Spatial patterns of enzymatic activity in large water bodies: Ship-borne measurements of beta-D-glucuronidase activity as a rapid indicator of microbial water quality

Recent advances of sensing strategies for the detection of β-glucuronidase activity

β-Glucuronidase (β-GLU), a kind of hydrolase, is widely distributed in mammalian tissues, body fluids, and microbiota. Abnormal changes of β-GLU activity are often correlated with the occurrence of diseases and deterioration of water quality. Therefore, detection of β-GLU activity is of great significance in biomedicine and environmental health such as cancer diagnosis and water monitoring. However, the conventional β-GLU activity assay suffers from the limitations of low sensitivity, poor accuracy, and complex procedure. With the development of analytical chemistry, many advances have been made in the detection of β-GLU activity in recent years. The sensors for β-GLU activity detection which have the advantages of rapid and reliable detection have been attracting increased attentions. In this paper, the principles, performances, and limitations of these β-GLU sensors, including colorimetric sensing, fluorescent sensing, electrochemical sensing for the determination of β-GLU activity, have been summarized and discussed. Moreover, the challenges and research trends of β-GLU activity assay are proposed.

Genetic Microbial Source Tracking Support QMRA Modeling for a Riverine Wetland Drinking Water Resource

Riverine wetlands are important natural habitats and contain valuable drinking water resources. The transport of human- and animal-associated fecal pathogens into the surface water bodies poses potential risks to water safety. The aim of this study was to develop a new integrative modeling approach supported by microbial source tracking (MST) markers for quantifying the transport pathways of two important reference pathogens, Cryptosporidium and Giardia, from external (allochthonous) and internal (autochthonous) fecal sources in riverine wetlands considering safe drinking water production. The probabilistic-deterministic model QMRAcatch (v 1.1 python backwater) was modified and extended to account for short-time variations in flow and microbial transport at hourly time steps. As input to the model, we determined the discharge rates, volumes and inundated areas of the backwater channel based on 2-D hydrodynamic flow simulations. To test if we considered all relevant fecal pollution sources and transport pathways, we validated QMRAcatch using measured concentrations of human, ruminant, pig and bird associated MST markers as well as E. coli in a Danube wetland area from 2010 to 2015. For the model validation, we obtained MST marker decay rates in water from the literature, adjusted them within confidence limits, and simulated the MST marker concentrations in the backwater channel, resulting in mean absolute errors of < 0.7 log₁₀ particles/L (Kruskal–Wallis p > 0.05). In the scenarios, we investigated (i) the impact of river discharges into the backwater channel (allochthonous sources), (ii) the resuspension of pathogens from animal fecal deposits in inundated areas, and (iii) the pathogen release from animal fecal deposits after rainfall (autochthonous sources). Autochthonous and allochthonous human and animal sources resulted in mean loads and concentrations of Cryptosporidium and Giardia (oo)cysts in the backwater channel of 3–13 × 10⁹ particles/hour and 0.4–1.2 particles/L during floods and rainfall events, and in required pathogen treatment reductions to achieve safe drinking water of 5.0–6.2 log₁₀. The integrative modeling approach supports the sustainable and proactive drinking water safety management of alluvial backwater areas.

Simple enumeration of Escherichia coli concentrations in river water samples by measuring β-d-glucuronidase activities in a microplate reader

Monitoring of Escherichia coli concentrations in river water (RW) is essential to identify fecal pollution of the river. The objective of this study was to assess the suitability of a novel, simple and high throughput method developed in our laboratory to enumerate E. coli concentrations in RW samples. The method is based on the use of the synthetic substrate specific for the β-d-glucuronidase (GUS) produced by E. coli. GUS activities and E. coli concentrations were monitored at eight selected sites in rivers running through Sapporo, Japan. Because the fluorescence intensities of the synthetic substrate in the RW samples increased linearly over a 4-h incubation period, we could estimate the GUS activities of the RW samples. The GUS activities were highly correlated with E. coli concentrations at >100 most probable numbers 100 mL^-1 with a correlation coefficient of 0.87. The GUS activities of the RW samples collected from all sampling sites fitted well to a single correlation equation, which indicates that it was applicable to the estimation of E. coli concentrations regardless of the sampling sites. This method is simple, rapid, reliable, inexpensive, and high throughput, and is therefore useful for monitoring E. coli in RW.

Intelligent Wide-Area Water Quality Monitoring and Analysis System Exploiting Unmanned Surface Vehicles and Ensemble Learning

Water environment pollution is an acute problem, especially in developing countries, so water quality monitoring is crucial for water protection. This paper presents an intelligent three-dimensional wide-area water quality monitoring and online analysis system. The proposed system is composed of an automatic cruise intelligent unmanned surface vehicle (USV), a water quality monitoring system (WQMS), and a water quality analysis algorithm. An automatic positioning cruising system is constructed for the USV. The WQMS consists of a series of low-power water quality detecting sensors and a lifting device that can collect the water quality monitoring data at different water depths. These data are analyzed by the proposed water quality analysis algorithm based on the ensemble learning method to estimate the water quality level. Then, a real experiment is conducted in a lake to verify the feasibility of the proposed design. The experimental results obtained in real application demonstrate good performance and feasibility of the proposed monitoring system.

New Methods for Microbiological Monitoring at Riverbank Filtration Sites

Water suppliers aim to achieve microbiological stability throughout their supply system by regular monitoring of water quality. Monitoring temporal biomass dynamics at high frequency is time consuming due to the labor-intensive nature and limitations of conventional, cultivation-based detection methods. The goal of this study was to assess the value of new rapid monitoring methods for quantifying and characterizing dynamic fluctuations in bacterial biomass. Using flow cytometry and two precise enzymatic detection methods, bacterial biomass-related parameters were monitored at three riverbank filtration sites. Additionally, the treatment capacity of an ultrafiltration pilot plant was researched using online flow-cytometry. The results provide insights into microbiological quality of treated water and emphasize the value of rapid, easy and sensitive alternatives to traditional bacterial monitoring techniques.

Therapeutic significance of β-glucuronidase activity and its inhibitors: A review

The emergence of disease and dearth of effective pharmacological agents on most therapeutic fronts, constitutes a major threat to global public health and man's existence. Consequently, this has created an exigency in the search for new drugs with improved clinical utility or means of potentiating available ones. To this end, accumulating empirical evidence supports molecular target therapy as a plausible egress and, β-glucuronidase (βGLU) - a lysosomal acid hydrolase responsible for the catalytic deconjugation of β-d-glucuronides has emerged as a viable molecular target for several therapeutic applications. The enzyme's activity level in body fluids is also deemed a potential biomarker for the diagnosis of some pathological conditions. Moreover, due to its role in colon carcinogenesis and certain drug-induced dose-limiting toxicities, the development of potent inhibitors of βGLU in human intestinal microbiota has aroused increased attention over the years. Nevertheless, although our literature survey revealed both natural products and synthetic scaffolds as potential inhibitors of the enzyme, only few of these have found clinical utility, albeit with moderate to poor pharmacokinetic profile. Hence, in this review we present a compendium of exploits in the present millennium directed towards the inhibition of βGLU. The aim is to proffer a platform on which new scaffolds can be modelled for improved βGLU inhibitory potency and the development of new therapeutic agents in consequential.

Tracking the contribution of multiple raw and treated wastewater discharges at an urban drinking water supply using near real-time monitoring of β-d-glucuronidase activity

Past waterborne outbreaks have demonstrated that informed vulnerability assessment of drinking water supplies is paramount for the provision of safe drinking water. Although current monitoring frameworks are not designed to account for short-term peak concentrations of fecal microorganisms in source waters, the recent development of online microbial monitoring technologies is expected to fill this knowledge gap. In this study, online near real-time monitoring of β-d-glucuronidase (GLUC) activity was conducted for 1.5 years at an urban drinking water intake impacted by multiple point sources of fecal pollution. Parallel routine and event-based monitoring of E. coli and online measurement of physico-chemistry were performed at the intake and their dynamics compared over time. GLUC activity fluctuations ranged from seasonal to hourly time scales. All peak contamination episodes occurred between late fall and early spring following intense rainfall and/or snowmelt. In the absence of rainfall, recurrent daily fluctuations in GLUC activity and culturable E. coli were observed at the intake, a pattern otherwise ignored by regulatory monitoring. Cross-correlation analysis of time series retrieved from the drinking water intake and an upstream Water Resource Recovery Facility (WRRF) demonstrated a hydraulic connection between the two sites. Sewage by-passes from the same WRRF were the main drivers of intermittent GLUC activity and E. coli peaks at the drinking water intake following intense precipitation and/or snowmelt. Near real-time monitoring of fecal pollution through GLUC activity enabled a thorough characterization of the frequency, duration and amplitude of peak contamination periods at the urban drinking water intake while providing crucial information for the identification of the dominant upstream fecal pollution sources. To the best of our knowledge, this is the first characterization of a hydraulic connection between a WRRF and a downstream drinking water intake across hourly to seasonal timescales using high frequency microbial monitoring data. Ultimately, this should help improve source water protection through catchment mitigation actions, especially in a context of de facto wastewater reuse.