Alien pest molecular diagnostics: can DNA traces be exploited to assess the damage caused by the western conifer seed bug on stone pine fructification?

The exotic western conifer seed bug (WCSB) Leptoglossus occidentalis Heidemann is considered one of the most important pests of stone pine nut production in the Mediterranean region. However, aside from radiographic analysis, none of the diagnostic tools, already implemented in North America to assess the real impact of the WCSB on conifer seeds, have found application on the European stone pine yet. For the first time, specific DNA-based diagnostic protocols to detect WCSB DNA traces were developed in this study, in the effort of characterizing and monitoring WCSB damage on stone pine fructification in Europe. We designed two primer pairs targeting the WCSB DNA sequences for the mitochondrial gene coding for the subunit I of cytochrome c oxidase (COI), according to the data available on the main online databases. Specificity and sensitivity of these primers were assessed via End Point and Real Time PCR. As negative control, DNA from stone pine tissues was used as well as from five other insect species. The COI primer pair used in End Point PCR gave amplicons of the expected length only when WCSB DNA was used as template. Moreover, it successfully detected WCSB DNA into the insect liquid saliva, with a sensitivity as low as 100 fg/μl. However it failed to detect WCSB DNA when tested on WCSB-attacked seed samples. Conversely, the Real Time PCR protocol, still targeting the WCSB COI gene, was proved to be more sensitive (10 fg/μl) and also led to promising results when tested on attacked plant tissues. In fact, a distinctive melting temperature peak was found for all WCSB positive samples, including WCSB fed upon and feces contaminated seeds. The same primer pair was used for High Resolution Melting (HRM) analysis, which allowed the detection of intra-species single nucleotide polymorphisms (SNPs) in WCSB samples of different geographical origins, thus highlighting the potential of HRM analysis for insect genotyping.