Abstract:The diverse inactivation rates observed in bacteria from different faecal sources have implications when these rates are used to model faecal pollution in water. The use of FIBT of different sources is essential to develop reliable predictive models. Since different inactivation of E. coli regarding the source of pollution has been observed, the source of the pollution has to be considered for modelling approaches.
“…HF183/BacR287 values in the uncovered mesocosm were smaller than all 16 literature value inactivation rate constants whereas in the covered mesocosm, mean values were smaller than seven out of the nine literature value inactivation rate constants ( Fig. 4 ) (ranging from −0.03 to −2.55 d −1 ) ( Ahmed et al., 2014 , 2019 ; Bae and Wuertz, 2015 ; Balleste et al., 2018 , 2019 ; Dick et al., 2010 ; Eichmiller et al., 2014 ; Gilpin et al., 2013 ; Green et al., 2011 ; He et al., 2016 ; Jeanneau et al., 2012 ; Kirs et al., 2016 ; Liang et al., 2012 ; Walters and Field, 2009 ). Fig.…”
Fecal indicator bacteria (FIB) are typically used to monitor microbial water quality but are poor representatives of viruses due to different environmental fate. Viral fecal indicators have been proposed as alternatives to FIB; however, data evaluating the persistence of emerging viral fecal indicators under realistic environmental conditions is necessary to evaluate their potential application. In this study, we examined the persistence of five viral fecal indicators, including crAssphage and pepper mild mottle virus (PMMoV), and three bacterial fecal indicators (
E. coli
, enterococci and HF183/BacR287) in large-scale experimental ponds and freshwater mesocosms. Observed inactivation rate constants were highly variable and ranged from a minimum of −0.09 d
−1
for PMMoV to a maximum of −3.5 d
−1
for HF183/BacR287 in uncovered mesocosms. Overall, viral fecal indicators had slower inactivation than bacterial fecal indicators and PMMoV was inactivated more slowly than all other targets. These results demonstrate that bacterial fecal indicators inadequately represent viral fate following aging of sewage contaminated water due to differential persistence, and that currently used fecal indicator monitoring targets demonstrate highly variable persistence that should be considered during water quality monitoring and risk assessment.
“…HF183/BacR287 values in the uncovered mesocosm were smaller than all 16 literature value inactivation rate constants whereas in the covered mesocosm, mean values were smaller than seven out of the nine literature value inactivation rate constants ( Fig. 4 ) (ranging from −0.03 to −2.55 d −1 ) ( Ahmed et al., 2014 , 2019 ; Bae and Wuertz, 2015 ; Balleste et al., 2018 , 2019 ; Dick et al., 2010 ; Eichmiller et al., 2014 ; Gilpin et al., 2013 ; Green et al., 2011 ; He et al., 2016 ; Jeanneau et al., 2012 ; Kirs et al., 2016 ; Liang et al., 2012 ; Walters and Field, 2009 ). Fig.…”
Fecal indicator bacteria (FIB) are typically used to monitor microbial water quality but are poor representatives of viruses due to different environmental fate. Viral fecal indicators have been proposed as alternatives to FIB; however, data evaluating the persistence of emerging viral fecal indicators under realistic environmental conditions is necessary to evaluate their potential application. In this study, we examined the persistence of five viral fecal indicators, including crAssphage and pepper mild mottle virus (PMMoV), and three bacterial fecal indicators (
E. coli
, enterococci and HF183/BacR287) in large-scale experimental ponds and freshwater mesocosms. Observed inactivation rate constants were highly variable and ranged from a minimum of −0.09 d
−1
for PMMoV to a maximum of −3.5 d
−1
for HF183/BacR287 in uncovered mesocosms. Overall, viral fecal indicators had slower inactivation than bacterial fecal indicators and PMMoV was inactivated more slowly than all other targets. These results demonstrate that bacterial fecal indicators inadequately represent viral fate following aging of sewage contaminated water due to differential persistence, and that currently used fecal indicator monitoring targets demonstrate highly variable persistence that should be considered during water quality monitoring and risk assessment.
“…We did not detect a correlation between the human and swine marker concentrations, which we interpreted as evidence that non-specific amplification from the swine marker was not occurring when human fecal contamination was present. However, the lack of correlation may have been caused by differences in stability of the signal between the human and swine markers due to factors such as differences in decay rates among markers from different sources 62 . Differences in environmental persistence among MST markers and markers from different sources may also explain why we did not detect a significant association between any of the MST markers and the pathogenic E. coli marker.…”
Recreational waters are primary attractions at many national and state parks where feral swine populations are established, and thus are possible hotspots for visitor exposure to feral swine contaminants. Microbial source tracking (MST) was used to determine spatial and temporal patterns of fecal contamination in Congaree National Park (CONG) in South Carolina, U.S.A., which has an established population of feral swine and is a popular destination for water-based recreation. Water samples were collected between December 2017 and June 2019 from 18 surface water sites distributed throughout CONG. Host specific MST markers included human (HF183), swine (Pig2Bac), ruminant (Rum2Bac), cow (CowM3), chicken (CL), and a marker for shiga toxin producing Escherichia coli (STEC; stx2). Water samples were also screened for culturable Escherichia coli (E. coli) as part of a citizen science program. Neither the cow nor chicken MST markers were detected during the study. The human marker was predominantly detected at boundary sites or could be attributed to upstream sources. However, several detections within CONG without concurrent detections at upstream external sites suggested occasional internal contamination from humans. The swine marker was the most frequently detected of all MST markers, and was present at sites located both internal and external to the Park. Swine MST marker concentrations ≥ 43 gene copies/mL were associated with culturable E. coli concentrations greater than the U.S. Environmental Protection Agency beach action value for recreational waters. None of the MST markers showed a strong association with detection of the pathogenic marker (stx2). Limited information about the health risk from exposure to fecal contamination from non-human sources hampers interpretation of the human health implications.
“…When a new set of ST markers are developed and presented to the scientific community, in the first instance they are normally tested with fresh faecal samples and sometimes with environmental samples. Although this is a good starting point, assessing marker performance in the real environment is more challenging, because of the impact of other factors (Cho et al, 2016): dilution in the water body and the effect of rainfall (Sercu et al, 2011), aging of the pollution between discharge and sampling (Ballesté et al, 2018;Blaustein et al, 2013;Van Kessel et al, 2007), or mixing with other potential faecal sources. To approximate real conditions, an in silico matrix of 10,000 samples was generated using faecal samples, taking into account their potential dilution and aging in the environment.…”
Section: Discussionmentioning
confidence: 99%
“…As ST markers from different geographical areas can vary in sensitivity and specificity (Haramoto and Osada, 2018;Mayer et al, 2018;Yahya et al, 2017), a more local study using regionally tailored ST markers with samples from a smaller geographical range could reduce the number of markers while increasing the power of the models. It should be born in mind that the indicators selected here were the best in a given framework, but they may differ when using another input matrix (different markers, indicators and source samples) or altering the given inactivation, which can vary according to the season and environmental conditions (W. Ballesté et al, 2018;Blaustein et al, 2013;Solecki et al, 2011). Thus, the decay rate and dilution will vary according to the target scenario.…”
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