High-Throughput DNA Barcoding Reveals Multi-Trophic Networks of Plants, Leafminers and Parasitoids in a Tropical Dry Forest.

Authors

Ariel H Muñoz-Sánchez, Gonzalo Contreras-Negrete, Alejandro Zaldívar-Riverón, Rafael Torres Colín, Evgeny V Zakharov, Carlos López-Vaamonde, Antonio Hernández-López

Published in

Molecular ecology resources. Volume 26. Issue 6. Pages e70183.

Abstract

Tropical dry forests host highly diverse insect communities and complex trophic interactions, yet these networks remain difficult to resolve using conventional molecular or rearing-based approaches. Here, we integrate long-read DNA barcoding, non-target sequence co-amplification, and host plant taxonomy to reconstruct tri-trophic interactions among leaf-mining insects, their host plants, and associated parasitoids in a Mexican tropical dry forest. Using Single Molecule, Real-Time (SMRT) sequencing on the PacBio Sequel IIe platform, we generated high-fidelity barcodes from individual leaf-miner larvae and from parasitoid larvae and pupae recovered from leaf mines. From 253 specimens, we obtained 214 sequences, and identified 83 operational taxonomic units including leaf-mining Lepidoptera, Diptera, Coleoptera, and their hymenopteran parasitoids, plus 31 non-target sequences. Of the 214 sequences, 69 were parasitoid wasps (32.2%). Of these, 40 were obtained from parasitoids dissected directly from leaf mines, while 29 were co-amplified from leaf-miner samples, demonstrating that SMRT-based co-amplification allows detection of parasitism without rearing. Our analysis revealed 156 trophic interaction types and 247 interaction events. Network analyses showed a highly modular tripartite network, with module structure primarily driven by host plant identity and a reduced set of influential leaf-miner and parasitoid taxa. Bipartite networks supported the hypothesis that interactions are more strongly compartmentalized between leafminers and host plants than at higher trophic levels. These results demonstrate that long-read DNA barcoding with co-amplification detection provides a scalable framework for reconstructing multi-trophic interactions from individual specimens, overcoming key limitations of rearing-based methods and enabling robust biodiversity and ecological network assessments in species-rich ecosystems.

PMID:
42644667
Bibliographic data and abstract were imported from PubMed on 26 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.