Article
Assessment of virus concentration methods for detecting SARS‑CoV‑2 IN wastewater
Registro en:
RIBEIRO, André V. C. et al. Assessment of virus concentration methods for detecting SARS‑CoV‑2 IN wastewater. Brazilian Journal of Microbiology, p. 1 - 9, Mar. 2023.
1678-4405
10.1007/s42770-023-00941-3
Autor
Ribeiro, André V.
Mannarino, Camille F.
Castro, Eduardo S. G. de
Prado, Tatiana
Ferreira, Fernando C.
Fumian, Tulio M.
Miagostovich, Marize P.
Resumen
Abstract
Wastewater-based epidemiology has been described as a valuable tool for monitoring the spread of severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) in a community. However, there is no consensus on the best concentration
method to allow reliable detection of SARS-CoV-2 in this matrix, considering different laboratory facilities. This study
compares two viral concentration methods, ultracentrifugation (ULT) and skimmed-milk flocculation (SMF), for detecting
SARS-CoV-2 in wastewater samples. The analytical sensitivity (limits of detection and quantification [LoD/LoQ]) of both
methods was evaluated using a bovine respiratory syncytial virus (BRSV) as a surrogate. Three different approaches were
conducted to establish LoD of each method based on the assays on the standard curve (ALoDsc), on the dilution of internal
control (ALoDiC), and the processing steps (PLoD). For PLoD, ULT method had the lowest value (1.86 × 103
genome copy/
microliter [GC/μL]) when compared to the SMF method (1.26 × 107
GC/μL). The LoQ determination showed a mean value
of 1.55 × 105
GC/μL and 3.56 × 108
GC/μL to ULT and SMF, respectively. The detection of SARSCoV-2 in naturally contaminated
wastewater revealed 100% (12/12) and 25% (3/12) of detection using ULT and SMF with quantification ranging
from 5.2 to 7.2 log10 genome copy/liter (GC/L) and 5.06 to 5.46 log10 GC/L, respectively. The detection success rate of
BRSV used as an internal control process was 100% (12/12) for ULT and 67% (8/12) for SMF, with an efficiency recovery
rate ranging from 12 to 38% and 0.1 to 5%, respectively. Our data consolidates the importance of assessing the methods
used; however, further analysis should be carried out to improve low-cost concentration methodologies, essential for use in
low-income and developing countries.