Marie-Krystel Gauthier, Abdelmadjid Djoumad, Tara L. Bal, Guillaume J. Bilodeau, Marc F. DiGirolomo, Meher Ony, Denita Hadziabdic, Kelsey C. McLaughlin, Laura Miles, Isabel Munck, Karen Lynn Snover-Clift, Philippe Tanguay
{"title":"用于指导橡树枯萎病 eDNA 监测的 Bretziella fagacearum 分子检测测定的实验室间评估","authors":"Marie-Krystel Gauthier, Abdelmadjid Djoumad, Tara L. Bal, Guillaume J. Bilodeau, Marc F. DiGirolomo, Meher Ony, Denita Hadziabdic, Kelsey C. McLaughlin, Laura Miles, Isabel Munck, Karen Lynn Snover-Clift, Philippe Tanguay","doi":"10.1002/edn3.70012","DOIUrl":null,"url":null,"abstract":"<p>Oak wilt disease, caused by the fungus <i>Bretziella fagacearum</i>, can kill mature red oaks within months of infection, severely affecting biodiversity, landscapes, and industries. The disease, originally only present in the United States, was officially reported for the first time in Canada in June 2023. The aim of this study was to suggest a standardized assay and sample processing method to optimize oak wilt detection both in infection centers and ahead of the disease front. Two previously published molecular assays, a Nested PCR and a TaqMan qPCR, were compared to detect <i>B. fagacearum</i> in a variety of samples in a ring trial across five laboratories. Sample types investigated included eDNA from trapped insect vectors (sorted insects and bulk content from traps), infested and healthy oak wood chips, and <i>B. fagacearum</i> conidia dilutions. Results demonstrated that both Nested and TaqMan assays can be used for molecular confirmation of oak wilt, and results are reproducible across different labs. There is a general agreement between both detection assays when testing true-positive and true-negative samples. Both methods demonstrated overall good accuracy. The TaqMan assay was more sensitive and detected lower amounts of DNA target. Both tests were 100% specific to oak wood samples, which was the best sample type to use for detection. In general, samples with high Cts were more prompted to yield false negative Nested results. Detecting oak wilt from bulk insect samples was by far more rapid than sorted sap beetles, but resulted in lower detection signals, especially with the Nested assay. The time-period when the insect traps were set up also had considerable influence on detection results. We hope this study helps to formulate guidelines in oak wilt detection and biosurveillance management.</p>","PeriodicalId":52828,"journal":{"name":"Environmental DNA","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/edn3.70012","citationCount":"0","resultStr":"{\"title\":\"Interlaboratory Evaluation of Bretziella fagacearum Molecular Detection Assays to Guide the eDNA Monitoring of Oak Wilt Disease\",\"authors\":\"Marie-Krystel Gauthier, Abdelmadjid Djoumad, Tara L. Bal, Guillaume J. Bilodeau, Marc F. DiGirolomo, Meher Ony, Denita Hadziabdic, Kelsey C. McLaughlin, Laura Miles, Isabel Munck, Karen Lynn Snover-Clift, Philippe Tanguay\",\"doi\":\"10.1002/edn3.70012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Oak wilt disease, caused by the fungus <i>Bretziella fagacearum</i>, can kill mature red oaks within months of infection, severely affecting biodiversity, landscapes, and industries. The disease, originally only present in the United States, was officially reported for the first time in Canada in June 2023. The aim of this study was to suggest a standardized assay and sample processing method to optimize oak wilt detection both in infection centers and ahead of the disease front. Two previously published molecular assays, a Nested PCR and a TaqMan qPCR, were compared to detect <i>B. fagacearum</i> in a variety of samples in a ring trial across five laboratories. Sample types investigated included eDNA from trapped insect vectors (sorted insects and bulk content from traps), infested and healthy oak wood chips, and <i>B. fagacearum</i> conidia dilutions. Results demonstrated that both Nested and TaqMan assays can be used for molecular confirmation of oak wilt, and results are reproducible across different labs. There is a general agreement between both detection assays when testing true-positive and true-negative samples. Both methods demonstrated overall good accuracy. The TaqMan assay was more sensitive and detected lower amounts of DNA target. Both tests were 100% specific to oak wood samples, which was the best sample type to use for detection. In general, samples with high Cts were more prompted to yield false negative Nested results. Detecting oak wilt from bulk insect samples was by far more rapid than sorted sap beetles, but resulted in lower detection signals, especially with the Nested assay. The time-period when the insect traps were set up also had considerable influence on detection results. We hope this study helps to formulate guidelines in oak wilt detection and biosurveillance management.</p>\",\"PeriodicalId\":52828,\"journal\":{\"name\":\"Environmental DNA\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/edn3.70012\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental DNA\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/edn3.70012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental DNA","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/edn3.70012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
Interlaboratory Evaluation of Bretziella fagacearum Molecular Detection Assays to Guide the eDNA Monitoring of Oak Wilt Disease
Oak wilt disease, caused by the fungus Bretziella fagacearum, can kill mature red oaks within months of infection, severely affecting biodiversity, landscapes, and industries. The disease, originally only present in the United States, was officially reported for the first time in Canada in June 2023. The aim of this study was to suggest a standardized assay and sample processing method to optimize oak wilt detection both in infection centers and ahead of the disease front. Two previously published molecular assays, a Nested PCR and a TaqMan qPCR, were compared to detect B. fagacearum in a variety of samples in a ring trial across five laboratories. Sample types investigated included eDNA from trapped insect vectors (sorted insects and bulk content from traps), infested and healthy oak wood chips, and B. fagacearum conidia dilutions. Results demonstrated that both Nested and TaqMan assays can be used for molecular confirmation of oak wilt, and results are reproducible across different labs. There is a general agreement between both detection assays when testing true-positive and true-negative samples. Both methods demonstrated overall good accuracy. The TaqMan assay was more sensitive and detected lower amounts of DNA target. Both tests were 100% specific to oak wood samples, which was the best sample type to use for detection. In general, samples with high Cts were more prompted to yield false negative Nested results. Detecting oak wilt from bulk insect samples was by far more rapid than sorted sap beetles, but resulted in lower detection signals, especially with the Nested assay. The time-period when the insect traps were set up also had considerable influence on detection results. We hope this study helps to formulate guidelines in oak wilt detection and biosurveillance management.