Plants are constantly exposed to would-be pathogens and pests, and thus have a sophisticated immune system to ward off these threats, which otherwise can have devastating ecological and economic consequences on ecosystems and agriculture. Plants employ receptor kinases (RKs) and receptor-like proteins (RLPs) as pattern recognition receptors (PRRs) to monitor their apoplastic environment and detect non-self and damaged-self patterns as signs of potential danger. Plant PRRs contribute to both basal and non-host resistances, and treatment with pathogen-/microbe-associated molecular patterns (PAMPs/MAMPs) or damage-associated molecular patterns (DAMPs) recognized by plant PRRs induces both local and systemic immunity. Here, we comprehensively review known PAMPs/DAMPs recognized by plants as well as the plant PRRs described to date. In particular, we describe the different methods that can be used to identify PAMPs/DAMPs and PRRs. Finally, we emphasize the emerging biotechnological potential use of PRRs to improve broad-spectrum, and potentially durable, disease resistance in crops.

Function, Discovery, and Exploitation of Plant Pattern Recognition Receptors for Broad-Spectrum Disease Resistance

Wheat is one of the primary staple foods throughout the planet. Significant yield gains in wheat production over the past 40 years have resulted in a steady balance of supply versus demand. However, predicted global population growth rates and dietary changes mean that substantial yield gains over the next several decades will be needed to meet this escalating demand. A key component to meeting this challenge is better management of fungal incited diseases, which can be responsible for 15%-20% yield losses per annum. Prominent diseases of wheat that currently contribute to these losses include the rusts, blotches and head blight/scab. Other recently emerged or relatively unnoticed diseases, such as wheat blast and spot blotch, respectively, also threaten grain production. This review seeks to provide an overview of the impact, distribution and management strategies of these diseases. In addition, the biology of the pathogens and the molecular basis of their interaction with wheat are discussed.

/pdf/a-review-of-wheat-diseases-a-field-perspective-50uyi8unno.pdf

A review of wheat diseases-a field perspective.

Deployment of fast-evolving disease-resistance genes is one of the most successful strategies used by plants to fend off pathogens1,2. In gene-for-gene relationships, most cloned disease-resistance genes encode intracellular nucleotide-binding leucine-rich-repeat proteins (NLRs) recognizing pathogen-secreted isolate-specific avirulence (Avr) effectors delivered to the host cytoplasm3,4. This process often triggers a localized hypersensitive response, which halts further disease development 5 . Here we report the map-based cloning of the wheat Stb6 gene and demonstrate that it encodes a conserved wall-associated receptor kinase (WAK)-like protein, which detects the presence of a matching apoplastic effector6-8 and confers pathogen resistance without a hypersensitive response 9 . This report demonstrates gene-for-gene disease resistance controlled by this class of proteins in plants. Moreover, Stb6 is, to our knowledge, the first cloned gene specifying resistance to Zymoseptoria tritici, an important foliar fungal pathogen affecting wheat and causing economically damaging septoria tritici blotch (STB) disease10-12.

Wheat receptor-kinase-like protein Stb6 controls gene-for-gene resistance to fungal pathogen Zymoseptoria tritici.

Structural variation contributes substantially to polymorphism within species. Chromosomal rearrangements that impact genes can lead to functional variation among individuals and influence the expression of phenotypic traits. Genomes of fungal pathogens show substantial chromosomal polymorphism that can drive virulence evolution on host plants. Assessing the adaptive significance of structural variation is challenging, because most studies rely on inferences based on a single reference genome sequence. We constructed and analyzed the pangenome of Zymoseptoria tritici, a major pathogen of wheat that evolved host specialization by chromosomal rearrangements and gene deletions. We used single-molecule real-time sequencing and high-density genetic maps to assemble multiple genomes. We annotated the gene space based on transcriptomics data that covered the infection life cycle of each strain. Based on a total of five telomere-to-telomere genomes, we constructed a pangenome for the species and identified a core set of 9149 genes. However, an additional 6600 genes were exclusive to a subset of the isolates. The substantial accessory genome encoded on average fewer expressed genes but a larger fraction of the candidate effector genes that may interact with the host during infection. We expanded our analyses of the pangenome to a worldwide collection of 123 isolates of the same species. We confirmed that accessory genes were indeed more likely to show deletion polymorphisms and loss-of-function mutations compared to core genes. The pangenome construction of a highly polymorphic eukaryotic pathogen showed that a single reference genome significantly underestimates the gene space of a species. The substantial accessory genome provides a cradle for adaptive evolution.

/pdf/pangenome-analyses-of-the-wheat-pathogen-zymoseptoria-510nqxbedk.pdf

Pangenome analyses of the wheat pathogen Zymoseptoria tritici reveal the structural basis of a highly plastic eukaryotic genome.

The plant apoplast is integral to intercellular signalling, transport and plant-pathogen interactions. Plant pathogens deliver effectors both into the apoplast and inside host cells, but no computational method currently exists to discriminate between these localizations. We present ApoplastP, the first method for predicting whether an effector or plant protein localizes to the apoplast. ApoplastP uncovers features of apoplastic localization common to both effectors and plant proteins, namely depletion in glutamic acid, acidic amino acids and charged amino acids and enrichment in small amino acids. ApoplastP predicts apoplastic localization in effectors with a sensitivity of 75% and a false positive rate of 5%, improving the accuracy of cysteine-rich classifiers by > 13%. ApoplastP does not depend on the presence of a signal peptide and correctly predicts the localization of unconventionally secreted proteins. The secretomes of fungal saprophytes as well as necrotrophic, hemibiotrophic and extracellular fungal pathogens are enriched for predicted apoplastic proteins. Rust pathogens have low proportions of predicted apoplastic proteins, but these are highly enriched for predicted effectors. ApoplastP pioneers apoplastic localization prediction using machine learning. It will facilitate functional studies and will be valuable for predicting if an effector localizes to the apoplast or if it enters plant cells.

https://nph.onlinelibrary.wiley.com/doi/epdf/10.1111/nph.14946

ApoplastP: prediction of effectors and plant proteins in the apoplast using machine learning.

Zymoseptoria tritici is the causal agent of Septoria tritici blotch, a major pathogen of wheat globally and the most damaging pathogen of wheat in Europe. A gene-for-gene (GFG) interaction between Z. tritici and wheat cultivars carrying the Stb6 resistance gene has been postulated for many years, but the genes have not been identified. We identified AvrStb6 by combining quantitative trait locus mapping in a cross between two Swiss strains with a genome-wide association study using a natural population of c. 100 strains from France. We functionally validated AvrStb6 using ectopic transformations. AvrStb6 encodes a small, cysteine-rich, secreted protein that produces an avirulence phenotype on wheat cultivars carrying the Stb6 resistance gene. We found 16 nonsynonymous single nucleotide polymorphisms among the tested strains, indicating that AvrStb6 is evolving very rapidly. AvrStb6 is located in a highly polymorphic subtelomeric region and is surrounded by transposable elements, which may facilitate its rapid evolution to overcome Stb6 resistance. AvrStb6 is the first avirulence gene to be functionally validated in Z. tritici, contributing to our understanding of avirulence in apoplastic pathogens and the mechanisms underlying GFG interactions between Z. tritici and wheat.

https://nph.onlinelibrary.wiley.com/doi/epdf/10.1111/nph.14434

A small secreted protein in Zymoseptoria tritici is responsible for avirulence on wheat cultivars carrying the Stb6 resistance gene.

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.

https://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO-01-16-0018-R

An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

Reactive oxygen species are toxic byproducts of aerobic respiration that are also important in mediating a diversity of cellular functions. Reactive oxygen species form an important component of plant defenses to inhibit microbial pathogens during pathogen-plant interactions. Tolerance to oxidative stress is likely to make a significant contribution to the viability and pathogenicity of plant pathogens, but the complex network of oxidative stress responses hinders identification of the genes contributing to this trait. Here, we employed a forward genetic approach to investigate the genetic architecture of oxidative stress tolerance in the fungal wheat pathogen Zymoseptoria tritici. We used quantitative trait locus (QTL) mapping of growth and melanization under axenic conditions in two cross-populations to identify genomic regions associated with tolerance to oxidative stress. We found that QTLs associated with growth under oxidative stress as well as inherent growth can affect oxidative stress tolerance, and we identified two uncharacterized genes in a major QTL associated with this trait. Our data suggest that melanization does not affect tolerance to oxidative stress, which differs from what was found for animal pathogens. This study provides a whole-genome perspective on the genetic basis of oxidative stress tolerance in a plant pathogen.

Ziming Zhong

Papers

A small secreted protein in Zymoseptoria tritici is responsible for avirulence on wheat cultivars carrying the Stb6 resistance gene.

An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

Tolerance to oxidative stress is associated with both oxidative stress response and inherent growth in a fungal wheat pathogen