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  2. Real-time malaria detection in the Amazon rainforest via drone-collected eDNA and portable qPCR

Real-time malaria detection in the Amazon rainforest via drone-collected eDNA and portable qPCR Artículos académico

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Perfil

Autor

  • Andrea Desiderato
  • Christian Geckeler
  • Claus Melvad
  • Elvira Mächler
  • Florencia Sangermano
  • Frederik Bendix Thostrup
  • Guglielmo Murari
  • Jia Jin Marc Chang
  • Kristy Deiner
  • Luca Montemartini
  • Mailyn Adriana Gonzalez Herrera
  • Marina Mura
  • Martina Lüthi
  • Meret Jucker
  • Michele Gregorini
  • Nicolás D. Franco-Sierra
  • Stefano Mintchev
  • Steffen Kirchgeorg
  • Tobias Schindler
  • Yin Cheong Aden Ip

Resumen

  • Zoonotic malaria risk at human-wildlife-environment interfaces requires surveillance that integrates signals from reservoirs, vectors and the environment. We coupled a drone-based environmental DNA (eDNA) canopy swabbing approach with portable quantitative PCR (qPCR) to detect Plasmodium DNA in situ during a 24-h field exercise in the Amazon rainforest. Drone-lowered sterile swabs into the canopy, which were then extracted and subjected to a multiplex pan-Plasmodium assay targeting five human-infecting Plasmodium species (limit of detection 0.2 parasites μL −1 ). Of 12 samples (10 canopy swabs, 2 field blanks; 13 total runs including repeats), one canopy swab amplified in duplicate (Ct = 28.7 and 29.23), while positive controls amplified as expected (Ct = 30.82 and 31.11) and all other environmental samples and blanks were negative. Passive acoustics confirmed co-occurring howler monkeys (Alouatta spp.), a known reservoir, whereas Anopheles mosquitoes were not recovered from concurrently deployed insect canopy traps. The end-to-end workflow, from drone deployment to qPCR diagnostic readout, averaged 1.5 h per assay, without requiring cold-chain logistics. This proof-of-concept demonstrates that intracellular parasite DNA can be recovered from canopy surfaces and read out in real-time, providing upstream, landscape-level intelligence to guide targeted vector surveillance in remote settings. Our approach operationalizes One Health by integrating environmental, wildlife, and vector signals within a single technological platform, representing a paradigm shift from reactive, sector-specific surveillance to proactive, integrated pathogen intelligence across the human-animal-environment interface.

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autores

  • http://vivoweb.org/ontology/core#FacultyMember
    Paola Pulido Santacruz

Edición

  • 21

fecha de publicación

  • 2025-12-1

Identidad

Identificador de objeto digital (DOI)

  • https://doi.org/10.1016/j.onehlt.2025.101167