A rapid RNA extraction-free lateral flow assay for molecular point-of-care detection of SARS-CoV-2 augmented by chemical probes

Ketan Dighe, Parikshit Moitra, Maha Alafeef, Nivetha Gunaseelan, Dipanjan Pan

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the major shortcoming of healthcare systems globally in their inability to diagnose the disease rapidly and accurately. At present, the molecular approaches for diagnosing COVID-19 primarily use reverse transcriptase polymerase chain reaction (RT-PCR) to create and amplify cDNA from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA. Although molecular tests are reported to be specific, false negatives are quite common. Furthermore, literally all these tests require a step involving RNA isolation which does not make them point-of-care (POC) in the true sense. Here, we report a lateral flow strip-based RNA extraction and amplification-free nucleic acid test (NAT) for rapid diagnosis of positive COVID-19 cases at POC. The assay uses highly specific 6-carboxyfluorescein (6-FAM) and biotin labeled antisense oligonucleotides (ASOs) as probes those are designed to target N-gene sequence of SARS-CoV-2. Additionally, we utilized cysteamine capped gold-nanoparticles (Cyst-AuNPs) to augment the signal further for enhanced sensitivity. Without any large-stationary equipment and highly trained staffers, the entire sample-to-answer approach in our case would take less than 30 min from a patient swab sample collection to final diagnostic result. Moreover, when evaluated with 60 clinical samples and verified with an FDA-approved TaqPath RT-PCR kit for COVID-19 diagnosis, the assay obtained almost 99.99% accuracy and specificity. We anticipate that the newly established low-cost amplification-free detection of SARS-CoV-2 RNA will aid in the development of a platform technology for rapid and POC diagnosis of COVID-19 and other pathogens.

Original languageEnglish (US)
Article number113900
JournalBiosensors and Bioelectronics
Volume200
DOIs
StatePublished - Mar 15 2022

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biophysics
  • Biomedical Engineering
  • Electrochemistry

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