Optimized protocol for direct extraction of SARS-CoV-2 RNA from raw wastewater samples (ANRS 0160)

This study aimed to evaluate whether a nucleic acid extraction protocol specifically designed for raw wastewater (WW) provides a measurable advantage over protocols not originally intended for WW matrices. Three laboratories have independently compared two RNA extraction protocols, using paired WW samples. A common WW-designed protocol (Z), based on silica columns was tested across all labs. As comparators, three non-WW designed protocols were used: NS1 and NS2 both silica beads-based, with NS2 including an additional phenol-chloroform step; and SB a homemade protocol using also silica beads but differing in its formulation. As different samples were used across labs, direct statistical comparison was difficult; instead, paired comparisons within each lab were used to rank SARS-CoV-2 RNA detection and RT-qPCR inhibitor removal. NS1 yielded significantly higher SARS-CoV-2 RNA concentrations than Z (Logrank test, <i>p</i> ≤ 0.001), though with RT-qPCR inhibition in one sample. NS2 also showed higher SARS-CoV-2 RNA detection than Z (Wilcoxon test, <i>p</i> < 0.0001), with both protocols showing complete inhibitor removal. SB performed worse than Z for SARS-CoV-2 RNA detection (Logrank test, <i>p</i> ≤ 0.05), and showed inhibition in one sample. NS2 was the most effective option for both RNA detection and inhibitor removal.

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Publication Details

Journal
MethodsX
Published
2025-04-18
DOI
https://doi.org/10.1016/j.mex.2025.103323
Citations
2
Primary Topic
SARS-CoV-2 detection and testing
Type
article
Field-Weighted Citation Impact
2.79

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article

Optimized protocol for direct extraction of SARS-CoV-2 RNA from raw wastewater samples (ANRS 0160)

Julie Loutreul, Florian Sandron, Isabelle Bertrand, Zuzana Gerber et al.
2 citations
MethodsX
SARS-CoV-2 detection and testing
2.79
article

Optimized protocol for direct extraction of SARS-CoV-2 RNA from raw wastewater samples (ANRS 0160)

Julie Loutreul, Florian Sandron, Isabelle Bertrand, Zuzana Gerber, Robert Olaso, Jean‐François Deleuze, Christophe Gantzer, Ahlam Chaqroun, Nicolas Boudaud, Nicolas Cluzel, Olivier Rohr, Damien Delafoy, Julie Challant, Clémentine Wallet, Ghina El Soufi, Léo Di Jorio, Stéphanie Raffestin, Vincent Maréchal
article en
2 citations

Abstract

This study aimed to evaluate whether a nucleic acid extraction protocol specifically designed for raw wastewater (WW) provides a measurable advantage over protocols not originally intended for WW matrices. Three laboratories have independently compared two RNA extraction protocols, using paired WW samples. A common WW-designed protocol (Z), based on silica columns was tested across all labs. As comparators, three non-WW designed protocols were used: NS1 and NS2 both silica beads-based, with NS2 including an additional phenol-chloroform step; and SB a homemade protocol using also silica beads but differing in its formulation. As different samples were used across labs, direct statistical comparison was difficult; instead, paired comparisons within each lab were used to rank SARS-CoV-2 RNA detection and RT-qPCR inhibitor removal. NS1 yielded significantly higher SARS-CoV-2 RNA concentrations than Z (Logrank test, <i>p</i> ≤ 0.001), though with RT-qPCR inhibition in one sample. NS2 also showed higher SARS-CoV-2 RNA detection than Z (Wilcoxon test, <i>p</i> < 0.0001), with both protocols showing complete inhibitor removal. SB performed worse than Z for SARS-CoV-2 RNA detection (Logrank test, <i>p</i> ≤ 0.05), and showed inhibition in one sample. NS2 was the most effective option for both RNA detection and inhibitor removal.

MethodsXVol. 14
Centre National de la Recherche Scientifique (FR), Inserm (FR), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Université Paris-Saclay (FR), Sorbonne Université (FR), Centre National de Recherche en Génomique Humaine (FR), Institut Pasteur de la Guyane (GF), CEA Paris-Saclay (FR), Centre de Recherche Saint-Antoine (FR), Laboratoire de Chimie Physique et Microbiologie pour les Matériaux et l'Environnement (FR), Actalia (France) (FR), Unité de Modélisation Mathématique et Informatique des Systèmes Complexes (FR), SUMMIT, Université de Strasbourg (FR), Université de Lorraine (FR)
Agence Nationale de la Recherche
Clean water and sanitation
Openalex Percentile: Top 11%
SARS-CoV-2 detection and testing
2.79
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