RT qLAMP—Direct Detection of SARS-CoV-2 in Raw Sewage

Publication Name

Journal of Biomolecular Techniques

Abstract

A highly efficient, selective, and sensitive method for analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in raw sewage was developed and tested to illustrate basic characteristics of the procedure. The method uses reverse transcriptase (RT) loop mediated isothermal amplification (LAMP) in a quantitative application, RT qLAMP. The applicability of this procedure to detection of SARS-CoV-2 in clinical samples has been documented in many reports since early 2020. Basic LAMP characteristics depending on the multiple primer design that produce highly selective and sensitive target amplification virtually free of interferences in complex sample media make it ideal for application to target recognition in raw sewage. Three previously described primer sets targeting ORF1a, E-and N-gene regions were selected and tested to define method performance characteristics and performance for SARS-CoV-2 detection in raw sewage samples from a municipal sewage system serving > 600 000, between July and October, 2020. The virus was detected in all samples from each of three independent interceptors near their treatment terminus. Virus quantities varied significantly between samples and between primer targets within samples. Sewage sampling dates corresponded to relatively low COVID-19 incidence rates reported by the local service area health department. The limited number of samples and aggregating downstream sampling locations did not permit resolving concentration differences. The most significant finding was the ability of the RT qLAMP method to detect SARS-CoV-2 in the raw sewage samples directly without preprocessing to isolate or concentrate the virus or to extract and concentrate viral RNA.

Open Access Status

This publication may be available as open access

Volume

32

Issue

3

First Page

206

Last Page

213

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Link to publisher version (DOI)

http://dx.doi.org/10.7171/jbt.21-32-03-016