High‐resolution DNA melt‐curve analysis for cost‐effective mass screening of pairwise species interactions. (23rd July 2013)

• Record Type: Journal Article
• Authors: McCarthy, James K.; Didham, Raphael K.; Brockerhoff, Eckehard G.; van Bysterveldt, Katherine A.; Varsani, Arvind
• Is Part Of: Molecular ecology resources. Volume 13:Number 5(2013:Sep.)
• Page Start: 908
• Page End: 917
• Publication Date: 2013-07-23
• Subjects: bark beetle -- HRM -- insect vectoring -- interaction network -- rapid species identification -- sapstain fungi; Molecular ecology -- Periodicals; 572.8
• DOI: 10.1111/1755-0998.12143
• Languages: English
• ISSNs: 1755-098X

Abstract

Abstract: Ecological studies of pairwise interactions are constrained by the methods available for rapid species identification of the interacting organisms. The resolution of data required to characterize species interaction networks at multiple spatio‐temporal scales can be intensive, and therefore laborious and costly to collect. We explore the utility of high‐resolution DNA melt‐curve analysis (HRM) as a rapid species identification method. An approach was developed to identify organisms at the pairwise interaction level, with particular application to cryptic species interactions that are traditionally difficult to study. Here, we selected a challenging application; to identify the presence/absence of pathogenic fungi ( Sporothrix inflata, Ophiostoma nigrocarpum and Ophiostoma galeiforme ) transported by bark beetle vectors ( Hylastes ater and Hylurgus ligniperda ). The technique was able to distinguish between different species of DNA within a single, pooled sample. In test applications, HRM was effective in the mass screening and identification of pathogenic fungal species carried by many individual bark beetle vectors ( n = 455 beetles screened) across large geographic scales. For two of the fungal species, there was no difference in the frequency of association with either of their vectors, but for the third fungal species there was a shift in vector–pathogen associations across locations. This technique allows rapid, mass screening and characterization of species interactions at a fraction of the time and cost of traditional methods. It is anticipated that this method can be readily applied to explore other cryptic species interactions, or other studies requiring rapid generation of large data sets and/or high‐throughput efficiency.