A critical analysis of recreational water guidelines developed from temperate climate data and applied to the tropics

Comparative genomic analyses of pathogenic bacteria and viruses and antimicrobial resistance genes in an urban transportation canal

Water commuting is a major urban transportation method in Thailand. However, urban boat commuters risk exposure to microbially contaminated bioaerosols or splash. We aimed to investigate the microbial community structures, identify bacterial and viral pathogens, and assess the abundance of antimicrobial resistance genes (ARGs) using next-generation sequencing (NGS) at 10 sampling sites along an 18 km transportation boat route in the Saen Saep Canal, which traverses cultural, commercial, and suburban land-based zones. The shotgun metagenomic (Illumina HiSeq) and 16S rRNA gene amplicon (V4 region) (Illumina MiSeq) sequencing platforms revealed diverse microbial clusters aligned with the zones, with explicit segregation between the cultural and suburban sites. The shotgun metagenomic sequencing further identified bacterial and viral pathogens, and ARGs. The predominant bacterial pathogens (>0.5 % relative abundance) were the Burkholderia cepacia complex, Arcobacter butzleri, Burkholderia vietnamiensis, Klebsiella pneumoniae, and the Enterobacter cloacae complex. The viruses (0.28 %-0.67 % abundance in all microbial sequences) comprised mainly vertebrate viruses and bacteriophages, with encephalomyocarditis virus (33.3 %-58.2 % abundance in viral sequences), hepatitis C virus genotype 1, human alphaherpesvirus 1, and human betaherpesvirus 6A among the human viral pathogens. The 15 ARG types contained 611 ARG subtypes, including those resistant to beta-lactam, which was the most diverse and abundant group (206 subtypes; 17.0 %-27.5 %), aminoglycoside (94 subtypes; 9.6 %-15.3 %), tetracycline (80 subtypes; 15.6 %-20.2 %), and macrolide (79 subtypes; 14.5 %-32.1 %). Interestingly, the abundance of ARGs associated with resistance to beta-lactam, trimethoprim, and sulphonamide, as well as A. butzleri and crAssphage, at the cultural sites was significantly different from the other sites (p < 0.05). We demonstrated the benefits of using NGS to deliver insights into microbial communities, and antimicrobial resistance, both of which pose a risk to human health. Using NGS may facilitate microbial risk mitigation and management for urban water commuters and proximal residents.

Detangling Seasonal Relationships of Fecal Contamination Sources and Correlates with Indicators in Michigan Watersheds

Despite the widely acknowledged public health impacts of surface water fecal contamination, there is limited understanding of seasonal effects on (i) fate and transport processes and (ii) the mechanisms by which they contribute to water quality impairment. Quantifying relationships between land use, chemical parameters, and fecal bacterial concentrations in watersheds can help guide the monitoring and control of microbial water quality and explain seasonal differences. The goals of this study were to (i) identify seasonal differences in Escherichia coli and Bacteroides thetaiotaomicron concentrations, (ii) evaluate environmental drivers influencing microbial contamination during baseflow, snowmelt, and summer rain seasons, and (iii) relate seasonal changes in B. thetaiotaomicron to anticipated gastrointestinal infection risks. Water chemistry data collected during three hydroclimatic seasons from 64 Michigan watersheds were analyzed using seasonal linear regression models with candidate variables including crop and land use proportions, prior precipitation, chemical parameters, and variables related to both wastewater treatment and septic usage. Adaptive least absolute shrinkage and selection operator (LASSO) linear regression with bootstrapping was used to select explanatory variables and estimate coefficients. Regardless of season, wastewater treatment plant and septic system usage were consistently selected in all primary models for B. thetaiotaomicron and E. coli. Chemistry and precipitation-related variable selection depended upon season and organism. These results suggest a link between human pollution (e.g., septic systems) and microbial water quality that is dependent on flow regime.

IMPORTANCE In this study, a data set of 64 Michigan watersheds was utilized to gain insights into fecal contamination sources, drivers, and chemical correlates across seasons for general E. coli and human-specific fecal indicators. Results reaffirmed a link between human-specific sources (e.g., septic systems) and microbial water quality. While the importance of human sources of fecal contamination and fate and transport variables (e.g., precipitation) remain important across seasons, this study provides evidence that fate and transport mechanisms vary with seasonal hydrologic condition and microorganism source. This study contributes to a body of research that informs prioritization of fecal contamination source control and surveillance strategy development to reduce the public health burden of surface water fecal contamination.

Relationships between extreme flows and microbial contamination in inland recreational swimming areas

Inland recreational swimming sites provide significant social value globally. This study focused on public recreational swimming sites across the Murrumbidgee River and its tributaries in the Australian Capital Territory (ACT) throughout the swimming season (September-April) from 2009 to 2020 to determine whether high intestinal enterococci concentrations could be predicted with flow exceedance and routinely monitored physical and chemical parameters of water quality. Enterococci concentrations were positively correlated with the turbidity associated with high-flow conditions. The predictive accuracy of high enterococci levels during high-flow conditions was good (mean percentage correctly classified, 60%). The prediction of high enterococci levels at low flows was significantly less reliable (mean percentage correctly classified, 12-15%). As the ACT is expected to experience decreases in rainfall overall but increases in extreme rainfall events due to climate change, understanding the drivers of elevated intestinal enterococci under extreme flow conditions remains important from a public health perspective.

The relationship between environmental parameters and microbial water quality at two Costa Rican beaches from 2002 to 2017

Environmental conditions influence fecal indicator bacteria (FIB) levels, which are routinely used to characterize recreational water quality. This study examined 15 years of environmental and FIB data at Puntarenas and Jacó beach, Costa Rica. FIB relationships with sea level, wave height, precipitation, direct normal irradiance (DNI), wind, and turbidity were analyzed. Pearson's correlations identified lags between 24 and 96 h among environmental parameters and FIB. Multiple linear regression models composed of environmental parameters explained 24% and 27% of fecal coliforms and enterococci variability in Jacó, respectively. Puntarenas's models explained 17-26% of fecal coliforms and 12-18% enterococci variability. Precipitation, sea level anomalies, and wave height most frequently explained FIB variability. Hypothesis testing often identified significant differences in precipitation, wave height, daily sea level anomalies, and maximum sea level 24 h prior between days with and without FIB threshold exceedance. Unexpected FIB interactions with DNI, sea level, and turbidity highlight the importance of future investigations.

Relationships among microbial indicators of fecal pollution, microbial source tracking markers, and pathogens in Costa Rican coastal waters

Tropical coastal waters are understudied, despite their ecological and economic importance. They also reflect projected climate change scenarios for other climate zones, e.g., increased rainfall and water temperatures. We conducted an exploratory microbial water quality study at a tropical beach influenced by sewage-contaminated rivers, and tested the hypothesis that fecal microorganisms (fecal coliforms, enterococci, Clostridium perfringens, somatic and male-specific coliphages, pepper mild mottle virus (PMMoV), Bacteroides HF183, norovirus genogroup I (NoVGI), Salmonella, Cryptosporidium and Giardia) would vary by season and tidal stage. Most microorganisms' concentrations were greater in the rainy season; however, NoVGI was only detected in the dry season and Cryptosporidium was the only pathogen most frequently detected in rainy season. Fecal indicator bacteria (FIB) levels exceeded recreational water quality criteria standards in >85% of river samples and in <50% of ocean samples, regardless of the FIB or regulatory criterion. Chronic sewage contamination was demonstrated by detection of HF183 and PMMoV in 100% of river samples, and in >89% of ocean samples. Giardia, Cryptosporidium, Salmonella, and NoVGI were frequently detected in rivers (39%, 39%, 26%, and 39% of samples, respectively), but infrequently in ocean water, particularly during the dry season. Multivariate analysis showed that C. perfringens, somatic coliphage, male-specific coliphage, and PMMoV were the subset of indicators that maximized the correlation with pathogens in the rivers. In the ocean, the best subset of indicators was enterococci, male-specific coliphage, and PMMoV. We also executed redudancy analyses on environmental parameters and microorganim concentrations, and found that rainfall best predicted microbial concentrations. The seasonal interplay of rainfall and pathogen prevalence undoubtedly influences beach users' health risks. Relationships are likely to be complex, with some risk factors increasing and others decreasing each season. Future use of multivariate approaches to better understand linkages among environmental conditions, microbial predictors (fecal indicators and MST markers), and pathogens will improve prediction of high-risk scenarios at recreational beaches.