Estimating the delay between host infection and disease (incubation period) and assessing its significance to the epidemiology of plant diseases.

Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss.ML thanks the Institut Technique français de la Betterave industrielle (ITB) for funding this project. CAG and JANF were funded by the UK’s Biotechnology and Biological Sciences Research Council (BBSRC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

EPPO-Q-Bank - a tool for identification of plant quarantine pests

The increased risk of outbreaks of plant pests due to globalization and climate change requires up-to-date knowledge and quick and validated detection and identification methods. DNA barcoding is increasingly used for diagnostics in phytosanitary laboratories. This method uses short genomic sequences specific to a well-defined taxon for species identification. The aim of EPPO-Q-bank is to support species identification of quarantine plant pest based on barcodes. EPPO-Q-bank is composed of specific databases for arthropods, bacteria, fungi, nematodes, phytoplasmas, plants, viruses and viroids, which include sequences of quarantine pests and their look-alikes. The cornerstone of these databases is their curation by a team of 22 scientists with taxonomic, phytosanitary and diagnostic expertise from National Plant Protection Organizations and institutes with connections to relevant phytosanitary collections. Most strains, isolates or specimens, from which sequences included in the databases have been obtained, are available in physical collections. EPPO-Q-bank databases also provide valuable information about these specimens, strains or isolates, as well as populations, information about barcoding and sequencing methodologies and tools to perform single and multi-locus blast searches. Currently, the EPPO-Q-bank Databases include more than 2,095 species, 9,776 specimens, strains or isolates and 25,106 sequences. EPPO-Q-bank is hosted by EPPO since the 1st of May 2019

Transcriptome analysis reveals class IX ethylene response factors show specific up-regulation in resistant but not susceptible Medicago truncatula lines following infection with Rhizoctonia solani

The fungal pathogen Rhizoctonia solani AG8 causes substantial losses to cereal and legume production in Australia and the Pacific Northwest of the United States of America. Mutant analyses have revealed a critical role for ethylene mediated defence signalling for resistance to R. solani AG8 in the model legume Medicago truncatula which is, at least in part, mediated by ethylene dependent accumulation of isoflavonoids. In this study we investigate the potential for members of the ethylene response transcription factor (ERF) family in mediating the isoflavonoid and defence response. A strong and early Rhizoctonia-responsive expression pattern was observed for many of the class IX ERFs in the moderately resistant wild type line A17, while the ethylene insensitive and highly susceptible mutant sickle (skl) showed a very limited regulation of this class. Conversely, the skl mutant demonstrated up-regulation of class II ERFs known to act as transcriptional repressors. Analysis of the presence of the GCC box promoter element, thought to be responsible for ERF binding and transcriptional activity, in genes differentially regulated in A17 suggests indirect or alternative mechanisms of ERF mediated gene regulation may be contributing to the large scale transcriptional adaptation of A17 following R. solani AG8 infection. Comparison of the expression profile with that following infection of A17 and skl with the symbiotic bacterium Sinorhizobium medicae suggests that legumes have adapted the ERF family to perform diverse roles to balance defence against pathogens and symbiosis with beneficial microorganisms in the same root tissue