SLIDE: Saliva-Based SARS-CoV-2 Self-Testing with RT-LAMP in a Mobile Device

Zifan Tang, Jiarui Cui, Aneesh Kshirsagar, Tianyi Liu, Michele Yon, Suresh V. Kuchipudi, Weihua Guan

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Regular, accurate, rapid, and inexpensive self-testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is urgently needed to quell pandemic propagation. The existing at-home nucleic acid testing (NAT) test has high sensitivity and specificity, but it requires users to mail the sample to the central lab, which often takes 3-5 days to obtain the results. On the other hand, rapid antigen tests for the SARS-CoV-2 antigen provide a fast sample to answer the test (15 min). However, the sensitivity of antigen tests is 30 to 40% lower than nucleic acid testing, which could miss a significant portion of infected patients. Here, we developed a fully integrated SARS-CoV-2 reverse transcription loop-mediated isothermal amplification (RT-LAMP) device using a self-collected saliva sample. This platform can automatically handle the complexity and can perform the functions, including (1) virus particles' thermal lysis preparation, (2) sample dispensing, (3) target sequence RT-LAMP amplification, (4) real-time detection, and (5) result report and communication. With a turnaround time of less than 45 min, our device achieved the limit of detection (LoD) of 5 copies/μL of the saliva sample, which is comparable with the LoD (6 copies/μL) using FDA-approved quantitative real-time polymerase chain reaction (qRT-PCR) assays with the same heat-lysis saliva sample preparation method. With clinical samples, our platform showed a good agreement with the results from the gold-standard RT-PCR method. These results show that our platform can perform self-administrated SARS-CoV-2 nucleic acid testing by laypersons with noninvasive saliva samples. We believe that our self-testing platform will have an ongoing benefit for COVID-19 control and fighting future pandemics.

Original languageEnglish (US)
Pages (from-to)2370-2378
Number of pages9
JournalACS Sensors
Volume7
Issue number8
DOIs
StatePublished - Aug 26 2022

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Instrumentation
  • Process Chemistry and Technology
  • Fluid Flow and Transfer Processes

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