Frontiers in Bioengineering and Biotechnology (Sep 2022)

Quantitative detection of dengue serotypes using a smartphone-connected handheld lab-on-chip platform

  • Nicolas Moser,
  • Ling-Shan Yu,
  • Jesus Rodriguez Manzano,
  • Jesus Rodriguez Manzano,
  • Kenny Malpartida-Cardenas,
  • Anselm Au,
  • Paul Arkell,
  • Chiara Cicatiello,
  • Ahmad Moniri,
  • Luca Miglietta,
  • Luca Miglietta,
  • Wen-Hung Wang,
  • Wen-Hung Wang,
  • Wen-Hung Wang,
  • Sheng Fan Wang,
  • Sheng Fan Wang,
  • Alison Holmes,
  • Alison Holmes,
  • Yen-Hsu Chen,
  • Yen-Hsu Chen,
  • Yen-Hsu Chen,
  • Pantelis Georgiou

DOI
https://doi.org/10.3389/fbioe.2022.892853
Journal volume & issue
Vol. 10

Abstract

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Dengue is one of the most prevalent infectious diseases in the world. Rapid, accurate and scalable diagnostics are key to patient management and epidemiological surveillance of the dengue virus (DENV), however current technologies do not match required clinical sensitivity and specificity or rely on large laboratory equipment. In this work, we report the translation of our smartphone-connected handheld Lab-on-Chip (LoC) platform for the quantitative detection of two dengue serotypes. At its core, the approach relies on the combination of Complementary Metal-Oxide-Semiconductor (CMOS) microchip technology to integrate an array of 78 × 56 potentiometric sensors, and a label-free reverse-transcriptase loop mediated isothermal amplification (RT-LAMP) assay. The platform communicates to a smartphone app which synchronises results in real time with a secure cloud server hosted by Amazon Web Services (AWS) for epidemiological surveillance. The assay on our LoC platform (RT-eLAMP) was shown to match performance on a gold-standard fluorescence-based real-time instrument (RT-qLAMP) with synthetic DENV-1 and DENV-2 RNA and extracted RNA from 9 DENV-2 clinical isolates, achieving quantitative detection in under 15 min. To validate the portability of the platform and the geo-tagging capabilities, we led our study in the laboratories at Imperial College London, UK, and Kaohsiung Medical Hospital, Taiwan. This approach carries high potential for application in low resource settings at the point of care (PoC).

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