Identification of human and animal fecal contamination after rainfall in the Han River, Korea

Integrating fecal pollution markers and fluorescence analysis for water quality assessment of urban river

Human fecal contamination in urban rivers poses significant health risks, but their potential connections with other substances like dissolved organic matter (DOM) remain underexplored. In this study, five fecal pollution markers related to fecal Bacteroides or human fecal contamination (AllBac, HF183, BacH, Hum2, and Hum163) and DOM along an urban river were analyzed using quantitative polymerase chain reaction (qPCR) and three-dimensional excitation-emission (3D EEM) fluorescence spectrometry. All five markers were detected with average absolute abundance ranging from 2.51 to 6.28 lg gene copies/100 mL, showing a progressive increase along the river (R2 = 0.29-0.92, p < 0.05). Parallel factor analysis identified three dominant DOM components (humic acid-like, fulvic acid-like, and protein-like), with strong positive correlations between protein-like components and all fecal markers (R2 = 0.59-0.66, p < 0.001). Both fecal and DOM distributions consistently showed significant differences between upstream and downstream areas (p < 0.001), suggesting their complementary assessment. While DOM was more sensitive to environmental variables such as rainfall, rubber dam, and tidal dynamic, the combination of fecal pollution markers and 3D EEM analysis allowed a more comprehensive assessment of contamination levels, mitigating potential biases caused by the influence of multiple factors on a single method. Furthermore, due to the strong correlation between protein-like and fecal markers in the DOM, 3D EEM can be used as a pre-detection means for qPCR detection, reducing testing time and costs.

A Longitudinal Survey of Antibiotic-Resistant Enterobacterales in the Irish Environment, 2019-2020

The natural environment represents a complex reservoir of antibiotic-resistant bacteria as a consequence of different wastewater discharges including anthropogenic and agricultural. Therefore, the aim of this study was to examine sewage and waters across Ireland for the presence of antibiotic-resistant Enterobacterales. Samples were collected from the West, East and South of Ireland. Two periods of sampling took place between July 2019 and November 2020, during which 118 water (30 L) and 36 sewage samples (200 mL) were collected. Waters were filtered using the CapE method, followed by enrichment and culturing. Sewage samples were directly cultured on selective agars. Isolates were identified by MALDI-TOF and antibiotic susceptibility testing was performed in accordance with EUCAST criteria. Selected isolates were examined for bla_CTX-M, bla_VIM, bla_IMP, bla_OXA-48, bla_NDM, and bla_KPC by real time PCR and whole genome sequencing (n = 146). A total of 419 Enterobacterales (348 water, 71 sewage) were isolated from all samples. Hospital sewage isolates displayed the highest percentage resistance to many beta-lactam and aminoglycoside antibiotics. Extended-spectrum beta-lactamase-producers were identified in 78% of water and 50% of sewage samples. One or more carbapenemase-producing Enterobacterales were identified at 23 individual sampling sites (18 water, 5 sewage). This included the detection of bla_OXA-48 (n = 18), bla_NDM (n = 14), bla_KPC (n = 4) and bla_OXA-484 (n = 1). All NDM-producing isolates harbored the ble-MBL bleomycin resistance gene. Commonly detected sequence types included Klebsiella ST323, ST17, and ST405 as well as E. coli ST131, ST38 and ST10. Core genome MLST comparisons detected identical E. coli isolates from wastewater treatment plant (WWTP) influent and nursing home sewage, and the surrounding waters. Similarly, one Klebsiella pneumoniae isolated from WWTP influent and the surrounding estuarine water were identical. These results highlight the need for regular monitoring of the aquatic environment for the presence of antibiotic-resistant organisms to adequately inform public health policies.

Applicability Evaluation of Male-Specific Coliphage-Based Detection Methods for Microbial Contamination Tracking

Outbreaks of food poisoning due to the consumption of norovirus-contaminated shellfish continue to occur. Male-specific (F+) coliphage has been suggested as an indicator of viral species due to the association with animal and human wastes. Here, we compared two methods, the double agar overlay and the quantitative real-time PCR (RT-PCR)-based method, for evaluating the applicability of F+ coliphage-based detection technique in microbial contamination tracking of shellfish samples. The RT-PCR-based method showed 1.6-39 times higher coliphage PFU values from spiked shellfish samples, in relation to the double agar overlay method. These differences indicated that the RT-PCR-based technique can detect both intact viruses and non-particle-protected viral DNA/RNA, suggesting that the RT-PCR based method could be a more efficient tool for tracking microbial contamination in shellfish. However, the virome information on F+ coliphage-contaminated oyster samples revealed that the high specificity of the RT-PCR- based method has a limitation in microbial contamination tracking due to the genomic diversity of F+ coliphages. Further research on the development of appropriate primer sets for microbial contamination tracking is therefore necessary. This study provides preliminary insight that should be examined in the search for suitable microbial contamination tracking methods to control the sanitation of shellfish and related seawater.

Long-Term Water Quality Patterns in an Estuarine Reservoir and the Functional Changes in Relations of Trophic State Variables Depending on the Construction of Serial Weirs in Upstream Reaches

Water quality degradation is one of the major problems with artificial lakes in estuaries. Long-term spatiotemporal patterns of water quality in a South Korean estuarine reservoir were analyzed using seasonal datasets from 2002 to 2020, and some functional changes in relations of trophic state variables due to the construction of serial weirs in the upper river were also investigated. A total of 19 water quality parameters were used for the study, including indicators of organic matter, nutrients, suspended solids, water clarity, and fecal pollution. In addition, chlorophyll-a (CHL-a) was used to assess algal biomass. An empirical regression model, trophic state index deviation (TSID), and principal component analysis (PCA) were applied. Longitudinal fluctuations in nutrients, organic matter, sestonic CHL-a, and suspended solids were found along the axis of the riverine (Rz), transition (Tz), and lacustrine zones (Lz). The degradation of water quality was seasonally caused by resuspension of sediments, monsoon input due to rainfall inflow, and intensity of Asian monsoon, and was also related to intensive anthropic activities within the catchment. The empirical model and PCA showed that light availability was directly controlled by non-algal turbidity, which was a more important regulator of CHL-a than total nitrogen (TN) and total phosphorus (TP). The TSID supported our hypothesis on the non-algal turbidity. We also found that the construction of serial upper weirs influenced nutrient regime, TSS, CHL-a level, and trophic state in the estuarine reservoir, resulting in lower TP and TN but high CHL-a and high TN/TP ratios. The proportions of both dissolved color clay particles and blue-green algae in the TSID additionally increased. Overall, the long-term patterns of nutrients, suspended solids, and algal biomass changed due to seasonal runoff, turnover time, and reservoir zones along with anthropic impacts of the upper weir constructions, resulting in changes in trophic state variables and their mutual relations in the estuarine reservoir.

Evaluation of a multivariate analysis modeling approach identifying sources and patterns of nonpoint fecal pollution in a mixed use watershed

Surface waters listed on impaired waters (303 d) lists due to pathogen contamination pose a significant environmental and public health burden. The need to address impairments through the Total Maximum Daily Load (TMDL) process has resulted in method developments that successfully identify nonpoint fecal pollution sources by maximizing available resources to improve water quality. However, the ability of those methods to effectively and universally identify sources of fecal pollution requires further evaluation. The objective of this research was to assess the usefulness of a previously described multivariate statistical approach to identify common patterns influencing fate and transport of fecal pollutants from sources to receiving streams using the Tuckasegee River watershed in Western North Carolina as a test watershed. Two streams were routinely monitored using a targeted sampling approach to assess fecal pollution extent and identify nonpoint sources using canonical correlation and canonical discriminant analyses. Fecal pollution in the watershed varied spatially and temporally with significantly higher fecal coliform concentrations observed in Scott Creek (f = 9.49, p = 0.002) and during the summer months (f = 14.8, p < 0.0001). Canonical correlations described 62-67% of water quality variability and indicate that fecal pollution in portions of the watershed are influenced by stormwater runoff and fecal indicator bacteria resuspension from sediment, while fecal pollution in other portions are influenced by soil erosion and surface runoff. Canonical discriminant analyses indicate that LULC significantly influences the nature and extent of fecal pollution. These results demonstrate that chemical parameters are useful predictors of fecal pollution and can help identify nonpoint fecal pollution sources in relation to land use patterns and land management practices. This approach to water quality monitoring program design and data analysis may effectively and efficiently identify parameters that best predict fecal pollution to aid in development and implementation of effective TMDLs to remediate impaired waters.

Urbanization Impacts the Physicochemical Characteristics and Abundance of Fecal Markers and Bacterial Pathogens in Surface Water

Urbanization is increasing worldwide and is happening at a rapid rate in China in line with economic development. Urbanization can lead to major changes in freshwater environments through multiple chemical and microbial contaminants. We assessed the impact of urbanization on physicochemical characteristics and microbial loading in canals in Suzhou, a city that has experienced rapid urbanization in recent decades. Nine sampling locations covering three urban intensity classes (high, medium and low) in Suzhou were selected for field studies and three locations in Huangshan (natural reserve) were included as pristine control locations. Water samples were collected for physicochemical, microbiological and molecular analyses. Compared to medium and low urbanization sites, there were statistically significant higher levels of nutrients and total and thermotolerant coliforms (or fecal coliforms) in highly urbanized locations. The effect of urbanization was also apparent in the abundances of human-associated fecal markers and bacterial pathogens in water samples from highly urbanized locations. These results correlated well with land use types and anthropogenic activities at the sampling sites. The overall results indicate that urbanization negatively impacts water quality, providing high levels of nutrients and a microbial load that includes fecal markers and pathogens.

Weather and gastrointestinal disease in Spain: A retrospective time series regression study

BACKGROUND

A few studies in high-income countries have investigated the relationship between ambient temperature and/or precipitation and the occurrence of gastroenteritis. In most of the cases, hot temperatures and heavy precipitation events have been related to increases in infections. This is of concern as climate change predictions indicate an increase of those extreme events. Our aim was to evaluate the association between meteorological variables and daily gastroenteritis hospitalizations in Spain for the period 1997-2013.

METHODS

We obtained data on all hospitalizations which occurred in Spain for the study period from administrative databases and selected those with gastroenteritis as the main diagnosis. Meteorological data was obtained from the European Climate Assessment & Dataset. Daily counts of hospitalizations were linked to meteorological variables in a retrospective ecological time series study using quasi-Poisson regression models with overdispersion and applying the Distributed Lag Non-linear Model (DLNM) framework.

RESULTS

Both high and cold temperatures increased the risk of gastroenteritis hospitalizations (relative risk (RR) = 1.21, 95% confidence interval (CI): 1.09, 1.34; and RR = 1.07, 95% CI: 1.00, 1.15, respectively), whereas heavy precipitation was found protective for those hospitalizations (RR = 0.74, 95% CI: 0.63, 0.86). Hot temperatures increased hospitalizations for gastroenteritis classified as foodborne or idiopathic but not those in the group of Others, which were composed mainly of infections by rotavirus and were associated with cold temperatures.

CONCLUSIONS

Our findings suggest an important role of ambient temperatures, especially hot temperatures, in increasing gastroenteritis hospitalizations, while the exposure to heavy precipitation events pose opposite and unexpected effects on these infections.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality – particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL⁻¹. The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems.

Projections of hepatitis A virus infection associated with flood events by 2020 and 2030 in Anhui Province, China

Assessing and responding to health risk of climate change is important because of its impact on the natural and societal ecosystems. More frequent and severe flood events will occur in China due to climate change. Given that population is projected to increase, more people will be vulnerable to flood events, which may lead to an increased incidence of HAV infection in the future. This population-based study is going to project the future health burden of HAV infection associated with flood events in Huai River Basin of China. The study area covered four cities of Anhui province in China, where flood events were frequent. Time-series adjusted Poisson regression model was developed to quantify the risks of flood events on HAV infection based on the number of daily cases during summer seasons from 2005 to 2010, controlling for other meteorological variables. Projections of HAV infection in 2020 and 2030 were estimated based on the scenarios of flood events and demographic data. Poisson regression model suggested that compared with the periods without flood events, the risks of severe flood events for HAV infection were significant (OR = 1.28, 95 % CI 1.05-1.55), while risks were not significant from moderate flood events (OR = 1.16, 95 % CI 0.72-1.87) and mild flood events (OR = 1.14, 95 % CI 0.87-1.48). Using the 2010 baseline data and the flood event scenarios (one severe flood event), increased incidence of HAV infection were estimated to be between 0.126/10⁵ and 0.127/10⁵ for 2020. Similarly, the increased HAV infection incidence for 2030 was projected to be between 0.382/10⁵ and 0.399/10⁵. Our study has, for the first time, quantified the increased incidence of HAV infection that will result from flood events in Anhui, China, in 2020 and 2030. The results have implications for public health preparation for developing public health responses to reduce HAV infection during future flood events.

Microbiological and hydrogeological assessment of groundwater in southern Italy

This study represents the first investigation of microbiological groundwater pollution as a function of aquifer type and season for the Apulia region of southern Italy. Two hundred and seven wells were randomly selected from those monitored by the Regional Agency for Environmental Protection for emergency use. Both compulsory (Escherichia coli, Total Coliform, and Enterococci) and optional (Pseudomonas aeruginosa, Salmonella spp., Heterotrophic Plate Count at 37 and 22 °C) microbiological parameters were assessed regularly at these wells. Groundwater from only 18 of the 207 (8.7 %) wells was potable; these all draw from karst-fissured aquifers. The remaining 189 wells draw from karst-fissured (66.1 %) or porous (33.9 %) aquifers. Of these, 82 (43.4 %) tested negative for Salmonella spp. and P. aeruginosa, while 107 (56.6 %) tested positive for P. aeruginosa (75.7 %), Salmonella spp. (10.3 %), or for both Salmonella spp. and P. aeruginosa (14 %). A logistic regression model shows that the probability of potable groundwater depends on both season and aquifer type. Typically, water samples were more likely to be potable in autumn-winter than in spring-summer periods (odds ratio, OR = 2.1; 95 % confidence interval, 95 % CI = 1.6-2.7) and from karst-fissured rather than porous aquifers (OR = 5.8; 95 % CI = 4.4-7.8). Optional parameters only showed a seasonal pattern (OR = 2.6; 95 % CI = 1.7-3.9). Clearly, further investigation of groundwater microbiological aspects should be carried out to identify the risks of fecal contamination and to establish appropriate protection methods, which take into account the hydrogeological and climatic characteristics of this region.

Spatio-temporal characteristics of livestock and their effects on pollution in China based on geographic information system

Livestock pollution, caused by rural household's scatter breeding mainly, is one of the major non-point sources. Different animal manures are abundant with different nutrients. Adopting the policies, management practices, and technologies related to livestock production based on livestock structure analysis can improve the efficiency on preventing pollution. Based on statistical data, the component structure of livestock was analyzed and corresponding effect on pollution was evaluated during the period of 1992-2012 in China. The results showed that the average annual growth rate (AAGR) of total China was 1.58 % during the 20 years. Larger amounts of livestock were concentrated in Southwest China and East China. In the view of component structure, each type of livestock had different distribution characteristics and constant increasing amounts were presented during the 20 years. Cattle took the largest proportion in almost every province, and the number of heads was over 40 % of all the livestock quantity for most provinces. Pollution of total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) caused by livestock excretion in East and Southeast China was much more serious than that in other regions. However, the load of COD was far less than that of TN and TP. Cattle accounted most for the livestock pollution, and swine was the second one. The intensity characteristics of TN, TP, and COD were different from that of total pollution loads. The spatio-temporal characteristics of amounts and component structure of livestock were influenced by three kinds of factors (natural, economic, and social), such as climate, topography, modes of production, feed grain sector, related policies, and area of the study regions. Different livestock excrements had different impacts on environment. According to various livestock structures and economy conditions, different disposal methods should be adopted.

Effects of climate change on the persistence and dispersal of foodborne bacterial pathogens in the outdoor environment: A review

According to the Intergovernmental Panel on Climate Change (IPCC), warming of the climate system is unequivocal. Over the coming century, warming trends such as increased duration and frequency of heat waves and hot extremes are expected in some areas, as well as increased intensity of some storm systems. Climate-induced trends will impact the persistence and dispersal of foodborne pathogens in myriad ways, especially for environmentally ubiquitous and/or zoonotic microorganisms. Animal hosts of foodborne pathogens are also expected to be impacted by climate change through the introduction of increased physiological stress and, in some cases, altered geographic ranges and seasonality. This review article examines the effects of climatic factors, such as temperature, rainfall, drought and wind, on the environmental dispersal and persistence of bacterial foodborne pathogens, namely, Bacillus cereus, Brucella, Campylobacter, Clostridium, Escherichia coli, Listeria monocytogenes, Salmonella, Staphylococcus aureus, Vibrio and Yersinia enterocolitica. These relationships are then used to predict how future climatic changes will impact the activity of these microorganisms in the outdoor environment and associated food safety issues. The development of predictive models that quantify these complex relationships will also be discussed, as well as the potential impacts of climate change on transmission of foodborne disease from animal hosts.