The Pine Wood Nematode: Implications of Factors Past and Present for Pine Wilt Disease

2004 ◽  
pp. 55-64
Keyword(s):  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Pine Wood Nematode ◽  
Pine Wood ◽  
Pine Wilt

scholarly journals Comparison of the Surface Coat Proteins of the Pine Wood Nematode Appeared During Host Pine Infection and In Vitro Culture by a Proteomic Approach

2010 ◽  
Vol 100 (12) ◽  
pp. 1289-1297 ◽  
Author(s):  
Ryoji Shinya ◽  
Hironobu Morisaka ◽  
Yuko Takeuchi ◽  
Mitsuyoshi Ueda ◽  
Kazuyoshi Futai
Keyword(s):  
Immune Response ◽  
Pine Wilt Disease ◽  
Host Immune Response ◽  
Wilt Disease ◽  
Surface Coat ◽  
Pine Wood Nematode ◽  
Pine Wood ◽  
Pine Wilt ◽  
Proteomic Approach ◽  
Plant Parasitic

Pine wilt disease, caused by the pine wood nematode (PWN), Bursaphelenchus xylophilus, has become of worldwide quarantine concern in recent years. Here, we disclosed the surface coat (SC) proteins of the PWN which are thought to be one of the key components in pine wilt development. This is the first report that focused on the SC proteins and thoroughly identified those proteins of a plant-parasitic nematode using the proteomic approach. In this study, SC protein profiles were compared for PWNs grown on the fungus Botrytis cinerea and in host pine seedlings. The results demonstrated that the gross amount of PWN SC proteins drastically increased during infection of the host pine. Thirty-seven protein bands showed significant quantity differences between fungus-grown and host-origin PWNs, and were used for identification by matrix-assisted laser desorption ionization time of flight mass spectrometry analysis. These included several proteins that are presumed to be involved in the host immune response; for example, regulators of reactive oxygen species (ROS) and a ROS scavenger. These results might suggest that the PWN SC proteins are crucial in modulating or evading host immune response. Our data provide a new insight into the mechanism of pine wilt disease and the biological role of the SC proteins of plant-parasitic nematodes.

Identification of a novel effector BxSapB3 that enhances the virulence of pine wood nematode Bursaphelenchus xylophilus

2019 ◽  
Vol 51 (10) ◽  
pp. 1071-1078
Author(s):  
Xin Huang ◽  
Longjiao Hu ◽  
Xiaoqin Wu
Keyword(s):  
Virulent Strain ◽  
Pine Wilt Disease ◽  
Bursaphelenchus Xylophilus ◽  
Wilt Disease ◽  
Pcr Analysis ◽  
Pine Wood Nematode ◽  
Pine Wood ◽  
Early Stages ◽  
Pine Wilt ◽  
Weakly Virulent

Abstract Pine wilt disease, caused by the pine wood nematode Bursaphelenchus xylophilus, leads to severe damage to pine forests in China. In our previous study, effectors secreted by this pathogen were shown to play roles in the different infection stages of pine wilt disease, and a series of candidate effectors were predicted by transcriptome sequencing. This study identified and characterized a novel effector, BxSapB3, which was among these candidate effectors. Agrobacterium-mediated transient expression was used to identify BxSapB3. BxSapB3 was secreted by B. xylophilus and found to be capable of inducing cell death in Nicotiana benthamiana. Quantitative real-time PCR (qRT-PCR) analysis revealed that BxSapB3 was upregulated in a highly virulent strain of B. xylophilus and expressed at lower levels in a weakly virulent strain at the early stages of infection. When BxSapB3 was silenced in B. xylophilus, the process of infection was delayed. These results indicate that BxSapB3 acts as an effector and contributes to virulence at the early stages of B. xylophilus infection.

scholarly journals Detection and Location of Dead Trees with Pine Wilt Disease Based on Deep Learning and UAV Remote Sensing

2020 ◽  
Vol 2 (2) ◽  
pp. 294-307 ◽  
Author(s):  
Xiaoling Deng ◽  
Zejing Tong ◽  
Yubin Lan ◽  
Zixiao Huang
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Deep Learning ◽  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Pine Wood Nematode ◽  
Dead Tree ◽  
Pine Wood ◽  
Tree Detection ◽  
Pine Wilt

Pine wilt disease causes huge economic losses to pine wood forestry because of its destructiveness and rapid spread. This paper proposes a detection and location method of pine wood nematode disease at a large scale adopting UAV (Unmanned Aerial Vehicle) remote sensing and artificial intelligence technology. The UAV remote sensing images were enhanced by computer vision tools. A Faster-RCNN (Faster Region Convolutional Neural Networks) deep learning framework based on a RPN (Region Proposal Network) network and the ResNet residual neural network were used to train the pine wilt diseased dead tree detection model. The loss function and the anchors in the RPN of the convolutional neural network were optimized. Finally, the location of pine wood nematode dead tree was conducted, which generated the geographic information on the detection results. The results show that ResNet101 performed better than VGG16 (Visual Geometry Group 16) convolutional neural network. The detection accuracy was improved and reached to about 90% after a series of optimizations to the network, meaning that the optimization methods proposed in this paper are feasible to pine wood nematode dead tree detection.

scholarly journals Assessment of the PCR technique for identification of Bursaphelenchus mucronatus Mamiya & Enda 1979, B. xylophilus Steiner & Buhrer 1934 (Nickle 1970) and B. fraudulentus Rühm 1956 (Nematoda, Aphelenchoididae) in crude extract of nematodes isolated from wood

2021 ◽  
Vol 61 (4) ◽  
pp. 346-351
Keyword(s):  
Pine Wilt Disease ◽  
Bursaphelenchus Xylophilus ◽  
Wilt Disease ◽  
Coniferous Forests ◽  
Pine Wood Nematode ◽  
Direct Examination ◽  
Pine Wood ◽  
Pine Wilt ◽  
Detection And Identification ◽  
Pine Trees

The pine wood nematode, Bursaphelenchus xylophilus Steiner & Buhrer 1934 (Nickle 1970) is the major causative agent of the pine wilt disease which has become devastating to Asian and European coniferous forests. These regions are also naturally occupied by two other native but nonpathogenic species, i.e. B. mucronatus Mamiya & Enda 1979 and B. fraudulentus Rühm 1956 which are closely related to the invasive B. xylophilus. Moreover, all these three species can colonize pine trees, and potentially be extracted from the same wood samples. Due to the cosmopolitan character and wide genetic variation within- and between existing populations the taxonomic distinction of these species based exclusively on their morphology is difficult or, almost impossible. The present quarantine regulations related to B. xylophilus require the most credible and simple methods which could allow for a possibly earliest detection and precise identification of this species in wood shipments and conifer forests stands. The main objectives of the presently reported research were to simplify the presently available procedures for possibly fast and precise detection and identification of B. xylophilus examined in the background of the remaining Bursaphelenchus species of the xylophilus group and other bacterio- and mycetophagous nematodes naturally present in the pine wood samples. The developed method is based on a direct examination of the crude nematode extract from wood samples and subsequent use of PCR technique with earlier designed specific reaction starters amplifying ITS1–28S rDNA regions.

Role of resin canals in the early stages of pine wilt disease caused by the pine wood nematode

1997 ◽  
Vol 75 (2) ◽  
pp. 346-351 ◽  
Author(s):  
Kyoko Ishida ◽  
Taizo Hogetsu
Keyword(s):  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Pinus Thunbergii ◽  
Pine Wood Nematode ◽  
Pine Wood ◽  
Pine Wilt ◽  
Bark Peeling ◽  
Resin Canals ◽  
Cut Surface

The role of cortical resin canals in the early development of a pine wilt disease in Japanese black pine, Pinus thunbergii, was studied. A part of the bark of a 2 cm long segment from a current-year stem was removed by a tangential cut with a razor blade. Both cortex-exposed segments with cut cortical resin canals (designated as +RC segments) and those without cut resin canals (–RC segments) were obtained by chance. When a virulent nematode isolate (S6-1) was inoculated onto the cut surface, the surface of the +RC segments turned brown 4 d after inoculation, and in some segments this browning occurred more intensely around cortical resin canals. When segments were cut transversely at the middle, the transverse cut surface of the inoculated +RC segments was brown and fragile, but that of the inoculated –RC segments was pale green and stable, as was that of the non-inoculated controls. Correspondingly, tissue cells including epithelial cells of the cortical resin canal of the +RC segments were all dead, but those of the –RC segments and the controls were alive. When nematodes were inoculated onto the inner surface (cambium side) of a bark peeling at which cambial xylem cells were exposed, they did not kill the cambial cells. When inoculated on the transverse cut end of a bark peeling from which nematodes would enter resin canals, nematodes killed all cells in the peeling. The above results indicate that nematodes do not kill cortical cells immediately after inoculation but become harmful to pine cells after living in cortical resin canals. Key words: Bursaphelenchus xylophilus, pine wilt disease, pine wood nematode, Pinus thunbergii, resin canal.

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

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1679
Author(s):  
Juha Tuomola ◽  
Hannah Gruffudd ◽  
Kimmo Ruosteenoja ◽  
Salla Hannunen
Keyword(s):  
Pine Wilt Disease ◽  
Bursaphelenchus Xylophilus ◽  
Wilt Disease ◽  
Pine Wood Nematode ◽  
The European Union ◽  
Climate Data ◽  
Worst Case ◽  
Pine Wood ◽  
Pine Wilt ◽  
Temperature Concept

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.

scholarly journals Pine wilt disease by pine wood nematode.

1990 ◽  
Vol 64 (7) ◽  
pp. 1241-1242
Author(s):  
Kazuyoshi KAWAZU
Keyword(s):  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Pine Wood Nematode ◽  
Pine Wood ◽  
Pine Wilt

scholarly journals Applying a spread model to identify the entry points from which the pine wood nematode, the vector of pine wilt disease, would spread most rapidly across Europe

2011 ◽  
Vol 13 (12) ◽  
pp. 2981-2995 ◽  
Author(s):  
Christelle Robinet ◽  
Nico Van Opstal ◽  
Richard Baker ◽  
Alain Roques
Keyword(s):  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Pine Wood Nematode ◽  
Pine Wood ◽  
Pine Wilt ◽  
Spread Model ◽  
Entry Points
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