No abstract

Polyethylene glycol (PEG) precipitation is one of the conventional methods for virus concentration. This technique has been used to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. The procedures and seeded surrogate viruses were different among implementers; thus, the reported whole process recovery efficiencies considerably varied among studies. The present study compared five PEG precipitation procedures, with different operational parameters, for the RT-qPCR-based whole process recovery of murine hepatitis virus (MHV), bacteriophage phi6, and pepper mild mottle virus (PMMoV), and molecular process recovery of murine norovirus using 34 raw wastewater samples collected in Japan. The five procedures yielded significantly different whole process recovery of MHV (0.070%–2.6%) and phi6 (0.078%–0.51%). The observed concentration of indigenous PMMoV ranged from 8.9 to 9.7 log (7.9 × 10 8 to 5.5 × 10 9 ) copies/L. Interestingly, PEG precipitation with 2-h incubation outperformed that with overnight incubation partially due to the difference in molecular process recovery efficiency. The recovery load of MHV exhibited a positive correlation ( r = 0.70) with that of PMMoV, suggesting that PMMoV is the potential indicator of the recovery efficiency of SARS-CoV-2. In addition, we reviewed 13 published studies and found considerable variability between different studies in the whole process recovery efficiency of enveloped viruses by PEG precipitation. This was due to the differences in operational parameters and surrogate viruses as well as the differences in wastewater quality and bias in the measurement of the seeded load of surrogate viruses, resulting from the use of different analytes and RNA extraction methods. Overall, the operational parameters (e.g., incubation time and pretreatment) should be optimized for PEG precipitation. Co-quantification of PMMoV may allow for the normalization of SARS-CoV-2 RNA concentration by correcting for the differences in whole process recovery efficiency and fecal load among samples.

This study presents a novel methodology for estimating the concentration of environmental pollutants in water, such as pathogens, based on environmental parameters. The scientific uniqueness of this study is the prevention of excess conformity in the model fitting by applying domain knowledge, which is the accumulated scientific knowledge regarding the correlations between response and explanatory variables. Sign constraints were used to express domain knowledge, and the effect of the sign constraints on the prediction performance using censored datasets was investigated. As a result, we confirmed that sign constraints made prediction more accurate compared to conventional sign-free approaches. The most remarkable technical contribution of this study is the finding that the sign constraints can be incorporated in the estimation of the correlation coefficient in Tobit analysis. We developed effective and numerically stable algorithms for fitting a model to datasets under the sign constraints. This novel algorithm is applicable to a wide variety of the prediction of pollutant contamination level, including the pathogen concentrations in water. This article has been made Open Access thanks to the generous support of a global network of libraries as part of the Knowledge Unlatched Select initiative.

Estimating and predicting the epidemic size from wastewater surveillance results remain challenging for the practical implementation of wastewater-based epidemiology (WBE). In this study, by employing a highly sensitive detection method, we documented the time series of SARS-CoV-2 RNA occurrence in wastewater influent from an urban community with a 360,000 population in Japan, from August 2020 to February 2021. The detection frequency of the viral RNA increased during the outbreak events of COVID-19 and the highest viral RNA concentration was recorded at the beginning of January 2021, amid the most serious outbreak event during the study period. We found that: (1) direct back-calculation still suffers from great uncertainty dominated by inconsistent detection and the varying gap between the observed wastewater viral load and the estimated patient viral load, and (2) the detection frequency correlated well with reported cases and the prediction of the latter can be carried out via data-driven modeling methods. Our results indicate that wastewater virus occurrence can contribute to epidemic surveillance in ways more than back-calculation, which may spawn future wastewater surveillance implementations.

Slaked lime (calcium hydroxide) is a commonly used disinfectant for fecal sludge. Although viruses are inactivated by lime treatment, whether RNA viruses adapt to lime treatment has not yet been determined. Here, we show that murine norovirus developed higher tolerance during serial passages with lime treatment. We compared synonymous and non-synonymous nucleotide diversities of the three open reading frames of viral genome and revealed that virus populations were subjected to enhanced purifying selection over the course of serial passages with lime treatment. Virus adaptation to lime treatment was coincident with amino acid substitution of lysine to arginine at position 345 (K345R) on the major capsid protein VP1, which accounted for more than 90% of the population. The infectious clones with the K345R produced using a plasmid-based reverse genetics system exhibited greater tolerance in a lime solution, which indicated that the specific amino acid substitution was solely involved in the viral tolerance in lime treatment.