Phage resistance in Klebsiella pneumoniae and bidirectional effects impacting antibiotic susceptibility.

OBJECTIVES: Bacteriophage (phage) therapy is a promising anti-infective option to combat antimicrobial resistance. However, the clinical utilization of phage therapy has been severely compromised by the potential emergence of phage resistance. Although certain phage resistance mechanisms can restore bacterial susceptibility to certain antibiotics, a lack of knowledge of phage resistance mechanisms hinders optimal use of phages and their combination with antibiotics. METHODS: Genome-wide transposon screening was performed with a mutant library of Klebsiella pneumoniae MKP103 to identify phage pKMKP103_1-resistant mutants. Phage-resistant phenotypes were evaluated by time-kill kinetics and efficiency of plating assays. Phage resistance mechanisms were investigated with adsorption, one-step growth, and mutation frequency assays. Antibiotic susceptibility was determined with broth microdilution and population analysis profiles. RESULTS: We observed a repertoire of phage resistance mechanisms in K pneumoniae, such as disruption of phage binding (fhuA::Tn and tonB::Tn), extension of the phage latent period (mnmE::Tn and rpoN::Tn), and increased mutation frequency (mutS::Tn and mutL::Tn). Notably, in contrast to the prevailing view that phage resistance re-sensitizes antibiotic-resistant bacteria, we observed a bidirectional steering effect on bacterial antibiotic susceptibility. Specifically, rpoN::Tn increased susceptibility to colistin while mutS::Tn and mutL::Tn increased resistance to rifampicin and colistin. DISCUSSION: Our findings demonstrate that K pneumoniae employs multiple strategies to overcome phage infection, which may result in enhanced or reduced antibiotic susceptibility. Mechanism-guided phage steering should be incorporated into phage therapy to better inform clinical decisions on phage-antibiotic combinations.

Low-cost monitoring systems for urban water management: Lessons from the field.

Sound urban water management relies on extensive and reliable monitoring of water infrastructure. As low-cost sensors and networks have become increasingly available for environmental monitoring, urban water researchers and practitioners must consider the benefits and disadvantages of such technologies. In this perspective paper, we highlight six technical and socio-technological considerations for low-cost monitoring technology to reach its full potential in the field of urban water management, including: technical barriers to implementation, complementarity with traditional sensing technologies, low-cost sensor reliability, added value of produced information, opportunities to democratize data collection, and economic and environmental costs of the technology. For each consideration, we present recent experiences from our own work and broader literature and identify future research needs to address current challenges. Our experience supports the strong potential of low-cost monitoring technology, in particular that it promotes extensive and innovative monitoring of urban water infrastructure. Future efforts should focus on more systematic documenting of experiences to lower barriers to designing, implementing, and testing of low-cost sensor networks, and on assessing the economic, social, and environmental costs and benefits of low-cost sensor deployments.

BioRTC model enables exploration of real time control strategies for stormwater biofilters.

Biofilters with real time control (RTC) have great potential to remove microbes from stormwater to protect human health for uses such as swimming and harvesting. However, RTC strategies need to be further explored and optimised for each specific location or end-use. This paper demonstrates that the newly developed BioRTC model can fulfil this requirement and allow effective and efficient exploration of the potential of RTC applications. We describe the development of BioRTC as the first RTC model for stormwater biofilters, including: selection of a 'base' model for microbial removal prediction, its modification to include RTC capabilities, as well as calibration and validation. BioRTC adequately predicted the performance of two previously developed RTC strategies, with Nash Sutcliffe Efficiency (Ec) ranging from 0.65 to 0.80. In addition, high parameter transferability was demonstrated during model validation, where we employed the parameter sets calibrated for another biofilter study without RTC to predict the performance of RTC biofilters. We then employed the BioRTC model to explore RTC applications on a hypothetical biofilter system located at the outlet of an existing catchment. With different scenarios, we tested the impact of input parameters such as RTC set-points and design characteristics, and evaluated the influence of operational conditions on the microbial removal performance of the hypothetical biofilter with RTC. The results showed that strategy rules, set-point values, and biofilter design all govern the performance of RTC biofilters, and that operational conditions could impact the suitability of different RTC strategies. Particularly, the presence of Pareto fronts established that muti-objective optimisation is necessary to balance competing needs. These results underscore the importance of RTC, which allows for local experimentation, climate change adaptation, and adjustment to changing demands for the harvested water. Furthermore, they illustrate the practical use of the newly developed BioRTC model, enabling researchers and practitioners to explore and assess potential RTC strategies and scenarios quickly and cost-effectively.

A Low-Cost, Low-Power Water Velocity Sensor Utilizing Acoustic Doppler Measurement.

Current commercial sensors to monitor water flow velocities are expensive, bulky, and require significant effort to install. Low-cost sensors open the possibility of monitoring storm and waste water systems at a much greater spatial and temporal resolution without prohibitive costs and resource investment. To aid in this, this work developed a low-cost, low-power velocity sensor based on acoustic Doppler velocimetry. The sensor, costing less than 50 USD is open-source, open-hardware, compact, and easily interfaceable to a wide range of data-logging systems. A freely available sensor design at this price point does not currently exist, and its novelty is in enabling high-resolution real-time monitoring schemes. The design is capable of measuring water velocities up to 1200 mm/s. The sensor is characterised and then verified in an in-field long-term test. Finally, the data from this test are then used to evaluate the performance of the sensor in a real-world scenario. The analysis concludes that the sensor is capable of effectively measuring water velocity.

The feasibility of SARS-CoV-2 surveillance using wastewater and environmental sampling in Indonesia.

BACKGROUND: Wastewater-based epidemiology (WBE) surveillance as an early warning system (EWS) for monitoring community transmission of SARS-CoV-2 in low- and middle-income country (LMIC) settings, where diagnostic testing capacity is limited, needs further exploration. We explored the feasibility to conduct a WBE surveillance in Indonesia, one of the global epicenters of the COVID-19 pandemic in the middle of 2021, with the fourth largest population in the world where sewer and non-sewered sewage systems are implemented. The feasibility and resource capacity to collect samples on a weekly or fortnightly basis with grab and/or passive sampling methods, as well as to conduct qualitative and quantitative identification of SARS-CoV-2 ribonucleic acid (RNA) using real-time RT-PCR (RT-qPCR) testing of environmental samples were explored. MATERIALS AND METHODS: We initiated a routine surveillance of wastewater and environmental sampling at three predetermined districts in Special Region of Yogyakarta Province. Water samples were collected from central and community wastewater treatment plants (WWTPs), including manholes flowing to the central WWTP, and additional soil samples were collected for the near source tracking (NST) locations (i.e., public spaces where people congregate). RESULTS: We began collecting samples in the Delta wave of the COVID-19 pandemic in Indonesia in July 2021. From a 10-week period, 54% (296/544) of wastewater and environmental samples were positive for SARS-CoV-2 RNA. The sample positivity rate decreased in proportion with the reported incidence of COVID-19 clinical cases in the community. The highest positivity rate of 77% in week 1, was obtained for samples collected in July 2021 and decreased to 25% in week 10 by the end of September 2021. CONCLUSION: A WBE surveillance system for SARS-CoV-2 in Indonesia is feasible to monitor the community burden of infections. Future studies testing the potential of WBE and EWS for signaling early outbreaks of SARS-CoV-2 transmissions in this setting are required.

Riparian buffers: Disrupting the transport of E. coli from rural catchments to streams.

High levels of E. coli and associated faecal microbes in waterways as a result of agricultural and residential land use can pose environmental, human health, and economic risks. This study aims to understand the impacts of land use, climatic variables, and riparian buffers on in-stream E. coli concentrations. Flow, temperature, and E. coli were monitored during three sampling campaigns within eleven independent catchments. These catchments have varying land use and extents of riparian buffer coverage. Results showed that catchments with predominantly agricultural and residential land uses (average = 349.7 MPN/100 mL) had higher E. coli concentrations than predominantly forested catchments (average = 111.8 MPN/100 mL). However, there were no statistically significant differences in E. coli concentrations between the agricultural and residential land uses. Riparian buffers appear to reduce E. coli concentrations in streams, as indicated by significant negative correlations between in-stream E. coli concentrations with the riparian buffer areal coverage (Pearson's r = -0.95, Spearman's ρ = -0.90) and the ratio of buffer length to stream length (Pearson's r = -0.87, Spearman's ρ = -0.90). We find that riparian buffers potentially disrupt transport pathways that govern E. coli movement, which in-turn can affect the concentration-discharge relationship. This reinforces the importance of protecting and restoring riparian buffers along drainage lines in agricultural and rural-residential catchments to improve downstream microbial water quality.

Performance analysis of a stormwater green infrastructure model for flow and water quality predictions.

Nature-based solutions or Green infrastructure (GI) used for managing stormwater pollution are growing in popularity across the globe. Stormwater GI models are important tools to inform the planning of these systems (type, design, size), in the most efficient and cost-effective manner. MUSIC, an example of such a tool, uses regression and first order decay models. Studies validating MUSIC model performance are, however, scarce, hindering future model development and transferability of the model for systems operating under different design and climatic conditions. To close this gap, this paper evaluates MUSIC for a field scale bioretention system, stormwater wetland and vegetated swale operating under Singapore tropical climate. The treatment modules were able to simulate outflows and effluent pollutant concentrations reasonably well for cumulative event volumes (mostly within ±25%) and cumulative TP and TN loads (within ±30%). Outflow TSS loads were significantly under-estimated as a result of greater variability in measured TSS concentrations across events. The findings indicate that simple empirical models such as MUSIC can be transferred to different regions provided that management decisions are based on long-term modelling efforts. The modules generally simulated the outflow hydrographs and pollutographs of the different inflow and drying/wetting conditions relatively poorly.

Interactive effect of temperature and plant species on nitrogen cycling and treatment in stormwater biofiltration systems.

Stormwater biofiltration systems (also known as biofilters, bioretention, rain gardens) are engineered nature-based solutions, which help mitigate aquatic nitrogen pollution arising from storm runoff. These systems are being increasingly used in a range of climates across the world. A decline in treatment performance is frequently observed in cold weather conditions. While plant species comprise an important design factor influencing system performance, the effect of temperature on the fate of dissolved nitrogen forms, namely ammonium (NH4+) and nitrate (NO3-), in the presence of different plant species in these systems remains unclear. A large scale laboratory experiment was undertaken that measured potential rates of nitrification, denitrification and dissimilatory nitrate reduction to ammonium (DNRA) as well as the microbial community structure to investigate nitrogen fate and hence removal under two different temperature conditions (2 °C and 15 °C) in the presence of four distinct plant species. The results indicate that lower nitrification rates (reduced by a factor of 4) coupled with potential media NH4+ desorption could be contributing to reduced NH4+ removal during cold conditions. Planting with species exhibiting good nutrient uptake capacity can reduce the extent of this performance decline. While NO3- reduction generally remains problematic during cold weather (<0 to 55% reduction), which may not be significantly different from warmer periods, the study demonstrated that the denitrification potential and gene abundance (nap, nar, NirS, norB, nosZ) to be higher than those of nitrification (amoA). Denitrification may not proceeding at optimal rates due to lack of conducive environmental conditions. Nitrogen transformation via DNRA was found to be relatively insignificant. Future studies should investigate the potential of employing cold-resilient plant species to maintain both NH4+ and NO3- removal in cold weather conditions.

Monitoring of SARS-CoV-2 in sewersheds with low COVID-19 cases using a passive sampling technique.

Monitoring SARS-CoV-2 RNA in sewer systems, upstream of a wastewater treatment plant, is an effective approach for understanding potential COVID-19 transmission in communities with higher spatial resolutions. Passive sampling devices provide a practical solution for frequent sampling within sewer networks where the use of autosamplers is not feasible. Currently, the design of upstream sampling is impeded by limited understanding of the fate of SARS-CoV-2 RNA in sewers and the sensitivity of passive samplers for the number of infected individuals in a catchment. In this study, passive samplers containing electronegative membranes were applied for at least 24-h continuous sampling in sewer systems. When monitoring SARS-CoV-2 along a trunk sewer pipe, we found RNA signals decreased proportionally to increasing dilutions, with non-detects occurring at the end of pipe. The passive sampling membranes were able to detect SARS-CoV-2 shed by >2 COVID-19 infection cases in 10,000 people. Moreover, upstream monitoring in multiple sewersheds using passive samplers identified the emergence of SARS-CoV-2 in wastewater one week ahead of clinical reporting and reflected the spatiotemporal spread of a COVID-19 cluster within a city. This study provides important information to guide the development of wastewater surveillance strategies at catchment and subcatchment levels using different sampling techniques.

Comparison of Auto Sampling and Passive Sampling Methods for SARS-CoV-2 Detection in Wastewater.

Wastewater-based surveillance is emerging as an important tool for the COVID-19 pandemic trending. Current methods of wastewater collection, such as grab and auto-composite sampling, have drawbacks that impede effective surveillance, especially from small catchments with limited accessibility. Passive samplers, which are more cost-effective and require fewer resources to process, are promising candidates for monitoring wastewater for SARS-CoV-2. Here, we compared traditional auto sampling with passive sampling for SARS-CoV-2 detection in wastewater. A torpedo-style 3D-printed passive sampler device containing both cotton swabs and electronegative filter membranes was used. Between April and June 2021, fifteen passive samplers were placed at a local hospital's wastewater outflow alongside an autosampler. Reverse transcription and quantitative polymerase chain reaction (RT-qPCR) was used to detect SARS-CoV-2 in the samples after processing and RNA extraction. The swab and membrane of the passive sampler showed similar detection rates and cycle threshold (Ct) values for SARS-CoV-2 RNA for the N1 and N2 gene targets. The passive method performed as well as the grab/auto sampling, with no significant differences between N1 and N2 Ct values. There were discrepant results on two days with negative grab/auto samples and positive passive samples, which might be related to the longer duration of passive sampling in the study. Overall, the passive sampler was rapid, reliable, and cost-effective, and could be used as an alternative sampling method for the detection of SARS-CoV-2 in wastewater.

Passive Sampling of SARS-CoV-2 for Wastewater Surveillance.

The shedding of pathogens by infected humans enables the use of sewage monitoring to conduct wastewater-based epidemiology (WBE). Although most WBE studies use data from large sewage treatment plants, timely data from smaller catchments are needed for targeted public health action. Traditional sampling methods, like autosamplers or grab sampling, are not conducive to quick ad hoc deployments and high-resolution monitoring at these smaller scales. This study develops and validates a cheap and easily deployable passive sampler unit, made from readily available consumables, with relevance to the COVID-19 pandemic but with broader use for WBE. We provide the first evidence that passive samplers can be used to detect SARS-CoV-2 in wastewater from populations with low prevalence of active COVID-19 infections (0.034 to 0.34 per 10,000), demonstrating their ability for early detection of infections at three different scales (lot, suburb, and city). A side by side evaluation of passive samplers (n = 245) and traditionally collected wastewater samples (n = 183) verified that the passive samplers were sensitive at detecting SARS-CoV-2 in wastewater. On all 33 days where we directly compared traditional and passive sampling techniques, at least one passive sampler was positive when the average SARS-CoV-2 concentration in the wastewater equaled or exceeded the quantification limit of 1.8 gene copies per mL (n = 7). Moreover, on 13 occasions where wastewater SARS-CoV-2 concentrations were less than 1.8 gene copies per mL, one or more passive samplers were positive. Finally, there was a statistically significant (p < 0.001) positive relationship between the concentrations of SARS-CoV-2 in wastewater and the levels found on the passive samplers, indicating that with further evaluation, these devices could yield semi-quantitative results in the future. Passive samplers have the potential for wide use in WBE with attractive feasibility attributes of cost, ease of deployment at small-scale locations, and continuous sampling of the wastewater. Further research will focus on the optimization of laboratory methods including elution and extraction and continued parallel deployment and evaluations in a variety of settings to inform optimal use in wastewater surveillance.

A Low-Cost Water Depth and Electrical Conductivity Sensor for Detecting Inputs into Urban Stormwater Networks.

High-resolution data collection of the urban stormwater network is crucial for future asset management and illicit discharge detection, but often too expensive as sensors and ongoing frequent maintenance works are not affordable. We developed an integrated water depth, electrical conductivity (EC), and temperature sensor that is inexpensive (USD 25), low power, and easily implemented in urban drainage networks. Our low-cost sensor reliably measures the rate-of-change of water level without any re-calibration by comparing with industry-standard instruments such as HACH and HORIBA's probes. To overcome the observed drift of level sensors, we developed an automated re-calibration approach, which significantly improved its accuracy. For applications like monitoring stormwater drains, such an approach will make higher-resolution sensing feasible from the budget control considerations, since the regular sensor re-calibration will no longer be required. For other applications like monitoring wetlands or wastewater networks, a manual re-calibration every two weeks is required to limit the sensor's inaccuracies to ±10 mm. Apart from only being used as a calibrator for the level sensor, the conductivity sensor in this study adequately monitored EC between 0 and 10 mS/cm with a 17% relative uncertainty, which is sufficient for stormwater monitoring, especially for real-time detection of poor stormwater quality inputs. Overall, our proposed sensor can be rapidly and densely deployed in the urban drainage network for revolutionised high-density monitoring that cannot be achieved before with high-end loggers and sensors.

Stormwater herbicides removal with a solar-driven advanced oxidation process: A feasibility investigation.

The solar driven advanced oxidation process (AOP) has the potential to be developed as a passive stormwater post-treatment method. Despite its widespread studies in wastewater treatment, the applicability of the process for micropollutant removal in stormwater (which has very different chemical properties from wastewater) is still unknown. This paper investigated the feasibility of three different AOP processes for the degradation of two herbicides (diuron and atrazine) in pre-treated stormwater: (i) photoelectrochemical oxidation (PECO), (ii) electrochemical oxidation (ECO), and (iii) photocatalytic oxidation (PCO). The durability of different anode materials, the effects of catalyst loading, and solar photo- and thermal impacts under different applied voltages were studied. Boron-doped diamond (BDD) was found to be the most durable anode material compared to carbon fiber and titanium foil for long-term operation. Due to the very low electroconductivity of stormwater, a high voltage was required, causing severe oxidation of the carbon fiber material. PECO achieved the best degradation results compared to ECO and PCO, with over 90% degradation of both herbicides in 2 h under 5 V, following a first-order decay process (with a half-life value of 0.40 h for diuron and 0.58 h for atrazine). The voltage increase had a positive impact on the oxidation processes, with 5 V found to be the optimal applied voltage, while catalyst loading had a negligible effect. Interestingly, the solar thermal effect plays a dominant role in enhancing the performance of the PECO process, which indicates the potential of integrating a photovoltaic chamber with a PECO system to harness both the light and heat of solar energy for stormwater treatment.

Draft Genome Sequences of Eight Campylobacter volucris Isolates from Freshwater Sources in Victoria, Australia.

Campylobacter spp. can survive and be transmitted from a range of environments. Here, we examine eight draft genome sequences of Campylobacter volucris, identified as part of an examination of waterborne Campylobacter species. This is the first report of environmental survival of C. volucris outside gull species.

BoSL FAL pump: A small, low-cost, easily constructed, 3D-printed peristaltic pump for sampling of waters.

Water sampling is an essential undertaking for water utilities and agencies to protect and enhance our natural resources. The high variability in water quality, however, often necessitates a spatially distributed sampling program which is impeded by high-cost and large sampling devices. This paper presents the BoSL FAL Pump - a low-cost, easily constructed, 3D-printed peristaltic pump which can be made from commonly available components and is sized to suit even the most space constrained installations. The pump is 38 mm in height and 28 mm in diameter, its components cost $19 AUD and the construction time is just 12 min (excluding 3D printing times). The pump is driven by a direct current motor which is commonly available, cheap and allows for flexibility in the energy supply (5-12 V). Optionally, the pump has a Hall effect sensor and magnet to detect rotation rates and pumping volumes to improve the accuracy of pumping rates/volumes. The pump can be easily controlled by commonly available microcontrollers, as demonstrated by this paper which implements the ATmega328P on the Arduino Uno R3. This paper validates the pump for long-term deployments at flow rates of up to 13 mL per minute in 0.14 mL volume increments at accuracy levels of greater than 99%. The pump itself is scalable, allowing for a wider range of pumping rates when, for example, large volume samples are required for pathogen and micropollutant detection.

The impact of stormwater biofilter design and operational variables on nutrient removal - a statistical modelling approach.

Biofiltration systems can help mitigate the impact of urban runoff as they can treat, retain and attenuate stormwater. It is important to select the optimal design characteristics of biofilters (e.g., vegetation, filter media depth) to ensure high treatment performance. Operational conditions (e.g., infiltration rate) can also lead to significant changes in biofilter treatment performance over time. The impact of specific operational conditions on water quality treatment performance of stormwater biofilters is still not well understood. Furthermore, despite the importance of design characteristics and operational conditions on biofilter treatment performance, there is a lack of models that can be used to determine the optimal design and operation. In this paper, we developed a series of statistical models to predict the Total Phosphorus (TP) and Total Nitrogen (TN) removal performance of stormwater biofilters using various numbers of design characteristics and operational conditions. These statistical models were tested using data collected from four extensive laboratory-scale biofilter column studies. It was found that all models performed relatively well with a Nash-Sutcliffe Efficiency (NSE) of 0.42 - 0.61 for TP and 0.37 - 0.63 for TN. The most important design characteristics were filter media type and depth for TP treatment, and vegetation type and submerged zone depth for TN treatment. In addition, infiltration rate and inflow concentrations were the operational conditions that greatly influence outflow TP and TN concentrations from stormwater biofilters. As such, these variables need to be carefully considered when designing and operating stormwater biofilters. Sensitivity analysis results indicate that the model was quite sensitive to all regression coefficients and intercepts. Additional modelling exercises show that the model could be further simplified by reducing the number of cross-correlated parameters. These models can be used by practitioners for not just optimising the design, but also operating biofilters using real-time monitoring and control to achieve optimum performance.

A spatial planning-support system for generating decentralised urban stormwater management schemes.

Current Water Sensitive Urban Design (WSUD) models are either purely technical or overly simplified, lacking consideration of urban planning and stakeholder preferences to adequately support stakeholders. We developed the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), which integrates stormwater management with urban planning to support the design and implementation of WSUD. This study specifically describes and tests UrbanBEATS' WSUD Planning Module, which combines spatial analysis, infrastructure design, preference elicitation and Monte Carlo methods to generate feasible stormwater management and harvesting infrastructure options in greenfield and existing urban environments. By applying UrbanBEATS to a real-world greenfield development case study in Melbourne, Australia (with data sourced from the project's water management plans and design consultants), we explore the variety of options generated by the model and analyse them collectively to demonstrate that UrbanBEATS can design similar WSUD systems (e.g. select suitable technology types, their sizes and locations) to actual infrastructure choices.

An in situ assembled WO3-TiO2 vertical heterojunction for enhanced Z-scheme photocatalytic activity.

The face-to-face contact of a vertical heterojunction is beneficial to charge interaction in photocatalysis. However, constructing a vertical heterojunction with uncompromised redox ability still remains a challenge. Herein, we report the successful synthesis of a WO3-TiO2 vertical heterojunction via establishing an internal electric field across the interface. Experimental investigation and computational simulations reveal that strong electric coupling occurs at the WO3-TiO2 interface forming an internal electric field. The internal electric field induces a Z-scheme charge-carrier transfer through the heterojunction under light irradiation, which leads to effective charge separation and maintains high reaction potentials of charge-carriers. The improved photocatalytic activity of the WO3-TiO2 heterojunction is proved by enhanced generation of reactive oxygen species and accelerated Escherichia coli (E. coli) disinfection. This study provides new insights into understanding and designing Z-scheme heterogeneous photocatalysts.

Validation and uncertainty analysis of a stormwater biofilter treatment model for faecal microorganisms.

Stormwater biofilters, also known as rain gardens or bioretention systems, are effective stormwater treatment systems. This paper presents the validation, sensitivity and uncertainty analyses of a model for microbial removal in stormwater biofilters. The model, previously developed based on a rather limited laboratory study, was fully validated using the data collected in extensive laboratory experiments and field tests. The lab-scale and field-scale systems used for validation were of various designs (e.g., system size, plant type, media type), and have been operated under a wide range of operational conditions (e.g., length of antecedent dry period, and the inflow volume and concentration). For each tested biofilter design, the predicted E. coli concentrations in biofilters' outflow showed relatively good agreement with the measured ones: e.g., Nash-Sutcliffe Efficiency (Ec) ranged from 0.50 to 0.60 for the laboratory tests, and Ec = 0.55 for the field system. The results from sensitivity analysis confirmed the significance of adsorption and desorption processes, and also revealed the impact of temperature on microbial die-off (which was not fully represented in the model development stage). Finally, parameter transferability from one system to another with similar design was examined, achieving generally promising Ec values (0.04-0.56 with the best-fit parameter set for the other system; maximum value: 0.46-0.63) and acceptable uncertainties (intersection between prediction uncertainty band and observation: 50%-97%). Most importantly, the prediction of E. coli outflow concentrations from the field system was reasonably good when laboratory-determined parameter values were adopted: with the best-fit parameter set for the lab-scale system, Ec = 0.39; maximum Ec = 0.55; intersection between prediction and observation = 83%. These results suggested that the very rare biofilter model for microbial removal could provide reliable prediction for large scale field systems, by simply calibrating parameters with limited laboratory-scale experiments.

Salmonella from a Microtidal Estuary Are Capable of Invading Human Intestinal Cell Lines.

Faecal contamination poses health risks for the recreational users of urban estuaries. However, our understanding of the potential pathogenicity of faecal microbes in these environments is limited. To this end, a study was conducted to understand the spatial and seasonal distribution of Salmonella in water and sediments of the Yarra River estuary, Melbourne, Australia. Among 210 samples in total, culturable Salmonella were recovered from 27%, 17%, and 19% of water, bank, and bed sediment samples, respectively. The combined detection increased from 15% in winter to 32% in summer (p < 0.05) indicating seasonal variation as potential part of public health risk assessments. Further, pathogenic potential of the Salmonella isolates was characterised via the quantification of attachment and invasion capacity using human epithelial colorectal cell line Caco-2 on a subset of isolates (n = 62). While all of these isolates could attach and invade Caco-2 cells, 52% and 13% of these showed greater attachment and invasiveness, respectively, than the corresponding mean values for S. Typhimurium ATCC14028 control. Isolates from winter were on average more invasive (seven out of eight isolates with the highest invasiveness recovered from the colder sampling period) than the isolates from summer, and Salmonella collected during summer showed lower invasion (p < 0.05) compared with the control. Similar low invasion compared with the same control was observed for isolates recovered from bank sediment (p < 0.05). While the higher prevalence in summer may imply higher risks during these peak recreational periods, it is essential that this information is used in combination with quantitative microbial risk assessments to fully understand the health risks posed by Salmonella in microtidal estuaries.