Molecular microbiological approaches reduce ambiguity about the sources of faecal pollution and identify microbial hazards within an urbanised coastal environment

Antibiotic-resistance genes and metals increase in polluted tropical rivers of the Baia da Ilha Grande, Rio de Janeiro, Brazil

Baia da Ilha Grande (BIG), Rio de Janeiro, Brazil, is one of the largest bays in the world. BIG is important because it serves as a route for the mining and oil industries and plays a vital role in mariculture activities. However, BIG has suffered significant impacts in recent years due to increased pollution and climate change, culminating in a local mariculture collapse. We examined the pollution levels of the bay. Biogeochemical, microbiological, and metagenomics analyses were conducted in ten rivers during the 2022 dry and rainy seasons. Combined data analyses showed that the bay's ten most significant rivers are polluted and classified into three decreasing levels of pollution groups (P1-P3). The P1 group (Centro, Japuíba, Jacuecanga) had the worst-case scenario for all pollution types, and the highest number of the nearby populations, nautical workshops and hospitals. Whereas the P2 (Jacarei, Perequeaçu and Taquari) and P3 (Frade, Bracuí, Mambucaba, São Roque) had relatively reduced pollution, as shown mainly by fecal bacteria. Metals, such as Al (>0.3 mg/L), Fe (>1.4 mg/L), Pb (>0.15 mg/L), and resistance genes (∼2 % metagenomic profile) were also more abundant in P1. High levels of metals and antibiotic resistance genes were a strong indication of pollution. The results from this study shed light on the health status of BIG rivers for further conservation programs and public policies to prevent rivers and marine biodiversity losses, and they serves as a warning on the urgent need to treat effluents in the region.

Climate change will amplify the impacts of harmful microorganisms in aquatic ecosystems

More than 70% of the human population lives within five kilometres of a natural water feature. These aquatic ecosystems are heavily used for resource provision and recreation, and represent the interface between human populations and aquatic microbiomes, which can sometimes negatively impact human health. Diverse species of endemic aquatic microorganisms, including toxic microalgae and pathogenic bacteria, can be harmful to humans. Aquatic ecosystems are also subject to intrusions of allochthonous pathogenic microorganisms through pollution and runoff. Notably, environmental processes that amplify the abundance and impact of harmful aquatic microorganisms are occurring with increasing frequency owing to climate change. For instance, increases in water temperature stimulate outbreaks of pathogenic and toxic species, whereas more intense precipitation events escalate microbial contamination from stormwater discharge. In this Perspective we discuss the influence of aquatic microbiomes on the health and economies of human populations and examine how climate change is increasing these impacts.

Microbial source tracking and identification of fecal contamination patterns in saltwater estuaries between base- and storm-flow events using dual genome-based approaches

Fecal contamination from natural and anthropogenic sources poses significant threats to saltwater estuaries, particularly after storms or heavy rainfall. Monitoring fecal contamination is essential for protecting these vulnerable ecosystems having important ecological and economic values. In this study, we investigated the abundance, sources, and potential causes of fecal contamination at three marine and seven freshwater stations across Vaughn Bay (WA, USA), a shellfish growing district, during base- and storm-flow events. Additionally, we evaluated the performance of fecal indicator bacteria (FIB) quantification, optical brightener assessment, and qPCR analysis for fecal contamination quantification. We compared the effectiveness of qPCR-based microbial source tracking (MST), which targeted a broad range of hosts including, such as humans, birds, cows, horses, ruminants, dogs, and pigs, with sequencing-based MST in identifying fecal contamination sources. Both MST analysis approaches identified birds and humans as the primary sources of fecal contamination. For marine water stations, freshwater creeks VBU001, VBU002, and VB047, along with drain VB007, were identified as the main sources of human-derived fecal contamination in Vaughn Bay, based on Kendall's tau analysis (τ: 0.58-0.97). This information indicates that the septic systems in the catchment areas of these creeks and drains require further investigation to achieve effective fecal contamination control. Optical brightener, FIB enumeration and qPCR quantification results were generally higher during storm-flow events, although they showed poor correlation with each other (Pearson r < 0.40), likely due to physiological and phylogenetic differences among the target organisms of these methods. However, the sequencing-based method faces challenges in precise quantitative identification of differences in fecal contamination between base- and storm-flow events. Due to its high-throughput and cost-effectiveness, we recommend using sequencing-based analysis for large-scale identification of the primary sources of fecal contamination in water environments, followed by targeted qPCR quantification of MST markers for more precise assessments.

Faecal contamination determines bacterial assemblages over natural environmental parameters within intermittently opened and closed lagoons (ICOLLs) during high rainfall

Intermittently closed and opened lakes and lagoons (ICOLLs) provide important ecosystem services, including food provision and nutrient cycling. These ecosystems generally experience low watershed outflow, resulting in substantial fluctuations in physicochemical parameters that are often compounded by anthropogenic contamination, however, how this impacts the patterns in microbiology within these environments remains uncharacterised. Therefore, we aimed to determine how seasonal heterogeneity in the physicochemical parameters, in comparison to faecal contamination, alter the dynamics of bacterial communities inhabiting ICOLLs on the eastern Australian coast. To address these aims, we sampled four ICOLLs on a monthly basis for one year, using 16S rRNA gene amplicon sequencing to monitor patterns in bacterial diversity and qPCR-based methods to measure faecal contamination from humans (sewage), dogs, and birds. Additionally, we used qPCR to monitor patterns of a suite of antibiotic resistance genes (ARGs) including sulI, tetA, qnrS, dfrA1, and vanB. Differences in bacterial community composition were often associated with temporal shifts in salinity, temperature, pH, dissolved oxygen, and dissolved organic matter, but following periods of high rainfall, bacterial assemblages in two of four ICOLLs changed in direct response to sewage inputs. Within these ICOLLs, indicator taxa for stormwater identified using the 16S rRNA amplicon sequencing data, as well as markers for sewage and dog faeces, and levels of the antibiotic resistance genes (ARGs) sulI, tetA, and dfrA1 were significantly more abundant after rainfall. Notably many of the stormwater indicator taxa were potential human pathogens including Arcobacter and Aeromonas hydrophilia, which also displayed significant correlations, albeit weak to moderate, with levels of the ARGs sulI, tetA, and dfrA1. This broad-scale shift in the nature of the bacterial community following rainfall will likely lead to a substantial, and perhaps detrimental, divergence in the ecosystem services provided by the bacterial assemblages within these ICOLLs. We conclude that following rainfall events, sewage was a principal driver of shifts in the microbiology of ICOLLs exposed to stormwater, while natural seasonal shifts in the physicochemical parameters controlled bacterial communities at other times. Increased occurrence of intense precipitation events is predicted as a ramification of climate change, which will lead to increased impacts of stormwater and sewage contamination on important ICOLL ecosystems in the future.

Application of a microbial and pathogen source tracking toolbox to identify infrastructure problems in stormwater drainage networks: a case study

Water scarcity and increasing urbanization are forcing municipalities to consider alternative water sources, such as stormwater, to fill in water supply gaps or address hydromodification of receiving urban streams. Mounting evidence suggests that stormwater is often contaminated with human feces, even in stormwater drainage systems separate from sanitary sewers. Pinpointing sources of human contamination in drainage networks is challenging given the diverse sources of fecal pollution that can impact these systems and the non-specificity of traditional fecal indicator bacteria (FIB) for identifying these host sources. As such, we used a toolbox approach that encompassed microbial source tracking (MST), FIB monitoring, and bacterial pathogen monitoring to investigate microbial contamination of stormwater in an urban municipality. We demonstrate that human sewage frequently contaminated stormwater (in >50% of routine samples), based on the presence of the human fecal marker HF183, and often exceeded microbial water quality criteria. Arcobacter butzleri, a pathogen of emerging concern, was also detected in >50% of routine samples, with 75% of these pathogen-positive samples also being positive for the human fecal marker HF183, suggesting human municipal sewage as the likely source for this pathogen. MST and FIB were used to track human fecal pollution in the drainage network to the most likely point source of contamination, for which a sewage cross-connection was identified and confirmed using tracer dyes. These results point to the ubiquitous presence of human sewage in stormwater and also provide municipalities with the tools to identify sources of anthropogenic contamination in storm drainage networks.IMPORTANCEWater scarcity, increased urbanization, and population growth are driving municipalities worldwide to consider stormwater as an alternative water source in urban environments. However, many studies suggest that stormwater is relatively poor in terms of microbial water quality, is frequently contaminated with human sewage, and therefore could represent a potential health risk depending on the type of exposure (e.g., irrigation of community gardens). Traditional monitoring of water quality based on fecal bacteria does not provide any information about the sources of fecal pollution contaminating stormwater (i.e., animals/human feces). Herein, we present a case study that uses fecal bacterial monitoring, microbial source tracking, and bacterial pathogen analysis to identify a cross-connection that contributed to human fecal intrusion into an urban stormwater network. This microbial toolbox approach can be useful for municipalities in identifying infrastructure problems in stormwater drainage networks to reduce risks associated with water reuse.

Occurrence, Sources and Virulence Potential of Arcobacter butzleri in Urban Municipal Stormwater Systems

A. butzleri is an underappreciated emerging global pathogen, despite growing evidence that it is a major contributor of diarrheal illness. Few studies have investigated the occurrence and public health risks that this organism possesses from waterborne exposure routes including through stormwater use. In this study, we assessed the prevalence, virulence potential, and primary sources of stormwater-isolated A. butzleri in fecally contaminated urban stormwater systems. Based on qPCR, A. butzleri was the most common enteric bacterial pathogen [25%] found in stormwater among a panel of pathogens surveyed, including Shiga-toxin producing Escherichia coli (STEC) [6%], Campylobacter spp. [4%], and Salmonella spp. [<1%]. Concentrations of the bacteria, based on qPCR amplification of the single copy gene hsp60, were as high as 6.2 log10 copies/100 mL, suggesting significant loading of this pathogen in some stormwater systems. Importantly, out of 73 unique stormwater culture isolates, 90% were positive for the putative virulence genes cadF, ciaB, tlyA, cjl349, pldA, and mviN, while 50-75% of isolates also possessed the virulence genes irgA, hecA, and hecB. Occurrence of A. butzleri was most often associated with the human fecal pollution marker HF183 in stormwater samples. These results suggest that A. butzleri may be an important bacterial pathogen in stormwater, warranting further study on the risks it represents to public health during stormwater use.

Using a combination of quantitative culture, molecular, and infrastructure data to rank potential sources of fecal contamination in Town Creek Estuary, North Carolina

Estuarine water quality is declining worldwide due to increased tourism, coastal development, and a changing climate. Although well-established methods are in place to monitor water quality, municipalities struggle to use the data to prioritize infrastructure for monitoring and repair and to determine sources of contamination when they occur. The objective of this study was to assess water quality and prioritize sources of contamination within Town Creek Estuary (TCE), Beaufort, North Carolina, by combining culture, molecular, and geographic information systems (GIS) data into a novel contamination source ranking system. Water samples were collected from TCE at ten locations on eight sampling dates in Fall 2021 (n = 80). Microbiological water quality was assessed using US Environmental Protection Agency (U.S. EPA) approved culture-based methods for fecal indicator bacteria (FIB), including analysis of total coliforms (TC), Escherichia coli (EC), and Enterococcus spp. (ENT). The quantitative microbial source tracking (qMST) human-associated fecal marker, HF183, was quantified using droplet digital PCR (ddPCR). This information was combined with environmental data and GIS information detailing proximal sewer, septic, and stormwater infrastructure to determine potential sources of fecal contamination in the estuary. Results indicated FIB concentrations were significantly and positively correlated with precipitation and increased throughout the estuary following rainfall events (p < 0.01). Sampling sites with FIB concentrations above the U.S. EPA threshold also had the highest percentages of aged, less durable piping materials. Using a novel ranking system combining concentrations of FIB, HF183, and sewer infrastructure data at each site, we found that the two sites nearest the most aged sewage infrastructure and stormwater outflows were found to have the highest levels of measurable fecal contamination. This case study supports the inclusion of both traditional water quality measurements and local infrastructure data to support the current need for municipalities to identify, prioritize, and remediate failing infrastructure.

Detection limit of FT-IR-based bacterial typing based on optimized sample preparation and typing model

Accurate and efficient bacterial typing methods are crucial to microbiology. Fourier transform infrared (FT-IR) spectroscopy enables highly distinguishable fingerprint identification of closely related bacterial strains by producing highly specific fingerprints of bacteria, which is increasingly being considered as an alternative to genotypic methods, such as pulsed field gel electrophoresis (PFGE) and whole genome sequencing (WGS), for bacterial typing. Compared with genotypic methods, FT-IR has significant advantages of convenient operation, fast speed, and low cost. Fundamental research into the detection limit based on optimized analytical conditions for FT-IR bacterial typing, which can avoid excessive bacterial culture time or sampling volume, is particularly important, especially in clinical practice. However, the corresponding parameters have not been fully investigated. In this study, we developed a simplified and reliable procedure for sample preparation, optimized the data analysis procedure, and evaluated the FT-IR detection limit based on the above conditions. In particular, we combined the film mold and calcium fluoride plate for sample preparation. We evaluated the detection limit (about 108 CFU/mL) after parameter optimization using hierarchical cluster analysis (HCA) and artificial neural network (ANN). The optimization and evaluation of these key fundamentals will better promote future application of FT-IR-based bacterial typing.

Identification and quantification of Acanthamoeba spp. within seawater at four coastal lagoons on the east coast of Australia

Acanthamoeba is an opportunistic free-living heterotrophic protist that is the most predominant amoeba in diverse ecological habitats. Acanthamoeba causes amoebic keratitis (AK), a painful and potentially blinding corneal infection. Major risk factors for AK have been linked to non-optimal contact lens hygiene practices and Acanthamoeba contamination of domestic and recreational water. This study investigated the incidence and seasonal variation of Acanthamoeba spp. within coastal lagoons located on the eastern coast of Australia and then examined the association between Acanthamoeba and water abiotic factors and bacterial species within the water. Water samples were collected from four intermittently closed and open lagoons (ICOLLs) (Wamberal, Terrigal, Avoca and Cockrone) every month between August 2019 to July 2020 except March and April. qPCR was used to target the Acanthamoeba 18S rRNA gene, validated by Sanger sequencing. Water abiotic factors were measured in situ using a multiprobe metre and 16S rRNA sequencing (V3-V4) was performed to characterise bacterial community composition. Network analysis was used to gauge putative associations between Acanthamoeba incidence and bacterial amplicon sequence variants (ASVs). Among 206 water samples analysed, 79 (38.3%) were Acanthamoeba positive and Acanthamoeba level was significantly higher in summer compared with winter, spring, or autumn (p = 0.008). More than 50% (23/45) water samples of Terrigal were positive for Acanthamoeba which is a highly urbanised area with extensive recreational activities while about 32% (16/49) samples were positive from Cockrone that is the least impacted lagoon by urban development. All sequenced strains belonged to the pathogenic genotype T4 clade except two which were of genotype clades T2 and T5. Water turbidity, temperature, intl1 gene concentration, and dissolved O2 were significantly associated with Acanthamoeba incidence (p < 0.05). The ASVs level of cyanobacteria, Pseudomonas spp., Candidatus spp., and marine bacteria of the Actinobacteria phylum and Acanthamoeba 18S rRNA genes were positively correlated (Pearson's r ≥ 0.14). The presence of Acanthamoeba spp. in all lagoons, except Wamberal, was associated with significant differences in the composition of bacterial communities (beta diversity). The results of this study suggest that coastal lagoons, particularly those in urbanised regions with extensive water recreational activities, may pose an elevated risk to human health due to the relatively high incidence of pathogenic Acanthamoeba in the summer. These findings underscore the importance of educating the public about the rare yet devastating impact of AK on vision and quality of life, highlighting the need for collaborative efforts between public health officials and educators to promote awareness and preventive measures, especially focusing lagoons residents and travellers.