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1.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.06.28.21259398

ABSTRACT

Previous studies have described RT-LAMP methodology for the rapid detection of SARS-CoV-2 in nasopharyngeal/oropharyngeal swab and saliva samples. Here we describe the validation of an improved simple sample preparation method for Direct SARS-CoV-2 RT-LAMP, removing the need for RNA extraction, using 559 swabs and 86,760 saliva samples from asymptomatic and symptomatic individuals across multiple healthcare settings. Using this improved method we report a diagnostic sensitivity (DSe) of 70.35% (95% CI 63.48-76.60%) on swabs and 84.62% (79.50-88.88%) on saliva, with diagnostic specificity (DSp) 100% (98.98-100.00%) on swabs and 100% (99.72-100.00%) on saliva when compared to RT-qPCR. Analysing samples with RT-qPCR ORF1ab CT values of <25 and <33 (high and medium-high viral loads, respectively), we found DSe of 100% (96.34-100%) and 77.78% (70.99-83.62%) for swabs, and 99.01% (94.61-99.97%) and 87.32% (80.71-92.31%) for saliva. We also describe RNA RT-LAMP (on extracted RNA) performed on 12,619 swabs and 12,521 saliva samples to provide updated performance data with DSe and DSp of 95.98% (92.74-98.06%) and 99.99% (99.95-100%) for swabs, and 80.65% (73.54-86.54%) and 99.99% (99.95-100%) for saliva, respectively. We also report on daily samples collected from one individual from symptom onset where both Direct and RNA RT-LAMP detected SARS-CoV-2 in saliva collected on all six days where symptoms were recorded, with RNA RT-LAMP detecting SARS-CoV-2 for an additional further day. The findings from these studies demonstrate that RT-LAMP testing of swabs and saliva is potentially applicable to a variety of use-cases, including frequent, interval-based testing of saliva from asymptomatic individuals via Direct RT-LAMP that may be missed using symptomatic testing alone.

2.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.07.16.20155168

ABSTRACT

We describe the optimization of a simplified sample preparation method which permits rapid and direct detection of SARS-CoV-2 RNA within saliva using reverse-transcription loop-mediated isothermal amplification (RT-LAMP). Treatment of saliva samples prior to RT-LAMP by dilution 1:1 in MucolyseTM, followed by dilution (within the range of 1 in 5 to 1 in 40) in 10% (w/v) Chelex 100 Resin and a 98oC heat step for 2 minutes enabled detection of SARS-CoV-2 RNA in all positive saliva samples tested, with no amplification detected in pooled negative saliva. The time to positivity for which SARS-CoV-2 RNA was detected in these positive saliva samples was proportional to the real-time reverse-transcriptase PCR cycle threshold (CT), with SARS-CoV-2 RNA detected in as little as 05:43 (CT 21.08), 07:59 (CT 24.47) and 08:35 (CT 25.27) minutes, respectively. The highest CT where direct RT-LAMP detected SARS-CoV-2 RNA was 31.39 corresponding to a 1 in 40 dilution of a positive saliva sample (1:1 in MucolyseTM) with a starting CT of 25.27. When RT-LAMP was performed on pools of SARS-CoV-2 negative saliva samples spiked with whole inactivated SARS-CoV-2 virus, RNA was detected at dilutions spanning 1 in 5 to 1 in 160 representing CTs spanning 22.49-26.43. Here we describe a simple but critical rapid sample preparation method which can be used up front of RT-LAMP to permit direct detection of SARS-CoV-2 within saliva samples. Saliva is a sample which can be collected non-invasively without the use of highly skilled staff and critically can be obtained from both healthcare and home settings. Critically, this approach overcomes both the requirement and validation of different swabs and the global bottleneck in obtaining RNA extraction robots and reagents to enable molecular testing by PCR. Such testing opens the possibility of public health approaches for effective intervention to control the COVID-19 pandemic through regular SARS-CoV-2 testing at a population scale, combined with isolation and contact tracing for positive cases.


Subject(s)
COVID-19 , Severe Acute Respiratory Syndrome
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