Using the nematophagous fungus Esteya vermicola to control the disastrous pine wilt disease

AbstractPine wilt disease (PWD) caused by the nematode Bursaphelenchus xylophilus is a serious problem on pines, and there is currently no effective control strategy for this disease. Although the endoparasitic fungus Esteya vermicola showed great effectiveness in controlling pine wilt disease, the colonization patterns of the host pine tree xylem by this fungus are unknown. To investigate the colonization patterns of pine xylem by this fungus, the species Pinus koraiensis grown in a greenhouse was used as an experimental host tree. The fungal colonization of healthy and wilting pine trees by E. vermicola was quantified using PCR with a TaqMan probe, and a green fluorescence protein (GFP) transformant was used for visualization. The results reported a specific infection approach used by E. vermicola to infect B. xylophilus and specialized fungal parasitic cells in PWN infection. In addition, the inoculated blastospores of E. vermicola germinated and grew inside of healthy pine xylem, although the growth rate was slow. Moreover, E. vermicola extended into the pine xylem following spray inoculation of wounded pine seedling stems, and a significant increase in fungal quantity was observed in response to B. xylophilus invasion. An accelerated extension of E. vermicola colonization was shown in PWN-infected wilting pine trees, due to the immigration of fungal-infected PWNs. Our results provide helpful knowledge about the extension rate of this fungus in healthy and wilting PWN-susceptible pine trees in the biological control of PWD and will contribute to the development of a management method for PWD control in the field.Author summaryPine wilt disease, caused by Bursaphelenchus xylophilus, has infected most pine forests in Asian and European forests and led to enormous losses of forest ecosystem and economy. Esteya vermicola is a bio-control fungus against pinewood nematode, showed excellent control efficient to pine wilt disease in both of greenhouse experiments and field tests. Although this bio-control agent was well known for the management of pine wilt disease, the infection mechanism of fungal infection and colonization of host pine tree are less understand. Here, we use GFP-tagged mutant to investigate the fungal infection to pinewood nematode; additionally, the temporal and spatial dynamics of E. vermicola colonize to pine tree were determined by the TaqMan real-time PCR quantification, as well as the response to pinewood nematode invasion. We found a specific infection approach used by E. vermicola to infect B. xylophilus and specialized fungal parasitic cells in PWN infection. In addition, the fungal germination and extension inside of pine tree xylem after inoculation were revealed. In addition, the quantity of E. vermicola increased as response to pinewood nematode invasion was reported. Our study provides two novel technologies for the visualization and detection of E. vermicola for the future investigations of fungal colonization and its parasitism against pinewood nematode, and the mechanisms of the bio-control process.

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Research advance on Esteya vermicola, a high potential biocontrol agent of pine wilt disease

Mycological Progress ◽

10.1007/s11557-015-1137-9 ◽

2015 ◽

Vol 14 (12) ◽

Cited By ~ 9

Author(s):

Wen Hui Chu ◽

Qing Dou ◽

Hong Long Chu ◽

Hai Hua Wang ◽

Chang Keun Sung ◽

...

Keyword(s):

Biocontrol Agent ◽

Pine Wilt Disease ◽

Wilt Disease ◽

High Potential ◽

Pine Wilt ◽

Potential Biocontrol Agent ◽

Research Advance ◽

Esteya Vermicola

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Effects of cavitation on the development of pine wilt disease caused by Bursaphelenchus xylophilus.

Japanese Journal of Phytopathology ◽

10.3186/jjphytopath.54.606 ◽

1988 ◽

Vol 54 (5) ◽

pp. 606-615 ◽

Cited By ~ 34

Author(s):

Keiko KURODA ◽

Toshihiro YAMADA ◽

Kazuhiko MINEO ◽

Hirotada TAMURA

Keyword(s):

Pine Wilt Disease ◽

Bursaphelenchus Xylophilus ◽

Wilt Disease ◽

Pine Wilt

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Early detection of pine wilt disease in Pinus tabuliformis in North China using a field portable spectrometer and UAV-based hyperspectral imagery

Forest Ecosystems ◽

10.1186/s40663-021-00328-6 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Run Yu ◽

Lili Ren ◽

Youqing Luo

Keyword(s):

Early Stage ◽

Vegetation Indices ◽

Pine Wilt Disease ◽

Wilt Disease ◽

Pinus Tabulaeformis ◽

Pine Tree ◽

Preventative Measures ◽

Pine Wilt ◽

Pine Trees ◽

Airborne Vehicle

Abstract Background Pine wilt disease (PWD) is a major ecological concern in China that has caused severe damage to millions of Chinese pines (Pinus tabulaeformis). To control the spread of PWD, it is necessary to develop an effective approach to detect its presence in the early stage of infection. One potential solution is the use of Unmanned Airborne Vehicle (UAV) based hyperspectral images (HIs). UAV-based HIs have high spatial and spectral resolution and can gather data rapidly, potentially enabling the effective monitoring of large forests. Despite this, few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine. Method To fill this gap, we used a Random Forest (RF) algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data (data directly collected from trees in the field). We compared relative accuracy of each of these data collection methods. We built our RF model using vegetation indices (VIs), red edge parameters (REPs), moisture indices (MIs), and their combination. Results We report several key results. For ground data, the model that combined all parameters (OA: 80.17%, Kappa: 0.73) performed better than VIs (OA: 75.21%, Kappa: 0.66), REPs (OA: 79.34%, Kappa: 0.67), and MIs (OA: 74.38%, Kappa: 0.65) in predicting the PWD stage of individual pine tree infection. REPs had the highest accuracy (OA: 80.33%, Kappa: 0.58) in distinguishing trees at the early stage of PWD from healthy trees. UAV-based HI data yielded similar results: the model combined VIs, REPs and MIs (OA: 74.38%, Kappa: 0.66) exhibited the highest accuracy in estimating the PWD stage of sampled trees, and REPs performed best in distinguishing healthy trees from trees at early stage of PWD (OA: 71.67%, Kappa: 0.40). Conclusion Overall, our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage, although its accuracy must be improved before widespread use is practical. We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data. We believe that these results can be used to improve preventative measures in the control of PWD.

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Dynamical aspects of pine wilt disease and control measures

Chaos Solitons & Fractals ◽

10.1016/j.chaos.2021.110764 ◽

2021 ◽

Vol 145 ◽

pp. 110764

Author(s):

Takasar Hussain ◽

Adnan Aslam ◽

Muhammad Ozair ◽

Fatima Tasneem ◽

J.F. Gómez-Aguilar

Keyword(s):

Pine Wilt Disease ◽

Wilt Disease ◽

Control Measures ◽

Pine Wilt ◽

And Control

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Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Forests ◽

10.3390/f12060731 ◽

2021 ◽

Vol 12 (6) ◽

pp. 731

Author(s):

Zhuoqing Hao ◽

Jixia Huang ◽

Yantao Zhou ◽

Guofei Fang

Keyword(s):

River Basin ◽

Yangtze River ◽

Yangtze River Basin ◽

Pine Wilt Disease ◽

Wilt Disease ◽

Spatiotemporal Pattern ◽

Pinewood Nematode ◽

The Yangtze River ◽

Pine Wilt ◽

The Yangtze River Basin

The Yangtze River Basin is among the river basins with the strongest strategic support and developmental power in China. As an invasive species, the pinewood nematode (PWN) Bursaphelenchus xylophilus has introduced a serious obstacle to the high-quality development of the economic and ecological synchronization of the Yangtze River Basin. This study analyses the occurrence and spread of pine wilt disease (PWD) with the aim of effectively managing and controlling the spread of PWD in the Yangtze River Basin. In this study, statistical data of PWD-affected areas in the Yangtze River Basin are used to analyse the occurrence and spread of PWD in the study area using spatiotemporal visualization analysis and spatiotemporal scanning statistics technology. From 2000 to 2018, PWD in the study area showed an “increasing-decreasing-increasing” trend, and PWD increased explosively in 2018. The spatial spread of PWD showed a “jumping propagation-multi-point outbreak-point to surface spread” pattern, moving west along the river. Important clusters were concentrated in the Jiangsu-Zhejiang area from 2000 to 2015, forming a cluster including Jiangsu and Zhejiang. Then, from 2015–2018, important clusters were concentrated in Chongqing. According to the spatiotemporal scanning results, PWD showed high aggregation in the four regions of Zhejiang, Chongqing, Hubei, and Jiangxi from 2000 to 2018. In the future, management systems for the prevention and treatment of PWD, including ecological restoration programs, will require more attention.

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