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.
RNA viruses form a dynamic distribution of mutant swarms (termed “quasispecies”) due to the accumulation of mutations in the viral genome. The genetic diversity of a viral population is affected by several factors, including a bottleneck effect. Human-to-human transmission exemplifies a bottleneck effect, in that only part of a viral population can reach the next susceptible hosts. In the present study, two lineages of the rhesus rotavirus (RRV) strain of rotavirus A were serially passaged five times at a multiplicity of infection (MOI) of 0.1 or 0.001, and three phenotypes (infectious titer, cell binding ability, and specific growth rate) were used to evaluate the impact of a bottleneck effect on the RRV population. The specific growth rate values of lineages passaged under the stronger bottleneck (MOI of 0.001) were higher after five passages. The nucleotide diversity also increased, which indicated that the mutant swarms of the lineages under the stronger bottleneck effect were expanded through the serial passages. The random distribution of synonymous and nonsynonymous substitutions on rotavirus genome segments indicated that almost all mutations were selectively neutral. Simple simulations revealed that the presence of minor mutants could influence the specific growth rate of a population in a mutant frequency-dependent manner. These results indicate a stronger bottleneck effect can create more sequence spaces for minor sequences. IMPORTANCE In this study, we investigated a bottleneck effect on an RRV population that may drastically affect the viral population structure. RRV populations were serially passaged under two levels of a bottleneck effect, which exemplified human-to-human transmission. As a result, the genetic diversity and specific growth rate of RRV populations increased under the stronger bottleneck effect, which implied that a bottleneck created a new space in a population for minor mutants originally existing in a hidden layer, which includes minor mutations that cannot be distinguished from a sequencing error. The results of this study suggest that the genetic drift caused by a bottleneck in human-to-human transmission explains the random appearance of new genetic lineages causing viral outbreaks, which can be expected according to molecular epidemiology using next-generation sequencing in which the viral genetic diversity within a viral population is investigated.
Hazard analysis and critical control point (HACCP) are a series of actions to be taken to ensure product consumption safety. In food poisoning risk management, researchers in the field of predictive microbiology calculate the values that provide minimum stress (e.g., temperature and contact time in heating) for sufficient microbe inactivation based on mathematical models. HACCP has also been employed for health risk management in sanitation safety planning (SSP), but the application of predictive microbiology to water-related pathogens is difficult because the variety of pathogen types and the complex composition of the wastewater matrix does not allow us to make a simple mathematical model to predict inactivation efficiency. In this study, we performed a systematic review and meta-analysis to construct predictive inactivation curves using free chlorine for enteric viruses based on a hierarchical Bayesian model using parameters such as water quality. Our model considered uncertainty among virus disinfection tests and difference in genotype-dependent sensitivity of a virus to disinfectant. The proposed model makes it possible to identify critical disinfection stress capable of reducing virus concentration that is below the tolerable concentration to ensure human health.
Rotavirus is the main etiological factor for infantile diarrhea. It is a double-stranded (ds) RNA virus and forms a genetically diverse population, known as quasispecies, owing to their high mutation rate. Here, we describe how to measure the specific growth rate and the cell-binding ability of rotavirus as its phenotypes. Rotavirus is treated with trypsin to recognize the cell receptor and then inoculated into MA104 cell culture. The supernatant, including viral progenies, is collected intermittently. The plaque assay is used to confirm the virus titer (plaque-forming unit: pfu) of each collected supernatant. The specific growth rate is estimated by fitting time-course data of pfu/mL to the modified Gompertz model. In the assay of cell-binding, MA104 cells in a 24-well plate are infected with rotavirus and incubated for 90 min at 4 °C for rotavirus adsorption to cell receptors. A low temperature restrains rotavirus from invading the host cell. After washing to remove unbound virions, RNA is extracted from virions attached to cell receptors followed by cDNA synthesis and reverse-transcription quantitative PCR (RT-qPCR). These protocols can be applied for investigating the phenotypic differences among viral strains.
Purpose of Review Major waterborne viruses comprise numerous variants rather than only a master sequence and form a genetically diverse population. High genetic diversity is advantageous for adaptation to environmental changes because the highly diverse population likely includes variants resistant to an adverse effect. Disinfection is a broadly employed tool to inactivate pathogens, but due to virus evolvability, waterborne viruses may not be inactivated sufficiently in currently applied disinfection conditions. Here, by focusing on virus population genetics, we explore possibility and factor of emergence of disinfection sensitivity change. Recent Findings To test whether virus population obtains disinfection resistance, the evolutionary experiment developed in the field of population genetics has been applied, indicating the change in disinfection sensitivity. It has been also confirmed that the sensitivity of environmental strains is lower than that of laboratory strains. In some of these studies, genetic diversity within a population less sensitive to disinfection is higher. Researches in virus population genetics have shown the contribution of intra-population genetic diversity to virus population phenotype, so disinfection sensitivity change may attribute to the genetic diversity. Summary The research elucidating a relationship between virus evolution and disinfection has only recently begun, but significant information about the relationship has been accumulated. To develop an effective disinfection strategy for the control of waterborne virus spread, we need to clarify whether disinfection practice truly affects virus outbreaks by refining both laboratory and field experiments related to virus evolution in the disinfection-exerted environment.
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