfected ‘Hort16A’ orchard displayed the least α-diversity (D=0.737). There was low evenness (ED) among all sampling sites (0.136 to 0.290). Similarly, the four different sampling sites shared few species (Sørensen’s index of dissimilarity = 0.847).

### Multilocus sequence typing

45 unique sequence types (ST) were discovered among the 148 sequenced strains. All STs were novel, except for ST904 (*Psa*), and not described in the Plant Associated and Environmental Microbes Database (PAMDB). For a more global analysis, *P. syringae* allelic profiles were sourced from PAMDB and NCBI (accessions listed in Table S2), along with *P. syringae* isolated from kiwifruit in Japan (NCBI), NZ and the US (Visnovsky et al. 2016).

Infected orchards (both ‘Hayward’ and ‘Hort16A’) harboured the highest number of unique STs, sharing only three STs between them (Figure S2). No STs were present in all four orchards, but two STs were found in three orchards (ST1 and ST3). From the perspective of clonal complexes (CC), the predominant ST (predicted founder) was present along with several SLVs (single locus variants). Two clonal complexes (CC) (21 strains), 5 doubletons (32 strains) and 28 singletons (95 strains) were identified (Figure S3). CC1 and CC2 are comprised of 11 and 10 strains, respectively. ST904 (*Psa*, 15/148) and ST1 (PG3, 24/148) made up 25% of the sample (Figure S3). Strikingly, ST3 (PG3a) was isolated from three out of four orchards and was also sampled from uninfected gold (A. *chinensis* var. *chinensis*) and green (*A.chinensis* var. *deliciosa*) kiwifruit in NZ (2010) (Visnovsky et al., 2016) and Japan (2015), respectively (Figure 1). ST16 was also recovered from uninfected kiwifruit leaves in NZ in both 1991 and 2013. Other Japanese kiwifruit STs group closely with P.syringae originating from kiwifruit in NZ.

![Figure 1.](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2018/03/07/235853/F1.medium.gif)

[Figure 1.](http://biorxiv.org/content/early/2018/03/07/235853/F1)

Figure 1. Global Minimum Spanning Tree (MST).
Displaying the relationships between STs at the triple-locus-variant level, illustrated using PHYLOViZ (Francisco et al., 2012). The size of the circle correlates with the frequency of the ST. Color-coded accorded to origin: green = this study, black = PAMDB, blue = Visnovsky et al. (2016), purple = Japan.

### Sequence diversity

The total concatenated alignment length was 2010 bp with no insertions or deletions detected for either of the four loci. The number of alleles ranged from 25 (*gapA*) to 35 (*rpoD*) (Table 1). There were a total of 412 polymorphic sites, ranging from 80 (16.81%, *gapA*) to 145 (28.6%, *gyrB*). The nucleotide diversity index π and Watterson’s θ were highly consistent among loci, varying from 0.040 to 0.055 and 0.024 to 0.041 respectively. The average GC content of 57.99% is similar to that found in other *P. syringae* studies (59-61%). The pairwise genetic difference within phylogroups (PGs) was not greater than 2.7%, whereas among PGs the variability ranged from 6-11% (Table 2), consistent with previous accounts of genetic variability for *P. syringae* (Sarkar and Guttman, 2004; Morris et al., 2010; Berge et al., 2014).

View this table:
[Table 1:](http://biorxiv.org/content/early/2018/03/07/235853/T1)

Table 1: Nucleotide and amino acid diversity.
L = length in bp, AA = amino acid, GC = average GC content in %, NA = number of alleles, P = number of polymorphic sites, *d**N*/*d**S* ration, mut = mutations, π = nucleotide diversity indices, θ = Watterson’s theta.

View this table:
[Table 2:](http://biorxiv.org/content/early/2018/03/07/235853/T2)

Table 2: Average pairwise genetic diversity between and among phylogroups.
Analyses were conducted on the concatenated alignment (2006 bp, gaps removed) using the Maximum Composite Likelihood model with a gamma distribution of 1. N= number of strains.

### Genetic diversity varies by host cultivar and infection status

To test whether genetic diversity was influenced by the presence of ecological structure, multivariate analyses (PERMANOVA) were performed. A highly significant difference in genetic diversity was observed among sampled orchards (Pseudo-F = 5.99, *P <* 0.0001); with pairwise Permanova tests revealing that the uninfected green orchard differed significantly from every other orchard (*P*<0.003). The cultivar (‘Hayward’ vs. ‘Hort16A’) (Pseudo-F = 5.62, *P*<0.001) and infection status of an orchard (Pseudo-F = 11.72, *P* <0.001) also had a significant effect on genetic diversity, whereas no temporal effect was found (Pseudo-F = 1.10, *P* >0.34). When testing the nested effect of all three factors, only the infection status (Pseudo-F = 6.42, *P* <0.01) had a significant impact on genetic diversity (Table S3).

### Recombination among *P. syringae*

Intragenic recombination rates (ρ) ranged from 0.012 (*rpoD*) to 0.038 (*gyrB*) and 0.006 for the concatenated dataset. The ratio ε (recombination rate/mutation rate) ranged from 0.187 (concatenated) to 0.931 (*gyrB*) suggesting that any single nucleotide polymorphism is up to five times more likely to have arisen from a mutation than recombination (Table 3).

View this table:
[Table 3:](http://biorxiv.org/content/early/2018/03/07/235853/T3)

Table 3: LDhat recombination analysis.
Showing the length of the alignment in bp, N = number of sequences, mutation rate θ (=2Neμ) per site, recombination rate ρ (=2Ner) per site, ratio ε = ρ/ θ and Tajima’s D.

Clustering sequences by PG revealed no evidence of recombination within PG1 and PG5 (ρ=0), however for these phylogroups the sample size was low. There was evidence of recombination in PG3, more specifically for *gltA* (ε=1.18) and *rpoD* (ε=4.07), whereas in PG2 recombination was evident in *rpoD* (ε=1.734) alone. Recombination was neither affected by the host cultivar or infection status (Table S4). The analysis was repeated with the inclusion of non-redundant global strains. Overall, intergenic recombination rates were low among PGs, ranging from 0.005 to 0.012 for the concatenated dataset (Table S5). In order to pinpoint any effects of recombination on phylogenetic reconstruction, single gene trees were constructed and compared. Tree topologies were significantly different from each other and from the concatenated dataset (SH test, *P*<0.05) (Figure S4).

### A kiwifruit-associated clade of *P. syringae*

Maximum likelihood trees built using the concatenated alignment of unique STs revealed that nearly all NZ *P. syringae* kiwifruit isolates fell within four PGs: PG1 (13%), PG2 (29%) and PG3 (56%), with only a few isolates falling into PG5 (2%, Figure 2). Surprisingly, within PG3 all NZ kiwifruit-associated isolates grouped within a new clade of PG3, hereafter referred to as PG3a. The uninfected orchards showed a higher number of PG3a isolates compared to infected orchards, although no influence of infection status was reflected in the number of unique sequence types (Table S1). We also found that two strains isolated from kiwifruit in NZ in 2010 and 2011 (Visnovsky et al., 2016) belong to this subclade.

![Figure 2.](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2018/03/07/235853/F2.medium.gif)

[Figure 2.](http://biorxiv.org/content/early/2018/03/07/235853/F2)

Figure 2. Bayesian tree based on the concatenated alignment (2010 bp) of four housekeeping genes: *gapA, gyrB, gltA* and *rpoD*.
The Bayesian tree was reconstructed using MrBayes based on the Tamura-Nei + G + I model using 30,000,000 MCMC. Single representative sequences for each ST were used to improve readability (corresponding STs and frequency of each ST listed in Table S2). Values indicated at nodes are Bayesian posterior probabilities. The corresponding phylogroups (PG) are indicated, eg. PG1 = phylogroup 1 with clades 1a and 1b. Origin of isolates is illustrated in colour coded boxes, green = this study, black = PAMDB, blue = Visnovsky et al. 2016, purple = Japan.

This discovery led us to question whether the PG3a subclade might be prevalent on kiwifruit vines in other countries. To this end we interrogated an unpublished set of *gltA* sequences from *P. syringae* strains collected from kiwifruit leaves in China (sampling as described in McCann et al. (2017), GenBank accession numbers: [MG674624](http://biorxiv.org/lookup/external-ref?link\_type=GEN&access_num=MG674624&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) – [MG674645](http://biorxiv.org/lookup/external-ref?link_type=GEN&access_num=MG674645&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom)). A phylogenetic tree based on *gltA* for NZ, Japanese and Chinese kiwifruit isolates revealed that isolates obtained from Chinese kiwifruit also clustered within PG3a (Figure 3). Interestingly, included in this group is isolate 47L9, which was collected from tea leaves (Camellia sp.) growing in a former kiwifruit orchard in China. No other *P. syringae* strain from the PAMDB database grouped with PG3a, suggesting PG3a is persistently associated with kiwifruit on a global scale.

![Figure 3.](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2018/03/07/235853/F3.medium.gif)

[Figure 3.](http://biorxiv.org/content/early/2018/03/07/235853/F3)

Figure 3. Global Bayesian tree reconstructed from *gltA* sequences highlighting the particularity of PG3a, which includes kiwifruit isolates from NZ, China, Japan, the US and France.
The tree was built on a 529 bp alignment using MrBayes (TN+G+I model; 1,700,000 MCMC), using *Pseudomonas fluorescens* SBW25 as outgroup. Values indicated at nodes are Bayesian posterior probabilities. The source of each isolate is highlighted in colour-coded boxes, green = this study, red = China, black = PAMDB, purple = Japan, blue = US, NZ and France.

### Ecological interactions between PG3a and PG1

To assess whether kiwifruit-associated PG3a strains are stably maintained with *Psa* (PG1), co-inoculation experiments were performed *in vitro* and in planta. Two isolates sampled from the same leaf were chosen for these experiments: *P. syringae* G33C (ST1, PG3a) and *Psa* NZ54 (ST904, PG1).

### In vitro *dynamics*

*Psa* NZ54 and *P. syringae* G33C showed similar growth dynamics when grown individually *in vitro* (Figure 4). However, when co-inoculated in liquid King’s B (KB) media at an equal starting ratio, *Psa* NZ54 growth was significantly reduced (up to 100-fold) at 24 h (*P* <0.001, paired *t*-tests). This effect was amplified in shaken liquid minimal M9 medium, which better approximates nutrient poor conditions in the leaf compared to KB medium (Hernández-Morales et al., 2009): *Psa* NZ54 population density collapsed by 20 h in shaken M9 media (relative fitness −12.1 ±0.09, Figure 4).

![Figure 4.](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2018/03/07/235853/F4.medium.gif)

[Figure 4.](http://biorxiv.org/content/early/2018/03/07/235853/F4)

Figure 4. Individual growth dynamics of *Psa* NZ54 and *P. syringae* G33C compared with co-inoculation (1:1 ratio) *in vitro*.
Competition experiments were performed in a 1:1 ratio (founding ratio 5×106 cfu ml−1 each), with individual inoculations as reference. Solid lines represent individual growth and dashed lines represent growth in competition. The presented mean and standard error were calculated from three replicates. Asterisk indicate significance between individual and co-cultured growth at the 5% level (paired *t-*test).

In order to establish whether the instability of the interaction was influenced by the ratio of founder cells, we investigated whether *P. syringae* G33C could invade from rare initial frequency. A strain is able to invade from rare when it increases relative to its founding density. *P. syringae* G33C successfully invaded from rare after only 24 h in both rich KB and minimal M9 media (10:1 *Psa* NZ54: *P. syringae* G33C) and reached a similar population size as when cultured on its own in M9 (Figure 5A). Conversely, *Psa* NZ54 also invaded *P. syringae* G33C from rare (1:10 *Psa* NZ54: *P. syringae* G33C), though it established a 100-fold reduced population size of 105 - 106 cfu ml−1 compared to growth alone. The population collapse of *Psa* NZ54 in shaken M9, as observed for the 1:1 competition experiments, was once again observed (Figure 5B). The striking suppression of *Psa* NZ54 by *P. syringae* G33C was unambiguously repeated across three experiments. *P. syringae* G33C outcompetes *Psa* NZ54, though both isolates can invade from rare *in vitro* (with the exception of *Psa* NZ54 in shaken M9), which suggests that in a controlled environment the polymorphism is stable.

![Figure 5.](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2018/03/07/235853/F5.medium.gif)

[Figure 5.](http://biorxiv.org/content/early/2018/03/07/235853/F5)

Figure 5. *In vitro* growth curves from invasion from rare experiments for *Psa* NZ54: *P. syringae* G33C and vice versa.
Vials were inoculated with a (A) 10:1 ratio and (B) 1:10 ratio for *Psa* NZ54: *P. syringae* G33C. The presented mean and standard error were calculated from three replicates. Parameters of relative fitness of *Psa* NZ54 relative to *P. syringae* G33C calculated as ln difference *Psa* NZ54 – *P. syringae* G33C using the Malthusian parameters at 24hrs were −2.1* ±0.02 (KB shaken), −1.9*±0.05 (KB static), −12.1*±0.09 (M9 shaken) and −3.9*±0.00 (M9 static). Asterisks indicate significance at the 1% level (Students *t*-test).

### In planta *dynamics*

*In planta* experiments were performed on two gold cultivars, ‘Hort16A’ and ‘SunGold’, to determine whether *Psa* NZ54 and *P. syringae* G33C also form a stable polymorphism on kiwifruit leaves. *P. syringae* G33C established an epiphytic and endophytic population size in both cultivars (Figure 6) and did not produce any visible symptoms in ‘Hort16A’ and ‘SunGold’ (Figure S5, Figure S6). *Psa* NZ54 attained a population size at least 10,000-fold greater than *P. syringae* G33C in both hosts. However, endophytic and epiphytic growth were reduced 10-fold in ‘SunGold’ compared to ‘Hort16A’ (*P* <0.05, Mann-Whitney U test). Plants inoculated with *Psa* NZ54 developed the first leaf spots at 4 dpi and exhibited severe symptoms at 7 dpi in the more susceptible ‘Hort16A’, whereas in ‘SunGold’ leaves displayed only minor symptoms at 7 dpi.

![Figure 6.](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2018/03/07/235853/F6.medium.gif)

[Figure 6.](http://biorxiv.org/content/early/2018/03/07/235853/F6)

Figure 6. 1:1 competition growth assays of *Psa* NZ54 vs. *P. syringae* G33C *in planta*.
‘Hort16A’ plantlets (A) and ‘SunGold’ plantlets (B) were inoculated with a 1:1 mix of *P. syringae* G33C: *Psa* NZ54 (founding density 8×107 cfu ml−1). (C) ‘SunGold’ plants were inoculated with 1:1 mix of *P. syringae* G33C: *Psa* NZ13 Δ*hrcC* (founding density 8×107 cfu ml−1). Solid lines represent individual growth and dashed lines represent growth in competition. The presented mean and standard error were calculated from the mean of four (‘Hort16A’) and five (‘SunGold’) individual measurements. Asterisk indicate significance between individual and co-cultured growth at the 5% level (paired *t-*test).

In 1:1 competition experiments non-pathogenic *P. syringae* G33C maintained a stable population size. The presence of *Psa* NZ54 had a highly significant positive effect on the growth of *P. syringae* G33C in both plant hosts (Figure 6A&B). *P. syringae* G33C established up to 1000-fold higher epiphytic population densities in ‘Hort16A’ (*P* <0.01, paired *t*-tests) and 10-fold higher epiphytic and endophytic population densities in ‘SunGold&’ plants (*P* <0.05, paired *t*-test) compared to its individual growth. Co-inoculated *Psa* NZ54 exhibited a significant reduction (*P* <0.05, paired *t*-test) in epiphytic and endophytic growth on ‘Hort16A’ in the presence of *P. syringae* G33C, but only in the early stages of the experiment. On ‘SunGold’ the diminished growth of *Psa* NZ54 was more pronounced, with a 100-fold decrease for the endophytic population at 7 dpi (*P* <0.05, paired *t*-test, Figure 6B). Co-inoculated ‘Hort16A’ plants exhibited a notable delay in symptom onset compared to singly inoculated plants (Figure S5), whereas there was no difference for ‘SunGold’ (Figure S6). The increased fitness of *Psa* NZ54 relative to *P. syringae* G33C in ‘Hort16A’ competition experiments was reflected in the relative fitness parameters (0.7± 0.1* for epiphytic and 4.9± 0.8* for endophytic, * *P* <0.05, *t*-test), whereas in ‘SunGold’ plants *P. syringae* G33C performed better in the epiphytic environment (−1.6 ± 0.2; 4.7 ± 0.1* for endophytic growth).

To assess whether the heightened growth of *P. syringae* G33C in the presence of *Psa* NZ54 was due to the virulence activity of the pathogen elicited by the Type 3 Secretion System (T3SS), the competition experiment was performed using a T3SS deficient mutant (*Psa* NZ13 Δ*hrcC*). Epiphytic growth of *P. syringae* G33C on ‘SunGold’ remained elevated when co-inoculated with *Psa* NZ13 Δ*hrcC*, indicating the virulence activity encoded by the T3SS was not responsible for the advantage conferred to the non-pathogenic strain (*P* <0.05, paired *t*-test, Figure 6C).

A rarity threshold for *P. syringae* G33C determines the ability to establish a stable population in planta. Upon co-inoculation in a 100:1 (*Psa* NZ54: *P. syringae* G33C) ratio on ‘Hort16A’, *P. syringae* G33C was able to invade from rare over the first 4 days, but was then excluded by *Psa* NZ54 (Figure 7B). An initial increase in growth of *P. syringae* G33C from 0 dpi to 4 dpi was followed by a population collapse at 7 dpi with no endophytic growth detected and minimal epiphytic growth in environments dominated by *Psa* NZ54. Conversely, *Psa* NZ54 grew to the same population size in the presence of *P. syringae* G33C, as when inoculated individually (*P* >0.1, paired *t*-tests).

![Figure 7.](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2018/03/07/235853/F7.medium.gif)

[Figure 7.](http://biorxiv.org/content/early/2018/03/07/235853/F7)

Figure 7. Invasion from rare experiments for *Psa* NZ54: *P. syringae* G33C *in planta*.
‘Hort16A’ plantlets were inoculated with different ratios of strains *Psa* NZ54: *P. syringae* G33C. A) Individual growth. B) Invasion from rare 100:1 and C) invasion from rare 1:100. Solid lines represent individual growth and dashed lines represent growth in competition. The presented mean and standard error were calculated from the mean of four individual measurements. Asterisks indicate significance between individual and co-cultured growth at the 5#x0025; level (paired *t-*test).

In the reciprocal experiment (1:100 *Psa* NZ54: *P. syringae* G33C), *Psa* NZ54 successfully invaded from rare in both the endophytic and epiphytic environment, although the rate of invasion was reduced on the leaf surface. However, both epi- and endophytic population sizes were significantly reduced compared to single inoculations (*P* <0.01, paired *t*-tests) (Figure 7). Despite the growing population of *Psa* NZ54, *P. syringae* G33C maintained the same epiphytic population size as when inoculated individually (*P* >0.2, paired *t*-tests). The endophytic population size of *P. syringae* G33C increased (*P* <0.01, 7dpi, paired *t*-test), which mirrored the results from the 1:1 competition experiments, where the presence of *Psa* NZ54 also had a positive effect on growth of *P. syringae* G33C.

In order to establish whether there was an advantage to being an early colonist, a time-stagger experiment was performed to see whether immigration history influences the interaction (Fukami et al., 2007). ‘Hort16A’ plants were pre-inoculated with either of the two strains and followed by a subsequent inoculation of the other strain after three days. Early colonization provided no advantage to *Psa* NZ54 (Figure 8A), as *P. syringae* G33C maintained and established a stable population by 7 dpi and exhibited no significant difference in growth compared to individual growth (*P* >0.3, paired *t*-tests). Reducing the secondary inoculation density resulted in a reduced initial population size at 3 and 7 dpi for *P. syringae* G33C (*P* <0.05, paired *t*-tests), but by 10 dpi the level was the same as when the two strains were grown individually (Figure S7C).

![Figure 8.](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2018/03/07/235853/F8.medium.gif)

[Figure 8.](http://biorxiv.org/content/early/2018/03/07/235853/F8)

Figure 8. In planta priority effect of *Psa* NZ54 or P. syingae G33C with subsequent inoculation of the respective second strain with the same founding density.
(A) *In planta* growth assay of *P. syringae* G33C using ‘Hort16A’ plantlets pre-inoculated for three days with *Psa* NZ54 (8×107 cfu ml−1). (B) *in planta* growth assay of *Psa* NZ54 using ‘Hort16A’ plantlets pre-inoculated for three days with *P. syringae* G33C (8×107 cfu ml-1). Solid lines represent individual growth and dashed lines represent growth in competition. The presented mean and standard error were calculated from the mean of five individual measurements. Asterisks indicate significance between individual and co-cultured growth at the 5#x0025; level (paired *t-*test).

When *P. syringae* G33C was the first colonist (Figure 8B) *Psa* NZ54 grew to the same population size by 7 dpi as compared to individually inoculated plants (*P* >0.5, paired *t*-tests). The growth of *Psa* NZ54 was initially lower compared to individual growth when inoculated at a lower density (*P* <0.05, paired *t*-tests), but this difference was no longer evident for the epiphytic population by 10 dpi (Figure S7B).

## DISCUSSION

Studies of pathogen populations rarely take into consideration co-occurring commensal types and yet such types are likely to be important contributors to population structure and infection progress (Lindow and Brandl, 2003; Demba Diallo et al., 2012; Bartoli et al., 2015; Buonaurio et al., 2015; Rufián et al., 2017). Here, with focus on P. syringae, we have combined traditional population genetic approaches with experiments designed to investigate interactions among members of an ecologically cohesive population. The most significant findings include (i) a clonal population structure for commensal kiwifruit *P. syringae* (ii) strong association of genetic diversity with ecological factors, (iii) discovery of a new clade of kiwifruit-associated kiwifruit *P. syringae* within PG3 (PG3a) (Figure 2, Figure 3), (iv) complex interactions between the pathogenic *Psa* isolate and PG3a with evidence of a stable polymorphism under some *in vitro* conditions, but not in planta (Figure 4, Figure 6).

Overall, we found that *P. syringae* from kiwifruit display a clonal population structure, comprised of two clonal complexes and a small number of abundant STs. This is in accordance with earlier reports of clonal population structure for P. syringae, despite focus on pathogenic isolates which tend to undergo clonal expansion upon host specialisation (Sarkar and Guttman, 2004). Homologous recombination events are few and limited to within phylogroups for P. syringae, which is also supported by well-defined phylogenetic clades (Baltrus et al., 2011; Bull et al., 2011; Berge et al., 2014; Nowell et al., 2016). A more fine-scale analysis of a collection of *Pseudomonas viridiflava* (now *P. syringae* PG7 and PG8 (Bartoli et al., 2014; Berge et al., 2014)) isolated from Arabidopsis thaliana suggests that recombination at the phylogroup level is primarily within-clade rather than between clade (Goss et al., 2005). Apart from the occurrence of recombination at the local scale, evidence of recombination has also been shown between crop strains and environmental isolates (Monteil et al., 2013).

Genetic diversity varied according to ecological factors, most strikingly for *P. syringae* collected from infected orchards, where genetic diversity was highest. This may reflect effects of *Psa* on the kiwifruit immune response, which may facilitate migration of leaf colonists into the apoplast and vascular tissues and thus allow access to water and nutrients. Such effects have been reported for infection of potatoes by *Pectobacterium atrosepticum* (Kõiv et al., 2015) and herbivore-damaged bitter cress leaves (*Cardamine cordifolia*) (Humphrey et al., 2014), where in both instances Pseudomonas population densities and diversity increased following plant damage.

We observed differences in *P. syringae* genetic diversity that appear to be attributable to differences in plant genotypes. Host species and cultivar identity is known to significantly affect the composition of phyllosphere bacterial communities (Adams and Kloepper, 2002; Van Overbeek and Van Elsas, 2008; Whipps et al., 2008; Bodenhausen et al., 2014; Laforest-Lapointe et al., 2016; Wagner et al., 2016). Differences in phyllosphere *P. syringae* diversity may also be influenced by environmental factors (such as humidity, nutrient availability or UV radiation) and orchard management practices. Different fertilizer and spray regimes (copper, antibiotics, ActigardTM and biological agents) are employed by growers to prevent or manage *Psa* infection throughout the growing season ([http://www.kvh.org.nz/vdb/document/99346](http://www.kvh.org.nz/vdb/document/99346)). These practices may have selected for copper and streptomycin resistance in *Psa* and kiwifruit epiphytes in NZ and elsewhere (Han et al., 2003; Colombi et al., 2017; Petriccione et al., 2017).

Strains grouping with four major phylogroups (PG1, PG2, PG3, PG5) were recovered. This level of diversity in a cultivated environment is not surprising (Goss et al., 2005; Bull et al., 2011; Kniskern et al., 2011; Beiki et al., 2016; Hall et al., 2016). Two clades of endophytic *P. syringae* pv. syringae were recovered from symptomatic grapevines in Australia with pathogenic and non-pathogenic isolates clustering together (Hall et al., 2016). Samples obtained from citrus orchards suffering from citrus blast caused by *P. syringae* pv. syringae revealed isolates associated with PG2, PG7 and an unknown clade (Beiki et al., 2016). Two distinct and highly divergent subclades of Pseudomonas viridiflava (*P. syringae* PG7) were recovered from a global sampling of wild A. thaliana (Goss et al., 2005).

The newly recognised PG3a subclade of *P. syringae* appear to colonise kiwifruit leaves not only in NZ (dating back to 2010 (Visnovsky et al., 2016)), but also in other kiwifruit growing regions of the world, including Japan and China. Data from leaf samples indicate that PG3a is not displaced by *Psa*, but the total number of PG3a isolates collected is reduced in infected orchards. Interestingly the diversity of PG3a does not seem to be affected by infection status. Strains clustering with PG3a formed the majority (>50%) of kiwifruit isolates, and these have not yet been isolated from any other plant hosts recorded in PAMDB, with the exception of isolate 47L9, collected from tea leaves (*Camellia* sp.) growing in a former kiwifruit orchard. This indicates that PG3a forms a persistent association with kiwifruit plants – an observation that is further supported by the repeated isolation of PG3a from kiwifruit across large geographic distances, suggests that PG3a may have been coevolving with its host for some time. PG3a is thus also likely to be disseminated with the exchange of plant material (such as pollen or plant cuttings) between kiwifruit growing countries. The prevalence of PG3a in other kiwifruit growing countries (e.g. Korea, France or Italy) is at present unknown. The preferential occurrence of PG3 with woody hosts (Bartoli et al., 2015; Nowell et al., 2016) could explain the particular grouping of the kiwifruit resident clade within PG3. A similarly intriguing signal of host association was found in a collection of *P. syringae* isolates from A. thaliana, where PG2 representatives dominated (Kniskern et al., 2011; Karasov et al., 2017). Distinct lineages of non-pathogenic isolates have also been described for other plant pathogens such as *Xanthomonas arboricola*, where non-pathogenic strains are distant relatives of pathogenic lineages, despite being isolated from the same host (Essakhi et al., 2015; Triplett et al., 2015).

The kiwifruit commensal *P. syringae* G33C (representative of the PG3a subclade) successfully colonized the leaf surface and apoplast of kiwifruit without production of visible disease symptoms. This is reflected in the population size, which was reduced by 4-logs compared to pathogenic population size of *Psa* at 3 dpi. Similar population sizes have been reported for *P. syringae* pv. *phaseolicola*, which grows to a four-log higher population size on its host plant *Phaseolus vulgaris* compared to a non-pathogenic isolate; a 4-log reduction was also observed in resistant vs susceptible hosts (Omer and Wood, 1969; Young, 1974). Similar observations have been made for other plant pathogens, for example non-pathogenic *Xanthomonas* sp. displays a 4-log reduced growth compared to the disease-causing X. *oryzae* pv. *oryzae* (Triplett et al., 2015). Bacterial population density appears to be directly related to the production of disease symptoms, as was demonstrated for environmental *P. syringae* strains inoculated in kiwifruit, which grew to near pathogen population size levels, but induced symptoms of disease (Bartoli et al., 2015).

When grown in competition with *Psa* NZ54, *P. syringae* G33C population size increased. Studies exploring the dynamics of mixed infections have demonstrated inoculum density-dependent effects on colonization (Young, 1974; Macho et al., 2007). The ability of non-pathogenic *P. syringae* to colonize wider territories in the presence of a pathogenic strain was nicely demonstrated in a confocal microscopy study (Rufián et al., 2017). It is possible that *P. syringae* G33C benefits from the virulence activity of *Psa* NZ54. T3SS-dependent hitch-hiking effects have been observed for *P. syringae* pv. *syringae* (Hirano et al., 1999), however the increase in *P. syringae* G33C growth persists even in the absence of a functional T3SS in the pathogenic *Psa* strain. Virulence activities not encoded by the T3SS, such as phytotoxin production, may be responsible for this outcome.

Epiphytic and *in vitro* growth of *Psa* NZ54 was significantly reduced when co-inoculated with *P. syringae* G33C. Similarly, *Psa* growth may be suppressed by co-inoculation with environmental isolates of *P. syringae* (Bartoli et al., 2015). Epiphytes may suppress pathogen growth either as direct antagonists or indirectly via resource competition (Wilson and Lindow, 1994). The specific mechanism by which *P. syringae* G33C suppresses *Psa* remains undetermined. The *Psa* NZ54 population collapse in shaken M9 was delayed at 10:1 inoculation ratios, which suggests that this effect was most likely due to the accumulation of antimicrobial compounds produced by *P. syringae* G33C. Phytotoxin production is widespread among fluorescent pseudomonads with some toxins having antimicrobial activity that can be induced dependent on culture conditions (still vs. shaken) *in vitro* (Durbin, 1982; Bender et al., 1999). Contact-dependant growth inhibition (CDI) via Type 5 and 6 secretion systems or bacteriocins may also mediate *P. syringae* interactions (Hayes et al., 2010; Haapalainen et al., 2012; Ruhe et al., 2013; Hockett et al., 2015).

Our in-depth localised sampling has revealed a global association of PG3a with kiwifruit. Additionally, we have shown that this clade of non-pathogenic *P. syringae* engage in complex interactions with pathogenic *Psa*. This highlights the value of understanding genotypic diversity and ecological interactions among pathogens and non-pathogens in field settings. Clarifying how commensals persist in association with specific hosts over long periods without causing disease and the mechanism by which they modulate pathogen invasion and proliferation will contribute to a fuller understanding of plant-microbe interactions.

## EXPERIMENTAL PROCEDURES

### Plant tissue collection and bacterial isolation

The sampling scheme was designed to obtain strains from *Psa* infected and uninfected hosts, irrespective of disease stage (symptom development) or pathogenicity potential of the isolate. *P. syringae* was isolated from the leaf surfaces of two different cultivars of *Actinidia chinensis*: *A. chinensis* var. *chinensis* Hort16A (gold) and A. *chinensis* var. *deliciosa* Hayward (green), which vary in their susceptibility to *Psa*: ‘Hort16A’ is more susceptible than the green ‘Hayward’ (Ferrante and Scortichini, 2010; Cameron and Sarojini, 2014). One infected and one uninfected orchard of each variety was sampled by collecting three leaves from six separate vines along a diagonal path of ∼400m (Table S1). Sampling occurred at three intervals during the growing season: spring (after bud break), summer and autumn (prior to harvest). Vine trunks and canes (secondary branches) were tagged to ensure resampling of the same spot. Some ‘Hort16A’ canes were removed during routine disease management; neighbouring canes on the same vine were then sampled and tagged. All uninfected Hayward vines were cut down prior to the last sampling day so the adjoining block of Hayward was sampled instead. The location of each sampled orchard is listed in Table S2.

Leaves were individually placed in 50 mL conical centrifuge tubes and washed with 40 mL 10mM MgSO4 buffer supplemented with 0.2 #x0025; Tween (Invitrogen, US) by alternately shaking and vortexing at slow speed for 3 min. After removing the leaf, the leaf wash was centrifuged at 4600 rpm for 10 min. The supernatant was removed and the pellet was resuspended in 200 μL 10mM MgSO4. 100 μL of the resuspension was stored at −80°C and 100 μL was plated on *Pseudomonas* agar base (Oxoid, UK) supplemented with 10 mg/L cetrimide, 10 mg/L fucidin and 50 mg/L cephalosporin (CFC supplement, Oxoid, UK). For each leaf two isolates exhibiting *P. syringae* colony morphology (round, creamy white) were selected randomly from the plate and restreaked, then used to inoculate liquid overnight cultures for storage at −80°C. Isolates were tested for the absence of cytochrome C oxidase using Bactident Oxidase strips (Merck KgaA, Germany), characteristic of P. syringae. A total of 148 *P. syringae* isolates were obtained from the four orchards (Table S1).

### PCR amplification & sequencing

A lysate was prepared for each isolate by resuspending a colony in 100 μL ddH20 and lysing the cells at 96°C for 10 min. Strains were sequenced using the Hwang et al. (2005) MLST scheme for four housekeeping genes *gapA, gyrB, gltA (=cts)* and *rpoD* (reverse). Due to amplification problems, the forward primer for *rpoD* from Sarkar and Guttman (2004) was used. PCR amplification was performed with a BIO-RAD T100 Thermal Cycler following an adapted protocol of Hwang et al. (2005): a total reaction volume of 50 μl with a final concentration of 1x PCR buffer (Invitrogen, US), 1 μM for each primer, 0.2 mM dNTP’s (Bioline, UK), 1 U Taq Polymerase (Invitrogen, US), 1 μl lysed bacterial cells, 2% DMSO (Sigma-Aldrich, US) and 1.5 mM MgCl2. Initial denaturation was at 94°C for 2 min, followed by 30 cycles of amplification with denaturation at 94°C for 30 s, annealing at 63°C for 30 s and elongation at 72°C for 1 min. Final elongation was for 3 min at 72°C. Samples were purified using the Exo-CIP method and sequenced by Macrogen Inc (South Korea). Sequence analysis was performed with Geneious v7.1.7 (Kearse et al., 2012). Sequences were trimmed to the same length (476 bp *gap1*, 507 bp *gyrB*, 529 bp *gltA*, 498 bp *rpoD*) and concatenated (201 0 bp) (GenBank accession numbers: *gapA* MG642149 - MG642296; *gyrB* MG642297 - MG642444; *gltA* MG642445 - MG642592; *rpoD* MG642593 - MG642740).

### Population genetics

#### Sequence diversity indices

A rarefaction analysis was performed using MOTHUR v.1.34.4 by subsampling using 1,000 iterations (Schloss et al., 2009). Pairwise genetic distances between isolates were calculated and sequences assigned to Operational Taxonomic Units (OTUs) based on the corresponding average pairwise genetic distance of each group.

Simpson’s index of diversity (D) and evenness (ED) (α-diversity) and Sørensen’s index of dissimilarity (β-diversity) were calculated using the *vegan* package (Oksanen et al., 2016) in R v3.3.1 (R.Core.Team, 2016). Simpson’s D was converted to the effective number of species (Dc) in order to account for the non-linear properties of Simpson’s index of diversity (Jost, 2006).

#### Multilocus Sequence Typing

Sequence types (STs) sharing three out of four alleles (SLV, single locus variants) were grouped using eBURST v3 (bootstrapped with 1,000,000 resamplings) (Feil et al., 2004; Spratt et al., 2004). A Minimum Spanning Tree providing an overview of triple locus variants was constructed using Phyloviz v2.0 (Francisco et al., 2012).

165 non-redundant ST profiles of *P. syringae* strains were downloaded from the Plant Associated and Environmental Microbes Database (PAMDB, [http://genome.ppws.vt.edu/cgi-bin/MLST/home.pl](http://genome.ppws.vt.edu/cgi-bin/MLST/home.pl)) (Almeida et al., 2010). *P. syringae* sequences isolated recently from kiwifruit and air in Japan (NCBI) and kiwifruit isolates from NZ, France and the United States (Visnovsky et al., 2016) were also included. A reduced set of 37 *P. syringae* isolates representing the different monophyletic groups of *P. syringae*, as well as the Japanese kiwifruit strains and the US, France and NZ kiwifruit isolates from previous years were used to provide better resolution in the phylogenies displayed in Figure 2, Figure 3 and Figure S4.

#### Sequence diversity and recombination

START2 (v0.9.0 beta) was employed to calculate parameters of genetic diversity, number of alleles and polymorphic sites, GC content and the ratio of non-synonymous to synonymous substitutions (*d**N*/*d**S* ratio) (Jolley et al., 2001). The number of mutations and amino acid changes and nucleotide diversity parameter π were calculated with DnaSP v. 5.10.1 (Rozas and Rozas, 1995). Jmodeltest 2.1.7 (Guindon and Gascuel, 2003; Darriba et al., 2012) was used with default parameter settings to find the best-fitting evolutionary model. Pairwise genetic variability among and between phylogroups was calculated using MEGA7 (Kumar et al., 2016).

To test whether genetic diversity varied by sampling location, time of sampling, orchard infection status and/or cultivar, a permutational multivariate analysis of variance (PERMANOVA) (Anderson, 2001; McArdle and Anderson, 2001) was performed using PRIMER v 6.1.12 (PRIMER-E Ltd., Plymouth, UK, PERMANOVA+ add-on v. 1.0.2.). Pairwise distances among unique STs were used as input and tests were run with 9999 permutations. Any effects due to unequal sample size were taken into account using the Type III SS (sum of squares) option.

LDHAT v2.2a (Auton and McVean, 2007) was used to estimate the rate of mutation (Watterson’s θ) and recombination (ρ) using the composite likelihood method of Hudson (Hudson, 2001) with an adaption to finite-site models. Only polymorphic sites with two alleles were included and the frequency cut-off for missing data was set to 0.2.

#### Phylogenetic reconstruction

Trees were built using single representatives of each unique ST from this study to improve readability of the tree. MrBayes v.3.2 (Ronquist et al., 2012) was used to construct Bayesian trees, using the best-fitting evolutionary model (jModeltest) for individual genes and the concatenated alignment. Single gene trees (Figure S4) were constructed with TREEPUZZLE (Schmidt et al., 2002) and Dnaml (PHYLIP v3.695, Felsenstein 1989) was used to test for congruence between single trees (SH-test) using default parameters, providing Maximum Likelihood trees as input and a random number seed of 333.

### Strains and culture conditions

A list of all bacterial strains used in this study can be found in Table S2. *Pseudomonas* strains were cultured in King’s B or minimal M9 media at 28°C and *E. coli* was cultured in Luria Bertani medium at 37°C. Liquid overnight cultures were inoculated from single colonies and shaken at 250 rpm for 16 hrs. The antibiotics kanamycin (kan) and nitrofurantoin (nf) were used at a concentration of 50 µg/ml. Kanamycin resistant *Psa* NZ54 and *Psa* NZ13 Δ*hrcC* were employed in all *in vitro* and *in planta* experiments. Both *Psa* strains belong to the same pandemic clade of *Psa* (biovar 3), and differ in three SNPs across the core genome as defined in McCann et al. (2017).

### Mutant development

*Psa* NZ13Δ*hrcC* was constructed by in-frame deletion of *hrcC* via marker exchange mutagenesis. Knockout construct was generated by overlap extension PCR (Ho et al., 1989) using the primers listed in Table S6. DNA was amplified from *Psa* NZ13 with Phusion® High-Fidelity DNA polymerase. The deletion construct was inserted into pK18mobsacB (Schäfer et al., 1994). The recombinant vector was transferred into *Psa* NZ13 via triparental mating, using as helper *E. coli* DH5α strain containing pRK2013. Mutants were selected by plating on KB kanamycin (50 µg/mL) and subsequently on KB containing 5#x0025; sucrose. Mutants were screened by PCR using external primers (Table S6) and the deletion was then confirmed by sequencing.

Triparental matings were performed to introduce a kanamycin resistant Tn*5* transposon into *Psa* NZ54 and *Psa* NZ13 Δ*hrcC*. *E. coli* S17-1 Tn*5hah Sgid1* (donor) (Zhang et al., 2015), *E. coli pRK2013* (helper) (Ditta et al., 1980) and *Psa* NZ54 or *Psa* NZ13 Δ*hrcC* (recipient) were grown in shaken liquid media overnight. 200 µ l of donor and helper and 2mL of recipient were individually washed, pelleted and combined in 30 µ l 10 mM MgCl2. The mixture was plated on a pre-warmed LB agar plate and incubated at 28°C for 24 hrs. The cells were scraped off and resuspended in 1 mL 10 mM MgCl2 and plated on KB plates supplemented with kanamycin and nitrofurantoin. Bacterial growth was compared to the wild type recipient in both KB and M9 media to ensure marker introduction did not result in a loss of fitness.

### Competition assays

The two isolates (*P. syringae* G33C and *Psa* NZ54) used for competition assays were isolated from the same leaf in a *Psa* infected orchard, reflecting co-occurrence of the strains in nature.

#### In vitro competition assays

Competition experiments were performed *in vitro* using rich (King’s B) and minimal (M9) media in a shaken and static environment. Competition experiments were performed in 1:1, 1:10 and 10:1 ratios for each of the four assay conditions. Liquid overnight cultures of each strain in KB were established from single colony inoculations. 30 mL vials with 4 mL of the appropriate media were inoculated with each strain, adjusted to a founding density of either 5×106 cfu ml−1 (OD600 0.006) or 4×104 cfu ml−1 (OD600 0.0004). Control vials were inoculated with a single strain, adjusted to 5×106 cfu ml−1. Cultures were incubated at 28°C and grown over a period of 72 hrs, either still or shaken at 250rpm. Bacterial density was calculated at 0, 24,48 and 72 hrs by plating dilutions on KB kan and M9 agar plates to distinguish between competing strains. The experiment was performed using three replicates and repeated three times.

#### In planta competition and pathogenicity assays

Epiphytic and endophytic growth of *Psa* NZ54, *Psa* NZ13 Δ*hrcC* and *P. syringae* G33C was evaluated on 4-week old kiwifruit plantlets using single and mixed-culture inoculation. Clonally propagated *A. chinensis* var. *chinensis* ‘Hort16A’ and ‘SunGold’ were grown for a minimum of one month in a Conviron CMP6010 growth cabinet at 21°C with a 14/10 hr light/dark cycle and 70#x0025; humidity. Bacterial strains were incubated for two days at 28°C on KB plates, after which they were resuspended in 10 mM MgSO4 buffer. Mixed inoculum (1:1, 1:100 and 100:1) was prepared in 50 mL 10 mM MgSO4 buffer and 0.002% Silwet-70 (surfactant), with strains adjusted to 8×107 cfu ml−1 (OD600 0.1) or 8×105 cfu ml−1 (OD600 0.001). Single strain plant inoculations were also performed using an initial 8×107 cfu ml−1 (OD6000.1).

Plants were inoculated by submerging leaves in the inoculum for 5 s and allowing to air-dry. Plants were returned to the growth cabinet and watered every second day. Bacterial density was assessed at either 0, 2, 4, 7 and 10 days post inoculation (dpi) or 0, 3, and 7 dpi (Δ*hrcC* competition experiments). Epiphytic growth was assessed by placing inoculated leaves in separate sterile plastic bags with 35 mL 10 mM MgSO4 buffer and shaking manually for 3 minutes. The leaf wash was centrifuged at 4600 rpm for 3 min and the supernatant discarded. Bacteria were resuspended in 200 µl buffer and serial dilutions plated on M9 and KB+kan agar plates.

Endophytic growth was assessed by removing one 1cm2 leaf disk per plant (including the midrib), surface sterilizing in 70% EtOH for 30 sec, drying and homogenising for 1 minute in a 1.5 mL Eppendorf tube containing 200 μl buffer and two metal beads with the TissueLyser II (QIAGEN). The plant homogenate was serially diluted and plated on M9 and KB+kan agar plates. All experiments were performed in duplicate, with at least 4 replicates per experiment.

### Statistical analysis

A Student’s *t*-test was used to verify the statistical difference where applicable. For non-normally distributed data with unequal variance, the Mann Whitney U test was performed.

The fitness of each strain in the competition experiments is expressed as the Malthusian parameter (Lenski et al., 1991). The Malthusian parameter was calculated as *M*= (*ln*(*N*1*f*1/*N*1*i*)) /(*ln*(*N*2*f*/*N*2*i*)), where *N*1*i* is initial number of cfu of strain 1 at 0h and *N*1*f* cfu after 24 hrs (*in vitro*) or 2/3 dpi (*in planta*, ‘Hort16A’/’SunGold’).

## BIOSECURITY AND APPROVAL

All worked was performed in approved facilities and in accord with APP201675, APP201730, APP202231.

## SUPPORTING INFORMATION

**Figure S1. Rarefaction curves based on the concatenated sequences.** Two curves each are shown for *P. syringae* (n=148) and the sequences grouped according to phylogroups (PG): solid lines represent grouping based on unique STs and dashed lines according to a cut-off equal to the average pairwise genetic distance of the group: PG1, PG2 & PG3 = 0.02 cut-off, Psyr all = 0.05 cut-off.

**Figure S2. Shared and unique STs among orchards.** Gold I = infected ‘Hort16A’; Gold NI= uninfected ‘Hort16A’; Green NI = uninfected ‘Hayward’; Green I = infected ‘Hayward’ orchard; n= number of STs found in orchard.

**Figure S3. eBurst snapshot of STs at the single locus variant level.** The size of the circles correlates with the frequency of the respective ST found in the dataset. Colours correspond to the different orchards, orange = infected ‘Hort16A’, yellow = uninfected ‘Hort16A, dark green = infected ‘Hayward’, light green = uninfected ‘Hayward’. CC = clonal complex.

**Figure S4. Maximum Likelihood trees based on single genes.** Each Maximum Likelihood tree is rooted on *Pseudomonas fluorescens* SBW 25 and was reconstructed using TREEPUZZLE based on the Tamura-Nei model using 100,000 puzzling steps. Trees were built using single representatives of each unique ST to improve readability of the tree. Values indicated at nodes are bootstrap values. The corresponding phylogroup distinctions based on the concatenated ML tree are indicated with the coloured squares.

**Figure S5. Leaves of ‘Hort16A’ plants inoculated with *Psa* NZ54, *P. syringae* G33C and a 1:1 mix of *Psa* NZ54: *P. syringae* G33C at 2, 4, and 7 days post inoculation.**

**Figure S6. Leaves of ‘SunGold’ plants inoculated with *Psa* NZ54, *P. syringae* G33C, *Psa* NZ13 ΔhrcC and 1:1 mix of the respective strain combinations at 3 and 7 days post inoculation**. For leaves showing minor leaf spots, the lower side of the leaf is also shown for easier detection of symptoms.

**Figure S7. *In planta* priority effect of *Psa* NZ54 or *P. syringae* G33C with subsequent inoculation of the second strain with 100-fold lower concentration.** *In planta* growth assay using ‘Hort16A’ plantlets pre-inoculated (8×107 cfu ml−1) with one strain followed by inoculation of the second strain at (8×105 cfu ml−1). The two panels display growth curves for endo- and epiphytic growth respectively. A) Individual growth, B) inoculation of *Psa* NZ 54 at day 3 and C) inoculation of *P. syringae* G33C at 3 dpi. Solid lines represent individual growth and dashed lines represent growth in competition. The presented mean and standard error were calculated from the mean of five individual measurements. Asterisks indicate significance between individual and co-cultured growth at the 5% level (paired *t-*test).

**Table S1. Geographic location of orchards, strain summaries and diversity indices per orchard.** Specification of cultivar and infection status at the time according to KVH (Kiwifruit Vine Health), orchard ID, GPS coordinates, location and month of sampling, N = number of collected *P. syringae* strains, N PG3a = number of PG3a strains in total sample, N STs = number of unique STs, N STs PG3a = number of unique STs grouping with PG3a, D = Simpsons index of diversity, Dc = converted to effective number of species, ED = Simpsons evenness.

**Table S2. List of all strains.** Strain information and assigned sequence type of strains used for MLST study (all) and strains used for phylogenetic analysis (highlighted in grey). Phylogroup association only provided for isolates used for phylogenetic analysis. Alias provides the name used for competition experiments.

**Table S3. PERMANOVA results of 3-factor nested analysis for differences in genetic diversity.**

**Table S4. LDhat recombination analysis for host and disease status.** Length of alignment in bp, number of sequences, number of segregating sites, mutation rate θ, recombination rate ρ and ratio ε (ρ/ θ).

**Table S5. LDhat recombination analysis for global data sorted according to phylogroup (PG)**. Length of alignment in bp, N = number of sequences, number of segregating sites, mutation rate θ, recombination rate ρ and ratio ε (ρ/ θ).

**Table S6. List of primers used for construction of the deletion mutant *Psa* NZ13 Δ*hrcC*.**

## ACKNOWLEDGEMENTS

We want to particularly thank kiwifruit growers David French, Rex Reed and Bruce and Fiona Aitken for granting access to their orchards. The work conducted was supported by the New Zealand Ministry for Business, Innovation and Employment (C11X1205). Christina Straub was supported through a PhD scholarship from the New Zealand Institute for Advanced Studies (NZIAS) and Plant & Food Research.

## Footnotes

*   * Joint senior authors

*   Received December 17, 2017.
*   Revision received March 6, 2018.
*   Accepted March 7, 2018.


*   © 2018, Posted by Cold Spring Harbor Laboratory

The copyright holder for this pre-print is the author. All rights reserved. The material may not be redistributed, re-used or adapted without the author's permission.

## REFERENCES

1.  Abelleira, A., López, M.M., Peñalver, J., Aguín, O., Mansilla, J.P., Picoaga, A., and García, M.J. (2011) First report of bacterial canker of kiwifruit Caused by Pseudomonas syringae pv. actinidiae in Spain. Plant Dis. 95: 1583.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1094/PDIS-06-11-0507&link_type=DOI) 

2.  Adams, P.D. and Kloepper, J.W. (2002) Effect of host genotype on indigenous bacterial endophytes of cotton (Gossypium hirsutum L.). Plant Soil 240: 181–189.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1023/A:1015840224564&link_type=DOI) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000176099300017&link_type=ISI) 

3.  Almeida, N.F., Yan, S., Cai, R., Clarke, C.R., Morris, C.E., Schaad, N.W., et al. (2010) PAMDB, a multilocus sequence typing and analysis database and website for plant-associated microbes. Phytopathology 100: 208–215.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1094/PHYTO-100-3-0208&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=20128693&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

4.  Anderson, M.J. (2001) A new method for non parametric multivariate analysis of variance. Austral Ecol. 26: 32–46.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1442-9993.2001.01070.pp.x&link_type=DOI) 

5.  Auton, A. and McVean, G. (2007) Recombination rate estimation in the presence of hotspots. Genome Res. 17: 1219–1227.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NjoiZ2Vub21lIjtzOjU6InJlc2lkIjtzOjk6IjE3LzgvMTIxOSI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

6.  Balestra, G.M., Mazzaglia, A., Spinelli, R., Graziani, S., Quattrucci, A., and Rossetti, A. (2008) Cancro batterico su Actinidia chinensis. L’informatore Agrar. 38: 75–76.
    
    

7.  Baltrus, D.A., Nishimura, M.T., Romanchuk, A., Chang, J.H., Mukhtar, M.S., Cherkis, K., et al. (2011) Dynamic evolution of pathogenicity revealed by sequencing and comparative genomics of 19 Pseudomonas syringae isolates. PLoS Pathog. 7: e1002132.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1371/journal.ppat.1002132&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=21799664&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

8.  Bartoli, C., Berge, O., Monteil, C.L., Guilbaud, C., Balestra, G.M., Varvaro, L., et al. (2014) The Pseudomonas viridiflava phylogroups in the P. syringae species complex are characterized by genetic variability and phenotypic plasticity of pathogenicity-related traits. Environ. Microbiol. 16: 2301–2315.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/1462-2920.12433&link_type=DOI) 

9.  Bartoli, C., Lamichhane, J.R., Berge, O., Guilbaud, C., Varvaro, L., Balestra, G.M., et al. (2015) A framework to gauge the epidemic potential of plant pathogens in environmental reservoirs: the example of kiwifruit canker. Mol. Plant Pathol. 16: 137–49.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/mpp.12167&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=24986268&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

10. Beiki, F., Busquets, A., Gomila, M., Rahimian, H., Lalucat, J., and García-Valdés, E. (2016) New Pseudomonas spp. are pathogenic to citrus. PLoS One 11: e0148796.
    
    

11. Bender, C.L., Alarcon-Chaidez, F., Gross, D.C., Alarcón-Chaidez, F., and Gross, D.C. (1999) Pseudomonas syringae phytotoxins: Mode of action, regulation, and biosynthesis by peptide and polyketide synthetases. Microbiol. Mol. Biol. Rev. 63: 266–292.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoibW1iciI7czo1OiJyZXNpZCI7czo4OiI2My8yLzI2NiI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

12. Berge, O., Monteil, C.L., Bartoli, C., Chandeysson, C., Guilbaud, C., Sands, D.C., and Morris, C.E. (2014) A user’s guide to a data base of the diversity of Pseudomonas syringae and its application to classifying strains in this phylogenetic complex. PLoS One 9: e105547.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1371/journal.pone.0105547&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=25184292&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

13. Berlec, A. (2012) Novel techniques and findings in the study of plant microbiota: Search for plant probiotics. Plant Sci. 193–194: 96–102.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1016/j.plantsci.2012.05.010&link_type=DOI) 

14. Bodenhausen, N., Bortfeld-Miller, M., Ackermann, M., and Vorholt, J.A. (2014) A Synthetic Community Approach Reveals Plant Genotypes Affecting the Phyllosphere Microbiota. PLoS Genet. 10: e1004283.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1371/journal.pgen.1004283&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=24743269&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

15. Bull, C.T., Clarke, C.R., Cai, R., Vinatzer, B.A., Jardini, T.M., and Koike, S.T. (2011) Multilocus sequence typing of Pseudomonas syringae sensu lato confirms previously described genomospecies and permits rapid identification of P. syringae pv. coriandricola and P. syringae pv. apii causing bacterial leaf spot on parsley. Phytopathology 101: 847–858.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1094/PHYTO-11-10-0318&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=21323469&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

16. Buonaurio, R., Moretti, C., da Silva, D.P., Cortese, C., Ramos, C., and Venturi, V. (2015) The olive knot disease as a model to study the role of interspecies bacterial communities in plant disease. Front. Plant Sci. 6: 1–12.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.3389/fpls.2015.00385&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=25653664&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

17. Cameron, A. and Sarojini, V. (2014) Pseudomonas syringae pv. actinidiae: chemical control, resistance mechanisms and possible alternatives. Plant Pathol. 63:.
    
    

18. Colombi, E., Straub, C., Künzel, S., Templeton, M.D., McCann, H.C., and Rainey, P.B. (2017) Evolution of copper resistance in the kiwifruit pathogen Pseudomonas syringae pv. actinidiae through acquisition of integrative conjugative elements and plasmids. Environ. Microbiol. 19: 819–832.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/1462-2920.13662&link_type=DOI) 

19. Darriba, D., Taboada, G.L., Doallo, R., and Posada, D. (2012) ModelTest 2: more models, new heuristics and parallel computing. Nat. Methods 9: 772–772.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/nmeth.2109&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22847109&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

20. Demba Diallo, M., Monteil, C.L., Vinatzer, B.A., Clarke, C.R., Glaux, C., Guilbaud, C., et al. (2012) Pseudomonas syringae naturally lacking the canonical type III secretion system are ubiquitous in nonagricultural habitats, are phylogenetically diverse and can be pathogenic. ISME J. 6: 1325–1335.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/ismej.2011.202&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22237542&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

21. Ditta, G., Stanfield, S., Corbin, D., and Helinski, D.R. (1980) Broad host range DNA cloning system for gram-negative bacteria: construction of a gene bank of Rhizobium meliloti. Proc. Natl. Acad. Sci. 77: 7347–7351.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMDoiNzcvMTIvNzM0NyI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

22. 1.  Mount, M.S. and 
    2.  Lacy, G.H.
    
    Durbin, R.D. (1982) Toxins and Pathogenesis. In, Mount, M.S. and Lacy, G.H. (eds), Phytopathogenic Prokaryotes Vol 1. Academic Press, pp. 423–439.
    
    

23. Essakhi, S., Cesbron, S., Fischer-Le Saux, M., Bonneau, S., Jacques, M.A., and Manceau, C. (2015) Phylogenetic and variable-number tandem-repeat analyses identify nonpathogenic Xanthomonas arboricola lineages lacking the canonical type III secretion system. Appl. Environ. Microbiol. 81: 5395–5410.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYWVtIjtzOjU6InJlc2lkIjtzOjEwOiI4MS8xNi81Mzk1IjtzOjQ6ImF0b20iO3M6Mzc6Ii9iaW9yeGl2L2Vhcmx5LzIwMTgvMDMvMDcvMjM1ODUzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

24. Everett, K.R., Taylor, R.K., Romberg, M.K., Rees-George, J., Fullerton, R.A., Vanneste, J.L., and Manning, M.A. (2011) First report of Pseudomonas syringae pv. actinidiae causing kiwifruit bacterial canker in New Zealand. Australas. Plant Dis. Notes 6: 67–71.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1007/s13314-011-0023-9&link_type=DOI) 

25. Feil, E.J., Li, B.C., Aanensen, D.M., Hanage, W.P., and Spratt, B.G. (2004) eBURST: inferring patterns of evolutionary descent among clusters of related bacterial genotypes from Multilocus Sequence Typing Data. J. Bacteriol. 186: 1518–1530.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MjoiamIiO3M6NToicmVzaWQiO3M6MTA6IjE4Ni81LzE1MTgiO3M6NDoiYXRvbSI7czozNzoiL2Jpb3J4aXYvZWFybHkvMjAxOC8wMy8wNy8yMzU4NTMuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9) 

26. Felsenstein, J. (1989) Phylip: phylogeny inference package (version 3.2). Cladistics 5: 164–166.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.l096-0031.1989.tb00562.x&link_type=DOI) 

27. Ferrante, P. and Scortichini, M. (2010) Molecular and phenotypic features of Pseudomonas syringae pv. actinidiae isolated during recent epidemics of bacterial canker on yellow kiwifruit (Actinidia chinensis) in central Italy. Plant Pathol. 59: 954–962.
    
    

28. Francisco, A.P., Vaz, C., Monteiro, P.T., Melo-Cristino, J., Ramirez, M., and Carriço, J.A. (2012) PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods. BMC Bioinformatics 13: 87.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1186/1471-2105-13-87&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22568821&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

29. Fujikawa, T. and Sawada, H. (2016) Genome analysis of the kiwifruit canker pathogen Pseudomonas syringae pv. actinidiae biovar 5. Sci. Rep. 6:.
    
    

30. Fukami, T., Beaumont, H.J.E., Zhang, X.-X., and Rainey, P.B. (2007) Immigration history controls diversification in experimental adaptive radiation. Nature 446: 436–439.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/nature05629&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=17377582&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000245079500039&link_type=ISI) 

31. Goss, E.M., Kreitman, M., and Bergelson, J. (2005) Genetic diversity, recombination and cryptic clades in Pseudomonas viridiflava infecting natural populations of Arabidopsis thaliana. Genetics 169: 21–35.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6ODoiZ2VuZXRpY3MiO3M6NToicmVzaWQiO3M6ODoiMTY5LzEvMjEiO3M6NDoiYXRvbSI7czozNzoiL2Jpb3J4aXYvZWFybHkvMjAxOC8wMy8wNy8yMzU4NTMuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9) 

32. Guindon, S. and Gascuel, O. (2003) A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52: 696–704.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1080/10635150390235520&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=14530136&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000185732500010&link_type=ISI) 

33. Haapalainen, M., Mosorin, H., Dorati, F., Wu, R.F., Roine, E., Taira, S., et al. (2012) Hcp2, a secreted protein of the phytopathogen Pseudomonas syringae pv. tomato DC3000, is required for fitness for competition against bacteria and yeasts. J. Bacteriol. 194: 4810–4822.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MjoiamIiO3M6NToicmVzaWQiO3M6MTE6IjE5NC8xOC80ODEwIjtzOjQ6ImF0b20iO3M6Mzc6Ii9iaW9yeGl2L2Vhcmx5LzIwMTgvMDMvMDcvMjM1ODUzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

34. Hall, S.J., Dry, I.B., Blanchard, C.L., and Whitelaw-Weckert, M.A. (2016) Phylogenetic relationships of Pseudomonas syringae pv. syringae isolates associated with bacterial iInflorescence rot in grapevine. Plant Dis. 100: 607–616.
    
    

35. Han, H.S., Nam, H.Y., Koh, Y.J., Hur, J.-S., and Jung, J.S. (2003) Molecular bases of high-level streptomycin resistance in Pseudomonas marginalis and Pseudomonas syringae pv. actinidiae. J. Microbiol. 41: 16–21.
    
    

36. Haubold, B. and Rainey, P.B. (1996) Genetic and ecotypic structure of a fluorescent Pseudomonas population. Mol. Ecol. 5: 747–761.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1365-294X.1996.tb00371.x&link_type=DOI) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=A1996WB05200005&link_type=ISI) 

37. Hayes, C.S., Aoki, S.K., and Low, D.A. (2010) Bacterial contact-dependent delivery systems. Annu. Rev. Genet. 44: 71–90.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1146/annurev.genet.42.110807.091449&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=21047256&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000286042600004&link_type=ISI) 

38. Hernández-Morales, A., De la Torre-Zavala, S., Ibarra-Laclette, E., Hernández-Flores, J., Jofre-Garfias, A., Martínez-Antonio, A., and Álvarez-Morales, A. (2009) Transcriptional profile of Pseudomonas syringae pv. phaseolicola NPS3121 in response to tissue extracts from a susceptible Phaseolus vulgaris L. cultivar. BMC Microbiol. 9: 257.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1186/1471-2180-9-257&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=20003402&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

39. Hibbing, M.E., Fuqua, C., Parsek, M.R., and Peterson, S.B. (2010) Bacterial competition: surviving and thriving in the microbial jungle. Nat. Rev. Microbiol. 8: 15–25.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/nrmicro2259&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=19946288&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000272820900009&link_type=ISI) 

40. Hirano, S.S., Charkowski, A.O., Collmer, A., Willis, D.K., and Upper, C.D. (1999) Role of the Hrp type III protein secretion system in growth of Pseudomonas syringae pv. syringae B728a on host plants in the field. Proc. Natl. Acad. Sci. 96: 9851–9856.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMDoiOTYvMTcvOTg1MSI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

41. Hirano, S.S. and Upper, C.D. (2000) Bacteria in the leaf ecosystem with emphasis on Pseudomonas syringae - a pathogen, ice nucleus, and epiphyte. Microbiol. Mol. Biol. Rev. 64: 624–653.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoibW1iciI7czo1OiJyZXNpZCI7czo4OiI2NC8zLzYyNCI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

42. Ho, S.N., Hunt, H.D., Horton, R.M., Pullen, J.K., and Pease, L.R. (1989) Site-directed mutagenesis by overlap extension using the polymerase chain reaction. Gene 77: 51–59.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1016/0378-1119(89)90358-2&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=2744487&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=A1989U265400006&link_type=ISI) 

43. Hockett, K.L., Renner, T., and Baltrus, D.A. (2015) Independent co-option of a tailed bacteriophage into a killing complex in Pseudomonas. MBio 6: 1–11.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.3391/mbi.2015.6.1.01&link_type=DOI) 

44. Hudson, R.R. (2001) Two-locus sampling distributions and their application. Genetics 159: 1805–1817.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6ODoiZ2VuZXRpY3MiO3M6NToicmVzaWQiO3M6MTA6IjE1OS80LzE4MDUiO3M6NDoiYXRvbSI7czozNzoiL2Jpb3J4aXYvZWFybHkvMjAxOC8wMy8wNy8yMzU4NTMuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9) 

45. Humphrey, P.T., Nguyen, T.T., Villalobos, M.M., and Whiteman, N.K. (2014) Diversity and abundance of phyllosphere bacteria are linked to insect herbivory. Mol. Ecol. 23: 1497–1515.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/mec.12657&link_type=DOI) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000332773700019&link_type=ISI) 

46. Hwang, M.S.H., Morgan, R.L., Sarkar, S.F., Wang, P.W., and Guttman, D.S. (2005) Phylogenetic characterization of virulence and resistance phenotypes of Pseudomonas syringae. Appl. Environ. Microbiol. 71: 5182–5191.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYWVtIjtzOjU6InJlc2lkIjtzOjk6IjcxLzkvNTE4MiI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

47. Istock, C.A., Duncan, K.E., Ferguson, N., and Zhou, X. (1992) Sexuality in a natural population of bacteria - Bacillus subtilis challenges the clonal paradigm. Mol. Ecol. 1: 95–103.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1365-294X.1992.tb00161.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=1344989&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000206802300004&link_type=ISI) 

48. Jolley, K.A., Feil, E.J., Chan, M.S., and Maiden, M.C. (2001) Sequence type analysis and recombinational tests (START). Bioinformatics 17: 1230–1231.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/bioinformatics/17.12.1230&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=11751234&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000173050500019&link_type=ISI) 

49. Jost, L. (2006) Entropy and diversity. Oikos 113: 363–375.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.2006.0030-1299.14714.x&link_type=DOI) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000237655400019&link_type=ISI) 

50. Karasov, T.L., Barrett, L., Hershberg, R., and Bergelson, J. (2017) Similar levels of gene content variation observed for Pseudomonas syringae populations extracted from single and multiple host species. PLoS One 12: 1–18.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1371/journal.pone.0179159&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=28957441&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

51. Kearse, M., Moir, R., Wilson, A., Stones-Havas, S., Cheung, M., Sturrock, S., et al. (2012) Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28: 1647–1649.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/bioinformatics/bts199&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22543367&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000305419800052&link_type=ISI) 

52. Kniskern, J.M., Barrett, L.G., and Bergelson, J. (2011) Maladaptation in wild populations of the generalist plant pathogen Pseudomonas syringae. Evolution (N. Y). 65: 818–830.
    
    

53. Koh, Y.J., Kim, G.H., Koh, H.S., Lee, Y.S., Kim, S.C., and Jung, J.S. (2012) Occurrence of a new type of Pseudomonas syringae pv. actinidiae strain of bacterial canker on kiwifruit in Korea. Plant Pathol. 28: 423–427.
    
    

54. Kõiv, V., Roosaare, M., Vedler, E., Ann Kivistik, P., Toppi, K., Schryer, D.W., et al. (2015) Microbial population dynamics in response to Pectobacterium atrosepticum infection in potato tubers. Sci. Rep. 5: 11106.
    
    

55. Kumar, S., Stecher, G., and Tamura, K. (2016) MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 33: 1870–1874.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/molbev/msw054&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=27004904&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

56. Laforest-Lapointe, I., Messier, C., Kembel, S.W., Lindow, S., Brandl, M., Herre, E., et al. (2016) Host species identity, site and time drive temperate tree phyllosphere bacterial community structure. Microbiome 4: 27.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1186/s40168-016-0174-1&link_type=DOI) 

57. Lamichhane, J.R. and Venturi, V. (2015) Synergisms between microbial pathogens in plant disease complexes: a growing trend. Front. Plant Sci. 6: 385.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.3389/fpls.2015.00385&link_type=DOI) 

58. Lenski, R.E., Rose, M.R., Simpson, S.C., and Tadler, S.C. (1991) Long-term experimental evolution in Escherichia coli. I. Adaptation and divergence during 2,000 generations. Am. Nat. 138: 1315–1341.
    
    

59. Lindow, S.E. (1986) Construction of isogenic Ice strains of Pseudomonas syringae for evaluation of specificity of competition on leaf surfaces. Perspect. Microb. Ecol. Slov. Soc. Microbiol. Ljubljana 509–515.
    
    

60. Lindow, S.E. and Brandl, M.T. (2003) Microbiology of the phyllosphere. Appl. Environ. Microbiol. 69: 1875–1883.
    
    [FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiRlVMTCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYWVtIjtzOjU6InJlc2lkIjtzOjk6IjY5LzQvMTg3NSI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

61. Macho, A.P., Zumaquero, A., Ortiz-Martín, I., and Beuzón, C.R. (2007) Competitive index in mixed infections: A sensitive and accurate assay for the genetic analysis of Pseudomonas syringae-plant interactions. Mol. Plant Pathol. 8: 437–450.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1364-3703.2007.00404.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=20507512&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000247477300009&link_type=ISI) 

62. Marchi, G., Sisto, A., Cimmino, A., Andolfi, A., Cipriani, M.G., Evidente, A., and Surico, G. (2006) Interaction between Pseudomonas savastanoi pv. savastanoi and Pantoea agglomerans in olive knots. Plant Pathol. 55: 614–624.
    
    

63. McArdle, B.H. and Anderson, M.J. (2001) Fitting multivariate models to community data: a comment on distance-based redundancy analysis. Ecology 82: 290–297.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.2307/2680104&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22997256&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000166488200024&link_type=ISI) 

64. McCann, H.C., Li, L.L., Liu, Y., Li, D., Pan, H., Zhong, C., et al. (2017) Origin and evolution of the kiwifruit canker pandemic. Genome Biol. Evol. 9: 932–944.
    
    

65. McCann, H.C., Rikkerink, E.H.A., Bertels, F., Fiers, M., Lu, A., Rees-George, J., et al. (2013) Genomic analysis of the kiwifruit pathogen Pseudomonas syringae pv. actinidiae provides insight into the origins of an emergent plant disease. PLoS Pathog. 9: e1003503.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1371/journal.ppat.1003503&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23935484&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

66. Mohr, T.J., Liu, H., Yan, S., Morris, C.E., Castillo, J.A., Jelenska, J., and Vinatzer, B.A. (2008) Naturally occurring nonpathogenic isolates of the plant pathogen Pseudomonas syringae lack a type III secretion system and effector gene orthologues. J. Bacteriol. 190: 2858–2870.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MjoiamIiO3M6NToicmVzaWQiO3M6MTA6IjE5MC84LzI4NTgiO3M6NDoiYXRvbSI7czozNzoiL2Jpb3J4aXYvZWFybHkvMjAxOC8wMy8wNy8yMzU4NTMuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9) 

67. Monier, J.-M. and Lindow, S.E. (2003) Differential survival of solitary and aggregated bacterial cells promotes aggregate formation on leaf surfaces. Proc. Natl. Acad. Sci. 100: 15977–15982.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMjoiMTAwLzI2LzE1OTc3IjtzOjQ6ImF0b20iO3M6Mzc6Ii9iaW9yeGl2L2Vhcmx5LzIwMTgvMDMvMDcvMjM1ODUzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

68. Monteil, C.L., Cai, R., Liu, H., Mechan Llontop, M.E., Leman, S., Studholme, D.J., et al. (2013) Nonagricultural reservoirs contribute to emergence and evolution of Pseudomonas syringae crop pathogens. New Phytol. 199: 800–811.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/nph.12316&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23692644&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

69. Monteil, C.L., Lafolie, F., Laurent, J., Clement, J.-C.C., Simler, R., Travi, Y., and Morris, C.E. (2014) Soil water flow is a source of the plant pathogen Pseudomonas syringae in subalpine headwaters. Environ. Microbiol. 16: 2038–2052.
    
    

70. Monteil, C.L., Yahara, K., Studholme, D.J., Mageiros, L., Méric, G., Swingle, B., et al. (2016) Population-genomic insights into emergence, crop-adaptation, and dissemination of Pseudomonas syringae pathogens. Microb. Genomics 2: 1–16.
    
    

71. Moretti, C., Hosni, T., Vandemeulebroecke, K., Brady, C., de Vos, P., Buonaurio, R., and Cleenwerck, I. (2011) Erwinia oleae sp. nov., isolated from olive knots caused by Pseudomonas savastanoi pv. savastanoi. Int. J. Syst. Evol. Microbiol. 61: 2745–2752.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1099/ijs.0.026336-0&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=21186287&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

72. Morris, C.E., Sands, D.C., Vanneste, J.L., Montarry, J., Oakley, B., Guilbaud, C., and Glaux, C. (2010) Inferring the evolutionary history of the plant pathogen Pseudomonas syringae from its biogeography in headwaters of rivers in North America, Europe, and New Zealand. MBio 1: e00107.
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=20802828&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

73. Morris, C.E., Sands, D.C., Vinatzer, B.A., Glaux, C., Guilbaud, C., Buffière, A., et al. (2008) The life history of the plant pathogen Pseudomonas syringae is linked to the water cycle. ISME J. 2: 321–334.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/ismej.2007.113&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=18185595&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000254359000009&link_type=ISI) 

74. Nakahara, H., Mori, T., Sadakari, N., Matsusaki, H., and Matsuzoe, N. (2016) Selection of effective non-pathogenic Ralstonia solanacearum as biocontrol agents against bacterial wilt in eggplant. J. Plant Dis. Prot. 123: 119–124.
    
    

75. Nowell, R.W., Laue, B.E., Sharp, P.M., and Green, S. (2016) Comparative genomics reveals genes significantly associated with woody hosts in the plant pathogen Pseudomonas syringae. Mol. Plant Pathol. 17: 1409–1424.
    
    

76. Oksanen, J., Blanchet, F.G., Friendly, M., Kindt, R., Legendre, P.,  Dan McGlinn, Peter R. Minchin, R.B.O., et al. (2016) vegan: Community Ecology Package.
    
    

77. Omer, M.E.H. and Wood, R.K.S. (1969) Growth of Pseudomonas phaseolicola in susceptible and in resistant bean plants. Ann. Appl. Biol. 63: 103–116.
    
    

78. Van Overbeek, L. and Van Elsas, J.D. (2008) Effects of plant genotype and growth stage on the structure of bacterial communities associated with potato (Solanum tuberosum L.). FEMS Microbiol. Ecol. 64: 283–296.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1574-6941.2008.00469.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=18355298&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000254948400013&link_type=ISI) 

79. Petriccione, M., Zampella, L., Mastrobuoni, F., and Scortichini, M. (2017) Occurrence of copper-resistant Pseudomonas syringae pv. syringae strains isolated from rain and kiwifruit orchards also infected by P. s. pv. actinidiae. Eur. J. Plant Pathol. 1–16.
    
    

80. Pfeilmeier, S., Caly, D.L., and Malone, J.G. (2016) Bacterial pathogenesis of plants: future challenges from a microbial perspective: Challenges in Bacterial Molecular Plant Pathology. Mol. Plant Pathol. 17: 1298–1313.
    
    

81. Polz, M.F., Alm, E.J., and Hanage, W.P. (2013) Horizontal gene transfer and the evolution of bacterial and archaeal population structure. Trends Genet. 29: 170–175.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1016/j.tig.2012.12.006&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23332119&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000316243500007&link_type=ISI) 

82. R.Core.Team (2016) R: A language and environment for statistical computing.
    
    

83. Ronquist, F., Teslenko, M., van der Mark, P., Ayres, D.L., Darling, A., Hohna, S., et al. (2012) MrBayes 3.2: Efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61: 539–542.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/sysbio/sys029&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22357727&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

84. Rozas, J. and Rozas, R. (1995) DnaSP, DNA sequence polymorphism: an interactive program for estimating population genetics parameters from DNA sequence data. CABIOS 11: 621–625.
    
    

85. Rufián, J.S., Macho, A.P., Corry, D.S., Mansfield, J., Arnold, D., and Beuzón, C.R. (2017) Confocal microscopy reveals in planta dynamic interactions between pathogenic, avirulent and non-pathogenic Pseudomonas syringae strains. Mol. Plant Pathol. DOI: 10.1111/mpp.12539.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/mpp.12539&link_type=DOI) 

86. Ruhe, Z.C., Low, D.A., and Hayes, C.S. (2013) Bacterial contact-dependent growth inhibition. Trends Microbiol. 21: 230–237.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1016/j.tim.2013.02.003&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23473845&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000319247700004&link_type=ISI) 

87. Sarkar, S.F. and Guttman, D.S. (2004) Evolution of the core genome of Pseudomonas syringae, a highly clonal, endemic plant pathogen. Appl. Environ. Microbiol. 70: 1999–2012.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYWVtIjtzOjU6InJlc2lkIjtzOjk6IjcwLzQvMTk5OSI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

88. Sawada, H. (2015) Characterization of biovar 3 strains of Pseudomonas syringae pv. actinidiae isolated in Japan. Japanese J. Phyopathology 81: 111–126.
    
    

89. Sawada, H.H., Suzuki, F.F., Matsuda, I.I., and Saitou, N.N. (1999) Phylogenetic analysis of Pseudomonas syringae pathovars suggests the horizontal gene transfer of argK and the evolutionary stability of hrp gene cluster. J. Mol. Evol. 49: 627–644.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1007/PL00006584&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=10552044&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000083442000010&link_type=ISI) 

90. Schäfer, A., Tauch, A., Jäger, W., Kalinowski, J., Thierbach, G., and Pühler, A. (1994) Small mobilizable multi-purpose cloning vectors derived from the Escherichia coli plasmids pK18 and pK19: selection of defined deletions in the chromosome of Corynebacterium glutamicum. Gene 145: 69–73.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1016/0378-1119(94)90324-7&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=8045426&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=A1994NZ73400010&link_type=ISI) 

91. Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B., et al. (2009) Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75: 7537–7541.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYWVtIjtzOjU6InJlc2lkIjtzOjEwOiI3NS8yMy83NTM3IjtzOjQ6ImF0b20iO3M6Mzc6Ii9iaW9yeGl2L2Vhcmx5LzIwMTgvMDMvMDcvMjM1ODUzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

92. Schmidt, H.A., Strimmer, K., Vingron, M., and von Haeseler, A. (2002) TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics 18: 502–504.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/bioinformatics/18.3.502&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=11934758&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000174708500024&link_type=ISI) 

93. Singer, M. (2010) Pathogen-pathogen interaction. Virulence 1: 10–18.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.4161/viru.1.1.9933&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=21178409&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000292467700006&link_type=ISI) 

94. Souza, V., Nguyen, T.T., Hudson, R.R., Piñero, D., and Lenski, R.E. (1992) Hierarchical analysis of linkage disequilibrium in Rhizobium populations: evidence for sex? Proc. Natl. Acad. Sci. U. S. A. 89: 8389–93.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMDoiODkvMTcvODM4OSI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

95. Spratt, B.G., Hanage, W.P., Li, B., Aanensen, D.M., and Feil, E.J. (2004) Displaying the relatedness among isolates of bacterial species -- the eBURST approach. FEMS Microbiol. Lett. 241: 129–134.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1016/j.femsle.2004.11.015&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=15598523&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000226174000001&link_type=ISI) 

96. Spratt, B.G. and Maiden, M.C.J. (1999) Bacterial population genetics, evolution and epidemiology. Philos. Trans. R. Soc. B Biol. Sci. 354: 701–710.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1098/rstb.1999.0423&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=10365396&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000080160200003&link_type=ISI) 

97. Stubbendieck, R.M., Vargas-Bautista, C., and Straight, P.D. (2016) Bacterial communities: Interactions to scale. Front. Microbiol. 7: 1234.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.3389/fmicb.2016.01234&link_type=DOI) 

98. Triplett, L.R., Verdier, V., Campillo, T., Van Malderghem, C., Cleenwerck, I., Maes, M., et al. (2015) Characterization of a novel clade of Xanthomonas isolated from rice leaves in Mali and proposal of Xanthomonas maliensis sp. nov. Antonie van Leeuwenhoek, Int. J. Gen. Mol. Microbiol. 107: 869–881.
    
    

99. Visnovsky, S.B., Fiers, M., Lu, A., Panda, P., Taylor, R., and Pitman, A.R. (2016) Draft genome sequences of 18 strains of Pseudomonas isolated from kiwifruit plants in New Zealand and overseas. Genome Announc. 4: e00061–16.
    
    

100.Völksch, B. and May, R. (2001) Biological Control of Pseudomonas syringae pv. glycinea by Epiphytic Bacteria under Field Conditions. Microb. Ecol. 41: 132–139.
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=12032618&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

101.Vorholt, J.A. (2012) Microbial life in the phyllosphere. Nat. Rev. Microbiol. 10: 828–840.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/nrmicro2910&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23154261&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 

102.Wagner, M.R., Lundberg, D.S., del Rio, T.G., Tringe, S.G., Dangl, J.L., and Mitchell-Olds, T. (2016) Host genotype and age shape the leaf and root microbiomes of a wild perennial plant. Nat. Commun. 7: 12151.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/ncomms12151&link_type=DOI) 

103.Whipps, J.M., Hand, P., Pink, D., and Bending, G.D. (2008) Phyllosphere microbiology with special reference to diversity and plant genotype. J. Appl. Microbiol. 105: 1744–1755.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1365-2672.2008.03906.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=19120625&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2018%2F03%2F07%2F235853.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000261125300003&link_type=ISI) 

104.Wilson, M., Hirano, S.S., and Lindow, S.E. (1999) Location and survival of leaf-associated bacteria in relation to pathogenicity and potential for growth within the leaf. Appl. Environ. Microbiol. 65: 1435–1443.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYWVtIjtzOjU6InJlc2lkIjtzOjk6IjY1LzQvMTQzNSI7czo0OiJhdG9tIjtzOjM3OiIvYmlvcnhpdi9lYXJseS8yMDE4LzAzLzA3LzIzNTg1My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

105.Wilson, M. and Lindow, S.E. (1994) Coexistence among epiphytic bacterial Populations mediated through nutritional resource partitioning. Appl. Environ. Microbiol. 60: 4468–4477.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYWVtIjtzOjU6InJlc2lkIjtzOjEwOiI2MC8xMi80NDY4IjtzOjQ6ImF0b20iO3M6Mzc6Ii9iaW9yeGl2L2Vhcmx5LzIwMTgvMDMvMDcvMjM1ODUzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

106.Young, J.M. (1974) Development of bacterial populations in vivo in relation to plant pathogenicity. New Zeal. J. Agric. Res. 17: 105–113.
    
    

107.Zhang, X.X., Gauntlett, J.C., Oldenburg, D.G., Cook, G.M., and Rainey, P.B. (2015) Role of the transporter-like sensor kinase CbrA in histidine uptake and signal transduction. J. Bacteriol. 197: 2867–2878.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MjoiamIiO3M6NToicmVzaWQiO3M6MTE6IjE5Ny8xNy8yODY3IjtzOjQ6ImF0b20iO3M6Mzc6Ii9iaW9yeGl2L2Vhcmx5LzIwMTgvMDMvMDcvMjM1ODUzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

108.Zhao, Z.B., Gao, X.N., Huang, Q.L., Huang, L.L., Qin, H.Q., and Kang, Z.S. (2013) Identification and characerization of the causal agent of bacterial canker of kiwifruit in the Shaanxi province of China. J. Plant Pathol. 95: 155–162.