High-resolution melting analysis: a new molecular approach for the early detection of Diplodia pinea in Austrian pine

Genetic Analysis of Plant Pathogens Natural Populations

Population genetics allow to address fundamental questions about the biology of plant pathogens. By testing specific hypotheses, population genetics provide insights into the population genetic variability of pathogens across different geographical areas, time, and associated plant hosts, as well as on the structure and differentiation of populations, and on the possibility that a population is introduced and from where it has originated. In this chapter, basic concepts of population genetics are introduced, as well as the five evolutionary factors affecting populations, that is, mutations, recombination, variation in population size, gene flow, and natural selection. A step-by-step workflow, from sampling to data analysis, on how to perform a genetic analysis of natural populations of plant pathogens is discussed. Increased knowledge of the population biology of pathogens is pivotal to improve management strategies of diseases in agricultural and forest ecosystems.

Highly Clonal Structure and Abundance of One Haplotype Characterise the Diplodia sapinea Populations in Europe and Western Asia

Diplodia sapinea is a cosmopolitan endophyte and opportunistic pathogen having occurred on several conifer species in Europe for at least 200 years. In Europe, disease outbreaks have increased on several Pinus spp. in the last few decades. In this study, the genetic structure of the European and western Asian D. sapinea population were investigated using 13 microsatellite markers. In total, 425 isolates from 15 countries were analysed. A high clonal fraction and low genetic distance between most subpopulations was found. One single haplotype dominates the European population, being represented by 45.3% of all isolates and found in nearly all investigated countries. Three genetically distinct subpopulations were found: Central/North European, Italian and Georgian. The recently detected subpopulations of D. sapinea in northern Europe (Estonia) share several haplotypes with the German subpopulation. The northern European subpopulations (Latvia, Estonia and Finland) show relatively high genetic diversity compared to those in central Europe suggesting either that the fungus has existed in the North in an asymptomatic/endophytic mode for a long time or that it has spread recently by multiple introductions. Considerable genetic diversity was found even among isolates of a single tree as 16 isolates from a single tree resulted in lower clonal fraction index than most subpopulations in Europe, which might reflect cryptic sexual proliferation. According to currently published allelic patterns, D. sapinea most likely originates from North America or from some unsampled population in Asia or central America. In order to enable the detection of endophytic or latent infections of planting stock by D. sapinea, new species-specific PCR primers (DiSapi-F and Diplo-R) were designed. During the search for Diplodia isolates across the world for species specific primer development, we identified D. africana in California, USA, and in the Canary Islands, which are the first records of this species in North America and in Spain.

Development of a Multiplex High-Throughput Diagnostic Assay for the Detection of Strawberry Crown Rot Diseases Using High-Resolution Melting Analysis

Rapid and accurate disease diagnosis is a prerequisite for an effective disease management program in strawberry production. In Florida, Colletotrichum spp., Phytophthora spp., and Macrophomina phaseolina are the primary microorganisms causing strawberry crown rot. Even though the diseases can be caused by different pathogens, symptoms are indistinguishable and equally devastating. To inform strawberry growers in a timely fashion of diagnostic results for effective deployment of chemical control practices, we developed a multiplex high-resolution melting (HRM) assay to rapidly and accurately detect the abovementioned pathogens. The multiplex HRM assays using three predesigned primer pairs showed high specificity for individual species by generating specific melting peaks without cross-reaction between primers or with other common strawberry pathogens. The amplification limit of the assay was 1 pg of Colletotrichum and Phytophthora and 100 pg of M. phaseolina DNA per 10-μl reaction. However, the presence of different melting peaks was observed in mixed DNA samples and was concentration and target DNA dependent. A crude DNA extraction protocol was developed to allow high-throughput screening by minimizing the inhibitory effects. Moreover, we applied the HRM assay to 522 plant samples and found high correlations between conventional pathogen isolation and HRM and between singleplex and multiplex assays. Altogether, this multiplex HRM assay is specific, cost effective, and reliable for the timely detection of strawberry crown rot pathogens.

Fast and reliable molecular methods to detect fungal pathogens in woody plants

Plant diseases caused by pathogenic microorganisms represent a serious threat to plant productivity, food security, and natural ecosystems. An effective framework for early warning and rapid response is a crucial element to mitigate or prevent the impacts of biological invasions of plant pathogens. For these reasons, detection tools play an important role in monitoring plant health, surveillance, and quantitative pathogen risk assessment, thus improving best practices to mitigate and prevent microbial threats. The need to reduce the time of diagnosis has prompted plant pathologists to move towards more sensitive and rapid methods such as molecular techniques. Considering prevention to be the best strategy to protect plants from diseases, this review focuses on fast and reliable molecular methods to detect the presence of woody plant pathogens at early stage of disease development before symptoms occur in the host. A harmonized pool of novel technical, methodological, and conceptual solutions is needed to prevent entry and establishment of new diseases in a country and mitigate the impact of both invasive and indigenous organisms to agricultural and forest ecosystem biodiversity and productivity.

Detecting and Differentiating Phytoplasmas Belonging to Subgroups 16SrIV-A and 16SrIV-D Associated With Lethal Declines of Palms in Florida Using qPCR and High-Resolution Melt Analysis (HRMA)

Lethal yellowing (LY) and Texas Phoenix palm decline (TPPD) are two important phytoplasma diseases of palms in Florida. Both have been responsible for major economic losses historically and remain a constant threat to the sustainability of palm production in the landscaping and nursery industries in Florida. These two diseases cause rapid, lethal decline in afflicted palms, so rapid detection and identification is crucial to implement appropriate management strategies to reduce further spread and losses. In this study, a qPCR assay was developed to detect and identify the causal agents of LY and TPPD. Based on sequence data of the 16S gene for the 16SrIV-A phytoplasma (LY) and the 16SrIV-D phytoplasma (TPPD), two regions were identified in the gene that possessed sufficient variation to yield amplicons with measurable differences in melting temperature based on high resolution melt analysis (HRMA). One region was in the 5' region and the other was located in the 3' region of the gene. Products from both regions yielded amplicons with significantly different melting temperatures between the two phytoplasma strains. This research allows for the detection and identification of phytoplasmas in palms rapidly by eliminating many lengthy and post-PCR steps commonly used in phytoplasma identification.

Powerful qPCR assays for the early detection of latent invaders: interdisciplinary approaches in clinical cancer research and plant pathology

Latent invaders represent the first step of disease before symptoms occur in the host. Based on recent findings, tumors are considered to be ecosystems in which cancer cells act as invasive species that interact with the native host cell species. Analogously, in plants latent fungal pathogens coevolve within symptomless host tissues. For these reasons, similar detection approaches can be used for an early diagnosis of the invasion process in both plants and humans to prevent or reduce the spread of the disease. Molecular tools based on the evaluation of nucleic acids have been developed for the specific, rapid, and early detection of human diseases. During the last decades, these techniques to assess and quantify the proliferation of latent invaders in host cells have been transferred from the medical field to different areas of scientific research, such as plant pathology. An improvement in molecular biology protocols (especially referring to qPCR assays) specifically designed and optimized for detection in host plants is therefore advisable. This work is a cross-disciplinary review discussing the use of a methodological approach that is employed within both medical and plant sciences. It provides an overview of the principal qPCR tools for the detection of latent invaders, focusing on comparisons between clinical cancer research and plant pathology, and recent advances in the early detection of latent invaders to improve prevention and control strategies.

Development of a two-step high-resolution melting (HRM) analysis for screening sequence variants associated with resistance to the QoIs, benzimidazoles and dicarboximides in airborne inoculum of Botrytis cinerea

A rapid, high-resolution melting (HRM) analysis protocol was developed to detect sequence variations associated with resistance to the QoIs, benzimidazoles and dicarboximides in Botrytis cinerea airborne inoculum. HRM analysis was applied directly in fungal DNA collected from air samplers with selective medium. Three and five different genotypes were detected and classified according to their melting profiles in BenA and bos1 genes associated with resistance to benzimidazoles and dicarboximides, respectively. The sensitivity of the methodology was evident in the case of the QoIs, where genotypes varying either by a single nucleotide polymorphism or an additional 1205-bp intron were separated accurately with a single pair of primers. The developed two-step protocol was completed in 82 min and showed reduced variation in the melting curves' formation. HRM analysis rapidly detected the major mutations found in greenhouse strains providing accurate data for successfully controlling grey mould.

Genetic relationships in an international collection of Puccinia horiana isolates based on newly identified molecular markers and demonstration of recombination

The obligate biotrophic pathogen Puccinia horiana is the causal agent of chrysanthemum white rust. Although P. horiana is a quarantine organism, it has been able to spread to most chrysanthemum-producing regions in the world since the 1960s; however, the transfer routes are largely obscure. An extremely low level of allelic diversity was observed in a geographically diverse set of eight isolates using complexity reduction of polymorphic sequences (CRoPS) technology. Only 184 of the 16,196 contigs (1.1%) showed one or more single-nucleotide polymorphisms (SNPs). Thirty-two SNPs and one simple-sequence repeat were translated into molecular markers and used to genotype 45 isolates originating from North and South America, Asia, and Europe. In most cases, phylogenetic clustering was related to geographic origin, indicating local establishment. The European isolates mostly grouped in two major populations that may relate to the two historic introductions previously reported. However, evidence of recent geographic transfer was also observed, including transfer events between Europe and South America and between Southeast Asia and Europe. In contrast with the presumed clonal propagation of this microcyclic rust, strong indications of marker recombination were observed, presumably as a result of anastomosis, karyogamy, and somatic meiosis. Recombination and transfer also explain the geographic dispersal of specific markers. A near-to-significant correlation between the genotypic data and previously obtained pathotype data was observed and one marker was associated with the most virulent pathotype group. In combination with a fast SNP detection method, the markers presented here will be helpful tools to further elucidate the transfer pathways and local survival of this pathogen.

High-resolution DNA melt-curve analysis for cost-effective mass screening of pairwise species interactions

Ecological studies of pairwise interactions are constrained by the methods available for rapid species identification of the interacting organisms. The resolution of data required to characterize species interaction networks at multiple spatio-temporal scales can be intensive, and therefore laborious and costly to collect. We explore the utility of high-resolution DNA melt-curve analysis (HRM) as a rapid species identification method. An approach was developed to identify organisms at the pairwise interaction level, with particular application to cryptic species interactions that are traditionally difficult to study. Here, we selected a challenging application; to identify the presence/absence of pathogenic fungi (Sporothrix inflata, Ophiostoma nigrocarpum and Ophiostoma galeiforme) transported by bark beetle vectors (Hylastes ater and Hylurgus ligniperda). The technique was able to distinguish between different species of DNA within a single, pooled sample. In test applications, HRM was effective in the mass screening and identification of pathogenic fungal species carried by many individual bark beetle vectors (n = 455 beetles screened) across large geographic scales. For two of the fungal species, there was no difference in the frequency of association with either of their vectors, but for the third fungal species there was a shift in vector-pathogen associations across locations. This technique allows rapid, mass screening and characterization of species interactions at a fraction of the time and cost of traditional methods. It is anticipated that this method can be readily applied to explore other cryptic species interactions, or other studies requiring rapid generation of large data sets and/or high-throughput efficiency.

High-resolution melting analysis: a genotyping tool for population studies on Daphnia

Determining genetic variation at the DNA level within and between natural populations is important for understanding the role of natural selection on phenotypic traits, but many techniques of screening for genetic variation are either cost intensive, not sensitive enough or too labour- and time-consuming. Here, we demonstrate high-resolution melting analysis (HRMA) as a cost-effective and powerful tool for screening variable target genes in natural populations. HRMA is based on monitoring the melting of PCR amplicons. Owing to saturating concentrations of a dye that binds at high concentrations to double-stranded DNA, it is possible to genotype high numbers of samples rapidly and accurately. We analysed digestive trypsins of two Daphnia magna populations as an application example for HRMA. One population originated from a pond containing toxic cyanobacteria that possibly produce protease inhibitors and the other from a pond without such cyanobacteria. The hypothesis was that D. magna clones from ponds with cyanobacteria have undergone selection by these inhibitors, which has led to different trypsin alleles. We first sequenced pooled genomic PCR products of trypsins from both populations to identify variable DNA sequences of active trypsins. Second, we screened variable DNA sequences of each D. magna clone from both populations for single nucleotide polymorphisms via HRMA. The HRMA results revealed that both populations exhibited phenotypic differences in the analysed trypsins. Our results indicate that HRMA is a powerful genotyping tool for studying the variation of target genes in response to selection within and between natural Daphnia populations.