In this study, we applied a widely used insect surveillance metabarcoding workflow, modified through development and implementation of aphid-specific primers, to enhance targeted detection of aphid prey consumed by ladybeetles. We evaluated performance of this prey-targeted metabarcoding approach for dietary analysis and quantified aphid DNA detectability under controlled feeding and starvation regimes. We hypothesised that aphid DNA could be reliably recovered from whole ladybeetle samples using standard surveillance metabarcoding protocols, enabling detection of prey taxa present exclusively as gut contents, which may impact surveillance and diagnostics programs.

Aphid DNA from multiple species was detected up to seventy-two hours post-ingestion and up to one hundred hours following cessation of ad libitum feeding, although detectability varied among aphid species and pre-feeding starvation treatments. These results demonstrate that prey-targeted metabarcoding increases sensitivity for dietary inference in predatory insects and provides a robust framework for detecting cryptic trophic interactions. Our findings further indicate that unintended prey detection may be common in arthropod metabarcoding datasets, with important implications for interpretation in biosurveillance and biosecurity monitoring.

The design of the feeding experiments reflects a deliberate attempt to mimic conditions that ladybeetles encounter in real cropping systems. In the short starvation experiment, adult spotted amber ladybeetles were first allowed to gorge on corn leaf aphids for nine days, simulating a period of high pest abundance in the field, before being starved for seventeen hours and then offered a small number of aphids from a different species. This structure allowed the researchers to distinguish DNA from a recent, quantifiable feeding event from DNA already circulating in the gut from earlier meals. Because the corn leaf aphid was the colony species used for pre-feeding, the alternative prey species chosen for the experimental meal, namely Russian wheat aphids and sow thistle aphids, could be tracked independently through the metabarcoding results. Each ladybeetle was given one and a half hours to feed on five aphids, a window chosen to represent a realistic foraging bout, and the number of aphids consumed was recorded so that detectability could be interpreted in light of actual prey intake.

Sampling at zero, one, two, four, and seventy-two hours after feeding provided a coarse but informative decay curve for aphid DNA inside the predators. The gap between the four-hour and seventy-two-hour timepoints was a logistical compromise, and it means that the precise shape of the detectability decline during that interval remains unresolved. Nevertheless, the recovery of aphid DNA at the seventy-two-hour mark is notable, because it demonstrates that gut contents can remain molecularly detectable for days after a feeding event, long after any physical prey remains would have been processed. For surveillance programs that bulk-collect arthropods into ethanol and sequence them later, this persistence means that a predator caught in a trap may carry molecular evidence of meals consumed well before capture, effectively extending the temporal window of dietary inference far beyond what visual gut dissection could achieve.

The long starvation experiment extended this logic by removing the pre-feeding period altogether. Ladybeetles were starved for ninety-six hours before being offered either corn leaf aphids or cabbage aphids, and sampling continued at zero, one, two, four, twenty-four, forty-eight, and ninety-six hours after feeding. This denser sampling regime captured the early hours of digestion in much finer detail, and the comparison between the two experiments revealed that pre-feeding starvation history materially alters detectability. A hungry predator that has not fed for days may process prey differently than one that has recently gorged, and the resulting differences in DNA decay rates have direct consequences for how field-collected predators should be interpreted. A detection of pest DNA in a beetle starved for several days may indicate a more recent meal than the same detection in a well-fed beetle, complicating any attempt to timestamp predation events from molecular data alone.

Species-level variation in detectability emerged as a consistent theme across both experiments. Aphid DNA from different prey species did not decay at identical rates, which means that the absence of a particular aphid species from a metabarcoding result cannot be taken as evidence that the predator never consumed it. Some prey may simply become undetectable sooner than others, whether because of differences in body size, cuticle thickness, gut chemistry, or the copy number of the target genetic region within the prey genome. This species-specific bias is a well-recognised challenge in dietary metabarcoding generally, but the present study quantifies it in a controlled setting for aphids specifically, providing empirical grounding for interpreting detections and non-detections in agricultural surveillance datasets.

The choice of the spotted amber ladybeetle as the primary predator reflects its status as a known and commercially available biocontrol agent in Australian grain ecosystems. Eggs and adults can be sourced commercially, which makes this species a practical candidate for release programs and, by extension, a logical focal species for post-release monitoring. The inclusion of the large spotted ladybeetle, collected from garden plants near the research campus, added a comparative dimension, allowing the researchers to ask whether detectability patterns generalise across coccinellid species or whether they are idiosyncratic to particular predator-prey pairings. Frass from both adult and larval spotted amber ladybeetles was also sampled, opening the possibility that non-invasive sampling of predator droppings could substitute for, or complement, the destruction of whole specimens during DNA extraction.

The prey assemblage used in the experiments spans a meaningful slice of aphid diversity relevant to Australian grains. Corn leaf aphids and Russian wheat aphids were drawn from laboratory colonies maintained on caged barley plants under controlled temperature and light conditions, ensuring a consistent prey quality and genetic background. Bird cherry-oat aphids, another economically significant grain pest, were also colony-reared. In contrast, cabbage aphids and sow thistle aphids were collected from field mustard and sow thistle plants on the university campus only an hour before the feeding trials began, introducing wild-caught prey with their own microbiomes and genetic variation. California maple aphids, collected from a Japanese maple in a regional botanic garden, served as an additional positive control, broadening the taxonomic coverage of the primer validation. Wild psyllids collected from an Acacia tree on the same campus provided a non-target feeder insect, allowing the researchers to test whether the aphid-specific primers would inadvertently amplify DNA from related hemipterans that a ladybeetle might encounter in the field.

The broader significance of this work lies in what it reveals about the interpretation of existing metabarcoding datasets. Insect surveillance programs that use universal primers on bulk trap samples routinely generate taxonomic lists that may include species for which no physical specimen can be found during visual examination of the sample. Previous work comparing metabarcoding results with morphological identification of trapped arthropods has documented such incongruencies, and the present study offers a plausible mechanistic explanation: at least some of these phantom detections may represent prey DNA inside the guts of predators that were themselves caught in the trap. A ladybeetle full of aphid DNA contributes aphid reads to a bulk sample even though no aphid specimen is physically present, and this can inflate apparent aphid diversity or abundance in a way that misrepresents the actual community composition at the collection site.

For biosecurity monitoring, this distinction matters considerably. If a pest species is detected molecularly in a trap sample, the response may differ depending on whether that detection reflects a living population at the site or merely the gut contents of a predator that fed elsewhere and flew in. The detectability windows quantified here, extending to seventy-two hours after a discrete feeding event and up to one hundred hours after the cessation of sustained feeding, provide a temporal framework for reasoning about this problem. A predator carrying detectable pest DNA consumed that pest within roughly the last few days, which constrains but does not eliminate the geographic uncertainty associated with the detection. Combined with knowledge of predator dispersal distances and local pest phenology, such temporal bounds could help biosecurity officers triage molecular detections and decide which warrant follow-up physical inspection.

For biological control practitioners, the ability to confirm consumption of target pests by released agents addresses a persistent gap in post-release evaluation. Traditional approaches to measuring biocontrol efficacy rely on cage trials, sentinel prey, or population counts before and after release, all of which are labour-intensive and subject to confounding by predator movement and prey dynamics. Molecular dietary analysis offers a complementary line of evidence: if released ladybeetles can be recaptured and shown, through metabarcoding of their gut contents, to have consumed the target aphid species, this provides direct confirmation that the biocontrol agent is engaging with the pest under field conditions. The aphid-specific primers developed in this study increase the sensitivity of such confirmations, particularly for prey that are rare in the diet or consumed in small numbers.

The methodological workflow itself, adapted from a widely adopted Australian insect surveillance metabarcoding protocol, is significant because it demonstrates that existing infrastructure can be repurposed for dietary analysis with relatively modest modification. Rather than requiring a wholly new analytical pipeline, the addition of taxon-specific primers to an established surveillance workflow allows the same laboratory processes that identify community composition to simultaneously probe trophic interactions. This dual capability means that a single sequencing run on a bulk trap sample can yield both a census of the arthropods present and, for predatory specimens within that sample, evidence of what they have been eating. As metabarcoding becomes further embedded in routine agricultural diagnostics, such multiplexed utility increases the value derived from each sample processed.

Finally, the controlled experimental framework established here, with defined feeding events, quantified prey numbers, staged starvation periods, and time-series sampling, provides a template that can be extended to other predator-prey systems. Detectability periods are known to vary with both predator and prey identity, and the factors governing that variation, including prey abundance, predator metabolic rate, and the interplay between feeding rate and starvation history, remain only partially characterised. By quantifying detectability under controlled conditions for a biocontrol-relevant predator and a suite of grain pest aphids, this study contributes empirical parameters that can inform the design of future field studies and the interpretation of molecular surveillance data across agricultural landscapes.

Subject of Research: Metabarcoding and Metagenomics

Article Title: A feast of aphids: assessing the detectability of prey aphid DNA inside ladybeetle predators using taxon-specific metabarcoding

Article References: Willmott, N. J., Scanlan, J. L., Blacket, M. J., Rodoni, B. C., Nancarrow, N., Jones, T. M., & Martoni, F. (2026). A feast of aphids: assessing the detectability of prey aphid DNA inside ladybeetle predators using taxon-specific metabarcoding. Metabarcoding and Metagenomics, 10, Article e196568. https://doi.org/10.3897/mbmg.10.196568

Image Credits: AI Generated

DOI: 10.3897/mbmg.10.196568

Keywords: metabarcoding, ladybeetles, aphids, biological control, integrated pest management, feast, assessing, detectability, prey, aphid, inside, ladybeetle