Biology subjects

Wigginton, K.

Publications and source records attributed to Wigginton, K..

5 recordsLinked to original sources

bioRxiv2026

A Statistical Review of Virus Reduction in Coagulation, Flocculation, and Sedimentation Treatment Processes

Coagulation, flocculation, and sedimentation (CFS) is widely applied as a combined unit process in the treatment of drinking water, wastewater, and recycled water; however, virus reduction through CFS has not been sufficiently characterized to assign pathogen log reduction value (LRV) credits. This study collected data through a systematic review that yielded over 1000 LRVs from 43 manuscripts covering 46 viruses to characterize virus reduction through CFS. The results demonstrate that CFS is effective at reducing viruses, with 68% of virus LRVs greater than 1. A mixed-effects model was used to identify potential mechanisms of virus reduction with ferric and aluminum coagulants, as well as factors associated with variability in performance. Key insights from the model show that virus reduction is: (1) improved at lower pH, similar to natural organic matter (NOM) reduction, (2) lower in secondary effluent than surface water for drinking water treatment, (3) virus-dependent, and (4) dependent on virus enumeration methods, with lower LRVs observed for molecular techniques. These findings demonstrate the potential for CFS to provide consistent and explainable virus reduction, potentially establishing a foundation for regulatory crediting in potable reuse applications. Future crediting frameworks will need to account for the factors impacting performance to accurately quantify and assign credit for virus reduction.

microbiology↗

bioRxiv2023

Linear Mixed Model of Virus Disinfection by Chlorine to Harmonize Data Collected Across Broad Environmental Conditions

Despite the critical importance of virus disinfection by chlorine, we lack a fundamental understanding of the relative susceptibility of different viruses to chlorine and robust quantitative relationships between virus disinfection rate constants and environmental parameters. We conducted a rapid systematic review of virus inactivation by free chlorine and used the resulting data set to develop a linear mixed model that estimates chlorine inactivation rate constants for viruses based on experimental conditions. Over 550 data points were collected in our systematic review, representing 82 viruses over a broad range of environmental conditions. The harmonized inactivation rate constants under reference conditions (pH = 7.53, T = 20 {degrees}C, [Cl-] < 50 mM) spanned 4 orders of magnitude, ranging from 0.0196 to 1150 L mg-1 min-1 and uncovered important trends between viruses. Whereas common surrogate bacteriophage MS2 does not serve as a conservative chlorine disinfection surrogate for many human viruses, CVB5 was one of the most resistant viruses in the dataset. The model quantifies the role of pH, temperature, and chloride levels across viruses, and an online tool allows users to predict rate constants for viruses and conditions of interest. Results from the model highlighted potential shortcomings in current USEPA disinfection guidelines. SynopsisViruses must be adequately removed by disinfection processes to protect public health. We review data on virus inactivation of chlorine to determine what concentrations of chlorine are required to remove viruses and whether current regulations are adequately protective.

microbiology↗

bioRxiv2022

Evaluating limitations of quantitative metagenomics with synthetic dsDNA and ssDNA standards

Quantitative metagenomic methods are maturing but continue to lack clearly-defined analytical limits. Here, we developed a computational tool, QuantMeta, to determine the absolute abundance of targets in metagenomes spiked with synthetic DNA standards. The tool establishes (1) entropy-based detection thresholds to confidently determine the presence of targets, and (2) an approach to identify and correct read mapping or assembly errors and thus improve the quantification accuracy. Together this allows for an approach to confidently quantify absolute abundance of targets, be they microbial populations, genes, contigs, or metagenome assembled genomes (MAGs). We applied the approach to quantify single- and double-stranded DNA viruses in wastewater viral metagenomes, including pathogens and bacteriophages. Concentrations of total DNA viruses in wastewater influent and effluent were greater than 108 copies/mL using QuantMeta. Human-associated DNA viruses were detected and quantifiable with QuantMeta thresholds, including polyomavirus, papillomavirus, and crAss-like phages, at concentrations similar to previous reports that utilized quantitative PCR-based assays. Our results highlight the higher detection thresholds of quantitative metagenomics ([~]500 copies/L) as compared to PCR-based quantification ([~]10 copies/L) despite a sequencing depth of 200 million reads per sample. The QuantMeta approach, applicable to both viral and cellular metagenomes, advances quantitative metagenomics by improving the accuracy of measured target absolute abundances.

genomics↗

bioRxiv2021

A Snapshot of the Global Drinking Water Virome: Diversity and Metabolic Potential Vary with Residual Disinfectant Use

Viruses are important drivers of microbial community ecology and evolution, influencing microbial mortality, metabolism, and horizontal gene transfer. However, the effects of viruses remain largely unknown in many environments, including in drinking water systems. Drinking water metagenomic studies have offered a whole community perspective of bacterial impacts on water quality, but have not yet considered the influences of viruses. In this study, we address this gap by mining viral DNA sequences from publicly available drinking water metagenomes from distribution systems in six countries around the world. These datasets provide a snapshot of the taxonomic diversity and metabolic potential of the global drinking water virome; and provide an opportunity to investigate the effects of geography, climate, and drinking water treatment practices on viral diversity. Both environmental conditions and differences in sample processing were found to influence the viral composition. Using free chlorine as the residual disinfectant was associated with clear differences in viral taxonomic diversity and metabolic potential, with significantly fewer viral populations and less even viral community structures than observed in distribution systems without residual disinfectant. Additionally, drinking water viruses carry antibiotic resistance genes (ARGs), as well as genes to survive oxidative stress and nitrogen limitation. Through this study, we have demonstrated that viral communities are diverse across drinking water systems and vary with the use of residual disinfectant. Our findings offer directions for future research to develop a more robust understanding of how virus-bacteria interactions in drinking water distribution systems affect water quality.

microbiology↗

bioRxiv2020

Predictive modeling of virus inactivation by UV

Disinfection strategies are commonly applied to inactivate pathogenic viruses in water, food, air, and on surfaces to prevent the spread of infectious diseases. Determining how quickly viruses are inactivated to mitigate health risks is not always feasible due to biosafety restrictions or difficulties with virus culturability. Therefore, methods that would rapidly predict kinetics of virus inactivation by UV254 would be valuable, particularly for emerging and difficult-to-culture viruses. We conducted a rapid systematic literature review to collect high-quality inactivation rate constants for a wide range of viruses. Using these data and basic virus information (e.g., genome sequence attributes), we developed and evaluated four different model classes, including linear and non-linear approaches, to find the top performing prediction model. For both the (+) ssRNA and dsDNA virus types, multiple linear regressions were the top performing model classes. In both cases, the cross-validated root mean squared relative prediction errors were similar to those associated with experimental rate constants. We tested the models by predicting and measuring inactivation rate constants for two viruses that were not identified in our systematic review, including a (+) ssRNA mouse coronavirus and a dsDNA marine bacteriophage; the predicted rate constants were within 7% and 71% of the experimental rate constants, respectively. Finally, we applied our models to predict the UV254 rate constants of several viruses for which high-quality UV254 inactivation data are not available. Our models will be valuable for predicting inactivation kinetics of emerging or difficult-to-culture viruses.

microbiology↗