Sampling and metabarcoding of arthropod environmental DNA traces from flowers - David Wari; Yoshinobu Kusumoto; Toshio Kitamura (MethodsX, 2025)
Screening and selection of insectary plants that promote natural enemies has been mostly approached via conventional methods that employ mundane man-hours of manual surveys, sampling, sorting, and viewing under microscope. In this digital age, mundane man-hours in ecological surveys can be approached with revolutionary sequencing technology, i.e. the Next Generation Sequencing (NGS). Ecological scientist, especially marine biologists have been tracing environmental DNA (eDNA) by utilizing the NGS technology to study/monitor micro- and macro-organisms in aquatic conditions. The eDNA technology has now been adopted by applied entomologists and ecologists to survey and monitor arthropod biodiversity through space and time. Several advancements have been made in detecting arthropod eDNA traces cryopreserved in plant tissues such as stems, branches, leaves, and flowers. Using the techniques developed thus far, we adopted, and slightly modified the method originally intended for aquatic studies to evaluate arthropod eDNA traces on flowers of flowering plants. Corroborating the method, we showed that eDNA traces washed off from floral parts revealed plethora of arthropod species. Furthermore, data sets generated from eDNA analysis may assist in improving the data gathered using conventional methods. • Conventional methods used in surveying arthropod fauna (especially indigenous natural enemies) on flowering plants can be a tedious exercise. Here, we adopted and optimized the method initially designed for aquatic environmental DNA analysis to supplement conventional methods in arthropod studies. • The optimized method showed that traces of arthropod eDNA materials on floral parts are detectable. • The eDNA technology can be used to generate qualitative data, especially data on the cryptic and unknown species of flowering plant-associated-natural enemies, that can supplement the quantitative data gathered from conventional methods.