A Molecular Assay Allows the Simultaneous Detection of 12 Fungi Causing Fruit Rot in Cranberry

Development of a PCR-based assay for specific and sensitive detection of Fusarium buharicum from infected okra plant

Fusarium wilt, caused by the fungus Fusarium buharicum, is an emerging disease of okra in Japan. The disease was first reported in Japan in 2015, causing significant damage to okra seedlings. Due to the potential threat in okra cultivation, the development of an accurate detection method for F. buharicum is needed for the surveillance and management of the disease. In this study, we designed a primer set and developed conventional and nested PCR assays for the specific detection of F. buharicum in infected okra plants and contaminated soil, respectively. We compared the diversity of the translation elongation factor 1 alpha (EF-1α) gene of F. buharicum with 103 other fungal species/isolates to design a species-specific primer. This primer pair successfully amplified approximately 400 bp of PCR product that was only detected in the F. buharicum isolate, not in the other fungal isolates. The developed nested PCR method was highly sensitive and could detect the fungus from a 0.01 fg DNA sample. The primer successfully detected the pathogen in artificially infected plants and soil by conventional and nested PCR, respectively. This is the first report of the development of the F. buharicum-specific primer set and detection assays, which can be used for the specific and sensitive detection of F. buharicum in field samples and for taking early control measures.

Novel plant disease detection techniques-a brief review

Plant pathogens cause severe losses to agricultural yield worldwide. Tracking plant health and early disease detection is important to reduce the disease spread and thus economic loss. Though visual scouting has been practiced from former times, detection of asymptomatic disease conditions is difficult. So, DNA-based and serological methods gained importance in plant disease detection. The progress in advanced technologies challenges the development of rapid, non-invasive, and on-field detection techniques such as spectroscopy. This review highlights various direct and indirect ways of detecting plant diseases like Enzyme-linked immunosorbent assay, Lateral flow assays, Polymerase chain reaction, spectroscopic techniques and biosensors. Although these techniques are sensitive and pathogen-specific, they are more laborious and time-intensive. As a consequence, a lot of interest is gained in in-field adaptable point-of-care devices with artificial intelligence-assisted pathogen detection at an early stage. More recently computer-aided techniques like neural networks are gaining significance in plant disease detection by image processing. In addition, a concise report on the latest progress achieved in plant disease detection techniques is provided.

New Insights into the Fungal Diversity of Cranberry Fruit Rot in Québec Farms Through a Large-Scale Molecular Analysis

Cranberry fruit rot (CFR) pathogens are widely reported in the literature, but performing large-scale analysis of their presence inside fruit has always been challenging. In this study, a new molecular diagnostic tool, capable of identifying simultaneously 12 potential fungal species causing CFR, was used to better define the impact of CFR across cranberry fields in Québec. For this purpose, 126 fields and 7,825 fruits were sampled in three cranberry farms distributed throughout the province and subjected to comparative analyses of fungal presence and abundance according to cultural practices, sampling times, and cranberry cultivars. All 12 pathogens were detected throughout the study, but as a first major finding, the analyses revealed that four species, Godronia cassandrae, Colletotrichum fructivorum, Allantophomopsis cytisporea, and Coleophoma empetri, were consistently predominant regardless of the parameters studied. Comparison of conventional and organic productions showed a significant reduction in fungal richness and relative abundance. Interestingly, Monilinia oxycocci was found almost exclusively in organic productions, indicating that fungicides had a strong and persistent effect on its population. Surprisingly, there were no significant differences in fungal relative abundance or species richness between fruit sampled at harvest or in storage, suggesting that there may not exist a clear distinction between field and storage rot, as was previously thought. Comparative analysis of fungal species found on eight different cranberry cultivars indicated that they were all infected by the same fungi but could not rule out differences in genetic resistance. This large-scale analysis allows us to draw an exhaustive picture of CFR in Québec and provides new information with respect to its management.

Conventional Gel Electrophoresis and TaqMan Probes Enable Rapid Confirmation of Thousand Cankers Disease from Diagnostic Samples

Thousand cankers disease (TCD) is caused by the fungal pathogen Geosmithia morbida and vectored by the walnut twig beetle Pityophthorus juglandis. In infected walnut and butternut (Juglans spp.) hosts and wingnut species (Pterocarya spp.) hosts, tree decline and death results in ecological disruption and economic losses. A rapid molecular detection protocol for TCD using microsatellite markers can confirm the presence of insect vector or fungal pathogen DNA, but it requires specialized expensive equipment and technical expertise. Using four different experimental approaches, capillary and conventional gel electrophoresis, and traditional polymerase chain reaction (PCR) and quantitative PCR (qPCR), we describe simplified and inexpensive processes for diagnostic confirmation of TCD. The improved and rapid detection protocols reported in this study reduce time and equipment costs associated with detection of molecular pest and pathogen DNA by (1) using conventional gel electrophoresis or TaqMan molecular probes to elucidate the detection limits for G. morbida and P. juglandis DNA and (2) identifying resources that allow visualization of positive test results for infected host plant tissue samples. Conventional gel electrophoresis and TaqMan molecular probe protocols detected presence of DNA from TCD-associated fungal and insect samples. These procedural improvements can be readily adopted by diagnostic end-users and adapted for use with other complex disease systems to enable rapid pest and pathogen detection.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Recent Advances in Molecular Diagnostics of Fungal Plant Pathogens: A Mini Review

Phytopathogenic fungal species can cause enormous losses in quantity and quality of crop yields and this is a major economic issue in the global agricultural sector. Precise and rapid detection and identification of plant infecting fungi are essential to facilitate effective management of disease. DNA-based methods have become popular methods for accurate plant disease diagnostics. Recent developments in standard and variant polymerase chain reaction (PCR) assays including nested, multiplex, quantitative, bio and magnetic-capture hybridization PCR techniques, post and isothermal amplification methods, DNA and RNA based probe development, and next-generation sequencing provide novel tools in molecular diagnostics in fungal detection and differentiation fields. These molecular based detection techniques are effective in detecting symptomatic and asymptomatic diseases of both culturable and unculturable fungal pathogens in sole and co-infections. Even though the molecular diagnostic approaches have expanded substantially in the recent past, there is a long way to go in the development and application of molecular diagnostics in plant diseases. Molecular techniques used in plant disease diagnostics need to be more reliable, faster, and easier than conventional methods. Now the challenges are with scientists to develop practical techniques to be used for molecular diagnostics of plant diseases. Recent advancement in the improvement and application of molecular methods for diagnosing the widespread and emerging plant pathogenic fungi are discussed in this review.

First report of Godronia cassandrae as a major cranberry fruit rot pathogen in Eastern Canada

The complex etiology of cranberry fruit rot (CFR) (Oudemans et al., 1998) has made it difficult to precisely identify the fungi involved in CFR and their relative importance in North America. To remedy this situation, a multiplex PCR approach targeting the 12 most commonly reported fungi in CFR was recently developed (Conti et al., 2019). However, in surveys conducted in Eastern Canada, the molecular tool revealed the presence of an unknown fungus in more than 30% of the collected samples. Analyses were thus undertaken to identify this species. From 117 rotten fruit collected at harvest in 2017, 34 samples of the unknown fungus, all morphologically similar, were isolated but not detected using the molecular tool. Their ITS ribosomal regions were sequenced using universal primers (Vilgalys and Hester, 1990; White et al., 1990) and searched against the GenBank database using the Blastn tool (Altschul et al., 1990). The top match was obtained with Godronia cassandrae (accession number: MH855281 (Vu et al., 2019), 98-100% of identity and an E-value of 0.0), even though some isolates had minor nucleotide differences, as presented in the tree. Sequences were deposited in GenBank as accession numbers MT599989 to MT600022. Since G. cassandrae had been reported, albeit rarely, on cranberry in Michigan (Olatinwo et al., 2003), it was supposed to amplify with the molecular tool developed from the strain DAOM C216021 (AAFC, Ottawa, ON) identified in 1993 on Vaccinium angustifolium as G. cassandrae. Analysis of the sequences used to build the specific primers from this strain confirmed the DAOM strain as being Neocucurbitaria juglandicola, which was never diagnosed in our cranberry samples. To confirm this revised diagnosis, a multi-sequence alignment (MSA) was performed on the ITS regions of the isolates from rotten cranberries and sequences available for the genus Godronia in the NCBI nucleotide database (NCBI txid269064). This MSA allowed us to find discriminant regions between Godronia spp. A pair of PCR primers specific to G. cassandrae found on cranberry fruit was then designed (the forward and reverse sequences are AAT CAG TGG CGG TGC CTG TC and TAC CGC TTC ACT CGC CGT TAC, respectively), generating 196 bp amplicons, with an annealing temperature of 65°C. The diagnosis of 7,835 fruit sampled at three time points (harvest, after three and after six weeks of storage) in 2018, from four cranberry farms located in Québec (CA) and Nova Scotia (CA), detected G. cassandrae in 2350 samples (30%). To assess the pathogenicity of four specimens from 2017, Koch's postulates were completed on two healthy fruit per isolate. The fruit were wounded with a sterilized pick and individually inoculated; two fruit were used as control. Based on our observations, the fungi isolated from cranberry fruit displayed a pale lemon yellow mycelium and black pycnidia. Conidia are hyaline, cylindrical and divided by a single septum. These morphological characters are similar to the ones described in the literature for G. cassandrae (Polashock et al., 2017). Rot symptoms appear as a discoloration from the firm, red and healthy cranberry fruit to a yellowish-orange softer fruit. Molecular characterization of the re-isolated fungus confirmed the presence of G. cassandrae. We report Godronia cassandrae for the first time as a major cause of CFR in Eastern Canada. Its prevalence in cranberry fields of Québec and Nova Scotia suggests that it supplants Physalospora as the main fungus involved in CFR in Eastern Canada.

Discriminant haplotypes of avirulence genes of Phytophthora sojae lead to a molecular assay to predict phenotypes

The soybean-Phytophthora sojae interaction operates on a gene-for-gene relationship, where the product of a resistance gene (Rps) in the host recognizes that of an avirulence gene (Avr) in the pathogen to generate an incompatible reaction. To exploit this form of resistance, one must match with precision the appropriate Rps gene with the corresponding Avr gene. Currently, this association is evaluated by phenotyping assays that are labour-intensive and often imprecise. To circumvent this limitation, we sought to develop a molecular assay that would reveal the avirulence allele of the seven main Avr genes (Avr1a, Avr1b, Avr1c, Avr1d, Avr1k, Avr3a, and Avr6) in order to diagnose with precision the pathotypes of P. sojae isolates. For this purpose, we analysed the genomic regions of these Avr genes in 31 recently sequenced isolates with different virulence profiles and identified discriminant mutations between avirulence and virulence alleles. Specific primers were designed to generate amplicons of a distinct size, and polymerase chain reaction conditions were optimized in a final assay of two parallel runs. When tested on the 31 isolates of known virulence, the assay accurately revealed all avirulence alleles. The test was further assessed and compared to a phenotyping assay on 25 isolates of unknown virulence. The two assays matched in 97% (170/175) of the interactions studied. Interestingly, the sole cases of discrepancy were obtained with Avr3a, which suggests a possible imperfect interaction with Rps3a. This molecular assay offers a powerful and reliable tool to exploit and study with greater precision soybean resistance against P. sojae.