Issue 9, 2022

Portable sample processing for molecular assays: application to Zika virus diagnostics

Abstract

This paper introduces a digital microfluidic (DMF) platform for portable, automated, and integrated Zika viral RNA extraction and amplification. The platform features reconfigurable DMF cartridges offering a closed, humidified environment for sample processing at elevated temperatures, as well as programmable control instrumentation with a novel thermal cycling unit regulated using a proportional integral derivative (PID) feedback loop. The system operates on 12 V DC power, which can be supplied by rechargeable battery packs for remote testing. The DMF system was optimized for an RNA processing pipeline consisting of the following steps: 1) magnetic-bead based RNA extraction from lysed plasma samples, 2) RNA clean-up, and 3) integrated, isothermal amplification of Zika RNA. The DMF pipeline was coupled to a paper-based, colorimetric cell-free protein expression assay for amplified Zika RNA mediated by toehold switch-based sensors. Blinded laboratory evaluation of Zika RNA spiked in human plasma yielded a sensitivity and specificity of 100% and 75% respectively. The platform was then transported to Recife, Brazil for evaluation with infectious Zika viruses, which were detected at the 100 PFU mL−1 level from a 5 μL sample (equivalent to an RT-qPCR cycle threshold value of 32.0), demonstrating its potential as a sample processing platform for miniaturized diagnostic testing.

Graphical abstract: Portable sample processing for molecular assays: application to Zika virus diagnostics

Supplementary files

Article information

Article type
Paper
Submitted
26 Nov. 2021
Accepted
18 Marts 2022
First published
31 Marts 2022

Lab Chip, 2022,22, 1748-1763

Portable sample processing for molecular assays: application to Zika virus diagnostics

T. Narahari, J. Dahmer, A. Sklavounos, T. Kim, M. Satkauskas, I. Clotea, M. Ho, J. Lamanna, C. Dixon, D. G. Rackus, S. J. R. D. Silva, L. Pena, K. Pardee and A. R. Wheeler, Lab Chip, 2022, 22, 1748 DOI: 10.1039/D1LC01068A

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