Evolution, genomics and epidemiology of Pseudomonas syringae

Summary

A remarkable shift in our understanding of plant‐pathogenic bacteria is underway. Until recently, nearly all research on phytopathogenic bacteria was focused on a small number of model strains, which provided a deep, but narrow, perspective on plant–microbe interactions. Advances in genome sequencing technologies have changed this by enabling the incorporation of much greater diversity into comparative and functional research. We are now moving beyond a typological understanding of a select collection of strains to a more generalized appreciation of the breadth and scope of plant–microbe interactions. The study of natural populations and evolution has particularly benefited from the expansion of genomic data. We are beginning to have a much deeper understanding of the natural genetic diversity, niche breadth, ecological constraints and defining characteristics of phytopathogenic species. Given this expanding genomic and ecological knowledge, we believe the time is ripe to evaluate what we know about the evolutionary dynamics of plant pathogens.

Introduction

Pseudomonas syringae is one of the pre‐eminent models for the exploration of plant–microbe interactions in both natural and laboratory systems. The species has played a central role in seminal studies and publications, including the development of the guard hypothesis (Dangl and Jones, 2001) and the zig–zag model (Jones and Dangl, 2006) of plant immunity. There is also a growing body of literature exploring its tremendous natural diversity (Baltrus et al., 2011; Berge et al., 2014; O'Brien et al., 2011b; Thakur et al., 2016). This foundation of molecular, genomic and ecological knowledge, coupled with near environmental ubiquity, have turned P. syringae into a powerful emerging model system for the study of microbial evolution in nature (Hirano and Upper, 2000; Morris et al., 2013; O'Brien et al., 2011b). Consequently, this review focuses exclusively on fundamental questions as they apply to P. syringae.

Our goal is to discuss how the principles of population genetics guide our understanding of the evolutionary processes that have shaped the natural diversity and host interactions of P. syringae. We specifically examine questions related to the cohesion of the P. syringae species complex, whether it should even be considered as a species, and why this is important. We then address the nature of bacterial populations, and how fundamental evolutionary forces impact P. syringae natural diversity, as well as the community of microbes with which it interacts.

Is P. syringae a Species?

Much time and effort have been spent on debating whether bacterial lineages can be circumscribed into natural species, and how these bounds can and should be defined. Although these arguments may seem fairly esoteric, they have both practical consequences for pathologists working on field isolates and fundamental implications for how we understand and interpret the ecological and evolutionary pressures that give rise to natural genetic diversity. With an increased appreciation of the extensive degree of genetic exchange among bacterial lineages, it is possible that no single, clear‐cut answer will ever emerge. However, we believe that it is worthwhile to examine the classification of P. syringae from both philosophical and biological standpoints with the hope that a broad analysis can provide structure for future discussions.

Species concepts and species delimitation

There has been considerable debate over the composition of the species P. syringae and whether the P. syringae complex is a cohesive unit or should be split into distinct species (Bull et al., 2010; Janse et al., 1996). The road describing the taxonomy and nomenclature of P. syringae is long and winding (Bull and Koike, 2015; Bull et al., 2008; Young, 2008, 2010). Strains were originally identified as members of the P. syringae complex if they were fluorescent pseudomonads positive for levan sucrase activity, negative for oxidase activity, unable to rot potato, able to produce arginine dihydrolase and able to cause a hypersensitive response on tobacco (the LOPAT group 1 strains) (Lelliott et al., 1966; Sands et al., 1970). In 1975, numerous formerly distinct LOPAT group 1 plant‐pathogenic species were combined into the species P. syringae when the International Committee on the Systematics of Prokaryotes revised the nomenclatural code for bacteria (Lapage et al., 1975). The general confusion that resulted led to the proposal that pathogens be given infrasubspecific pathovar names based on distinct pathogenic characters, including host of isolation (Young, 2008; Young et al., 1978). This reliance on phenotype‐based rules for classification has led to increased taxonomic confusion as more P. syringae strains have been isolated from non‐diseased tissues and environmental sources, such as rivers, lakes, snow fields and clouds (Morris et al., 2013). Furthermore, there is an increased awareness of the plasticity of taxonomically relevant phenotypes within and between closely related isolates (Bartoli et al., 2014; Demba Diallo et al., 2012). Given an emphasis on pathogenicity for the classification of P. syringae lineages, many of these strains currently remain outside of formal classification and continue to exist in what can best be described as ‘taxonomic limbo’.

Currently, the P. syringae species complex is subdivided into over 60 pathovars defined by pathogenic characters, nine genomospecies defined by DNA–DNA hybridization and 13 phylogenetic groups (phylogroups) defined by multilocus sequence analysis (Berge et al., 2014; Hwang et al., 2005; Sarkar and Guttman, 2004; Young, 2010) (Fig. 1). Seven of the phylogroups may be considered as ‘primary’ phylogroups (phylogroups 1, 2, 3, 4, 5, 6 and 10; D. S. Guttman, unpublished data) as they are monophyletic and quite distinct from the more divergent ‘secondary’ phylogroups, include the traditionally recognized diversity of the species and nearly all of the recognized pathovars and pathotype strains, and predominantly carry the canonical P. syringae type III secretion system (the only known exception being phylogroup 2C, see below). The remaining six secondary phylogroups (phylogroups 7, 8, 9, 11, 12 and 13) include many strains that have traditionally been assigned to species not normally associated with the P. syringae complex, such as P. viridiflava and P. cichorii, do not (exclusively) carry a canonical P. syringae type III secretion system and/or were isolated from environmental sources (Baltrus et al., 2014; Berge et al., 2014; Morris et al., 2007, 2008).

Figure 1.

Phylogenetic tree and type III secretion system distribution of Pseudomonas syringae type and pathotype strains. Maximum likelihood phylogenetic analysis of the P. syringae species complex including 62 type (T) and pathotype (PT) strains, as well as the three strains with finished (FG) genomes. Type strains are isolates to which the scientific name of that organism is formally attached under the rules of prokaryote nomenclature. Pathotype strains are similar to type strains, with the additional requirement that a pathotype strain has the pathogenic characteristics of its pathovar (for details, see Thakur et al., 2016). Phylogroup (PG) designations are indicated on the appropriate branches. The distribution of the four type III secretion systems is shown to the right: canonical (tripartite pathogenicity island, T‐PAI), rhizobial (R‐PAI), single (S‐PAI) and atypical‐A (A‐PAI).

Given the variety of methods used to describe, define and circumscribe the P. syringae complex, it is not surprising that there is substantial confusion and disagreement (Baltrus, 2016). What is largely missing from this debate is an attempt to define the species on the basis of fundamental evolutionary principles rather than fairly arbitrarily selected phenotypes, the interests of individual research programmes or the need to identify and control specific outbreaks. Although this last issue is clearly important, in and of itself it is a poor choice for defining the species, as the focus is highly biased towards pathogenic strains and specific phenotypic outcomes rather than general evolutionary principles. A species definition based on fundamental principles should apply to all isolates of a species regardless of their ecological niche (the ecological role played by the organism in its environment), and hold constant as long as the data supporting it are robust and unbiased. Importantly, these same principles can subsequently be used to identify significant and specific pathogens, thereby serving the needs of pathologists and the agricultural community.

An important distinction must be made between species concepts and species delimitation. A species concept describes a theoretical basis for why biological diversity is structured into distinct genetic units. These concepts are typically based on fundamental evolutionary and ecological principles, such as recombination, reproductive isolation, genetic drift and selection (de Queiroz, 2007). In contrast, species delimitation is a methodological process that describes how to identify the distinct units. Historically, microbial species delimitation was performed by studying phenotypic characters, such as growth, morphology, coloration, pathogenic potential or biochemical abilities. Since the widespread adoption of molecular methods, microbial species delimitation has been performed using data generated by DNA–DNA hybridization, 16S rRNA gene sequencing, average nucleotide identity, multilocus sequence analysis and, most recently, whole genome sequencing (Schleifer, 2009). In this article, we only concern ourselves with the conceptual issues and their underlying biological drivers.

The debate over the nature and even the reality of species in bacteria has gone on for many years, and is fundamentally driven by the inherent dissociation between reproduction and genetic exchange. At one end of the spectrum are strong arguments to reject the very notion that all bacterial groups will actually form recognizable species. These objections are based on the dynamic nature of the divergence process and the rate of horizontal genetic exchange among bacteria. An important claim is that recombination acting independently on loci around the genome scrambles the lines of descent and eliminates any common genealogical history for the genome as a whole. Evidence supporting this theory comes from the large number of loci in the pan‐genome (the total collection of genes and genetic elements shared by all members of a bacterial species) that have incompatible genealogical histories, and the extremely high variance observed in the times to most recent common ancestor for different loci (Doolittle and Papke, 2006; Doolittle and Zhaxybayeva, 2009; Retchless and Lawrence, 2007).

Countering this argument is the simple observation that most recognized bacterial species are distinct genetic clusters that are distinguishable from other clusters (Achtman and Wagner, 2008; Hanage et al., 2006b). These distinct genetic clusters are consistent with the idea of separately evolving metapopulation lineages, which is arguably the only necessary property of species (de Queiroz, 2007). A metapopulation here simply refers to a collection of subpopulations connected via gene flow. Although distinct genetic clusters must be established by underlying ecological and/or evolutionary mechanisms, the nature of these mechanisms, and the role of natural selection in particular, has been hotly debated.

The simplest ecological constraint known to establish genetic clusters is reproductive isolation as a result of geographical separation. Although geographical barriers are believed to play an important role in the maintenance of species bounds for mega‐organisms, the often cited hypothesis by Baas‐Becking, ‘everything is everywhere, but the environment selects”, is more generally accepted for microorganisms (O'Malley, 2007) (but see Sul et al., 2013) Therefore, we are left with either neutral or selective evolutionary processes to explain the formation of genetic clusters. Neutral models focus on the balance of mutation and recombination. In these cases, diversification is driven by neutral mutation and genetic drift, and opposed by the cohesive force of recombination (Fraser et al., 2007; Hanage et al., 2006a, 2006c). Selection‐based models view positive selection as the primary driver of diversification. The best‐developed selection‐based models are Cohan's ecotype models, which emphasize the role of recurrent selective sweeps (i.e. periodic selection) in defining the niche of distinct populations (Cohan, 2002; Cohan and Koeppel, 2008; Gevers et al., 2005; Koeppel et al., 2008; Wiedenbeck and Cohan, 2011). In this context, an ecotype is a distinct genetic lineage or clade that occupies a particular niche. Recombination also plays a role in the selection‐based models of bacterial species, as it is the only mechanism by which new adaptive mutations can be introduced into pre‐existing genetic backgrounds. Consequently, the interplay between recombination and selection determines how far an adaptive mutation will spread and, therefore, what is an ecologically distinct population. The unifying principle between both the neutral and selection‐based models is that recombination is the cohesive evolutionary force that defines the ecological bounds of a species.

Why is this important? Why do we care where the species boundaries are for P. syringae? The simple answer is that to understand what P. syringae is we must understand its ecological niche and how it adapts to its environment. If we use the fundamental evolutionary principles discussed above to define a bacterial species, we have a biological basis for the determination of how a lineage should be classified. These fundamental evolutionary principles boil down to the determination of the extent of genetic cohesion as a result of recombination. If recombination maintains genetic cohesion between two lineages by facilitating the spread of both neutral and adaptive mutations, the lineages should be considered as part of the same species. If there is no cohesion, which may be a result of some combination of reduced recombination or adaptation to distinct environments, the lineages should be considered as independent species.

To define P. syringae using these principles, we must measure the extent of recombination and determine the extent to which recombination disseminates ecologically adaptive genetic variation (as opposed to neutral or deleterious variants). Those lineages that share adaptive variation should be considered as part of the same species, whereas recombination is expected to be restricted among lineages of different species simply because they are adapting to different niches. A simple application would be to determine the rate of recombination between phylogroups. For example, if we find that the recombination rate among phylogroups 1, 2, 3, 4, 5 (P. cannabina) and 6 is significantly higher than the rate between the aforementioned six phylogroups and phylogroup 7 (P. viridiflava), we may conclude that the former are members of the same species, whereas the latter is a distinct species. Preliminary data (D. S. Guttman, unpublished data) support this conclusion.

A functional definition of P. syringae

The number and diversity of P. syringae genomes available enable the identification of phenotypes and, importantly, the underlying genotypes to distinguish taxonomically relevant ecotypes (O'Brien et al., 2011a, 2011b; Vinatzer et al., 2014). One defining and unifying feature across nearly all strains phenotypically (via LOPAT testing) classified as P. syringae is the presence of a type III secretion system (Lindeberg et al., 2012). There exist multiple versions of this structure across strains, although the phenotypic consequences of this diversity remain unclear (Fig. 2). The first type III secretion system described, and most prevalent among sequenced strains, is referred to as the tripartite pathogenicity island (T‐PAI) or canonical system, because the genomic island containing it is arrayed into three distinct sections. This particular system is required for virulence in planta in every pathogenic strain investigated thus far, and its presence is strongly correlated with pathogenic potential on agriculturally relevant plants (Hirano and Upper, 2000; Lindeberg et al., 2012).

Figure 2.

Type III secretion systems (TTSSs) across Pseudomonas syringae. At the top of the figure, one representative drawing is displayed for each known type III secretion class found within P. syringae sensu lato strains. Representations were adapted from the genomic annotations of the following strains: canonical (T‐PAI), P. syringae pv. tomato DC3000 (GenBank AE016853.1); rhizobial (R‐PAI), P. syringae pv. phaseolicola 1448a (GenBank CP000058.1); S‐PAI, P. viridiflava LMCA8 (GenBank JXQO00000000.1); atypical‐A, P. syringae Psy508 (GenBank ADGB00000000.1); atypical‐B, P. syringae UB246 (GenBank AVEQ00000000.1). The positions of select genes in the TTSS and border regions, as well as tRNA loci in proximity, are annotated within each drawing. The bottom of the figure displays the genomic context for each TTSS, using P. syringae pv. tomato DC3000 as a reference. Anchor points for genomic context were identified by manual inspection of genes outside of the TTSS of interest in its native genome (see above) as regions in which multiple open reading frames (ORFs) are conserved between the native genome and P. syringae pv. tomato DC3000. The ‘Atypical‐B’ TTSS is split across multiple contigs in the genome assembly of UB246, and anchor points were identified through inspection of identical contigs from genome sequences for closely related strains (D. A. Baltrus, unpublished data).

A second type III secretion system, first described by Araki et al. (2006), is referred to as the single PAI (S‐PAI) because of its genic composition. This system is required for full phytopathogenicity in both P. viridiflava and P. cichorii, is present in a separate genomic context from T‐PAI and appears to subtly differ in function from T‐PAI (Araki et al., 2006). Although strains containing S‐PAI display definitive differences in disease aetiology relative to T‐PAI strains, the contribution of the type III secretion system diversity to these differences is unknown.

A third system, referred to here and in other publications as ‘atypical’ (A‐PAI), was first described in strain Psy503 and was later shown to be conserved across phylogroup 2C (Clarke et al., 2010; Mohr et al., 2008) (Fig. 1). Strains containing this system can deliver effectors to trigger a hypersensitive response, but the pathogenicity of such strains is a topic of debate (Morris et al., 2013). It is possible that these strains are largely epiphytes and do not cause systemic disease in crops. Interestingly, differences in genomic context suggest that a version of this ‘atypical’ system was acquired independently by phylogroup 13 strains, such as UB246 and closely related phylogroups (Baltrus et al., 2014) (Fig. 2).

Finally, although the type III secretion systems described above appear to be mutually exclusive to each other within strains, some strains also maintain an additional type III secretion system resembling that found in Rhizobium species (R‐PAI) (Joardar et al., 2005; Martinez‐Garcia et al., 2015; O'Brien et al., 2011b). The functions of this system are not currently known, but it does not appear to be required for virulence in planta (Martinez‐Garcia et al., 2015). Nevertheless, the possibility that this system has been acquired via horizontal gene transfer multiple independent times by strains within the P. syringae complex, or selectively maintained by subsets of strains, implies some selective benefit in nature.

As at least one type III system is present within all strains defined as P. syringae, we suggest that the presence of such systems could provide a genomic foothold to start to define ecotypes for this species. By no means do we think that the presence of a type III secretion system is the only useful marker for delineation of the species, but this structure does provide a clean link between genetics and ecotypes relevant for the definition of agriculturally important P. syringae lineages. Other genetic systems may prove to be more important for some non‐agricultural populations, assuming that these populations show specific environmental adaptations.

It is unlikely that there will be adequate solutions to either the P. syringae species or nomenclatural problems in the near future, even with an abundance of genomic data. It is important to emphasize that genes found within the same genome do not necessarily have the same evolutionary histories. There are certainly subsets of genes which are crucial for some phenotypes, but not others (i.e. virulence, type III effectors, UV survival, DNA repair, etc.), and so there are inherently different answers to both species and nomenclatural questions depending on the focus. Although there are multiple reasons why these questions are important, we suggest that they need not be answered together. For instance, species names are not crucial to the characterization of phytopathogenic agents by government agencies; numerical and relative naming schemes would do very well (Baltrus, 2016). We can make the choice to regulate all strains that ‘look’ like P. syringae genomically or the subset that possesses the canonical type III secretion system, thereby overcoming confusion that arises over specific wording and names. Although such a scheme would inherently (and incorrectly) include non‐pathogenic strains, false positives may be the price to pay for clarity. Moreover, it is important to focus on the idea that, although strain comparisons are crucial to answering evolutionary and ecological questions, historically, nomenclature has just acted as a shortcut and representation of underlying phenotypes. These same comparisons can be made in the absence of names, just by collecting phenotypic data and linking to strain identifiers. Shortcuts are always welcome, but shortcuts that impart phenotypic information inaccurately only serve to confuse downstream results.

What Constitutes a P. syringae Population

Evolution largely takes place at the level of populations. Although Monod famously quipped that ‘anything found to be true of E. coli must also be true of elephants’, this statement ignores the fact that it is substantially easier to define elephant populations than bacterial populations (Shapiro and Polz, 2014). Moreover, it is quite possible that genes, individuals, populations and communities exist on some kind of an evolutionary continuum among parasexual bacteria, experiencing different and potentially contradictory selective pressures. Such semantic challenges might appear inconsequential at face value, but they underlie an important reality that it remains difficult to extrapolate the findings of many theoretical and experimental population genetics studies to natural microbial populations.

Although natural selection ultimately acts at the level of individuals, the strength and scope of selection are determined by the relative fitness of the genotype with respect to its population and associated meta‐populations. A population encompasses the collection of genotypes that have the potential for genetic exchange, and which are directly competing with one another for niche space (Shapiro and Polz, 2014). By extension, a metapopulation consists of multiple populations which are connected by gene flow or migration. For P. syringae, we are far from any clear consensus on the definitions of these variables.

Numerous genotypes and strains of P. syringae can be sampled from most terrestrial environments. Given that these are all relatively closely related compared with other bacteria, and are all found within the same environment, it is intuitive to assume that these are members of the same population. However, we should consider that one strain might prefer one type of sugar found in plants, such as sucrose, whereas another closely related strain might prefer a different carbon source found elsewhere. One lineage might excel at epiphytic survival, whereas another might have much more success during invasion of the apoplast. Although these strains might be in direct competition when both are present on the leaf surface, they would not necessarily be at any other point. From an alternative perspective, strains that differ in host preferences, so that they would ostensibly be grouped into different populations, may be susceptible to many of the same bacteriophages. If this is the case, such strains might not be in direct competition on the same host plant, but might recombine genetic material at a higher rate than would be expected based on their primary niche.

Unfortunately, there are currently few datasets available to adequately address questions related to P. syringae populations, although this is changing with recent reports (Karasov et al., 2014; Kniskern et al., 2011; Monteil et al., 2013; Vinatzer et al., 2014). The vast majority of P. syringae isolates were collected only after observing disease phenotypes on plants, and these isolates were specifically selected to identify the aetiology of disease. In many cases, no effort was made to isolate additional co‐habiting strains not responsible for disease or similar strains growing asymptomatically elsewhere. This sampling structure leads to a classic case of ‘iceberg bias’ in which only a subset of the total genetic variation is studied, thereby potentially leading to artefactual inferences of population structure, genetic associations and even dispersal (Tibayrenc, 1999). Recent efforts documenting the widespread presence of P. syringae across environments associated with the water cycle and across plants within the same environment highlight just how little we know about the life cycle of this species outside of the context of agricultural disease (Morris et al., 2013), but also highlight the challenges of the identification of evolutionarily relevant clusters. One potential path to remedy the absence of information lies in expanding the sampling schemes during outbreaks to include other potential geographically proximate hosts or environmental reservoirs, and in sampling the same areas post‐outbreak. If the same strain as that implicated in outbreaks is found outside focal plant hosts, it would strongly indicate the need to expand our characterization of P. syringae populations past one specific crop at any given time. A recent report has suggested that just this scenario occurs, that strains isolated from environmental sources are members of the same population as those during outbreaks (Monteil et al., 2016). Widespread incorporation of broader, ecologically informed, sampling schemes would give a rough idea of correlations in strain presence, which is important because these strains would have access to the same genetic pool.

How does Genetic Diversity Arise in P. syringae Lineages

Genetic diversity is the fuel for evolution. The sequencing revolution, coupled with a strong history of foundational research, has placed P. syringae in a unique position at the forefront of studies into phytopathogen genome evolution. Although our understanding of evolutionary dynamics is currently limited to snapshots in time, these studies provide a broad understanding of how genetic diversity is introduced into and dispersed throughout this species.

Mutation

Given that the vast majority of P. syringae strains share a similar genome size of approximately 5–6 Mb, one might expect roughly the same number of mutations (per cell per generation) to occur across all lineages (O'Brien et al., 2011b). There is nothing to suggest that this assumption is inherently incorrect; however, one must also note that mutation rates can be significantly affected by environmental factors (Gunasekera and Sundin, 2006). Depending on both ecology and expressed phenotypes, some lineages could be more sensitive to environmentally mediated changes in mutation rates than others. For example, it is well known that strains differ in fluorescence and pigment levels, which are capable of acting as UV protectants (Burke et al., 1990). Likewise, extra DNA repair genes found on some plasmids in P. syringae may lower the mutation rates of the host cell (Sundin and Murillo, 1999).

One phenomenon that has received relatively little attention in the plant pathology literature is the presence of hypermutator strains. Hypermutator strains have defects in DNA repair systems that result in an increased spontaneous mutation rate (Sniegowski et al., 1997; Taddei et al., 1997). Although these strains carry an increased mutational load which may lower the net fitness of the lineage, they also have a greater chance of spontaneously generating beneficial mutations that enhance adaptation to a specific environment. Hypermutator lineages are very commonly observed in chronic infections of humans, such as Pseudomonas aeruginosa infections of the cystic fibrosis lung, where hypermutation often leads to high levels of antibiotic resistance (Oliver and Mena, 2010). Hypermutator strains are thought to be beneficial in structured environments with strong, but varying selective pressures, such as the compartmentalized cystic fibrosis lung, in which intense antibiotic treatments impose strong selection (Oliver et al., 2000). As plants have lower structural complexity and lack an adaptive immune system, it remains to be seen whether phytopathogens experience selection pressures that would favour the widespread emergence of hypermutators. One of the few studies of this phenomenon in the P. syringae species complex was carried out on three P. viridiflava isolates collected from kiwifruit (Bartoli et al., 2015b). The authors collected multiple mucoid and transparent colony variants during in vitro growth, and found that the transparent variants evolved antibiotic resistance at a higher rate and lost the ability to cause disease in bean. Interestingly, none of the transparent hypermutator strains carried mutations in the canonical mismatch repair genes, such as mutS.

Recombination

Although mutation fulfils the simple and glamorous role of generating all de novo variation in a population, the complex effects of recombination on genetic diversity are often more contradictory, but no less important. Homologous recombination is often thought of as a force that homogenizes genetic variation among individuals—the evolutionary force that reins in and shuffles the individual novelty generated by mutation. This is true when considering recombination occurring among individuals from the same population. However, recombination also increases genetic diversity when it occurs among individuals from different populations or lineages (Guttman and Dykhuizen, 1994). Consequently, recombination can be either a genetic homogenizing or diversifying evolutionary force depending on the population structure and identity of the donor and recipient. As described above, the balance between these two extremes therefore makes recombination a dominant force in determining the evolutionary bounds of populations and species. This role is most apparent when considering two hypothetical, neutrally evolving species (i.e. no selection) with large effective population sizes (i.e. no genetic drift) at the extremes of the recombination spectrum. In the first case of a purely clonal species that undergoes no recombination, every mutation generates a new lineage. Each new lineage will have an independent evolutionary trajectory diverging indefinitely, and effectively be an independent species, as all lineages will be genetically independent. On the other end of the spectrum would be a species undergoing very high rates of recombination. In this extreme case, each mutation will get shuffled into the genetic background of every other mutation and, consequently, the lineages would be continuously mixed into a single panmictic population.

Although we understand the three primary mechanisms of genetic exchange in bacteria (conjugation, transformation and transduction), the relative balance and evolutionary impact of these processes across strains of P. syringae are still largely unknown. Strains of P. syringae appear to undergo a moderately high rate of recombination over a large number of loci (Yan et al., 2008). This is intriguing as the species is not known to be naturally competent for transformation, plasmid and phage‐mediated gene exchange mechanisms are usually localized, and DNA transfer by extracellular vesicles remains a largely unexplored possibility (Nowell et al., 2014; Schwechheimer and Kuehn, 2015). Nevertheless, it is undeniable that natural strains undergo recombination. It remains unclear why so much of the recombination appears to occur within ‘housekeeping’ genes whose functions should be conserved among related strains (Yan et al., 2008).

It is possible that patterns of recombination could be used to define functional populations. As recombination should occur more frequently among closely related strains interacting in the same niche, patterns of recombination among strains may reflect underlying environmental structure, and therefore help to define lineages of interest. A closer analysis of the loci which undergo higher rates of recombination could provide a coherent framework for the identification of genes, pathways and phenotypes that link strains to their ecotypes.

Horizontal gene transfer

The genomes of environmental bacteria, including most pseudomonads, tend to be large relative to those of other well‐studied, host‐associated bacteria. This trend is interesting in itself and potentially indicates a greater level of metabolic diversity within environmental bacteria (Konstantinidis and Tiedje, 2004), but also has broader implications given that larger genomes tend to be more receptive to horizontal transfer from distantly related species (Cordero and Hogeweg, 2009). A recent comparative genomic analysis of 27 P. syringae strains from the primary phylogroups placed the size of the core genome at 2595 proteins, the flexible or accessory genome (proteins variably present across multiple strains) at 5753, and the number of lineage‐specific proteins at 2677, giving a total pan‐genome of 11 025 proteins (Nowell et al., 2014). An analysis of the distribution of the encoding genes across genomes showed that most proteins are either found in a small number of strains, or the vast majority of the strains, resulting in the typical U‐shaped gene frequency distribution found in most bacterial species. Although the inclusion of additional strains from more phylogroups into this analysis would probably change the absolute numbers within each gene category, it is likely that the distribution would not change substantially. Although the distribution of the flexible genes could be caused by extensive gene loss, it has been suggested that horizontal transfer across the flexible genome occurs at a relatively high frequency, and has a disproportionate impact on strain adaptation in nature (Baltrus et al., 2011; Nowell et al., 2016).

There have only been sporadic attempts outside of virulence pathways to document how horizontal gene transfer shapes P. syringae adaptation, but there has been much work investigating the diversity of the vehicles of horizontal transfer (i.e. plasmids and prophage). Pseudomonas syringae genomes typically harbour at least one prophage region. Although only a small number of cases have documented the activation of these phages (Hockett et al., 2015), one prophage from PsyB728a has been shown to transfer among strains (D. A. Baltrus, unpublished data). Although most sequenced strains appear to contain plasmids, the fractured nature of draft genomes makes it difficult to definitively identify which genes are present on these secondary replicons (Baltrus et al., 2011). The plasmids that have been extensively studied harbour great phenotypic potential and can typically be grouped within the pPT23a family (Ma et al., 2007; Stavrinides and Guttman, 2004; Zhao et al., 2005). Of note, a pathovar lachrymans strain has been demonstrated to contain a circular chromid, referred to as pMPPla107, of approximately 1 Mb in size, which does not appear to be present within any other P. syringae strain, or other species (Baltrus et al., 2011). This replicon contains more than 700 coding sequences and is self‐transmissible to a variety of different pseudomonad species. Although the prediction of gene functions is ambiguous for most of pMPPla107, it contains a number of ‘housekeeping’ genes (such as parts of the PolIII holoenzyme complex), as well as nearly a full complement of tRNAs. Unlike most large megaplasmids, this replicon was discovered solely through genome sequencing, so that it remains to be seen what phenotypic capacities it provides to its parent strain. Perhaps most interesting, pMPPla107 could not be cured from its parent strain, even though it was readily curable from all novel host strains into which it was mated (Romanchuk et al., 2014). This suggests that this replicon may represent a hybrid between chromids and secondary chromosomes, and could significantly influence the future evolutionary trajectories of this strain (Cooper et al., 2010).

Like most pseudomonads and, indeed, many well‐studied bacteria, P. syringae genomes are highly diverse and dynamic. Dramatic and phenotypically important changes can be induced over the course of a few laboratory passages. This variability makes P. syringae an intriguing species to study, but can confound analyses that treat strains as static entities.

How do Neutral Processes Shape Genetic Diversity?

Pseudomonads are known for being ubiquitous across a variety of different environments, and P. syringae is no exception. Given this, it is tempting to assume that the population sizes for the species must be quite large and therefore that genetic drift has little importance in structuring P. syringae diversity. However, an assessment of the real effect of sampling in the context of population genetics pressures is much more complicated. Although the census population size (the number of bacteria that can be counted) is truly massive, the effective population size (the evolutionarily significant size determined by the amount of genetic diversity transmitted between generations) is often vastly smaller. The effective population size can be reduced by a number of factors. Perhaps the most significant in this case is the simple fact that bacteria reproduce clonally, so that, although a colony of bacteria may contain millions of cells, all are derived from a single parent cell. The effective population size can also be reduced by fluctuations in the census population size as a result of population bottlenecks caused by factors such as the death of hosts in winter, or by founder events caused by the founding of a new population by a small number of cells during transmission from one plant to another. In these cases, the effective population size is estimated as the sum of harmonic means, so that bottlenecks (i.e. the initiation of infection by a few cells) have a much larger and more lasting impact than the large populations found after expansion. All of these factors impact the level of standing variation found within populations and, therefore, the evolutionary potential of that population. Currently, we have a good sense of the global variation in the P. syringae complex, but a very poor understanding of how this variation is structured within and between populations and, therefore, how much variation is available for evolution to act on. This is largely a result of the very ad hoc nature by which most strains have been sampled in the past.

Outside of laboratory infection studies, in which population sizes can be strictly controlled, and epidemiological studies, in which the transmission of strains is measured under natural conditions, there have been few direct attempts to gauge population size dynamics within P. syringae. Even in this age of genomics, crucial parameters for the estimation of the effect of drift, such as inoculation doses under natural conditions, population sizes during transmission through the water cycle or within seeds, and what percentage of cells persist or die under various conditions outside of disease outbreaks, remain unknown. We now have the capabilities to sequence samples of P. syringae over a time course of natural infection and across fields, or over time within known reservoirs, to measure how genetic variance changes over multiple time scales. Measurements of genetic diversity through time would greatly inform our understanding of phytopathogen population dynamics. If bottlenecks during infection and transmission strongly influence the effective population size, one a priori prediction would be that a higher frequency of neutral to slightly deleterious mutations would rise to measurable frequency over the course of a disease outbreak. In parallel, as has been performed with Ralstonia, mathematical models of infection can be constructed to evaluate how changes in population size during infection affect disease progression (Jiang et al., 2016).

How does Natural Selection Shape P. syringae Diversity

Much of the recent research into P. syringae has focused on the identification and understanding of host–microbe interactions at a molecular level and the identification of the functions of virulence genes and pathways. Although this approach has yielded incredible insights into the dialogue between plant and pathogen, it is easy to lose sight of the fact that P. syringae cells probably spend much of their time surviving in the environment ex planta or persisting outside of disease outbreaks (Hirano and Upper, 2000; Morris et al., 2013). Any situation in which one genotype is fitter than other genotypes is an opportunity for natural selection to act. Differential nutrient scavenging abilities and metabolic efficiency are fairly obvious targets for selection. Natural selection can also occur if some genotypes are better able to persist under adverse conditions in the absence of growth. Clearly, there are a multitude of factors influencing P. syringae survival and success. Gaining insight into these factors and how they shape the evolutionary dynamics of the species as a whole will require the study of P. syringae populations throughout their full range of agricultural and non‐agricultural niches.

Survival within and transmission across hosts

Although it is generally appreciated that different host species represent different physical, nutritive and immunity environments, there is an undercurrent in the literature presuming that infections by P. syringae occur in a broadly similar fashion across plants. This is probably a significant oversimplification, particularly in the context of thinking about selection pressures acting on P. syringae populations. An annual and ephemeral plant, such as Arabidopsis thaliana, presents a far different selective environment year on year from the long‐lived woody perennial Aesculus hippocastanum (horse chestnut). Little is known about how variables such as host life cycle affect the evolution of P. syringae lineages, but one might expect pathogens of plants, such as Arabidopsis, to be more generalist or to survive ex planta better than those that infect trees, simply because of differences in host environment stability. If infection dynamics in long‐lived hosts are dominated by local selection pressures, rather than a balance between virulence and transmission, ‘short‐sighted’ within‐host microevolution may actually lead to the evolution of traits that decrease the pathogen's likelihood of transmission to other hosts (Levin and Bull, 1994; Winstanley et al., 2016). Moreover, immune systems certainly differ among plant species, but it remains largely unknown how such differences translate to differences in host adaptation (Zipfel, 2014). Further, with long‐lived hosts, there is greater potential for other members of the microbial community to co‐evolve with P. syringae populations, which would certainly modulate evolutionary dynamics and trajectories (Koskella and Parr, 2015). Even framing the questions in terms of where disease naturally occurs might be misleading from an evolutionary standpoint, because it is possible that growth and survival on plants in the absence of symptoms could provide relevant (and differential) selection pressures on lineages of P. syringae.

Although transmission under field conditions has been historically studied, there has been little recent discussion in the literature on the potential for lineages of P. syringae to display differential transmission patterns (Upper et al., 2003). If disease symptoms are correlated with transmission success, one might expect that differences in symptoms could directly reflect differences in transmission capabilities and overall strain fitness. Given that the study of P. syringae in the laboratory has almost exclusively focused on primary infections, it is likely that we have missed important factors influencing other components of survival and transmission. For instance, in Citrobacter, some type III effectors have been shown to function during transmission rather than for growth in vivo (Wickham et al., 2007). It is also likely that some lineages may have evolved preferences for different modes of transmission (e.g. seed‐borne relative to water‐borne transmission), which could reflect in differential ability to survive outside of plants. For example, strains from pathovar phaseolicola tend to be metabolically less versatile than other P. syringae strains and are rarely found during environmental sampling (Morris et al., 2010; Rico and Preston, 2008). In contrast, some lineages may be better adapted for broad transmission across a variety of hosts, and might thus be better than average in dispersal (Morris et al., 2008, 2013). Thus, strains from phylogroup II, which seem to be over‐represented in environmental samples and are better epiphytes than many other lineages, appear to have broader host ranges and maintain strong ice nucleation capabilities (Morris et al., 2013). All of these factors suggest that phylogroup II strains are more reliant on environmental transmission than is pathovar phaseolicola.

Much of the work on P. syringae has focused on growth and survival in a plant–microbe context, and certainly this environment plays a large role in shaping diversity across species. Nevertheless, this is not the only context in which P. syringae is found. Unfortunately, we have little knowledge of what P. syringae does when not associated with crop plants apart from the fact that viable strains can be isolated from rivers, lakes, snow fields, rains and leaf litter (Morris et al., 2007, 2008). These environmental samples raise fascinating and important questions about the ecology and evolution of P. syringae. Are strains growing significantly in environmental reservoirs, or are they simply persisting? What is the evolutionary significance of low‐level growth or persistence on ‘non‐host’ species? How do epidemiological predictions change if some lineages are more likely to exist in environmental or non‐host reservoirs? What is the polarity of source–sink dynamics between agricultural monocultures, natural plant populations and environmental reservoirs? Given the metabolic diversity and ‘hardiness’ of some lineages relative to others (i.e. pv. phaseolicola), as well as the differential presence during environmental sampling, it is very possible that extensive diversity exists across strains for the ability to survive or grow under environmental conditions. If such differences exist, they would dramatically change how we think about populations, and how we imagine selection acting on these populations.

Epidemiology

Epidemiological studies of P. syringae have traditionally focused on the distribution of P. syringae in the environment, linking disease emergence and progression with environmental variables to generate predictive models, and identifying major sources of inoculum (e.g. plant debris and soil) for outbreak events (Beattie and Lindow, 1994a, 1994b; Bonn and Gitaitis, 1982; Bonn et al., 1985; Ercolani et al., 1974; Fryda and Otta, 1978; Hirano and Upper, 1990, Hollaway et al., 2007; Langston et al., 2003, McCarter et al., 1983; Mirik et al., 2005; Sahin, 2001; Scortichini and Tropiano, 1994; Scortichini et al., 1995; Voloudakis et al., 1991; Wechter et al., 2006). Although significant advances in the identification and functional characterization of virulence factors have been made in the last decade, interest in P. syringae epidemiology largely stalled until recent technological advances and the discovery of the global distribution of P. syringae and its association with global water cycles (Cai et al., 2011b; Morris et al., 2008, 2010, 2013; Vinatzer et al., 2014).

Sequencing and analytical advances have tremendously enhanced our ability to study the origin, spread and evolution of bacterial pathogens (Bentley and Parkhill, 2015; Biek et al., 2015). Genomic epidemiology has been used to investigate local transmission, global dissemination and population subdivision (Cui et al., 2013; He et al., 2010; Holt et al., 2012; Jorth et al., 2015; Morelli et al., 2010; Wong et al., 2015), to identify lineages associated with disease progression and the emergence of drug resistance (Diaz Caballero et al., 2015; Feliziani et al., 2014; Marvig et al., 2014; Williams et al., 2015; Winstanley et al., 2016), to clarify the role of mutation and both homologous and heterologous recombination in introducing selectable variation (Croucher et al., 2011; Diaz Caballero et al., 2015; He et al., 2010; Wong et al., 2015), and to monitor disease outbreaks occurring in real time (Leekitcharoenphon et al., 2014). These methods may be readily applied to elucidate the epidemiological and population processes underlying the emergence and spread of pandemic P. syringae lineages.

Comprehensive and unbiased strain collections that include both historical and contemporary disease outbreak isolates are key for the identification of the geographical origin and dissemination routes of emerging epidemic strains (Wilson, 2012). An even more powerful approach utilizes repeated sampling of the same populations over time (longitudinal collection), which enables an estimation of the rates of evolutionary change, identification of the origin and identity of new genetic variants associated with traits of interest, and the inference of time to common ancestry for new epidemic lineages. Although there is considerable interest in the identification of recent transmission events occurring at fine temporal and spatial scales, the outcome of these analyses are dependent on the amount of measurable evolutionary change present in the samples (Biek et al., 2015). A recent phylogeographical investigation of Ralstonia solanacearum global transmission found that, despite sequencing 11 samples collected across 50 years, there were only seven mutations in the 2‐Mbp core genome (Clarke et al., 2015). Low mutation rates hamper efforts to estimate a molecular clock and the tendency to sample heavily during outbreak events (and infrequently between) can produce misleading results as the temporal and genetic structure will be confounded (Clarke et al., 2015; Duchene et al., 2015; Murray et al., 2016; Rieux and Balloux, 2016). Sequencing longitudinally sampled clones from a pathogen population known to be established by a single introduction event (e.g. pv. actinidiae in New Zealand) and/or experimentally inoculated hosts and microcosms would be an illuminating first step in determining the rates of evolution for pathogenic, epiphytic and environmental strains.

Although these approaches have been used extensively in other pathosystems to document waves of clonal emergence, interference and displacement (Didelot et al., 2015; Mutreja et al., 2011; Wong et al., 2015; Zhou et al., 2013), they have not yet been as widely applied to the study of P. syringae outbreaks. Two exceptions are the study of new, virulent lineages of tomato and kiwifruit pathogens. Vinatzer et al. (2014) studied the emergence of the T1 lineage of P. syringae pv. tomato. This clone was first collected in 1961, and completely displaced the JL‐1065 and DC3000 lineages in Europe and North America by 1999 (Cai et al., 2011a). Single nucleotide polymorphism (SNP) sequencing indicates that, although the T1 lineage is diversifying and migrating between Europe and North America, JL‐1065 and ancestral T1 strains persist in South America, Africa and Asia (Cai et al., 2011a).

The recent kiwifruit canker pandemic has been a particularly interesting opportunity for the study of plant disease emergence and global transmission. Early efforts to identify the origin of a pandemic strain of P. syringae pv. actinidiae responsible for disease outbreaks in Europe, New Zealand, Asia and South America identified China as a possible location for the source population (Mazzaglia et al., 2012), although a conclusive finding was clearly hindered by insufficient sampling of Asian isolates (Butler et al., 2013; Marcelletti et al., 2011; McCann et al., 2013). Interestingly, a new lineage sharing a common ancestor with the Korean outbreak lineage has been found recently in Japan, indicating that there is as yet unexplored diversity in the Asian source population of P. syringae pv. actinidiae (Fujikawa and Sawada, 2016). The importance of sampling a pathogen's global and temporal diversity when reconstructing outbreak origins cannot be understated. For example, a phylogenomic analysis of the global spread of a new pandemic lineage of Vibrio cholerae indicated that three successive waves of transmission from a source population in South Asia were responsible for separate outbreak events, with each wave displacing strains from earlier ones (Mutreja et al., 2011). The subsequent inclusion of additional V. cholerae genomes from China revealed an extensive network of inferred migrations between South Asia, China and Southeast Asia, with China acting as both a source and sink of pandemic strains (Didelot et al., 2015). The sampling of P. syringae pv. actinidiae isolates from both historical and contemporary outbreaks of kiwifruit canker disease is not only revealing the origin of the outbreak, but also the role of evolutionary processes in generating novel diversity. Although rates of recombination are lower in P. syringae pv. actinidiae than in other pathogens, such as Streptococcus pneumoniae and Helicobacter pylori, extensive between‐lineage recombination has occurred (McCann et al., 2013). This suggests that ancestors of these strains occupied the same niche prior to their emergence and establishment in agricultural environments in Japan, South Korea and China over the last few decades. Although homologous recombination provides an intriguing glimpse of a diverse source population of P. syringae pv. actinidiae from which different lineages have emerged to cause disease, its presence also makes phylogenetic inference much more difficult by reticulating gene genealogical histories and altering the genetic distance between lineages.

Another epidemiological issue that has received only limited study in P. syringae is the frequency and significance of co‐infections. There is an increasing appreciation from a wide range of pathosystems that interactions between distinct clonal lineages can strongly influence disease outcomes and epidemiological dynamics. For example, work by Bartoli et al. (2015a) has shown that co‐infections of environmental and outbreak P. syringae isolates on kiwifruit resulted in roughly the same total population sizes, although the density of both individual strains was lower than when inoculated individually. They also observed that the ability of the strains to move into the plant vessels and cause disease symptoms was strongly reduced during co‐infection. In other pathosystems, experimental co‐infections of two different Podosphaera plantaginis strains on Plantago lanceolata resulted in greater disease severity and higher transmission than singly infected plants (Susi et al., 2015). Co‐infection was also found to be common in natural populations and associated with heightened pathogen population sizes (Susi et al., 2015). Longitudinally sampled isolates of H. pylori from chronically infected hosts showed that mixed infections were frequent and associated with higher levels of both mutation and recombination than isolates from a single infection (Kennemann et al., 2011). Whole genome sequencing of 3085 S. pneumoniae isolates sampled from infants and mothers residing in a 2.4‐km² refugee camp over a period of 3 years revealed the coexistence of and frequent recombination between multiple lineages of S. pneumoniae (Chewapreecha et al., 2014). Rates of recombination varied between lineages, but the same genomic loci were consistently subject to recombination. These hotspots included genes encoding cell surface antigens and antibiotic resistance genes (Chewapreecha et al., 2014).

Another critically important, yet underexplored, question is whether it is possible to anticipate the emergence of new pathogenic clones. In the study by Bartoli et al. (2015a), the authors found that environmental (non‐agricultural) isolates shared many features with genetically similar, host‐associated lineages. These similarities included a key operon involved in metabolite catabolism and many, but not all, type III effectors. What is not entirely clear is what loci are necessary and sufficient for disease, and whether the environmental strains carry these loci.

Outbreaks of kiwifruit bleeding canker disease over the last three decades have been caused by distinct lineages of P. syringae pv. actinidiae (McCann et al., 2013). These lineages display a surprising level of variability: their core genomes differ from each other by approximately 1000 SNPs, and only 27 of 44 effectors were found to be conserved among all three canker‐causing lineages. Despite this, strains from all three lineages were able to grow to high densities in different host varieties. It is therefore highly likely that the severity of the latest pandemic is more strongly linked with the expansion of cultivation of a highly susceptible host variety and increased trade in plant material, than with the emergence of a more virulent strain. Evidence of between‐lineage recombination indicates that ancestors of these lineages coexisted in the same host environment long enough to exchange genetic material. The identification of the source from which these lineages emerged and the characterization of the diversity therein are necessary steps in predicting the likelihood of a novel variant emerging to cause disease in the future.

The development of bacterial genome‐wide association methods capable of managing problems related to the unique demographic and population genetics of bacteria (e.g. poorly defined population structures and complex patterns of recombination, selection and genetic hitchhiking) will tremendously accelerate our ability to identify genetic factors responsible for pathogen emergence (Chen and Shapiro, 2015; Dutilh et al., 2013; Sheppard et al., 2013). Hopefully, these data will ultimately enable us to identify, anticipate and pre‐empt new disease outbreaks.

The application of new methods in genomic epidemiology will contribute to our understanding of how epidemic clones of P. syringae adapt to specific crops, compete with pre‐existing clonal lineages and are disseminated. As host abundance and diversity are more readily quantifiable in agricultural systems, hosts are largely sessile (although there is extensive potential dispersal via pollen, seed and anthropogenic activity) and climate data can be readily acquired, plant–pathogen systems provide an excellent opportunity to explore the mechanisms, constraints and drivers of pathogen emergence, competition and transmission.

Microbiomes

Although our goal for this review was a general discussion of P. syringae evolution, we would like to end by mentioning one specific, yet widespread, selection pressure that probably shapes population dynamics across lineages. The last decade has witnessed tremendous growth in studies of microbiomes, their role in maintaining the health of their hosts and environments, and the complex of interactions that govern community stability and function. We are just beginning to understand how the plant microbiome influences plant growth, development and pathogen susceptibility, and cannot help but imagine how our understanding of these systems will be transformed as this field continues to grow and develop. In the context of discussions about selection pressures, it is likely that microbe–microbe interactions and direct competition between lineages strongly structure P. syringae communities. The analysis of interactions between lineages could therefore provide ecological insights into how to define population limits and which strains are in direct competition with one another under natural conditions. Moreover, interactions between microbes are key for the structuring of horizontal gene transfer. Such interactions remain relatively understudied, but a deeper understanding of these forces could lead to novel means to control the growth of pathogens and to promote the growth of beneficial bacteria.

It is clear that interactions between both prokaryotic and eukaryotic microbial species can directly alter P. syringae‐associated communities and probably influence evolutionary diversification. Some P. syringae toxins have well‐documented antibacterial and antifungal properties (Scholz‐Schroeder et al., 2001), and interspecific bacterial warfare clearly shapes P. syringae populations (Haapalainen et al., 2012). In an experimental study on the interactions among phyllosphere bacteria and herbivores in bittercress (Cardamine cordifolia), the abundance of pseudomonads was found to be negatively correlated with microbes, such as Sphingomonas and Brevidomonas, and positively correlated with Rathayibacter (Humphrey et al., 2014). The Sphingomonas correlation is particularly intriguing when one considers that strains from this genus have been shown to protect plants from infection by P. syringae and other phytopathogens, potentially through competitive exclusion and nutrient acquisition (Innerebner et al., 2011, Vogel et al., 2012). Of course, P. syringae also shares a niche with a wide variety of eukaryotic microbes, and it has been suggested that strains can scavenge nutrients from some of these fungi (Wichmann et al., 2008). A better understanding of interactions between P. syringae and fungi would provide an interesting parallel to those documented between P. aeruginosa and Candida (Mear et al., 2013). Furthermore, it remains possible that one or more type III secretion systems play a direct role in the interactions between P. syringae and fungi or other microbial eukaryotes (Cusano et al., 2011; Rezzonico et al., 2005). Finally, P. syringae populations probably experience strong selective pressures from resident phages over both space and time, at least in long‐lived plants, such as horse chestnut (Koskella, 2013, 2014).

Distinct lineages of P. syringae also interact with each other in the environment, and it is possible that intraspecific interactions are quite common during epiphytic growth. Evidence for strong intraspecific competition comes from the identification of bacteriocins in many P. syringae genomes. These proteinaceous compounds are thought to only target strains closely related to the producer. Indeed, our own recent efforts, and those of numerous other groups, have demonstrated the widespread presence of intraspecies killing activity across P. syringae strains. We have recently documented a phage‐derived bacteriocin locus conserved throughout P. syringae and found within other pseudomonads which is akin to, but independently evolved from, R‐type pyocins of P. aeruginosa (Hockett et al., 2015). This system stands out because of its widespread presence across the species, but also because, having been derived from phage, its target range appears to be highly specific. Conservation of this locus implies that its maintenance is beneficial for clones under natural conditions, and following from bacteriocin dogma, this strongly implies that intraspecies killing is an important aspect of survival in P. syringae populations. As strain coexistence is promoted by diversification of nutritional capabilities rather than overlap, it is possible that bacteriocins provide a direct means to competitively exclude strains that are in direct competition for limiting resources (Wilson and Lindow, 1994). Moreover, if bacteriocin production and resistance patterns reflect aspects of underlying strain ecology, it is possible that a deeper understanding of the forces shaping the production and evolution of these molecules will also provide insights into general questions about P. syringae evolution and species structure writ large.

These described selection pressures, and many more which we have not touched upon, no doubt shape P. syringae genetic diversity under natural conditions. Although it is easy to ‘just’ focus on virulence factors in planta, many other variables contribute to disease incidence and severity, as well as the evolution of bacterial populations in the field, a view captured by the idea of the ‘Disease Triangle’ (Scholthof, 2007). Unlike the vast majority of experimental work, these factors do not act in isolation. Epistatic interactions and pleiotropy are probably the rule rather than the exception, as well as complex genotype‐by‐phenotype interactions and stochastic processes. Furthermore, our understanding of microbe–host interactions is very strongly influenced by subjective and anthropocentric concepts of virulence and host range. These factors may help to explain why so many pathogen control strategies that are robust in the laboratory fail when moved into a more complex agricultural context. How these variables combine to shape natural infections remains a virtual black box, but one that is ripe for illumination in the age of genomics.

Conclusion and Future Prospects

Studies of P. syringae have historically played a foundational role for understanding the molecular basis of phytopathogen infection, as well as the ecology of plant‐associated bacterial populations. Although recent research efforts have largely focused on an understanding of the mechanistic basis of virulence, we believe that coupling the rich and diverse literature describing wild populations with incredible advances in genomics will facilitate a transformation in our understanding of the natural history of P. syringae. Our ability to catalogue extensive genomic diversity across P. syringae lineages has already raised new, major questions about ecology and evolution. ‘How do we define species limits for P. syringae?’ ‘Why is recombination rampant across subsets of strains?’ Now that it is possible to sequence microbial genomes in real time in the field, there are exciting possibilities for tracking the spread and dissemination of P. syringae outbreaks as they occur, but we still have no idea how to predict the next outbreak. Increased sampling of environmental and agricultural strains in the absence of disease and of non‐traditional reservoirs will provide critical context for evolutionary studies. Unbiased sampling is also required for any genome‐wide, association‐based analysis. Much more comprehensive and unbiased collections are required if we wish to take full advantage of comparative genomics to identify genotype–phenotype associations.

As we have highlighted in this review, there is great potential to exploit P. syringae to address fundamental evolutionary questions within an agriculturally relevant framework. Although operational and theoretical challenges persist, the diversity, ubiquity, agronomic significance and rich knowledge base of the species will help maintain its position at the forefront of bacterial phytopathogen research.

Conflict of Interest

The authors declare they have no conflicts of interest.