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Preliminary optimisation of a simplified sample preparation method to permit direct detection of SARS-CoV-2 within saliva samples using reverse-transcription loop-mediated isothermal amplification (RT-LAMP)
Emma Howson; Stephen Kidd; Jason Sawyer; Claire Cassar; David Cross; Tom Lewis; Jessica Hockey; Samantha Rivers; Saira Cawthraw; Ashley Banyard; Paul Anderson; Sabah Rahou; Michael Andreou; Nick Morant; Duncan Clarke; Charlotte Walsh; Shailen Laxman; Rebecca Houghton; Joanne Slater-Jefferies; Paula Costello; Ian Brown; Nick Cortes; Keith Godfrey; Veronica FOWLER.
Afiliação
  • Emma Howson; GeneSys Biotech Limited
  • Stephen Kidd; Hampshire Hospitals NHS Foundation Trust
  • Jason Sawyer; Animal and Plant Health Agency
  • Claire Cassar; Animal and Plant Health Agency
  • David Cross; Animal and Plant Health Agency
  • Tom Lewis; Animal and Plant Health Agency
  • Jessica Hockey; Animal and Plant Health Agency
  • Samantha Rivers; Animal and Plant Health Agency
  • Saira Cawthraw; Animal and Plant Health Agency
  • Ashley Banyard; Animal and Plant Health Agency
  • Paul Anderson; Animal and Plant Health Agency
  • Sabah Rahou; Animal and Plant Health Agency
  • Michael Andreou; OptiSense Limited
  • Nick Morant; GeneSys Biotech Limited
  • Duncan Clarke; GeneSys Biotech Limited
  • Charlotte Walsh; GeneSys Biotech Limited
  • Shailen Laxman; OptiSense Limited
  • Rebecca Houghton; Hampshire Hospitals NHS Foundation Trust
  • Joanne Slater-Jefferies; National Biofilms Innovation Centre
  • Paula Costello; MRC Lifecourse Epidemiology Unit
  • Ian Brown; Animal and Plant Health Agency
  • Nick Cortes; Hampshire Hospitals NHS Foundation Trust
  • Keith Godfrey; MRC Lifecourse Epidemiology Unit
  • Veronica FOWLER; Eco Animal Health
Preprint em En | PREPRINT-MEDRXIV | ID: ppmedrxiv-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 11 in Mucolyse, followed by dilution (within the range of 15 to 140) in 10% (w/v) Chelex(C) 100 Resin and a 98{degrees}C 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 0543 (CT 21.08), 0759 (CT 24.47) and 0835 (CT 25.27) minutes, respectively. The highest CT where direct RT-LAMP detected SARS-CoV-2 RNA was 31.39 corresponding to a 140 dilution of a positive saliva sample 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 15 to 1160 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 health care and home settings. Critically, this approach overcomes both the requirement and validation of different swabs and the global bottleneck observed 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.
Licença
cc_by_nd
Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-MEDRXIV Tipo de estudo: Observational_studies / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-MEDRXIV Tipo de estudo: Observational_studies / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Preprint