The Potential of Esteya spp. for the Biocontrol of the Pinewood Nematode, Bursaphelenchus xylophilus

The pinewood nematode (PWN), Bursaphelenchus xylophilus, is the causal agent of pine wilt disease (PWD) and a quarantine organism in many countries. Managing PWD involves strict regulations and heavy contingency plans, and present climate change scenarios predict a spread of the disease. The urgent need for sustainable management strategies has led to an increasing interest in promising biocontrol agents capable of suppressing the PWN, like endoparasitic nematophagous fungi of the Esteya genus. Here, we review different aspects of the biology and ecology of these nematophagous fungi and provide future prospects.

Effect of storage conditions on the shelf-life extension of fungus-colonized substrates based on Metarhizium anisopliae using modified atmosphere packaging

Metarhizium anisopliae is a promising alternative to chemical pesticides against pine wilt disease caused by Bursaphelenchus xylophilus. Herein, we investigated the efficacy of modified atmosphere packaging (MAP) to prolong the shelf-life of the M. anisopliae conidia. The effects of various conditions on its stability were also examined. M. anisopliae-inoculated millet grains were treated in a MAP system with different packaging materials (polypropylene, PP; polyethylene terephthalate, PET; ethylene vinyl alcohol, EVOH), gas compositions (high CO2 atmosphere, ≈ 90%; high O2 atmosphere, > 95%; high N2 atmosphere, > 95%; 30% CO2 + 70% N2; 50% CO2 + 50% N2; 70% CO2 + 30% N2), and storage temperatures (4 and 25 °C). Results revealed EVOH film as the best for the preservation of gases at all concentrations for 28 days. MAP treatment in the high-barrier EVOH film under an atmosphere of 30% CO2 + 70% N2 achieved 80.5% viability of dried conidia (7.4% moisture content), with 44.2–64.9% viability recorded with the other treatments. Cold storage for technical concentrates formulation promoted extension of shelf-life of MAP-treated conidia. These results imply that MAP under optimized conditions could enhance the shelf-life of fungus-based biopesticides in fungus-colonized substrates formulations.

Systemic Acquired Resistance-Mediated Control of Pine Wilt Disease by Foliar Application With Methyl Salicylate

Pine wilt disease (PWD), caused by the pinewood nematode, is the most destructive disease in pine forest ecosystems worldwide. Extensive research has been done on PWD, but effective disease management is yet to be devised. Generally, plants can resist pathogen attack via a combination of constitutive and inducible defenses. Systemic acquired resistance (SAR) is an inducible defense that occurs by the localized infection of pathogens or treatment with elicitors. To manage PWD by SAR in pine trees, we tested previously known 12 SAR elicitors. Among them, methyl salicylate (MeSA) was found to induce resistance against PWD in Pinus densiflora seedlings. In addition, the foliar applications of the dispersible concentrate-type formulation of MeSA (MeSA 20 DC) and the emulsifiable concentrate-type formulation of MeSA (MeSA 20 EC) resulted in significantly reduced PWD in pine seedlings. In the field test using 10-year-old P. densiflora trees, MeSA 20 DC showed a 60% decrease in the development of PWD. Also, MeSA 20 EC gave the best results when applied at 0.1 mM concentration 2 and 1 weeks before pinewood nematode (PWN) inoculation in pine seedlings. qRT-PCR analysis confirmed that MeSA induced the expression of defense-related genes, indicating that MeSA can inhibit and delay the migration and reproduction of PWN in pine seedlings by modulating gene expression. These results suggest that foliar application of MeSA could reduce PWD incidence by inducing resistance and provide an economically feasible alternative to trunk-injection agents for PWD management.

Multi-Omics of Pine Wood Nematode Pathogenicity Associated With Culturable Associated Microbiota Through an Artificial Assembly Approach

Pinewood nematode (PWN), the causal agent of pine wilt disease (PWD), causes massive global losses of Pinus species each year. Bacteria and fungi existing in symbiosis with PWN are closely linked with the pathogenesis of PWD, but the relationship between PWN pathogenicity and the associated microbiota is still ambiguous. This study explored the relationship between microbes and the pathogenicity of PWN by establishing a PWN-associated microbe library, and used this library to generate five artificial PWN–microbe symbiont (APMS) assemblies with gnotobiotic PWNs. The fungal and bacterial communities of different APMSs (the microbiome) were explored by next-generation sequencing. Furthermore, different APMSs were used to inoculate the same Masson pine (Pinus massoniana) cultivar, and multi-omics (metabolome, phenomics, and transcriptome) data were obtained to represent the pathogenicity of different APMSs at 14 days post-inoculation (dpi). Significant positive correlations were observed between microbiome and transcriptome or metabolome data, but microbiome data were negatively correlated with the reactive oxygen species (ROS) level in the host. Five response genes, four fungal genera, four bacterial genera, and nineteen induced metabolites were positively correlated with the ROS level, while seven induced metabolites were negatively correlated. To further explore the function of PWN-associated microbes, single genera of functional microbes (Mb1–Mb8) were reloaded onto gnotobiotic PWNs and used to inoculate pine tree seedlings. Three of the genera (Cladophialophora, Ochroconis, and Flavobacterium) decreased the ROS level of the host pine trees, while only one genus (Penicillium) significantly increased the ROS level of the host pine tree seedlings. These results demonstrate a clear relationship between associated microbes and the pathogenicity of PWN, and expand the knowledge on the interaction between PWD-induced forest decline and the PWN-associated microbiome.

Surveillance of pine wilt disease by high resolution satellite

Pine wilt disease caused by the pinewood nematode Bursaphelenchus xylophilus has led to the death of a large number of pine trees in China. This destructive disease has the characteristics of bring wide-spread, fast onset, and long incubation time. Most importantly, in China, the fatality rate in pines is as high as 100%. The key to reducing this mortality is how to quickly find the infected trees. We proposed a method of automatically identifying infected trees by a convolution neural network and bounding box tool. This method rapidly locates the infected area by classifying and recognizing remote sensing images obtained by high resolution earth observation Satellite. The recognition accuracy of the test data set was 99.4%, and the remote sensing image combined with convolution neural network algorithm can identify and determine the distribution of the infected trees. It can provide strong technical support for the prevention and control of pine wilt disease.

A Deep Learning-Based Generalized System for Detecting Pine Wilt Disease Using RGB-Based UAV Images

Pine wilt is a devastating disease that typically kills affected pine trees within a few months. In this paper, we confront the problem of detecting pine wilt disease. In the image samples that have been used for pine wilt disease detection, there is high ambiguity due to poor image resolution and the presence of “disease-like” objects. We therefore created a new dataset using large-sized orthophotographs collected from 32 cities, 167 regions, and 6121 pine wilt disease hotspots in South Korea. In our system, pine wilt disease was detected in two stages: n the first stage, the disease and hard negative samples were collected using a convolutional neural network. Because the diseased areas varied in size and color, and as the disease manifests differently from the early stage to the late stage, hard negative samples were further categorized into six different classes to simplify the complexity of the dataset. Then, in the second stage, we used an object detection model to localize the disease and “disease-like” hard negative samples. We used several image augmentation methods to boost system performance and avoid overfitting. The test process was divided into two phases: a patch-based test and a real-world test. During the patch-based test, we used the test-time augmentation method to obtain the average prediction of our system across multiple augmented samples of data, and the prediction results showed a mean average precision of 89.44% in five-fold cross validation, thus representing an increase of around 5% over the alternative system. In the real-world test, we collected 10 orthophotographs in various resolutions and areas, and our system successfully detected 711 out of 730 potential disease spots.

Could Pine Wood Nematode (Bursaphelenchus xylophilus) Cause Pine Wilt Disease or Even Establish inside Healthy Trees in Finland Now—Or Ever?

Pine wilt disease (PWD) caused by the pine wood nematode (PWN, Bursaphelenchus xylophilus) can, in suitable conditions, lead to mass mortality of susceptible trees. In the European Union, PWN is a quarantine pest. To support PWN risk management in Finland, we assessed the suitability of the Finnish present and future climate for both PWD and PWN establishment inside susceptible healthy trees. The former was done using the mean summer temperature concept and the latter by relating annual growing degree days to the likelihoods of PWN extinction and establishment inside healthy trees. The likelihoods were derived from the previously published modelling of PWN population dynamics for 139 locations in Germany. Both assessments were conducted using 10 × 10 km resolution climate data from 2000–2019 and Finland-specific climate change projections for 2030–2080. The results indicate that the present Finnish climate is too cool for both PWD and PWN establishment inside healthy trees. Furthermore, even global warming does not appear to turn the Finnish climate suitable for PWD or PWN establishment inside healthy trees by 2080, except under the worst-case representative concentration pathway scenario (RCP8.5). Consequently, giving top priority to PWN when allocating resources for biosecurity activities in Finland might deserve reconsideration.

Primary Metabolite Adjustments Associated With Pinewood Nematode Resistance in Pinus pinaster

The pinewood nematode (PWN) Bursaphelenchus xylophilus is the causal agent of the pine wilt disease (PWD) and represents one of the major threats to conifer forests. The detection of the PWN in Portugal, associated with Pinus pinaster, increased the concern of its spread to European forests. Despite its susceptibility to PWD, genetic variability found among P. pinaster populations has been associated with heritable PWD resistance. Understanding the mechanisms underlying tree resistance constitutes a valuable resource for breeding programs toward more resilient forest plantations. This study investigated changes in anatomy, chlorophyll a fluorescence (ChlF), and primary metabolism in susceptible and resistant P. pinaster half-sib plants, after PWN inoculation. Susceptible plants showed a general shutdown of central metabolism, osmolyte accumulation, photosynthetic inhibition, and a decrease in the plant water status. The ChlF transient rise (OJIP curve) revealed the appearance of L- and K-bands, indicators of environmental stress. In contrast, resistant plants revealed a regulated defense response and were able to restrict PWN migration and cellular damage. Furthermore, the accumulation of γ-aminobutyric acid (GABA) and succinate suggested a role of these metabolites in PWD resistance and the possible activation of the GABA shunt. Altogether, these results provide new insights to the role of primary metabolism in PWD resistance and in the selection of resistant phenotypes for disease mitigation.