
Novel diagnostic tools for rapid and early detection of oak wilt
Abdennour Abbas, Bioproducts & Biosystems Engineering
Background
Oak wilt (Ceratocystis fagacearum) is a fungal disease affecting oak species in 25 counties across the state. For tree removal costs alone, Minnesotans paid an estimated $60 million in the past decade because of this disease.
The key to oak wilt is spotting the problem before it’s too late. When infection is caught early, managers can take action to lower the risk of spread. But it can be weeks before visible signs appear, and symptoms are easy to confuse with damage from drought, pests or other diseases.
Lab testing has been a mainstay for reliable oak wilt diagnosis, but the process can be slow, expensive and susceptible to contamination. This work recognizes the urgent need for faster, more affordable diagnosis of oak wilt in the field. The team is developing a handheld reader that will allow managers to detect oak wilt from wood chips within one hour, at less than five dollars per sample.
Research questions
- Can DNA receptors specific to the oak wilt fungus, C. fagacearum, be used to detect infection in real samples?
- Can DNA identification technology be adapted into a handheld portable field device for rapid disease detection?
Practical implications
A rapid, reliable, affordable handheld field reader can improve oak wilt diagnosis rates dramatically and help stop the disease's spread in Minnesota.
Details
Funding:
$274,286
Collaborators:
US Forest Service
Research Team:
Abdennour Abbas, principal investigator
Brett Arenz, co-principal investigator
Jennifer Juzwik, co-principal investigator
News & Publications
- "Researchers use green gold to rapidly detect and identify harmful bacteria" Manufacturing.net
- Gold Nanoplate-Enhanced Chemiluminescence and Macromolecular Shielding for Rapid Microbial Diagnostics (Advanced Healthcare Materials, 2018)
- Microbial separation from a complex matrix by a hand-held microfluidic device (Chemical Communications, 2017)
Rapid and PCR-free DNA Detection by Nanoaggregation-Enhanced Chemiluminescence (Nature Scientific Reports, 2017)
Header image credit (right):
"Oak wilt" by Ronald F. Billings, Texas A&M Forest Service, Bugwood.org is licensed under CC BY-NC 3.0