Diagnostic PCR assays to unravel food web interactions in cereal crops with focus on biological control of aphids

Abstract

Successful biological control of agricultural pests is dependent on a thorough understanding of the underlying trophic interactions between predators and prey. Studying trophic interactions can be challenging, particularly when generalist predators that frequently use multiple prey and interact with both pest and alternative prey are considered. In this context, diagnostic PCR proved to be a suitable approach, however at present, prey-specific PCR primers necessary for assessing such interactions across trophic levels are missing. Here we present a new set of 45 primers designed to target a wide range of invertebrate taxa common to temperate cereal crops: cereal aphids, their natural enemies such as carabid beetles, ladybeetles, lacewings, and spiders, and potential alternative prey groups (earthworms, springtails, and dipterans). These primers were combined in three ‘ready to use’ multiplex PCR assays for quick and cost-effective analyses of large numbers of predator samples. The assays were tested on 560 carabids collected in barley fields in Sweden. Results from this screening suggest that aphids constitute a major food source for carabids in cereal crops (overall DNA detection rate: 51 %), whereas alternative extraguild and intraguild prey appear to be less frequently preyed upon when aphids are present (11 % for springtails and 12 % for earthworms; 1 % for spiders and 4 % for carabids). In summary, the newly developed molecular assays proved reliable and effective in assessing previously cryptic predator–prey trophic interactions, specifically with focus on biological control of aphids. The diagnostic PCR assays will be applicable manifold as the targeted invertebrates are common to many agricultural systems of the temperate region.Electronic supplementary materialThe online version of this article (doi:10.1007/s10340-015-0685-8) contains supplementary material, which is available to authorized users.

Habitat heterogeneity induces rapid changes in the feeding behaviour of generalist arthropod predators

“…In addition, spiders testing positive for “beetle” prey in the group‐specific “MPI” were further tested with “MPII beetles/thrips” to identify these prey types to a lower taxonomic level. Likewise, beetles testing positive for “spider” prey were tested with “MPII spiders.” Note that of 29 beetles testing positive for “spider” prey, 25 could not be assigned to a specific spider taxon in the “MPII spiders,” suggesting that feeding interactions occurred with spider taxa other than the targeted genera (for details on coverage, see Staudacher et al., ). To resolve this issue, these samples were additionally subjected to DNA barcoding and 15 samples could then be assigned, mostly to Linyphiidae and Lycosidae (see Appendix S2: Protocol S2‐2).…”

“…All PCR products were separated and visualized using the QIAxcel electrophoresis system (Qiagen, Hilden, Germany) following the protocol described in Staudacher et al. ().…”

Diet of generalist predators reflects effects of cropping period and farming system on extra‐ and intraguild prey

“…The screening was conducted as per the recommendations for molecular diagnostic work; DNA extraction process and assay sensitivity were highly standardized, and PCRs largely followed the protocols presented in Staudacher et al. () with some modifications (for details, see Appendix ). The standardization of the assay sensitivity (i.e., the number of copies of DNA fragments amplifiable by each of the primer pairs employed in the assays) improves the comparability of the detectability of all prey in all predators (Sint et al.…”

Evaluation of an automated protocol for efficient and reliable DNA extraction of dietary samples

“…Moreover, apart from screening high numbers of consumers simultaneously, analyzing concomitant predation on multiple prey species is possible by either using diagnostic multiplex PCR (King, Read, Traugott, & Symondson, ) or next‐generation sequencing (NGS)‐based approaches (Pompanon et al., ). Taken together, molecular identification of trophic interactions has shed light into complex food webs (Davey et al., ; Eitzinger, Micic, Körner, Traugott, & Scheu, ; Hrček, Miller, Quicke, & Smith, ; Joly et al., ; Staudacher, Jonsson, & Traugott, ). Examining these feeding networks with molecular methods usually entails processing large numbers of samples: Raso et al.…”