Genomic Approaches to Plant-Pathogen Epidemiology and Diagnostics

Population genomics and molecular epidemiology of wheat powdery mildew in Europe

Agricultural diseases are a major threat to sustainable food production. Yet, for many pathogens we know exceptionally little about their epidemiological and population dynamics, and this knowledge gap is slowing the development of efficient control strategies. Here we study the population genomics and molecular epidemiology of wheat powdery mildew, a disease caused by the biotrophic fungus Blumeria graminis forma specialis tritici (Bgt). We sampled Bgt across two consecutive years, 2022 and 2023, and compiled a genomic dataset of 415 Bgt isolates from 22 countries in Europe and surrounding regions. We identified a single epidemic unit in the north of Europe, consisting of a highly homogeneous population. Conversely, the south of Europe hosts smaller local populations which are less interconnected. In addition, we show that the population structure can be largely predicted by the prevalent wind patterns. We identified several loci that were under selection in the recent past, including fungicide targets and avirulence genes. Some of these loci are common between populations, while others are not, suggesting different local selective pressures. We reconstructed the evolutionary history of one of these loci, AvrPm17, coding for an effector recognized by the wheat receptor Pm17. We found evidence for a soft sweep on standing genetic variation. Multiple AvrPm17 haplotypes, which can partially escape recognition by Pm17, spread rapidly throughout the continent upon its introduction in the early 2000s. We also identified a new virulent variant, which emerged more recently and can evade Pm17 resistance altogether. Overall, we highlight the potential of genomic surveillance in resolving the evolutionary and epidemiological dynamics of agricultural pathogens, as well as in guiding control strategies.

Morpho-Molecular Characterization of Hypocrealean Fungi Isolated from Rice in Northern Thailand

Hypocreales is one of the largest orders within the class Sordariomycetes and is renowned for its diversity of lifestyles, encompassing plant, insect, and human pathogens, as well as endophytes, parasites, and saprobes. In this study, we focused on saprobic hypocrealean fungi isolated from rice in northern Thailand. Species identification was conducted using morphological characteristics and multilocus phylogenetic analyses, including the internal transcribed spacer region (ITS), 28S large subunit nuclear ribosomal DNA (LSU), translation elongation factor 1-alpha (tef1-α), RNA polymerase II second-largest subunit (rpb2), and calmodulin (cmdA). This research confirmed the presence of 14 species of hypocrealean taxa, viz. Fusarium (9), Ochronectria (1), Sarocladium (2), Trichothecium (1), and Waltergamsia (1). Among these were two new species (Fusarium chiangraiense and F. oryzigenum), four new host records (Fusarium kotabaruense, Ochronectria thailandica, Sarocladium bactrocephalum, and Waltergamsia fusidioides), and three new geographical records (Fusarium commune, F. guilinense, and F. hainanese).

Developing a crop- wild-reservoir pathogen system to understand pathogen evolution and emergence

Crop pathogens reduce yield and contribute to global malnourishment. Surveillance not only detects presence/absence but also reveals genetic diversity, which can inform our understanding of rapid adaptation and control measures. An often neglected aspect is that pathogens may also use crop wild relatives as alternative hosts. This study develops the beet (Beta vulgaris) rust (Uromyces beticola) system to explore how crop pathogens evolve to evade resistance using a wild reservoir. We test predictions that crop selection will drive virulence gene differentiation and affect rates of sex between crop- and wild-host rust populations. We sequenced, assembled, and annotated the 588 Mb beet rust genome, developed a novel leaf peel pathogen DNA extraction protocol, and analysed genetic diversity in 42 wild and crop isolates. We found evidence for two populations: one containing exclusively wild-host isolates; the other containing all crop-host isolates, plus five wild isolates. Effectors showed greater diversity in the exclusively wild population and greater differentiation between populations. Preliminary evidence suggests the rates of sexual reproduction may differ between populations. This study highlights how differences in pathogen populations might be used to identify genes important for survival on crops and how reproduction might impact adaptation. These findings are relevant to all crop-reservoir systems and will remain unnoticed without comparison to wild reservoirs.

Evolutionary genomics reveals variation in structure and genetic content implicated in virulence and lifestyle in the genus Gaeumannomyces

Gaeumannomyces tritici is responsible for take-all disease, one of the most important wheat root threats worldwide. High-quality annotated genome resources are sorely lacking for this pathogen, as well as for the closely related antagonist and potential wheat take-all biocontrol agent, G. hyphopodioides. As such, we know very little about the genetic basis of the interactions in this host-pathogen-antagonist system. Using PacBio HiFi sequencing technology we have generated nine near-complete assemblies, including two different virulence lineages for G. tritici and the first assemblies for G. hyphopodioides and G. avenae (oat take-all). Genomic signatures support the presence of two distinct virulence lineages in G. tritici (types A and B), with A strains potentially employing a mechanism to prevent gene copy-number expansions. The CAZyme repertoire was highly conserved across Gaeumannomyces, while candidate secreted effector proteins and biosynthetic gene clusters showed more variability and may distinguish pathogenic and non-pathogenic lineages. A transition from self-sterility (heterothallism) to self-fertility (homothallism) may also be a key innovation implicated in lifestyle. We did not find evidence for transposable element and effector gene compartmentalisation in the genus, however the presence of Starship giant transposable elements may contribute to genomic plasticity in the genus. Our results depict Gaeumannomyces as an ideal system to explore interactions within the rhizosphere, the nuances of intraspecific virulence, interspecific antagonism, and fungal lifestyle evolution. The foundational genomic resources provided here will enable the development of diagnostics and surveillance of understudied but agriculturally important fungal pathogens.

A host shift as the origin of tomato bacterial canker caused by Clavibacter michiganensis

The Actinomycetota (formerly Actinobacteria) genus Clavibacter includes phytopathogens with devasting effects in several crops. Clavibacter michiganensis, the causal agent of tomato bacterial canker, is the most notorious species of the genus. Yet, its origin and natural reservoirs remain elusive, and its populations show pathogenicity profiles with unpredictable plant disease outcomes. Here, we generate and analyse a decade-long genomic dataset of Clavibacter from wild and commercial tomato cultivars, providing evolutionary insights that directed phenotypic characterization. Our phylogeny situates the last common ancestor of C. michiganensis next to Clavibacter isolates from grasses rather than to the sole strain we could isolate from wild tomatoes. Pathogenicity profiling of C. michiganensis isolates, together with C. phaseoli and C. californiensis as sister taxa and the wild tomato strain, was found to be congruent with the proposed phylogenetic relationships. We then identified gene enrichment after the evolutionary event, leading to the appearance of the C. michiganesis clade, including known pathogenicity factors but also hitherto unnoticed genes with the ability to encode adaptive traits for a pathogenic lifestyle. The holistic perspective provided by our evolutionary analyses hints towards a host shift event as the origin of C. michiganensis as a tomato pathogen and the existence of pathogenic genes that remain to be characterized.

Genomic characterization of Listeria monocytogenes recovered from dairy facilities in British Columbia, Canada from 2007 to 2017

Listeria monocytogenes is a foodborne pathogen of concern in dairy processing facilities, with the potential to cause human illness and trigger regulatory actions if found in the product. Monitoring for Listeria spp. through environmental sampling is recommended to prevent establishment of these microorganisms in dairy processing environments, thereby reducing the risk of product contamination. To inform on L. monocytogenes diversity and transmission, we analyzed genome sequences of L. monocytogenes strains (n = 88) obtained through the British Columbia Dairy Inspection Program. Strains were recovered from five different dairy processing facilities over a 10 year period (2007-2017). Analysis of whole genome sequences (WGS) grouped the isolates into nine sequence types and 11 cgMLST types (CT). The majority of isolates (93%) belonged to lineage II. Within each CT, single nucleotide polymorphism (SNP) differences ranged from 0 to 237 between isolates. A highly similar (0-16 SNPs) cluster of over 60 isolates, collected over 9 years within one facility (#71), was identified suggesting a possible persistent population. Analyses of genome content revealed a low frequency of genes associated with stress tolerance, with the exception of widely disseminated cadmium resistance genes cadA1 and cadA2. The distribution of virulence genes and mutations within internalin genes varied across the isolates and facilities. Further studies are needed to elucidate their phenotypic effect on pathogenicity and stress response. These findings demonstrate the diversity of L. monocytogenes isolates across dairy facilities in the same region. Findings also showed the utility of using WGS to discern potential persistence events within a single facility over time.

Rapid New Diagnostic LAMP (Loop-Mediated Isothermal Amplification) Assays to Distinguish Among the Four Lineages of Phytophthora ramorum

Sudden oak death (SOD) is caused by Phytophthora ramorum, an invasive oomycete pathogen. This pathogen is of major regulatory concern for nurseries, horticulture, and forestry in the United States and around the world. Three of the 12 identified lineages of P. ramorum currently occur in the United States (NA1, NA2, and EU1) affecting wildland forests and nurseries. Rapid identification and lineage determination is essential to accelerate management decisions, detect introductions of new lineages, and control the spread of SOD. The objective of this study was to develop and validate diagnostic tools to rapidly identify P. ramorum and distinguish among the four common lineages of the pathogen and to accelarate management decision making. The loop-mediated isothermal amplification (LAMP) assays developed here are species specific with no cross reaction to common Phytophthora species found in Oregon, California, and Washington. The lineage-specific assays unambiguously distinguish among the four common clonal lineages. These assays are sensitive and able to detect P. ramorum DNA ranging in concentration from 30 to 0.03 ng/μl depending on the assay. These assays work effectively on a variety of sample types including plant tissue, cultures, and DNA. They have been integrated into the SOD diagnostic process in the forest pathology lab at Oregon State University. To date, 190 samples have been correctly identified from over 200 field samples tested for lineage determination. The development of these assays will help managers in forestry and horticulture identify and rapidly respond to new outbreaks of P. ramorum.

Mobile Genetic Element Flexibility as an Underlying Principle to Bacterial Evolution

Mobile genetic elements are key to the evolution of bacteria and traits that affect host and ecosystem health. Here, we use a framework of a hierarchical and modular system that scales from genes to populations to synthesize recent findings on mobile genetic elements (MGEs) of bacteria. Doing so highlights the role that emergent properties of flexibility, robustness, and genetic capacitance of MGEs have on the evolution of bacteria. Some of their traits can be stored, shared, and diversified across different MGEs, taxa of bacteria, and time. Collectively, these properties contribute to maintaining functionality against perturbations while allowing changes to accumulate in order to diversify and give rise to new traits. These properties of MGEs have long challenged our abilities to study them. Implementation of new technologies and strategies allows for MGEs to be analyzed in new and powerful ways.

Whole Genome Sequencing-Based Tracing of a 2022 Introduction and Outbreak of Xanthomonas hortorum pv. pelargonii

Globalization has made agricultural commodities more accessible, available, and affordable. However, their global movement increases the potential for invasion by pathogens and necessitates development and implementation of sensitive, rapid, and scalable surveillance methods. Here, we used 35 strains, isolated by multiple diagnostic laboratories, as a case study for using whole genome sequence data in a plant disease diagnostic setting. Twenty-seven of the strains were isolated in 2022 and identified as Xanthomonas hortorum pv. pelargonii. Eighteen of these strains originated from material sold by a plant breeding company that had notified clients following a release of infected geranium cuttings. Analyses of whole genome sequences revealed epidemiological links among the 27 strains from different growers that confirmed a common source of the outbreak and uncovered likely secondary spread events within facilities that housed plants originating from different plant breeding companies. Whole genome sequencing data were also analyzed to reveal how preparatory and analytical methods can impact conclusions on outbreaks of clonal pathogenic strains. The results demonstrate the potential power of using whole genome sequencing among a network of diagnostic labs and highlight how sharing such data can help shorten response times to mitigate outbreaks more expediently and precisely than standard methods.