Global efforts to monitor and contain the Covid-19 pandemic, caused by the beta-coronavirus SARS-CoV-2, currently rely on RT-qPCR-based diagnostic assays. Yet their high cost, moderate throughput, and dependence on sophisticated equipment limit a broad implementation. Loop-mediated isothermal amplification (RT-LAMP) is an alternative detection method that has the potential to overcome these limitations. Here, we established a robust, highly sensitive and versatile RT-LAMP-based SARS-CoV-2 detection assay that is insensitive to carry-over contaminations. Our approach uses a rapid upfront lysis step and hydroxy-naphthol-blue (HNB) for colorimetric detection, which enables the robust identification of Covid-19 infections from a variety of sample types within 30 minutes. By combining RT-LAMP with a simple nucleic acid enrichment method (bead-LAMP), we profoundly increased assay sensitivity to RT-qPCR-like levels, thereby extending applications to large-scale pooled testing. Finally, we developed HomeDip-LAMP for pipette-free SARS-CoV-2 detection for low-resource environments. Our combined optimizations set the stage for implementing RT-LAMP as SARS-CoV-2 diagnostics assay for population-wide and home-based testing.
RT-qPCR-based diagnostic tests play important roles in combating virus-caused pandemics such as Covid-19. However, their dependence on sophisticated equipment and the associated costs often limits their widespread use. Loop-mediated isothermal amplification after reverse transcription (RT-LAMP) is an alternative nucleic acid detection method that overcomes these limitations. Here, we present a rapid, robust, and sensitive RT-LAMP-based SARS-CoV-2 detection assay. Our 40-min procedure bypasses the RNA isolation step, is insensitive to carryover contamination, and uses a colorimetric readout that enables robust SARS-CoV-2 detection from various sample types. Based on this assay, we have increased sensitivity and scalability by adding a nucleic acid enrichment step (Bead-LAMP), developed a version for home testing (HomeDip-LAMP), and identified open-source RT-LAMP enzymes that can be produced in any molecular biology laboratory. On a dedicated website, rtlamp.org (DOI: 10.5281/zenodo.6033689), we provide detailed protocols and videos. Our optimized, general-purpose RT-LAMP assay is an important step toward population-scale SARS-CoV-2 testing.
The COVID-19 pandemic has demonstrated the need for massively-parallel, cost-effective tests monitoring viral spread. Here we present SARSeq, saliva analysis by RNA sequencing, a method to detect SARS-CoV-2 and other respiratory viruses on tens of thousands of samples in parallel. SARSeq relies on next generation sequencing of multiple amplicons generated in a multiplexed RT-PCR reaction. Two-dimensional, unique dual indexing, using four indices per sample, enables unambiguous and scalable assignment of reads to individual samples. We calibrate SARSeq on SARS-CoV-2 synthetic RNA, virions, and hundreds of human samples of various types. Robustness and sensitivity were virtually identical to quantitative RT-PCR. Double-blinded benchmarking to gold standard quantitative-RT-PCR performed by human diagnostics laboratories confirms this high sensitivity. SARSeq can be used to detect Influenza A and B viruses and human rhinovirus in parallel, and can be expanded for detection of other pathogens. Thus, SARSeq is ideally suited for differential diagnostic of infections during a pandemic.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.