Pan-genome analysis identifies intersecting roles for Pseudomonas specialized metabolites in potato pathogen inhibition

Agricultural soil harbors a diverse microbiome that can form beneficial relationships with plants, including the inhibition of plant pathogens. Pseudomonas spp. are one of the most abundant bacterial genera in the soil and rhizosphere and play important roles in promoting plant health. However, the genetic determinants of this beneficial activity are only partially understood. Here, we genetically and phenotypically characterize the Pseudomonas fluorescens population in a commercial potato field, where we identify strong correlations between specialized metabolite biosynthesis and antagonism of the potato pathogens Streptomyces scabies and Phytophthora infestans. Genetic and chemical analyses identified hydrogen cyanide and cyclic lipopeptides as key specialized metabolites associated with S. scabies inhibition, which was supported by in planta biocontrol experiments. We show that a single potato field contains a hugely diverse and dynamic population of Pseudomonas bacteria, whose capacity to produce specialized metabolites is shaped both by plant colonization and defined environmental inputs.


Introduction
Plant pathogenic microorganisms are responsible for major crop losses worldwide and represent a substantial threat to food security. Potato scab is one of the main diseases affecting potato quality (Larkin et al., 2011) and presents a significant economic burden to farmers around the world. The Gram-positive bacterium Streptomyces scabies, which is the causal organism of potato scab, is ubiquitous and presents a threat in almost all soils (Bignell et al., 2010;Lerat et al., 2009). Properly managed irrigation is a reasonably effective control measure for potato scab. However, scab outbreaks still regularly occur in irrigated soil, and with increasing pressures on water use it is clear that alternative approaches to the control of scab are needed. An attractive potential alternative involves the exploitation of soil microorganisms that suppress or kill plant pathogens, known as biocontrol agents (Köhl et al., 2019;Weller, 2007).
Many soil-dwelling Pseudomonas species form beneficial relationships with plants, positively affecting nutrition and health (Cheng et al., 2017;Loper et al., 2012;Zamioudis et al., 2013) and exhibiting potent antagonistic behavior towards pathogenic microorganisms (Biessy et al., 2019;Haas and Défago, 2005;Weller, 2007). Pseudomonas influence the plant environment using a diverse range of secondary metabolites (Arseneault et al., 2013;Gross and Loper, 2009;Nguyen et al., 2016;Stringlis et al., 2018) and secreted proteins (Ghequire and De Mot, 2014;Rangel et al., 2016). As such, Pseudomonas sp. have been identified as key biocontrol organisms in numerous plant-microbe systems (Mauchline et al., 2015;Wei et al., 2019), and these bacteria have potential applications as agricultural biocontrol agents and biofertilizers (Kwak and Weller, 2013;Weller, 2007). Many soil pseudomonads belong to the Pseudomonas fluorescens group, which consists of over 50 subspecies and exhibits huge phenotypic and genetic diversity (Biessy et al., 2019;Gomila et al., 2015;Loper et al., 2012;Melnyk et al., 2019;Silby et al., 2009), with a core genome of about 1300 genes and a pan-genome of over 30,000 genes (Garrido-Sanz et al., 2016). These bacteria use a variety of mechanisms to colonize the plant rhizosphere (Little et al., 2019), communicate with plants (Zamioudis et al., 2013), and suppress a range of plant pathogens (Haas and Défago, 2005), including bacteria (Arseneault et al., 2015), fungi (Michelsen et al., 2015), and insects (Flury et al., 2017), although a single strain is unlikely to have all of these attributes. Specialized metabolites are critical to many of these ecological functions, and the Pseudomonas specialized metabolome is one of the richest and best characterized of any bacterial genus (Gross and Loper, 2009;Nguyen et al., 2016;Stringlis et al., 2018).
Various studies have associated pseudomonads with potato scab suppression. A significant increase in the abundance of Pseudomonas taxa has been observed for irrigated fields, correlating with reduced levels of potato scab (Elphinstone et al., 2009). Naturally scab-suppressive soils have also been shown to contain a greater proportion of Pseudomonas when compared to scab-conducive eLife digest Potato scab and blight are two major diseases which can cause heavy crop losses.
They are caused, respectively, by the bacterium Streptomyces scabies and an oomycete (a fungus-like organism) known as Phytophthora infestans.
Fighting these disease-causing microorganisms can involve crop management techniques -for example, ensuring that a field is well irrigated helps to keep S. scabies at bay. Harnessing biological control agents can also offer ways to control disease while respecting the environment. Biocontrol bacteria, such as Pseudomonas, can produce compounds that keep S. scabies and P. infestans in check. However, the identity of these molecules and how irrigation can influence Pseudomonas population remains unknown.
To examine these questions, Pacheco-Moreno et al. sampled and isolated hundreds of Pseudomonas strains from a commercial potato field, closely examining the genomes of 69 of these. Comparing the genetic information of strains based on whether they could control the growth of S. scabies revealed that compounds known as cyclic lipopeptides are key to controlling the growth of S. scabies and P. infestans. Whether the field was irrigated also had a large impact on the strains forming the Pseudomonas population.
Working soils Rosenzweig et al., 2012), and phenazine production by P. fluorescens can contribute to scab control (Arseneault et al., 2015;Arseneault et al., 2013;Arseneault et al., 2016). Differences between soil microbial populations that enable effective pathogen suppression are routinely assessed using amplicon sequencing (Fierer, 2017;Rosenzweig et al., 2012). However, the heterogeneity of the P. fluorescens group limits the usefulness of these methods for observing changes at the species or even the genus level. To effectively determine the relationship between the soil Pseudomonas population and disease suppression, it is important to accurately survey genotypic and phenotypic variability at the level of individual isolates, and to determine how this variation is linked to agriculturally relevant environmental changes (Mauchline and Malone, 2017).
To investigate the genetic bases for S. scabies inhibition by P. fluorescens and to assess whether the scab-suppressive effects of irrigation derive from increased populations of biocontrol genotypes in the soil or on the plant, we focused on the Pseudomonas population from a potato field susceptible to potato scab. We first employed a phenotype-genotype correlation analysis across P. fluorescens strains isolated from a single potato field. We hypothesized that an unbiased correlation analysis would identify genetic loci and biosynthetic gene clusters (BGCs) that may be overlooked by screening for bioactive small molecules or by focusing on the biosynthetic repertoire of a limited number of strains. Here, we correlated phylogeny, phenotypes, specialized metabolism, and accessory genome loci, then investigated the importance of strong correlations by genetic manipulation of selected wild isolates. In total, 432 Pseudomonas strains were phenotyped (with 69 whole genomes sequenced). This approach also enabled us to answer a number of ancillary questions: how diverse is the P. fluorescens population from a single field location? Do the phenotypes associated with a P. fluorescens strain correlate with its biosynthetic capacity? What does irrigation do to both the population structure of the P. fluorescens group and to the wider bacterial community? Using this approach, we identify the P. fluorescens genes, gene clusters, and natural products that are required for potato pathogen suppression in vitro. We use this data to inform the discovery that the cyclic lipopeptide (CLP) tensin is a key determinant of in planta pathogen suppression by a Pseudomonas species. We show that irrigation induces profound and repeatable changes in the microbiome, both on a global level and within the P. fluorescens species group. Finally, we propose a model for the relationship between irrigation, pathogen suppression, and population-level shifts within the plant-associated P. fluorescens population.

Irrigation induces a significant change in the soil microbiome
The ability of irrigation to protect root vegetables against S. scabies infection is agriculturally important and widespread, but poorly understood. It is likely that the irrigated soil microbiota plays a role in mediating scab suppression, but how this occurs is unclear. We therefore assessed the impact of irrigation on the total bacterial population of a commercial potato field in the United Kingdom. Multiple soil samples were taken from two sites (A1 and B1) within this field, immediately prior to potato planting in January. Following potato planting, one site was irrigated as normal (site A), while the second was protected from irrigation (site B). Tuber-associated soil was sampled from both sites in May (A2 and B2) when tubers were just forming, and the plants were most susceptible to S. scabies infection. Total genomic DNA was then extracted from replicate samples of each site after each sampling event, and 16S rRNA amplicon sequencing was used to examine the bacterial population in each of these sites ( Figure 1).
We used voom (Law et al., 2014) with a false discovery rate (FDR) of 0.05 to assess population changes across the four sampling sites. In total, changes were observed for 26 bacterial orders ( Figure 1A), with the most significant changes observed between January and May regardless of irrigation. This partially reflects an increase in bacterial orders that have previously been associated with the potato root microbiome (Pfeiffer et al., 2017;Weinert et al., 2011), including Rhizobiales, Sphingomonadales, and Flavobacteriales. Significant population changes (FDR < 0.05) were also observed for eight bacterial orders between the irrigated (A2) and nonirrigated (B2) sites ( Figure 1B and C), including a larger proportion of Pseudomonadales bacteria in the irrigated site. In contrast, despite the potential for microbial heterogeneity across the fertilized field prior to planting, no significant changes were observed between pre-planting sites A1 and B1. Phenotypic, phylogenetic, and genomic analysis of the P. fluorescens field population Taxonomic identifications using 16S rRNA amplicon analysis showed order-level changes to the field microbiome between sites (Figure 1-figure supplement 1) but were unable to accurately capture diversity within genera or species groups. Therefore, biologically relevant variation within the populations of genetically diverse species groups such as P. fluorescens is potentially overlooked. To investigate the diversity of the fluorescent pseudomonad population, we isolated 240 individual Pseudomonas strains from our pre-and post-irrigation field sites (Supplementary file 1). These strains were screened for multiple phenotypes including motility, protease production, fluorescence (siderophore production), and on-plate suppression of S. scabies using a cross-streak assay (Figure 2-figure supplements 1 and 2). Each phenotype was scored on an ordinal scale between 0 (no phenotype The 26 bacterial orders whose populations were determined to significantly differ across one or more sampling sites using voom with a false discovery rate of 0.05. Data are shown as a heatmap of the log 2 -fold change with respect to the overall average counts per million for a given order. Sample A1a was omitted from the analysis due to possible contamination leading to an atypical bacterial population ( The eight bacterial orders whose populations were determined to significantly differ between irrigated and nonirrigated sites, represented as counts per million reads. Error bars represent the standard deviation of triplicate data. The online version of this article includes the following source data and figure supplement(s) for figure 1: Source data 1. Read counts for data reported in Figure 1. observed) and 3 (strong phenotype). The cross-streak assay provided a rapid read-out of bacterial antagonism for both contact-dependent and diffusible mechanisms of growth inhibition. On-plate suppression of S. scabies was a surprisingly rare trait, with 79% of Pseudomonas isolates outcompeted by S. scabies in this assay. To determine whether this suppressive activity correlated with specific genetic loci, 69 isolates were selected for whole-genome sequencing, where almost half (32 strains) exhibited on-plate suppression of S. scabies and the remaining strains represented a diverse selection (based on phenotypic variation and 16S rRNA sequencing) of nonsuppressive strains. We hypothesized that a comparative analysis of a similar number of genomes from suppressive and nonsuppressive strains would identify those BGCs that play important roles in suppressive activity. The phylogeny of the 69 sequenced strains was analyzed alongside various model pseudomonads, including representatives of the eight phylogenomic P. fluorescens groups defined by Garrido-Sanz et al., 2016. Our sequenced strain collection spans much of this characterized global phylogenetic diversity and contains representatives of at least five of the eight P. fluorescens phylogenomic groups (Garrido-Sanz et al., 2016), as well as strains belonging to the Pseudomonas putida and Pseudomonas syringae groups (Figure 2-figure supplement 3). This genetic heterogeneity was also reflected in the diverse specialized metabolome of these strains, as predicted by a detailed analysis of the BGCs encoded in their genomes. Each genome was subjected to antiSMASH 5.0 analysis (Blin et al., 2019), which was further refined by extensive manual annotation to improve the accuracy of predicted pathway products. This second annotation step was particularly important for BGCs that are atypically distributed across two distinct genomic loci (e.g., viscosin and pyoverdine). Our analysis was further expanded to include BGCs not identified by antiSMASH 5.0, including BGCs for hydrogen cyanide (HCN) , microcin B17-like pathways , and the auxin indole-3-acetic acid (IAA) Palm et al., 1989). This was achieved by searching the genomes with a curated set of known Pseudomonas BGCs using MultiGeneBlast (Medema et al., 2013) (see Appendix 1 for further details). This manual annotation provided a level of resolution superior to that provided by automated cluster-searching algorithms alone and provided confidence that the majority of natural product biosynthetic potential had been identified. Within a given pathway type (e.g., nonribosomal peptide synthetases [NRPSs]), likely pathway products were assigned where possible (e.g., CLPs) or assigned a code when a conserved uncharacterized BGC was identified (e.g., NRPS 1). All BGCs were mapped to strain phylogeny ( Figure 2).
In addition to these potentially antibacterial and cytotoxic compounds, all genomes contain BGCs predicted to produce the plant auxin IAA, while 23 genomes contained genes for IAA catabolism (Leveau and Gerards, 2008). All 69 strains had at least one BGC for the production of the electrontransport cofactor pyrroloquinoline quinone (PQQ) (Puehringer et al., 2008;Appendix 1-figure 4), reported to function as a plant growth promoter . Surprisingly, BGCs for numerous well-characterized Pseudomonas specialized metabolites were not found, including phenazine, pyrrolnitrin, or 2,4-diacylphloroglucinol BGCs (Gross and Loper, 2009). In total, 787 gene clusters were identified that could be subdivided into 61 gene cluster families ( Figure 2).
The P. fluorescens species group possesses a highly diverse array of nonessential accessory genes and gene clusters. These are often critical to the lifestyle of a given strain and can include motility determinants, proteases, secretion systems, polysaccharides, toxins, and metabolite catabolism pathways (Mauchline et al., 2015). These accessory genome loci were identified using MultiGeneBlast  In the phylogenetic tree of Pseudomonas strains, blue strains were collected from irrigated plots while orange strains were collected from unirrigated plots. All other strains were collected from the pre-irrigation plots.   (details in Appendix 1), which revealed a high degree of genomic diversity across strains. Specialized metabolism BGCs and accessory genome loci were mapped to strain phylogeny (Figure 2), which indicated that for some loci (e.g., the psl operon, auxin catabolism, HCN biosynthesis) there is a close, but not absolute, relationship between phylogeny and the presence of a gene cluster.
Correlation analysis identifies potential genetic determinants of S. scabies inhibition We hypothesized that genes associated with suppression of S. scabies could be identified by a correlation analysis between S. scabies cross-streak inhibition and the presence of BGC families or accessory genes. We therefore calculated Pearson correlation coefficients for each BGC with S. scabies inhibition ( Figure 3-figure supplement 1). The top 10 positively correlating genotypes and phenotypes ( Figure 3) comprised four BGC families (Pep1, CLP, Pep2, and HCN) (Appendix 1-figure 2), four accessory genome loci (chitinase ChiC, protease AprA, chitinase class 1, and the Pga operon), and two phenotypes (motility and secreted protease production). The production of HCN and/or CLPs by Pseudomonas strains has been previously associated with the suppression of various plant pathogens including fungi (Michelsen et al., 2015;Zachow et al., 2015) and oomycetes (Hultberg et al., 2010;Hunziker et al., 2015), and can also contribute to insect killing (Flury et al., 2017;Jang et al., 2013), but have not been linked to the suppression of bacteria. A variety of genotypes associated with plant-microbe interactions were moderately negatively correlated with suppression (ρ < -0.3), including BGCs for PQQ biosynthesis and catabolism of the plant auxins IAA and phenylacetic acid (PAA) ( Figure 3A). Interestingly, while certain BGC loci (e.g., CLP) positively correlated with both suppression and motility, this relationship was not seen for every locus (e.g., HCN correlates with suppression but is less strongly correlated with motility). Correlation does not equate to causation, especially considering the significant evolutionary association seen for some BGCs (Figure 2). The importance of correlating BGCs to S. scabies suppression was therefore investigated experimentally using a genetically tractable subset of suppressive isolates.    Production and role of CLPs in the suppression of S. scabies The strong positive correlation between putative CLP gene clusters and S. scabies suppression prompted us to investigate whether CLPs play a role in suppressive activity. Pseudomonas CLPs have previously been associated with a wide array of functions, including fungal growth inhibition, plant colonization, and promotion of swarming motility (Alsohim et al., 2014;Raaijmakers et al., 2010), although there are no reports of Pseudomonas CLPs functioning as inhibitors of streptomycete growth. However, prior work has shown that surfactin, a CLP from Bacillus subtilis, inhibits Streptomyces coelicolor aerial hyphae development (Straight et al., 2006), while iturin A, a CLP from Bacillus sp. sunhua, inhibits S. scabies development (Han et al., 2005).
To determine the identity of each CLP, we combined bioinformatic predictions of the NRPS products (Blin et al., 2019) with experimental identification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). In every strain that contained a CLP BGC, a molecule with an expected mass and MS/MS fragmentation pattern was identified ( Kuiper et al., 2004). In addition, an array of related metabolites were observed that differed by 14 or 28 Da, which is characteristic of different lipid chain lengths. This analysis also proved that the linear lipopeptides syringafactin A (m/z 1082.74) and cichofactin (m/z 555.38, [M + 2 H] 2+ ) were made by strains harboring BGCs predicted to make these phytotoxins (Götze et al., 2019;Pauwelyn et al., 2013;Figure 4- figure supplements 6 and 7). The metabolic capacity of all strains was mapped using mass spectral networking (Aron et al., 2020;Wang et al., 2016), which showed that CLPs were strongly associated with strains that inhibit S. scabies ( Figure 4).
To assess the potential role of CLPs in mediating the interaction between P. fluorescens and S. scabies, an NRPS gene predicted to be involved in the biosynthesis of a viscosin-like molecule in Ps682 was deleted by allelic replacement ( Figure 5A). The resulting Ps682 ∆visc strain was unable to make the viscosin-like molecule (m/z 1126.69, Figure 5B) or to undergo swarming motility ( Figure 5figure supplement 1). This is in agreement with earlier work on the role of viscosin in the motility of P. fluorescens SBW25 (Alsohim et al., 2014) and the observation that possession of a CLP BGC was the genotype that most strongly correlated with motility (ρ = 0.65, Figure 3-figure supplement 1). A cross-streak assay with S. scabies revealed an active role for this CLP in on-plate S. scabies inhibition ( Figure 5D). Wild-type (WT) Ps682 appeared to specifically colonize the S. scabies streak, whereas Ps682 ∆visc was unable to restrict S. scabies growth. Alternatively, it was possible that this instead could reflect diffusible inhibition of Streptomyces development by WT Ps682, leading to a 'bald' S. scabies phenotype (Flärdh and Buttner, 2009). To distinguish between these possible inhibition modes, a constitutively expressed lux operon was integrated into the chromosomal att::Tn7 site (K.-H. Choi et al., 2005) of Ps682 to visualize this interaction by bioluminescence. This clearly showed viscosin-dependent Pseudomonas colonization of the Streptomyces streaks ( Figure 5D).
To quantitatively assess the antagonistic effect of the Ps682 CLP, it was purified and structurally characterized using MS/MS (  et al., 2012). However, comparison of NMR data in DMF-d7 revealed some minor shift differences between published WLIP spectra (Rokni-Zadeh et al., 2012) and the Ps682 CLP, such as the γ-CH 2 group of Glu2 (WLIP = δ H 2.54 ppm, δ C 30.3 ppm; Ps682 CLP = δ H 2.24 ppm, δ C 34.8 ppm). Therefore, we could not conclusively confirm the absolute configuration of the Ps682 CLP and thus named it viscosin I (for viscosin Isomer). A disk diffusion assay of purified viscosin I with S. scabies ( Figure 5C) Figure 4. Mass spectral networking analysis of liquid chromatography-tandem mass spectrometry (LC-MS/MS) data from the Pseudomonas strains used in this study. Node area is proportional to the number of distinct strains where MS/MS data were acquired for a given metabolite. Node color reflects the proportion of MS/MS scans for a given node that come from strains with a S. scabies inhibition score ≥1. Nodes are labeled with the corresponding parent masses and nodes that relate to lipopeptides are labeled (multiple networks arise from differential fragmentation of [M + H] + , [M + 2H] 2+ , and [M + Na] + ions). Line thickness is proportional to the cosine similarity score calculated by Global Natural Product Social Molecular Networking (GNPS) (Aron et al., 2020). The table shows production of lipopeptides by strains containing lipopeptide biosynthetic gene clusters (BGCs). Color coding reflects level of S. scabies inhibition by each strain with same scale as                     indicated that the inhibition of S. scabies is temporary and growth partially resumes after several days. These data show that in addition to its role as a surfactant viscosin I functions by inhibiting the growth rate of S. scabies, consistent with the on-plate data for Ps682 ∆visc.
HCN and CLP production both contribute to on-plate S. scabies inhibition Pan-genome analysis showed that HCN production was predicted for a significant number of suppressive strains (ρ = 0.47, Figure 3-figure supplement 1), where 17 of the 19 strains containing HCN gene clusters were inhibitory towards S. scabies (Figure 2). The HCN pathway is encoded by the hcnABC gene cluster (Appendix 1-figure 2) and has previously been associated with insect and fungal pathogen inhibition in other Pseudomonas strains (Flury et al., 2017;Hunziker et al., 2015;Siddiqui et al., 2006). HCN is toxic to a wide variety of organisms, but not to Pseudomonas owing to their branched aerobic respiratory chain that has at least five terminal oxidases, including a cyanideinsensitive oxidase (Comolli and Donohue, 2002;Ugidos et al., 2008). We confirmed that nearly every strain with the hcnABC gene cluster produced HCN (18 out of 19) using the Feigl-Anger colorimetric detection reagent (Feigl and Anger, 1966; Supplementary file 1) and used this assay to identify HCN producers across the original collection of 240 Pseudomonas strains. This wider analysis showed that HCN production strongly correlated with S. scabies inhibition (ρ = 0.52, Figure 6figure supplement 1), in accordance with our analysis of the sequenced strains.
To examine the role of HCN in S. scabies suppression and whether it exhibited a synergistic effect with CLP production, Ps619 was investigated as this strain produces both HCN and a tensin-like CLP (Figures 2 and 6A). A tensin BGC has not previously been reported, but the predicted amino acid specificity, mass ( Figure 6A), and MS/MS fragmentation ( Figure 4-figure supplement 3) indicated that seven isolates produce tensin-like CLPs ( Figure 4). The hcn and ten gene clusters were inactivated by in-frame deletions to generate single and double mutants of Ps619, and the resulting Δhcn, Δten, and ΔhcnΔten mutants were subjected to cross-streak assays ( Figure 6B). A comparison of WT, single, and double mutants showed that HCN inhibits S. scabies growth and development across the entire plate, while tensin is important for Pseudomonas motility and helps the Pseudomonas to grow competitively at the cross-streak interface. Furthermore, this suppressive effect is additive: the Ps619 Δhcn and Δten single mutants both retained some inhibitory activity towards S. scabies, whereas the Ps619 ΔhcnΔten double mutant could not inhibit S. scabies.
In drier growth conditions expected to favor streptomycete growth and limit motility, the role of tensin-mediated motility was abrogated, yet tensin and HCN still possessed an additive inhibitory effect at the microbial interface ( Figure 6-figure supplement 2A). Notably, Ps619 Δhcn was able to induce a developmental defect in S. scabies at the microbial interface that was not present in Ps619 Δten or Ps619 ΔhcnΔten, showing that the tensin-like CLP induces a developmental defect in S. scabies that is independent of Pseudomonas motility, comparable to the inhibitory effect of isolated viscosin I. This analysis also clearly showed that at areas distant from the bacterial interaction S. scabies grew more vigorously when cultured with Δhcn strains, consistent with the volatility of HCN enabling a long-range inhibitory effect. A similar volatile effect was seen when Ps619 strains were separated from S. scabies by a barrier, where only those strains producing HCN inhibited growth and development ( Figure 6-figure supplement 2B).
To further probe how tensin and HCN affected the interaction between Ps619 strains and S. scabies, the interfacial regions of cross-streaks were imaged using cryo-scanning electron microscopy (cryo-SEM). WT Ps619 was able to colonize the S. scabies streak, meaning that the interfacial region imaged was further from the cross-streak intersection than all other co-cultures ( Figure 6C). Here, Ps619 inhibited S. scabies development, which appears as a mixture of deformed aerial hyphae and    vegetative growth reminiscent of a 'bald' phenotype (Tschowri et al., 2014). Cryo-SEM indicated that both the Ps619 Δhcn and Δten mutants induced a similar partially bald phenotype in S. scabies, but the ΔhcnΔten double mutant was unable to trigger the same developmental defect as S. scabies could develop aerial mycelia close to the microbial interface ( Figure 6C, Figure 6-figure supplement 3). This appears as a clear boundary between Ps619 ΔhcnΔten (single cells in background, bottom right panel of Figure 6C) and S. scabies (hyphae in the foreground). The volatile HCN can inhibit growth and development at a distance, whereas CLP inhibition of development only occurs close to the microbial interface. Both inhibitory mechanisms enable Ps619 to obtain a competitive advantage at the microbe-microbe interface ( Figure 6C, Figure 6-figure supplement 3), while the CLP also functions as a surfactant enabling Ps619 motility, promoting Pseudomonas invasion of the Streptomyces cross-streak.

Tensin is a key determinant of in planta inhibition of potato scab
To examine the in planta biocontrol properties of Ps619 and Ps682, and to determine the contribution of HCN and CLPs to activity, potato scab suppression assays were carried out in glasshouse trials. Maris Piper potatoes were infected with S. scabies 87-22 and scored for disease severity after 16 weeks using the method of Andrade et al., 2019. A subset of plants was also treated with Pseudomonas spp. and associated BGC mutants. Ps619 conferred significant protection against potato scab, where disease severity was reduced to levels similar to uninfected control plants (Figure 7). This suppressive ability was lost for Ps619 Δten and Ps619 ΔhcnΔten, resulting in disease severity similar to scab-infected tubers. In contrast, Ps619 Δhcn was just as effective as WT Ps619 at suppressing potato scab, which differed from the on-plate results for HCN. The significance of these results was supported by an independent in planta biocontrol experiment, where equivalent results were obtained for each strain (Figure 7-figure supplement 1). This result indicates that tensin plays an important role in the biocontrol of potato scab. In contrast to its on-plate suppressive activity, potato scab assays showed no significant antagonistic activity for Ps682 against S. scabies infection. Unfortunately, this meant that the role of viscosin I could not be determined in planta.
A subset of P. fluorescens strains are generalist pathogen suppressors To determine whether the strains and metabolites we identified have suppressive activity towards a range of plant pathogens, we investigated the ability of the potato field strain collection to suppress the growth of Phytophthora infestans, the oomycete that causes potato blight (Nowicki et al., 2012), and Gaeumannomyces graminis var. tritici, the fungus that causes take-all disease of cereal crops (Mauchline et al., 2015). These assays revealed strong congruence between the genotypes that correlated with suppression of each pathogen (Appendix 2-figure 1A). HCN and CLPs have both previously been identified as inhibitors of oomycete and fungal growth (Hunziker et al., 2015;Michelsen et al., 2015). To assess whether these natural products are critical for inhibition of P. infestans and G. graminis by Ps619 and Ps682, the HCN/CLP mutants were tested for inhibitory activity (Appendix 2-figure 1). Surprisingly, neither HCN or tensin were required for Ps619 inhibition of either G. graminis or P. infestans (Appendix 2-figure 1), indicating the production of at least one other secreted inhibitory factor. In contrast, inactivation of the viscosin I pathway in Ps682 abolished activity towards both pathogens (Appendix 2-figure 1D). These data indicate that a subset of pseudomonads can function as generalist pathogen suppressors, possessing multiple growth inhibition mechanisms (e.g., Ps619) and/or by producing molecules with broad bioactivity (e.g., Ps682).
Other studies indicate that DUF692 and DUF2063 proteins may be involved in heavy metal and/or oxidative stress responses (Clark et al., 2014;Price et al., 2018;Sarkisova et al., 2014). Further work is required to determine the significance of both the Pep BGCs and the accessory genome loci for pathogen inhibition.

The effect of irrigation on the soil Pseudomonas population
Irrigation is currently the only effective way to control potato scab, so we hypothesized that this may lead to an increase in the number of inhibitory bacteria associated with the soil and/or tuber, especially as the Pseudomonadales population moderately increased in irrigated soil ( Figure 1C). However, a greater number of strongly suppressive strains (inhibition score ≥2) were isolated from nonirrigated sites (7/60 strains) than from irrigated sites (1/60 strains). A similar pattern was observed for strongly motile (score ≥2) strains (six nonirrigated versus two irrigated). Analysis of the BGCs in our sequenced strains revealed a similar result, where 5/18 unirrigated strains contained CLP BGCs versus 0/16 irrigated strains. This counterintuitive observation led us to hypothesize that irrigation enables nonmotile, nonsuppressive bacteria to survive and colonize plant roots, whereas highly motile bacteria that produce multiple biological weapons can more effectively colonize plants in drier, more 'hostile' conditions.
To test these hypotheses, we sampled irrigated and unirrigated sites in a neighboring field 2 years after the first sampling event. 48 strains were isolated from bulk soil and the rhizospheres of tuberforming potato plants, with and without irrigation, providing a total of 192 P. fluorescens strains (Supplementary file 1). These strains were scored for motility, HCN production, and S. scabies suppression ( Figure 8A). Our results were in strong agreement with the first sample set, including strong positive correlations between S. scabies inhibition, motility, and HCN production ( Figure 8B). A negative correlation was observed between irrigation and S. scabies suppression on the plant roots, but not in the surrounding soil. This appeared to be driven primarily by differences in the unirrigated samples, where a substantially greater proportion of suppressive isolates were associated with roots than with the surrounding soil. We observed a strong positive correlation between motility and root association for unirrigated samples, while the reverse was true for irrigated plants ( Figure 8A). This effect of irrigation on the distribution of motile bacteria was striking -in dry plants, the motile population was almost entirely associated with roots, while in irrigated plants a comparable proportion of motile bacteria were found in the soil and roots ( Figure 8A).
This analysis therefore supports the root colonization hypothesis, where a lack of irrigation leads to a more specialized pseudomonad population colonizing the root. Upon irrigation, the difference between the bulk soil and root pseudomonad populations is much less significant. The mechanism for this population change is not yet defined, and these changes are counterintuitive in relation to the suppression of potato scab upon irrigation, given there is a drop in suppressive strains colonizing the potato root following irrigation. Irrigation did lead to moderately more motile pseudomonads in bulk soil versus unirrigated conditions, but this was not associated with more suppressive strains or HCN producers ( Figure 8A and B). The mechanism and significance of this irrigation effect require further investigation. It is possible that a protective microbiome in irrigated conditions actually contains a mixture of S. scabies-suppressive 'biocontrol' Pseudomonas strains alongside other nonmotile pseudomonads that interact with the plant in important ways due to traits usually absent from the 'biocontrol' strains, such as their ability to produce PQQ and catabolize auxins Leveau and Gerards, 2008). Profound irrigation-associated changes in antibiotic-producing Pseudomonas populations have previously been observed for the wheat rhizosphere (Mavrodi et al., 2018;Mavrodi et al., 2012).

Discussion
Prior studies on the suppression of potato scab have indicated a potential biocontrol role for Pseudomonas bacteria (Arseneault et al., 2015;Arseneault et al., 2013;Elphinstone et al., 2009;Rosenzweig et al., 2012). Fluorescent pseudomonads form multiple beneficial relationships with plants, including growth promotion and biocontrol (Haas and Défago, 2005;Zamioudis et al., 2013). However, there is limited understanding of the genetic factors that are critical for such activity, and little is known about the diversity of the P. fluorescens species group within a given agricultural field or how this population is shaped by environmental changes. In this study, we integrated genomics, metabolomics, phenotypic analysis, molecular biology, and in planta assays to identify the genetic determinants of Pseudomonas antagonism towards S. scabies. This population-level approach shows that the P. fluorescens population in a single field is highly complex, heterogeneous, and dynamic (Figures 2,  3 and 8), where the overall genotypic diversity is similar to the global diversity of P. fluorescens  (Garrido-Sanz et al., 2016). Pan-genome analysis and metagenomics represent increasingly powerful routes to understanding the genetic determinants of biological activity in plant-associated microbes (Beskrovnaya et al., 2020;Biessy et al., 2019;Carrión et al., 2019;Melnyk et al., 2019;Mullins et al., 2019;Tracanna et al., 2021). Multiple BGCs and accessory genome loci were identified that correlated with on-plate inhibition of S. scabies growth and development (Figure 3), including BGCs for CLPs and HCN. These loci also correlated with inhibition of P. infestans and G. graminis, and their contribution to suppression was validated genetically. This confirmed a role for both molecules in S. scabies inhibition (Figures 5 and  6), representing a new function for these Pseudomonas specialized metabolites. Co-culture assays and cryo-SEM imaging ( Figure 6) showed that HCN and a tensin-like CLP produced by Ps619 arrest the formation of streptomycete aerial hyphae and subsequent sporulation, providing the pseudomonad with a competitive advantage at the microbial interface.
In planta experiments confirmed that Ps619 could suppress potato scab and that CLP production was a key determinant of this inhibitory effect (Figure 7). In contrast, HCN production was not a requirement for potato scab suppression by Ps619. It is possible that HCN is not produced in sufficient amounts during root colonization for S. scabies inhibition, or that it instead has an alternative natural role, such as metal chelation (Rijavec and Lapanje, 2016). The roles of the CLPs are reminiscent of the interaction between B. subtilis and S. coelicolor, where the CLP surfactin functions as a surfactant required for the formation of aerial structures in B. subtilis and arrests aerial development in S. coelicolor (Straight et al., 2006). Collectively, these results are surprising given that streptomycetes themselves use surfactants to assist in the erection of aerial mycelia (Kodani et al., 2004;Willey et al., 2006) and points to secondary antagonistic roles for these molecules beyond the reduction of surface tension. This is strongly supported by the inhibitory effect of purified viscosin I towards S. scabies ( Figure 5C).
HCN and CLPs have also been associated with insect (Flury et al., 2017) and nematode (Siddiqui et al., 2006) killing, as well as the suppression of pathogenic fungi (Michelsen et al., 2015;Fukuda et al., 2021). This indicates that a subset of pseudomonads are generalist suppressors of pathogens (and presumably also nonpathogenic organisms) due to the production of these broad range antimicrobials. Genetic analysis indicates that these strains are more likely to produce multiple suppressive metabolites and proteins. Evidence for this is provided by the inhibition of both P. infestans and G. graminis by Ps619 ΔhcnΔten (Appendix 2-figure 1). A study of the inhibitory properties of bacteria associated with the Arabidopsis leaf microbiome showed that a large proportion of the total inhibitory activity was due to Pseudomonadales bacteria and that a subset of individual strains were active against a wide array of bacteria (Helfrich et al., 2018).
Unexpectedly, irrigation led to a decrease in the proportion of suppressive pseudomonads on potato roots ( Figure 8A) even though irrigation is one of the most effective ways to suppress potato scab. One possible reason for this discrepancy is that irrigation enables nonsuppressive Pseudomonas spp. with low motility to be transported to plant roots more effectively. Recruitment of nonsuppressive pseudomonads to the rhizosphere may benefit the plant in other ways, such as immune system priming (Bakker et al., 2007;Teixeira et al., 2021) or modulation of auxin biosynthesis. For example, Cheng et al., 2017 showed that auxin biosynthesis was linked to plant growth promotion and induced systemic resistance by P. fluorescens SS101. An alternative hypothesis is that changes in the overall relative abundance of soil Pseudomonas over Streptomyces resulting from irrigation may override the observed shift towards less-suppressive Pseudomonas genotypes. In support of this, drought-induced enrichment for commensal Streptomyces and depletion of Proteobacteria in sorghum and rice plants have been shown to be reversed by irrigation (Santos-Medellín et al., 2021;Xu et al., 2018). In this model, irrigation may reduce the relative fitness of S. scabies versus Pseudomonas spp., while the microbiome of irrigated roots simultaneously becomes less optimal for disease suppression.
Our data show that Ps619 is highly effective at inhibiting potato scab, yet Ps619-like strains are naturally less abundant in irrigated conditions. Therefore, possible future efforts to control potato scab could combine irrigation with pretreatment with effective biocontrol strains, like Ps619, to ensure tubers are colonized by a significant proportion of biocontrol strains. Such a strategy could reduce the quantity of water required for effective scab suppression. While our study was focused on fluorescent pseudomonads, interactions between these bacteria and the wider microbiome ( Figure 1) may also have a key role in potato scab suppression.
Moving forward, systematic analyses of individual organisms within microbiomes will continue to help answer questions relating to microbial communities and host interactions that are difficult to address using global 'omics approaches alone. For example, the role of many bacterial specialized metabolites in nature is poorly understood, especially for prolific producers such as the pseudomonads and the streptomycetes (van der Meij et al., 2017). Future studies could examine whether the host selects for bacterial populations enriched in specific BGCs and whether environmental stimuli modulate the abundance of these BGCs. Synthetic microbial communities based on well-characterized natural communities could then be used to test hypotheses on the role of specialized metabolites in shaping the community or modulating the health of the host organism.

Strains and growth conditions
All strains used in this study are listed in Supplementary file 2A. Unlessfigurotherwise stated, chemicals were purchased from Sigma-Aldrich, enzymes from New England Biolabs, and molecular biology kits from GE Healthcare and Promega. All P. fluorescens strains were grown at 28°C in L medium (Luria base broth, Formedium) and Escherichia coli at 37°C in lysogeny broth (LB) (Miller, 1972). 1.3% agar was added for solid media. Gentamicin was used at 25 μg/mL, carbenicillin at 100 μg/mL, and tetracycline (Tet) at 12.5 μg/mL. S. scabies spore suspensions were prepared using established procedures (Kieser et al., 2000).

Soil sample collection
Soil samples were collected from potato fields at RG Abrey Farms (East Wretham, Norfolk, UK, 52.4644° N, 0.8299° E). The first sampling was conducted in 2015 from two adjacent plots in a single field. Soil samples were taken on 22 January 2015, immediately prior to planting. One plot was then covered loosely in polythene to protect it from irrigation. The same field sites were sampled again in May at the point of maximum scab impact, once potato tubers had begun to form. In this case, soil samples were taken from the base of the plants, near the root system. For each sampling event, a total of 12 samples were taken from three parallel potato beds at regularly spaced intervals approximately 1 m apart. For the second experiment, 12 irrigated and 12 nonirrigated potato plants were uprooted from field sites in June 2017 and returned to the laboratory in large pots. Bulk soil samples were taken from these pots alongside an equivalent number of rhizosphere-associated samples, which were defined as isolated root systems gently shaken to remove bulk soil before processing as below. Samples were collected in sterile 50 mL tubes and stored at 4°C.

Isolation of soil Pseudomonas
Sample processing was conducted at 4°C throughout. 10 mL of sterile phosphate-buffered saline (PBS, per liter: 8 g NaCl, 0.2 g KCl, 1.44 g Na 2 HPO 4 , 0.24 g KH 2 PO 4 , pH 7.4) were added to 50 mL tubes containing 20 g of soil or root material, and vortexed vigorously for 10 min. Samples were then filtered through a sterile muslin filter to remove larger debris. The resulting suspension of soil and organic matter was centrifuged at 1000 rpm for 30 s to pellet remaining soil particles, before serial dilution in PBS and plating on Pseudomonas selective agar. The selection media comprised Pseudomonas agar base (Oxoid, UK) supplemented with CFC (cetrimide/fucidin/cephalosporin) Pseudomonas selective supplement (Oxoid, UK). Plates were incubated at 28°C until colonies arose, then isolated single colonies were patched on fresh CFC agar and incubated overnight at 28°C before streaking to single colonies on King's B (KB) agar plates (King et al., 1954). Six isolates were selected at random per soil sample and subjected to phenotypic/genomic analysis.

Amplicon sequencing
Genomic DNA was isolated from 3 g of pooled soil samples using the FastDNA SPIN Kit for soil (MP Biomedicals, UK) following the manufacturer's instructions. Genomic DNA concentration and purity was determined by NanoDrop spectrophotometry as above. Microbial 16S rRNA genes were amplified from soil DNA samples with barcoded universal prokaryotic primers (F515/R806) targeting the V4 region (Caporaso et al., 2011), and then subjected to Illumina MiSeq sequencing (600-cycle, 2 × 300 bp) at the DNA Sequencing Facility, Department of Biochemistry, University of Cambridge

Phenotypic assays
All phenotyping assays were conducted at least twice independently, and where disagreements were recorded in the ordinal data, additional repeats were conducted until a firm consensus was reached.
Swarming motility 0.5% KB agar plates were poured and allowed to set and dry for 1 hr in a sterile flow cabinet. Plates were then inoculated with 2 μL spots of overnight cultures and incubated overnight at room temperature. The motility of each isolate was tested in triplicate and scored from 0 (no motility) to 3 (high motility).
Secreted protease activity 5 μL of overnight cultures were spotted onto KB plates containing 1.0% skimmed milk powder. Plates were incubated at 28°C and photographed after 24 hr, with individual isolates scored as protease positive (score = 2) or negative (score = 0).

HCN production
An adaptation of the method described in Castric and Castric, 1983 was used. Pseudomonas isolates were inoculated into 150 μL of liquid KB medium in individual wells of a flat-bottomed 96-well plate. The plates were then overlaid with Feigl-Anger reagent paper (Feigl and Anger, 1966), prepared as follows. Whatman 3MM chromatography paper was soaked in Feigl-Anger detection reagent (5 mg/ mL copper(II) ethyl acetoacetate and 5 mg/mL 4,4'-methylenebis(N,N-dimethylaniline) dissolved in chloroform). After complete solvent evaporation, the paper was placed under the plate lid and strains were grown at 28°C overnight with gentle shaking. The intensity of blue staining on the paper was then scored from 0 (no color) to 3 (high blue intensity). The same method was applied to isolates growing on agar medium.

S. scabies inhibition
Two parallel lines of S. scabies 87-22 spores were streaked onto SFM plates (Kieser et al., 2000) using a sterile toothpick. These lines were then cross-streaked with overnight cultures of Pseudomonas isolates. Plates were incubated at 30°C, and the relative performance of each species was assessed daily for 5 days.

P. infestans inhibition
Assays were conducted with P. infestans #2006-3920A (6-A1) (The Sainsbury Laboratory, UK). This was maintained on rye agar medium supplemented with 2% sucrose (C-RSA) (Caten and Jinks, 1968) at 21°C. C-RSA was filtered through muslin fabric to enable clearer observation of oomycete growth. Three 10 μL drops of overnight cultures per Pseudomonas isolate strain were placed equidistantly 15 mm from the edge of C-RSA plates. A 3 mm plug from the leading edge of a P. infestans culture was then placed in the center of each plate and incubated for a further 7 days at 21°C before scoring and imaging.

Take-all inhibition
Assays were conducted with G. graminis var. tritici strain NZ.66.12 (Ggt) (Mauchline et al., 2015). Three 10 μL drops of overnight Pseudomonas cultures per strain were placed equidistantly 15 mm from the edge of potato dextrose agar (PDA) plates and incubated for 24 hr at 28°C. Ggt NZ.66.12 was cultured on PDA agar for 5 days at room temperature. A 3 mm plug from the leading edge of the NZ.66.12 culture was then placed in the center of each plate and incubated for a further 5 days at 22°C before the extent of Ggt inhibition was assessed.

DNA extraction and Illumina genome sequencing
Single colonies of each isolate to be sequenced were picked from L agar plates and grown overnight in L medium. DNA was then extracted from 2 mL of cell culture using a GenElute Bacterial Genomic DNA Kit (Sigma-Aldrich, USA). DNA samples were subjected to an initial quality check using a Nano-Drop spectrophotometer (Thermo Scientific, Wilmington, DE) before submission for Nextera library preparation and paired-end read sequencing on the Illumina MiSeq platform (600-cycle, 2 × 300 bp) at the DNA Sequencing Facility, Department of Biochemistry, University of Cambridge (UK). Reads from 35 pseudomonads collected in February 2015 were assembled into genomes using MaSuRCA v3.2.6 (Zimin et al., 2013) with the following settings: GRAPH_KMER_SIZE = auto; USE_LINKING_MATES = 1; LIMIT_JUMP_COVERAGE = 60; CA_ PARAMETERS = ovlMerSize = 30 cgwErrorRate = 0.25 ovlMemory = 4 GB; NUM_THREADS = 16; JF_SIZE = 100000000; DO_HOMOPOLYMER_TRIM = 0.
Reads from 32 samples collected in May 2015 were assembled into genomes using SPAdes v3.6.2 (Bankevich et al., 2012) with k-mer flag set to -k 2133557799127. All assembly tasks were conducted using 16 CPUs on a 256 GB compute node within the Norwich Bioscience Institutes (NBI) High Performance Computing cluster. An additional strain from May 2015 (Ps925) was sequenced and assembled by MicrobesNG (http://www.microbesng.uk), which is supported by the BBSRC (grant number BB/ L024209/1). The 69 assembled genome sequences were annotated using Prokka (Seemann, 2014), which implements Prodigal (Hyatt et al., 2010) as an open-reading frame calling tool. Assembly qualities were assessed using CheckM (Parks et al., 2015). Genome assemblies are available at the European Nucleotide Archive (http://www.ebi.ac.uk/ena/) with the project accession PRJEB34261.

Phylogenetic and bioinformatic analysis
The gyrB housekeeping gene sequence was identified in each newly sequenced genome by BLAST comparison with the sequence of gyrB from P. fluorescens SBW25. The full-length gyrB sequences from these strains and several reference strains were aligned using MUSCLE 3.8.31 (Edgar, 2004) with default settings, then a maximum likelihood tree was calculated using RAxML 8.2.12 (Stamatakis, 2014) on the CIPRES portal (Miller et al., 2015) with the following parameters: raxmlHPC-HYBRID-AVX -T 4f a -N autoMRE -n result -s infile. txt -c 25 m GTRCAT -p 12345k -x 12345. Genomes were subjected to bioinformatic analysis as described in Appendix 1. Phylogenetic trees and presence/absence data for accessory genes were visualized using Interactive Tree of Life (iTOL) (Letunic and Bork, 2016), with Pseudomonas aeruginosa PAO1 gyrB as the outgroup.

Molecular biology procedures
Cloning was carried out in accordance with standard molecular biology techniques. P. fluorescens deletion mutants were constructed by allelic exchange as described previously (Campilongo et al., 2017). Up-and downstream flanking regions (approximately 500 bp) to the target genes were amplified using primers listed in Supplementary file 2B. PCR products in each case were ligated into pTS1 (Scott et al., 2017) between XhoI and BamHI. The resulting deletion vectors were transformed into the target strains by electroporation, and single crossovers selected on L + Tet and re-streaked to isolate single colonies. 100 mL cultures in L medium from single crossovers were grown overnight at 28°C, then plated onto L + 10% sucrose plates to counter-select for double crossovers. Individual colonies from these plates were then patched onto L plates ± Tet, with Tet-sensitive colonies tested for gene deletion by colony PCR using primers external to the deleted gene in each case (Supplementary file 2B).
Luminescent-tagged strains were produced by introduction of the Aliivibrio fischeri luxCDABE cassette into the neutral att::Tn7 site in Pseudomonas chromosomes using the Tn7-based expression system described in Choi et al., 2005. Strains were electroporated with plasmids pUC18-miniTn7T-Gm-lux and the helper pTNS2, and transformant colonies were grown on solid L medium+ gentamicin for 2-3 days at 28°C. Integration of the lux cassette into Pseudomonas genomes was confirmed by PCR and with a luminometer. Luminescent cells were then tracked using the NightOWL visualization system (Berthold Technologies, Germany). All plasmids used in this study are reported in Supplementary file 2C.

LC-MS detection of lipopeptides
Pseudomonas isolates were grown overnight in L medium (10 mL) for 16 hr at 28°C. 100 μL of each culture was used to inoculate 40 mm diameter KB agar plates. Plates were incubated for 24 hr at 28°C, before the agar from each plate was decanted into a sterile 50 mL tube and extracted with 10 mL 50% EtOH with occasional vortexing for 3 hr. 2 mL was taken from each sample and centrifuged in 2 mL tubes for 5 min at 16,000 × g. The supernatant was collected and stored at -80°C. Samples were diluted with an equal volume of water, then subjected to LC-MS analysis using a Shimadzu Nexera X2 UHPLC coupled to a Shimadzu ion-trap time-of-flight (IT-TOF) mass spectrometer. Samples (5 μL) were injected onto a Phenomenex Kinetex 2.6 μm XB-C18 column (50 × 2.1 mm, 100 Å), eluting with a linear gradient of 5-95% acetonitrile in water +0.1% formic acid over 6 min with a flow rate of 0.6 mL/min at 40°C. To compare the retention times of viscosin I (Ps682), WLIP (Pseudomonas sp. LMG 2338), and viscosin (P. fluorescens SBW25), extracts were prepared from their producing organisms as described above. The same chromatography conditions as above were used, but with a linear gradient of 5-100% acetonitrile in water + 0.1% formic acid over 15 min.
Positive mode mass spectrometry data were collected between m/z 300 and 2000 with an ion accumulation time of 10 ms featuring an automatic sensitivity control of 70% of the base peak. The curved desolvation line temperature was 300°C, and the heat block temperature was 250°C. MS/MS data were collected in a data-dependent manner using collision-induced dissociation energy of 50% and a precursor ion width of 3 Da. The instrument was calibrated using sodium trifluoroacetate cluster ions prior to every run.
A molecular network was created using the online workflow at the Global Natural Product Social Molecular Networking (GNPS) site (https://gnps.ucsd.edu/; Aron et al., 2020). The data were filtered by removing all MS/MS peaks within ±17 Da of the precursor m/z. The data were then clustered with MS-Cluster with a parent mass tolerance of 1 Da and an MS/MS fragment ion tolerance of 0.5 Da to create consensus spectra. Consensus spectra that contained less than two spectra were discarded. A network was then created where edges were filtered to have a cosine score above 0.6 and more than four matched peaks. Further edges between two nodes were kept in the network if each of the nodes appeared in each other's respective top 10 most similar nodes. The spectra in the network were then searched against GNPS spectral libraries. The library spectra were filtered in the same manner as the input data. All matches kept between network spectra and library spectra were required to have a score above 0.7 and at least four matched peaks. Networks were visualized using Cytoscape v3.8.2 (Shannon et al., 2003), and the data were manually filtered to remove duplicate nodes (same m/z and retention time). The data are available as MassIVE dataset MSV000084283 at https://massive.ucsd. edu, and the GNPS analysis is available at https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=51ac 5fe596424cf88cfc17898985cac2.
High-resolution mass spectra were acquired on a Synapt G2-Si mass spectrometer equipped with an Acquity UPLC (Waters). Aliquots of the samples were injected onto an Acquity UPLC BEH C18 column, 1.7 μm, 1 × 100 mm (Waters) and eluted with a gradient of acetonitrile/0.1% formic acid (B) in water/0.1% formic acid (A) with a flow rate of 0.08 mL/min at 45°C. The concentration of B was kept at 1% for 1 min followed by a gradient up to 40% B in 9 min, ramping to 99% B in 1 min, kept at 99% B for 2 min and re-equilibrated at 1% B for 4 min. MS data were collected in positive mode with the following parameters: resolution mode, positive ion mode, scan time 0.5 s, mass range m/z 50-1200 calibrated with sodium formate, capillary voltage = 2.5 kV; cone voltage = 40 V; source temperature = 125°C; desolvation temperature = 300°C. Leu-enkephalin peptide was used to generate a lock-mass calibration with 556.2766, measured every 30 s during the run. For MS/MS fragmentation, a datadirected analysis (DDA) method was used with the following parameters: precursor selected from the four most intense ions; MS2 threshold: 5000; scan time 0.5 s; no dynamic exclusion. In positive mode, collision energy (CE) was ramped between 10-30 at low mass (m/z 50) and 15-60 at high mass (m/z 1200).

Purification and characterization of viscosin I
Pre-cultures of Ps682 were grown in 10 mL LB medium for 16 hr and 600 μL aliquots were used to inoculate 140 mm diameter KB agar plates. Fifteen plates were inoculated and incubated for 24 hr. The agar was decanted and extracted with 500 mL ethyl acetate for 2 hr with occasional mixing. The organic fraction was filtered off, washed with 3 × 200 mL water, dried over MgSO 4 , and then solvent was removed in vacuo. The resulting material was dissolved in MeOH and applied to a 12 g C18 flash chromatography column (Biotage), pre-equilibrated in 70% MeOH. Separation proceeded by a gradient of 70-100% MeOH over 10-column volumes. Each fraction was subject to LC-MS analysis using a Shimadzu Nexera X2 UHPLC coupled to a Shimadzu IT-TOF mass spectrometer, as described above.
Solvent was removed from viscosin I-containing fractions using a rotary evaporator and then a Genevac (SP Scientific). Fractions were then dissolved in MeOH to 1 mg/mL and further purified using a Thermo Dionex Ultimate 3000 HPLC system. 200 μL aliquots were injected onto a Phenomenex C18 Luna column (5 μm, 250 mm × 10 mm) and eluted with a linear gradient of 5-95% acetonitrile/H 2 O over 30 min, with a flow rate of 4 mL/min and UV absorption data collected at 210 nm. LC-MS analysis (as described above) was used to identify pure fractions, which were combined and dried in vacuo to yield 1.4 mg viscosin I as a white powder.
Viscosin I (1.4 mg) was dissolved in N,N-dimethylformamide-d 7 (DMF-d 7 ) and NMR spectra were acquired on a Bruker Avance Neo 600 MHz spectrometer equipped with a TCI cryoprobe. The experiments were carried out at 298 K with the residual DMF solvent used as an internal standard (δ H /δ C 2.75/29.76). The residual solvent signal from H 2 O was suppressed through a presaturation sequence in 1D 1 H. Resonances were assigned through 1D 1 H and DEPT135 experiments, and 2D COSY, HSQCed, HMBC, TOCSY, and HSQC-TOCSY experiments. Spectra were analyzed using Bruker TopSpin 3.5 and Mestrelab Research Mnova 14.0 software. NMR data are reported in

Disk diffusion assays
A S. scabies 87-22 spore suspension was diluted 1:100 in sterile MQ water and 60 μL aliquots were applied to instant potato medium (20 g/L Smash Instant Mash, 20 g/L agar) on 100 mm square plates. The spore solution was evenly distributed using a sterile cotton bud and the plate was dried for 30 min. Viscosin I was diluted in MeOH to produce a range of concentrations from 20 to 100 μg/mL. Each concentration was applied to a 6 mm filter paper disk, in 5 × 20 μL applications at 10 min intervals, and then dried for 30 min. The disks were then applied to the surface of the agar plate, which was incubated at 30°C and imaged daily.

Scanning electron microscopy
Small pieces of the Pseudomonas-Streptomyces co-culture samples were excised from the surface of agar plates and mounted on an aluminum stub using Tissue Tek (BDH Laboratory Supplies, Poole, England). The stub was then immediately plunged into liquid nitrogen slush at approximately -210°C to cryo-preserve the material. The sample was transferred onto the cryostage of an ALTO 2500 cryotransfer system (Gatan, Oxford, England) attached to an FEI Nova NanoSEM 450 (FEI, Eindhoven, The Netherlands). Sublimation of surface frost was performed at -95°C for 3 min before sputter coating the sample with platinum for 3 min at 10 mA, at colder than -110°C. After sputter coating, the sample was moved onto the cryo-stage in the main chamber of the microscope, held at -125°C. The sample was imaged at 3 kV and digital TIFF files were stored.

Potato scab biocontrol assays
In planta assays were performed as described previously (Lin et al., 2018;Sarwar et al., 2018) with some modifications. Briefly, 2 L of GYM (4 g/L glucose, 4 g/L yeast extract, 10 g/L malt extract, 2 g/L CaCO 3 , pH 7.2) was inoculated with a S. scabies 87-22 starter culture from a spore suspension and incubated for 48 hr at 30°C, 250 rpm. Each culture was then centrifuged at 16,994 × g for 15 min and washed twice with PBS (2 L). Pseudomonas strains Ps619, Ps682, and associated mutants were grown overnight at 28°C, 250 rpm in 50 mL L medium (Luria base broth, Formedium), centrifuged at 1520 × g for 15 min, washed twice with PBS (20 mL), and adjusted to OD 600 = 0.2 for the final inoculation. 50 mL of autoclaved vermiculite and 50 mL of bacterial culture were mixed to constitute the final inoculum. 5 L pots were filled with steam-sterilized substrate (John Innes Cereal Mix) and inoculum was applied into the pots and mixed with the soil. Different combinations of bacterial inocula were made accordingly following the same method. Potato seeds cv. Maris Piper obtained from VCS Potatoes Ltd (Suffolk, UK) were surfaced-disinfected by immersion in 1% sodium hypochlorite for 15 min. Tubers were then rinsed with water, air-dried, and placed in pots. Pots were watered until saturation according to their growth stage. Potato plants were grown in a glasshouse with a light cycle of 16 h/8 h at 18-20°C. Two independent experiments were run between 17 July and 6 November 2020 and 31 July and 20 November 2020, and 3-4 plants were used per treatment. Tubers were collected, washed, weighed, and scored accordingly to a 1-6 scale as described in Andrade et al., 2019. Potato plants were dried for 4 days at 30°C and aerial parts and tuber weights were both recorded, as well as tuber number. Treatment differences were carried out based on the disease index (DI) of each plant (n = 4 for each treatment). The DI was calculated as the mean of all the scored tubers per plant, and p-values were calculated using Dunnett's multiple-comparison test.