2022 ESA Annual Meeting (August 14 - 19)

PS 44-90 Developing a molecular based diagnostic test to detect parasitism in a highly-invasive lepidopteran

5:00 PM-6:30 PM
ESA Exhibit Hall
Kyle Miller, Newcastle University;James Kitson,Newcastle University;Neil Boonham,Newcastle University;Darren Evans,Newcastle University;Jake Morris,Department for Food, Environmental and Rural Affairs UK government;Andrew Hoppit,Forestry Commission;
Background/Question/Methods

The Oak Processionary moth (OPM) is a species native to central and southern Europe but is an invasive species, and serious forestry pest, in several northern European countries (Germany, the Netherlands, and the UK). OPM is a defoliator of Quercus (Oak) species and potential human health threat due to small urticating hairs which produce a pseudo-allergic response in humans. In London, OPM have been present since 2006, with a breeding population establishing and expanding. Concerns about the financial and environmental cost of nest removal and pesticide application have led to calls for alternative control measures, including biocontrol with parasitoids such as Carcelia iliaca.The lack of knowledge around C. iliaca ecology means that making informed management decisions is incredibly difficult. This data is also diffcult to gather to do the health and safety risks of handling OPM larvae in enclosed environments. Therefore, it would be appropriate to deploy a molecular methodology that is validated for sampling in the field, such as loop-mediated isothermal amplification (LAMP). This technique is also, cheap and rapid making it ideal for sampling many individuals across a wide area.

Results/Conclusions

Here, extracts of OPM larval samples with known parasitism status were used to test four LAMP primer sets. The results show the successful development of a LAMP based diagnostic assay that successfully amplifies C. iliaca from ground OPM lysate, excluding the need for complicated DNA extraction. Being able to gather C. iliaca distribution data from ground OPM samples allows for the development of predictive models to understand the ecological variables that allow for the presence of C. iliaca. This information would inform integrated pest management decision making frameworks for land managers.