1. Introduction
Faecal indicator bacteria have been used for over a century to indicate the faecal contamination of water and associated health risks [1]. While useful as indicators of faecally transmitted pathogens, reliance on E. coli and enterococci as proxies can miss out the presence of other pathogens including pathogens of a non-faecal origin. The WHO guidelines [2] recommend a risk-based approach to consider pathogens that are not necessarily and almost exclusively associated with faecal contamination. Non-faecally transmitted bacteria in recreational waters pose significant health risks to users, underscoring the limitations of relying solely on faecal indicator bacteria (FIB) to assess the water quality. These bacteria, which originate from sources other than faecal contamination, can include environmental pathogens such as Vibrio spp., Pseudomonas aeruginosa, and Legionella spp., as well as opportunistic bacteria that thrive in aquatic ecosystems [3,4,5]. In fact, a recent report from the Centres for Disease Control and Prevention (CDC) [6] shows that these organisms were the main cause of waterborne illness in treated recreational water between 2015 and 2019. All these pathogens can enter recreational waters through various sources and pathways. For instance, Vibrio species thrive in warm, brackish, or marine environments, and climate change, with increased water temperatures, is also an emerging factor for increases in Vibrio spp. [7]. Similarly, bacteria such as Pseudomonas aeruginosa can persist in sediments or biofilms, where they are shielded from environmental stressors [8]. Human activity also plays a role; the introduction of skin flora and the use of improperly treated recreational water features, such as pools or water parks, can amplify the presence of these bacteria [9].
While it is known that exposure to FIB can lead to gastrointestinal illness, exposure to non-faecally transmitted bacteria can lead to a range of health problems for recreational water users. These include skin and soft tissue infections, such as cellulitis, dermatitis, or, in severe cases, necrotising infections caused by pathogens like Vibrio vulnificus or Pseudomonas aeruginosa [10]. Contact with contaminated water can also result in ear, eye, and respiratory issues, including swimmer’s ear (otitis externa) [11] and respiratory illnesses linked to Legionella exposure [12]. For immunocompromised individuals, these pathogens may lead to systemic infections, including sepsis, particularly if the skin barrier is compromised.
The presence of these pathogens presents a challenge for water quality monitoring, which relies on FIB such as E. coli or enterococci [2,13]. As a result, a water body considered safe based on FIB levels may still harbour significant health risks from environmental bacteria. Additionally, the standard culture methods for determining FIB for the water quality assessment take over 24 h for the results, meaning the water quality is only known after exposure. In addition, sampling is not performed continuously so discrete points are all that regulators can use [14]. Moreover, by focusing solely on FIB, it is possible that other pathogens that are not necessarily of a faecal nature may go undetected. These drawbacks to the current culture-based approaches highlight the need for not only rapid, but also more complete solutions with the ability to monitor the water quality at many locations and at different times and to better indicate a broader set of pathogens.
A rapid and simple test of bacterial water quality would, therefore, be a very useful tool. Previous studies have suggested that measuring the endotoxin (lipopolysaccharide (LPS)), present in the outer membrane of Gram-negative bacteria and some cyanobacteria, may be a useful technique for rapidly determining the bacterial biomass and quality of water [15,16,17]. Previous work by our group has shown the applicability of using endotoxins as a marker of the faecal contamination of seawater [18,19] and that measuring endotoxins correlates with inflammatory effects of contaminated water samples [20]. Researchers at Molendotech have developed a near real-time assay (Bacterisk®) to assess the bacterial water quality based on endotoxins, which can be conducted by non-specialist staff in situ. The advantage of measuring endotoxins as an indicator for contaminated water is that the test is specific for LPS, a compound which only naturally occurs in the cell walls of Gram-negative bacteria. LPS comprises a relatively constant proportion of a Gram-negative bacterial cell and Gram-negative bacteria account for 80 to 95% of the prokaryotes found in waters [21]. Moreover, endotoxins could indicate the presence of Gram-negative pathogens not detected by the current culture of total coliforms or E. coli. Therefore, this novel assay would allow the near-real-time assessment of the water quality and the flexibility to sample at several locations and at different time points.
The presence of Anti-Microbial Resistance (AMR) genes (ARGs) is also not covered by FIB monitoring. Leonard et al. [22] emphasise the risk of human exposure to antibiotic-resistant bacteria during recreational activities in coastal waters, where the dissemination of ARGs is influenced by anthropogenic pollution. Recreational water use has been linked to an increased carriage of antimicrobial-resistant organisms [23] and wastewater and natural water systems may act as vectors for the spread of ARGs into recreational waters [24]. Variations in ARG profiles across different recreational water sources have also been demonstrated [25,26]. These findings underscore the critical need to monitor and mitigate ARG contamination to protect both environmental and public health. The rapid assessment of bacterial contamination including non-FIB, that may carry AMR genes, will aid in such monitoring and protect public health.
Previous reports have highlighted the usefulness of rapid Bacterisk technology in determining the coastal water quality [19]. The present study was undertaken to assess the use of Bacterisk as a rapid method to determine bacterial contamination in fresh (inland) waters and to provide evidence for the detection on non-faecal pathogens by this method. This study, therefore, challenges the sole use of FIB detection for the assessment of the water quality.
2. Materials and Methods
2.1. Water Sampling
A total of 36 inland water samples were collected from various river locations in the southwest of England. Briefly, 500 mL samples were taken using sterile bottles 30 cm below the water’s surface in water at least one meter deep. The samples were then transported in the dark and tested within 4 h or stored in a fridge (2–8 °C) and tested no later than 24 h after collection.
2.2. Bacterial Culture Identification (ISO Methods)
Appropriate volumes of each water sample (1 and 10 mL) were aseptically filtered through a 0.45 µm membrane (Whatman, Buckinghamshire, UK) using a 6-branch vacuum manifold (Sartorius, Epsom, UK). Following ISO 9308-2:2012 [27] and ISO 7899-2:2000 [28], membranes were placed on membrane TBX agar (Oxoid, Hampshire, UK) and incubated at 30 °C for 4 h, then at 37 °C for 14 h for the detection of presumptive E. coli, or on Slanetz and Bartley medium (Oxoid, Hampshire, UK) and incubated at 36 °C for 44 h for the detection of presumptive intestinal enterococci. The numbers of colony-forming units (CFU) were then calculated and expressed as CFU/100 mL.
2.3. Bacterisk Assay
The Bacterisk assay (Molendotech Ltd., Brixham, UK;
2.4. Sequencing Analysis
Bacterial gene sequencing was performed by Eurofins using the INVIEW Microbiome Profiling package (DADA2 Version 1.26 (Bioconductor)) with amplification and Illumina MiSeq sequencing of the hypervariable regions in the 16S rRNA gene. This method amplifies and sequences three targets from all DNA samples (16S V1–V3, 16S V3–V4 or 16S V3–V5).
2.5. qPCR
Species-specific quantitative real-time PCR and subsequent amplicon detections were performed on inland water samples by Friends of the Dart and Surfers Against Sewage UK.
2.6. Determination of Uncertainty of Measurement (UoM)
Data on samples using the Bacterisk methodology were analysed in duplicate (A and B). Analysis for Measurement of Uncertainty was performed following the guidelines for expanded uncertainty [29], often referred to as the square root of the sum of the squares multiplied by a coverage factor (k) to the desired confidence.
Sum ((log10B − log10A)2) n = total variance (T)
To calculate the expanded uncertainty, the relative SD is calculated by dividing the standard deviation by the mean of the Log10 observed values and represented as a percentage. To calculate the expanded uncertainty, this relative standard deviation is multiplied by a coverage factor (k) at the required confidence limit. Various values have been suggested for confidence limits both fixed and variable. A standard approach is to use a fixed k value of 2 for a 95% confidence.
2.7. Statistical Analysis
Receiver Operating Characteristics (ROC) analysis was used to determine the optimal threshold ERU value used to discriminate the water quality groups. The ROC curve uses 1 specificity on the x-axis, as calculated:
and sensitivity (true positive) on the y-axis, as calculated:The ROC curve also provides an area under the curve (AUC) value between 0 and 1. The closer the AUC value is to 1, the better the model is at predicting a correct classification, whereas a value of 0.5 represents a model with no ability to predict a correct classification. A model with an AUC of greater than 0.8 is considered acceptable [30].
3. Results
The use of Expanded Uncertainty was used to provide a limit of quantification for the Bacterisk method, i.e., a value where we could provide confidence in the observed result. To aid this, the observed values were plotted as pairs in a low–high format. These data appeared to demonstrate that values begin to show greater significance between 20 and 30 Endotoxin Risk Units (ERU). The expanded uncertainty was calculated for values of 20 ERU, 25 ERU, and 30 ERU; to be included in the assessment, only one of the pairs of results are required to satisfy this limit. The results obtained at the three different k values are shown in Table 1.
From the results obtained in Table 1, the Expanded Uncertainty of Measurement decreases as the lower limit of inclusion increases. Comparing this to results obtained from culture-based microbiology method (in-house testing) values range from 12% to around 25%. Therefore, we used a lower limit of accurate quantification of 25 ERU. The assay tends to saturate at endotoxin levels giving values greater than 180 ERU and this was used as an upper limit of accuracy.
A total of 36 inland water samples were analysed in parallel by the Bacterisk assay to calculate the ERU and by membrane filtration to enumerate the levels of E. coli and intestinal enterococci (CFU/100 mL), according to ISO 9308-1:2014 [27] and ISO 7899-2:2000 [28], respectively. The results were compared with data obtained for coastal water samples collected and analysed by the same methods as published previously [19].
Figure 1 shows the water quality of inland water samples determined by Bacterisk and compared with culture of E. coli and enterococci by the membrane filtration method. As can be seen, many of the samples of inland waters are seen to be of poor quality as assessed by the EU bathing water directive. All the data are presented in Tables S1 and S2 in the Supplementary Data.
The ROC analysis of the data from Figure 1A gave an area under the curve of 0.826 (p = 0.0013), sensitivity of 91.3%, and specificity of 46.2%. The low specificity is due to the Bacterisk assay detecting all Gram-negative bacteria, not just E. coli, and hence alerting to the presence of potential pathogens.
Though intestinal enterococci are also used as a FIB, it is a Gram-positive bacterium, and, in fact, the only current parameter recommended by the most recent WHO guidelines for recreational water quality; there was a correlation between intestinal enterococci and ERU. As can be seen from Figure 1, Bacterisk ERU values could track enterococci and ERU data were a good proxy for enterococci levels.
Due to Bacterisk determining the levels of a Gram-negative molecule (endotoxin) as a marker of water contamination, it not only provides a good correlation with E. coli, but will respond to other Gram-negative bacteria including non-FIB. These may be pathogenic and of concern for human health. These have been included in our data as ‘other’ or ‘off-target’ positives. It is important to understand what these other bacteria are and how they may contribute to the Bacterisk data. To accomplish this, a single location with an ‘off-target’ positive result and two ‘true positive’ results were DNA-sequenced to determine the bacterial flora composition. Representative results are shown in Figure 2. In addition, we obtained qPCR data from samples from one of the river locations. The qPCR data (Figure 3) reveal the presence of several pathogenic species including S. typhi.
A disadvantage of current methods of water quality monitoring, in addition to the time to result delays, is the restriction to single sites and infrequent sampling. We took samples at different times from the river locations we had sampled for the data in Figure 1, Figure 2 and Figure 3 to determine how the water quality might vary with the time and location. The results are shown in Figure 4. It should be noted that the water quality assessed by Bacterisk correlates well with the E. coli culture and that the water quality varies greatly on different dates of sampling, highlighting the flux in water contamination within rivers.
4. Discussion
While FIB are useful for assessing faecal contamination, they are unable to evaluate the broader spectrum of waterborne health risks. A more comprehensive approach to monitoring and managing the recreational water quality is needed to ensure the safety of all users and to address the emerging challenges posed by non-faecally transmitted pathogens. In addition, the current ISO reference methods of enteric pathogenic bacteria detection are time-consuming, expensive, and often insensitive even in fresh faeces [31]. Many recreational and professional beach users may suffer from a degree of immunological compromise and it is vital for beach managers to inform the public as thoroughly as possible of any risks associated with exposure to pathogens and opportunists at the beach [32]. There is thus an urgent need for validated rapid methods to assess the bacterial water quality that can be used in situ and cover a broader range of potential pathogens. This will enable proactive measures to be taken in the event of water contamination, thus protecting human health before use. Additionally, the recent water reuse policies regulated, for example, in the European Union by the recast of the Directive (EU) 2024/3019 of the European Parliament and of the Council of 27 November 2024 concerning urban wastewater treatment, which aim to protect the environment from pathogens, are based on the same slow-reference ISO methods [33]. These methods show an incomplete picture and may take too long when facing an extreme weather event or an environmental disaster assessment.
The current study utilised a rapid bacterial assessment method (Bacterisk) and compared it with E. coli and enterococci cultures to determine the bacterial water quality at different inland river and coastal sites in SW England. Bacterisk, which detects the endotoxin present in Gram-negative bacteria, has been used extensively and validated as a useful method to assess the bacterial contamination of coastal recreational waters [19,34]. In the latter reference, we have shown that while Bacterisk assay results could be used to obtain risk groups that differentiate different levels of water quality, we have used them as a binary classification model to determine whether a water source is either polluted (‘poor’) or clean (‘sufficient or better’), based on the regulatory levels of E. coli (EU bathing directive 2006) from thresholds of the ERU data from Bacterisk. The statistical analysis in the present study showed that the uncertainty of measurement for the Bacterisk assay gave a 95% confidence in measurements above 25 ERU and this level was set as the lower limit of detection for this method. From the ROC analysis, compared with E. coli detection by membrane filtration, the assay provides a high sensitivity (92%) but a lower specificity (46%)—this is expected as the assay is not specific for E. coli, but will also detect other Gram-negative bacteria including potential pathogens that are abundant in river water.
The present study has shown the applicability of this method for the analysis of recreational freshwaters, as was shown previously for coastal waters [19]. In each case, the detection of endotoxins correlates well with conventional FIB E. coli and enterococci and can provide thresholds or cut-offs using the EU bathing water directive guidelines [13]. The Bacterisk results, obtained in 15 min in situ, correlated well with conventional membrane filtration culture results. As Bacterisk is not restricted to detect only E. coli or enterococci, the present faecal indicator bacteria, it highlighted the presence of appreciable levels of other Gram-negative bacteria in river water. The DNA sequence and qPCR analysis of the river water samples testing positive by Bacterisk endotoxin detection, but low for E. coli by culture, confirmed the presence of pathogenic bacteria including Pseudomonas aeruginosa and Salmonella typhi [35,36]. Indeed, recent data from our group have demonstrated the use of Bacterisk in highlighting the presence of Pseudomonas aeruginosa in pools and spas when the E. coli culture was negative. This shows the advantage of being able to detect bacteria other than the current FIB, as other pathogens might be present in water identified as ‘good or sufficient’ by current regulatory standards. Moreover, evidence is presented for the presence of antimicrobial resistance genes in these water samples, highlighting the need to be able to detect the presence of such bacteria.
In addition to the long time to results for bacterial culture, limitations of the faecal indicator paradigm have long been acknowledged [37,38]. Researchers have identified many challenges and limitations to the effective use of both traditional and alternative faecal indicators to characterise risk, identify sources, and evaluate interventions [4,39]. Arguably, one of the most significant limitations is the inconsistent relationships between FIB occurrence, enteric pathogens, and health risks [4,40]. The FIB found to correlate with health risks vary widely by site [41]. Our data presented here (Figure 4) show that the levels of bacterial contamination vary greatly by site and by date. The co-occurrence of enteric pathogens and FIB in ambient waters is inconsistent [40,42] and commonly used FIB are known to persist and grow in the environment [43,44]. Upon introduction to the environment, microbial contaminants are subject to highly variable dispersal and decay processes [39,45]. Pathogens aside, there is also the propagation of resistance genes via recreational water, some of which are in E. coli [22,23,24,25,26]. This study also highlighted the presence of AMR genes in the river samples and recreational water use has been linked to an increased carriage of antimicrobial-resistant organisms [23,24].
The need to differentiate faecal sources in recreational waters led to the emergence of microbial source tracking (MST) methods in the early 2000s, most notably the PCR-based assays that target the 16S rRNA gene in Bacteroides spp. [46,47,48]. Some studies have found strong relationships between the MST markers and enterococci [49], while other studies have found either weak or no relationships [50,51], many of which are discussed in a review by Harwood et al. [52]. One main factor affecting the relationship between enterococci and the relative strength of different sources of faecal contamination is that enterococci can persist and grow in the environment, which can significantly influence their concentrations in recreational water [53]. Enterococci have been shown to persist in fresh water sediments and marine sediments often at high concentrations [54,55]. The decay of bacteria in water depends on many factors including sunlight, temperature, salinity, pH, etc., [56]. Previous studies have shown that Bacterisk ERU data also correlate well with enterococci culture data [19]. The results presented here also confirm that Bacterisk ERU data correlate with enterococci data from fresh waters. While enterococci do not contain endotoxins, this relationship probably reflects the decay of E. coli and other Gram-negative bacteria providing endotoxins that are detected while enterococci persist. Thus, the detection of endotoxin, a stable molecule present in live and dead bacteria that may persist for days or weeks, is a useful indirect proxy for the presence of enterococci [19].
There is clearly a need for more comprehensive water quality monitoring that extends beyond traditional FIB assessments while protecting public health in recreational waters remains an important goal. Techniques such as nanofluidic quantitative real-time PCR (qPCR) that could detect multiple FIB, MST, and pathogen genes in under 4 h [57] are possible, but their expense, complexity, and necessary expertise required preclude their routine use for direct pathogen detection.
Although FIB remain an essential tool for assessing faecal contamination, a more comprehensive approach to monitoring and managing the recreational water quality is needed to protect public health and address the emerging challenges posed by non-faecally transmitted pathogens. The results from the current study confirm the applicability of endotoxin detection as a rapid method for the risk assessment of the recreational water quality. It is not only rapid (15 min), but will alert to the presence of non-FIB pathogens vital to the protection of human health. The cost per sample for this rapid method is ~GBP 23; this compares well with culture methods which must also include costs of the sample transport and technical staff time and are at least ~GBP 25 per sample. We suggest that such a method could form a key component in the development of the quantitative microbial risk assessment (QMRA) to provide a comprehensive evaluation of the recreational water quality. In addition, it would also allow rapid testing in remote and disaster areas where access to laboratories and water testing facilities is challenging.
5. Conclusions
The faecal contamination of water continues to be a major public health concern, with new challenges necessitating a renewed urgency in developing rapid and reliable methods to detect contamination and prevent human exposures. Non-faecally transmitted bacteria in recreational waters pose significant health risks to users, underscoring the limitations of relying solely on faecal indicator bacteria (FIB) to assess the water quality. Outbreaks linked to these bacterial pathogens often expose gaps in standard monitoring practices, which can leave recreational users unaware of potential dangers. As a result, a water body considered safe based on FIB levels may still harbour significant health risks from environmental bacteria. This study highlights the need for more comprehensive water quality monitoring to extend beyond traditional FIB quantifications. Following the rapid screening and detection especially of ‘non-FIB’, pathogen-specific testing should be incorporated in monitoring programmes, particularly in high-risk recreational waters. Environmental surveillance is also crucial, with factors such as temperature, salinity, and nutrient levels monitored to predict conditions conducive to pathogen proliferation. This study has shown that bacterial endotoxins, measured in near-real-time with the Bacterisk assay, are a reliable marker not only of faecal contamination, but also of the presence of potential pathogens of a non-faecal origin. The portability and ease of use of this assay allows its convenient use to provide data on the water quality at different locations and at different times, providing a comprehensive surveillance tool.
Conceptualization, S.K.J., C.G. and J.B.; methodology, C.G., C.S. and A.W.; software, C.G. and A.W.; validation, C.G., S.K.J., C.S. and J.B.; formal analysis, C.G., A.W. and S.K.J.; investigation, S.K.J. and C.G.; resources, S.K.J. and C.G.; data curation, C.G. and A.W.; writing—original draft preparation, S.K.J., C.G. and J.B.; writing—review and editing, S.K.J., C.G. and J.B.; visualization, S.K.J. and J.B.; supervision, S.K.J.; project administration, C.G. and S.K.J.; funding acquisition, S.K.J. All authors have read and agreed to the published version of the manuscript.
The original contributions presented in this study are included in the article and
We gratefully acknowledge Kirsty Davies, Surfers Against Sewage UK, Kit Cregan, Friends of the Dart and Rachel Salvage, Watershed Investigations for the qPCR data.
Author Christian Good, Alistair White and Simon K. Jackson were employed by the company Molendotech Limited. Author Christopher Seymour was employed by the company Anglian Water. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Footnotes
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Figure 1 Scatter plot displaying the Bacterisk Endotoxin Risk Units against (A) E. coli and (B) enterococci enumerated using the membrane filtration method on TBX agar and S&B agar, respectively, for inland water samples. The chart is split into quadrants based on the ERU threshold (Y axis 50) and (A) E. coli cut-off (X axis 1000 CFU/100 mL), (B) enterococci cut-off (X axis 400 CFU/100 mL). n = 36. TN: true negative, TP: true positive, FN: false negative, OP: off-target positive.
Figure 2 16S RNA sequencing data from inland water samples showing the different genera present in typical samples. OP = Off-target positives; TP = True positives based on E. coli > 1000 CFU/100 mL.
Figure 3 (A) Copy number of independently detected pathogen marker genes in river water samples by qPCR. (B) AMR genes detected from these samples.
Figure 4 Water quality tracking using Bacterisk to measure ERU compared with E. coli along different rivers in SW England at different times.
Expanded Uncertainty of Measurements at 20 ERU, 25 ERU, and 30 ERU.
| ERU Limit | Degrees of Freedom (df) | Fixed k = 2 | Fixed k = 1.96 | Varying k Based on (df) | Expanded UoM |
|---|---|---|---|---|---|
| 20 | 287 | 31.94% | 31.30% | 1.968264 | 31.43% |
| 25 | 249 | 22.41% | 21.97% | 1.969537 | 22.07% |
| 30 | 199 | 15.87% | 15.56% | 1.971957 | 15.65% |
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; Seymour, Christopher 3
; Jackson, Simon K 4 1 Molendotech Limited, Brixham Laboratory, Blackball Lane, Freshwater Quarry, Brixham TQ5 8BA, UK; [email protected] (C.G.); [email protected] (A.W.)
2 National Institute of Health Dr. Ricardo Jorge, Department of Environmental Health, Av. Padre Cruz, 1649-016 Lisboa, Portugal; [email protected], cE3c—Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências da Universidade de Lisboa, Campo Grande 016, 1749-016 Lisboa, Portugal
3 Anglian Water, Kingfisher Way, Hinchingbrooke Business Park, Huntingdon, Cambridgeshire, PE29 6FL, UK; [email protected]
4 Molendotech Limited, Brixham Laboratory, Blackball Lane, Freshwater Quarry, Brixham TQ5 8BA, UK; [email protected] (C.G.); [email protected] (A.W.), School of Biomedical Science, Faculty of Health, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK