A biosensor platform for rapid detection of E. coli in drinking water

Advanced diagnostic methods for identification of bacterial foodborne pathogens: contemporary and upcoming challenges

It is a public health imperative to have safe food and water across the population. Foodborne infections are one of the primary causes of sickness and mortality in both developed and developing countries. An estimated 100 million foodborne diseases and 120 000 foodborne illness-related fatalities occur each year in India. Several factors affect foodborne illness, such as improper farming methods, poor sanitary and hygienic conditions at all levels of the food supply chain, the lack of preventative measures in the food processing industry, the misuse of food additives, as well as improper storage and handling. In addition, chemical and microbiological combinations also play a key role in disease development. But recent disease outbreaks indicated that microbial pathogens played a major role in the development of foodborne diseases. Therefore, prompt, rapid, and accurate detection of high-risk food pathogens is extremely vital to warrant the safety of the food items. Conventional approaches for identifying foodborne pathogens are labor-intensive and cumbersome. As a result, a range of technologies for the rapid detection of foodborne bacterial pathogens have been developed. Presently, many methods are available for the instantaneous detection, identification, and monitoring of foodborne pathogens, such as nucleic acid-based methods, biosensor-based methods, and immunological-based methods. The goal of this review is to provide a complete evaluation of several existing and emerging strategies for detecting food-borne pathogens. Furthermore, this review outlines innovative methodologies and their uses in food testing, along with their existing limits and future possibilities in the detection of live pathogens in food.

Nowcasting of fecal coliform presence using an artificial neural network

At least 2 billion people worldwide use drinking water sources that are contaminated with feces, causing waterborne diseases; poor sanitation, poor hygiene, and unsafe drinking water result in a daily death rate of more than 800 children under 5 years of age from diarrheal diseases. This study shows the feasibility of a novel method to nowcast fecal coliforms' (FC) presence in drinking water sources by applying a multilayer perceptron artificial neuron network (MLP-ANN) model. The model gives a binary answer for FC presence or absence in drinking water sources using a minimum of water quality and geographical parameters, which can be monitored in real-time as predictors with low-cost and in-situ equipment. Using 51,400 samples to train, validate and test the model with temperature, pH, electrical conductivity, turbidity, dissolved oxygen, and total dissolved solids (TDS) as water-quality inputs and the water source type and location (as districts in India) as geographical inputs. The model achieved a total accuracy of 92.8% and a sensitivity of 98.2%, meaning that most FC-contaminated samples were classified correctly. In addition, precision reached 93.1%, meaning that most FC-contamination classifications were actually contaminated. The MLP-ANN performed better than the Linear Regression and K-Nearest Neighbors models, with lower accuracies of 90.2% and 91.0%, respectively. The MLP-ANN model could characterize the water quality geospatially, learn from the parameters whether the water is contaminated by FC, and predict with high accuracy on new testing data. This method can be used as a part of a sensor for FC monitoring and management in water, reducing the time gaps between routine lab testing and thus improving drinking water quality and addressing the SDG 6 targets.

Development of magnetic nanoparticle assisted aptamer-quantum dot based biosensor for the detection of Escherichia coli in water samples

The contamination of food and potable water with microorganisms may cause food-borne and water-borne diseases. The common contaminants include Escherichia coli (E. coli), Salmonella sp. etc. The conventional methods for monitoring the water quality for the presence of bacterial contaminants are time-consuming, expensive, and not suitable for rapid on-spot detection in field conditions. In the current study, super paramagnetic iron oxide nanoparticles (SPIONs) were synthesized and conjugated with E. coli specific Aptamer I to detect E. coli cells qualitatively as well as quantitatively. The sludge consisting of E. coli- SPION complex was separated via magnetic separation. The presence of E. coli cells was confirmed with the help of standard techniques and confocal laser scanning microscopy (CLSM) employing Aptamer II conjugated CdTe-MPA quantum dots (QDs). Finally, an ATmega 328P prototype biosensor based on Aptamer II conjugated CdTe MPA QDs exhibited quantitative and qualitative abilities to detect E.coli. This prototype biosensor can even detect low bacterial counts (up to 1 × 10² cfu) with the help of a photodiode and plano-convex lens. Further, the prototype biosensor made up of ultraviolet light-emitting diode (UV LED), liquid crystal display (LCD) and ATmega328Pmicrocontroller offers on-spot detection of E.coli in water samples with high resolution and sensitivity. Similarly, this in-house developed prototype biosensor can also be utilized to detect bacterial contamination in food samples.

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.

The β-galactosidase assay in perspective: Critical thoughts for biosensor development

Recently, the β-galactosidase assay has become a key component in the development of assays and biosensors for the detection of enterobacteria and E. coli in water quality monitoring. The assay has often performed below its maximum potential, mainly due to a poor choice of conditions. In this study we establish a set of optimal conditions and provide a rough estimate of how departure from optimal values reduces the output of the assay potentially decreasing its sensitivity. We have established that maximum response for detecting low cell concentrations requires an induction of the samples using IPTG at a concentration of 0.2 mM during 180 min. Permeabilization of the samples is mandatory as lack of it results in an almost 60% reduction in assay output. The choice of enzyme substrate is critical as different substrates yield products with different extinction coefficients or fluorescence yields. The concentration of substrate used must be high enough (around 3 to 4 times K_m) to ensure that the activity measured is not substrate limited. Finally, as the color/fluorescence of the reaction products is highly dependent on pH, care must be taken to ensure that pH at the time of reading is high enough to provide maximum signal.

Online microbial monitoring of drinking water: How do different techniques respond to contaminations in practice?

Safeguarding the microbial water quality remains a challenge for drinking water utilities, and because of population growth and climate change, new issues arise regularly. To overcome these problems, biostable drinking water production and water reuse will become increasingly important. In this respect, high-resolution online microbial monitoring during treatment and distribution could prove essential. Here, we present the first scientific and practical comparison of multiple online microbial monitoring techniques in which six commercially available devices were set up in a full-scale drinking water production plant. Both the devices' response towards operational changes and contaminations, as well as their detection limit for different contaminations were evaluated and compared. During normal operation, all devices were able to detect abrupt operational changes such as backwashing of activated carbon filters and interruption of the production process in a fast and sensitive way. To benchmark their response to contaminations, the calculation of a dynamic baseline for sensitive separation between noise and events is proposed. In order of sensitivity, enzymatic analysis, ATP measurement, and flow cytometric fingerprinting were the most performant for detection of rain- and groundwater contaminations (0.01 - 0.1 v%). On the other hand, optical classification and flow cytometric cell counts showed to be more robust techniques, requiring less maintenance and providing direct information about the cell concentration, even though they were still more sensitive than plate counting. The choice for a certain technology will thus depend on the type of application and is a balance between sensitivity, price and maintenance. All things considered, a combination of several devices and use of advanced data analysis such as fingerprinting may be of added value. In general, the strategic implementation of online microbial monitoring as early-warning system will allow for intensive quality control by high-frequency sampling as well as a short event response timeframe.

Label-free E. coli detection based on enzyme assay and a microfluidic slipchip

An enzyme assay based method in a microfluidic slipchip was proposed for the rapid and label-free detection of E. coli. The specific target analyte of E. coli was β-d-glucuronidase (GUS) which could catalyze the substrate 6-chloro-4-methyl-umbelliferyl-β-d-glucuronide (6-CMUG) to release the fluorescent molecule 6-chloro-4-methyl-umbelliferyl (6-CMU). E. coli culture, lysis and enzymatic reaction steps could be conducted in a microfluidic slipchip without any pumps and valves, which was tailored for fluorescence detection using a commercial plate reader, to achieve a rapid E. coli test. A mixture of the culture broth, enzyme inducer and E. coli was injected into the chambers on the top layer. A mixture of the substrate and lysis solution was injected into the chambers on the bottom layer. Then, the slipchip was slid to make each chamber independent. E. coli was cultured in the chamber in the LB broth for 2.5 h. After that, the slipchip was slid again to introduce the lysis solution into the culture solution for GUS release and enzyme reaction, and then incubated in the plate reader at 42 °C for another 2.5 h. During incubation, the fluorescence intensity of each chamber was recorded. This proposed label-free method can directly detect E. coli with a low concentration of 8 CFU per chamber within 5 h, thus showing great potential in on-site E. coli detection.

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.

Monitoring Approaches for Faecal Indicator Bacteria in Water: Visioning a Remote Real-Time Sensor for E. coli and Enterococci

A comprehensive review was conducted to assess the current state of monitoring approaches for primary faecal indicator bacteria (FIB) E. coli and enterococci. Approaches were identified and examined in relation to their accuracy, ability to provide continuous data and instantaneous detection results, cost, environmental awareness regarding necessary reagent release or other pollution sources, in situ monitoring capability, and portability. Findings showed that several methods are precise and sophisticated but cannot be performed in real-time or remotely. This is mainly due to their laboratory testing requirements, such as lengthy sample preparations, the requirement for expensive reagents, and fluorescent tags. This study determined that portable fluorescence sensing, combined with advanced modelling methods to compensate readings for environmental interferences and false positives, can lay the foundations for a hybrid FIB sensing approach, allowing remote field deployment of a fleet of networked FIB sensors that can collect high-frequency data in near real-time. Such sensors will support proactive responses to sudden harmful faecal contamination events. A method is proposed to enable the development of the visioned FIB monitoring tool.

Modified Enzyme Substrates for the Detection of Bacteria: A Review

The ability to detect, identify and quantify bacteria is crucial in clinical diagnostics, environmental testing, food security settings and in microbiology research. Recently, the threat of multidrug-resistant bacterial pathogens pushed the global scientific community to develop fast, reliable, specific and affordable methods to detect bacterial species. The use of synthetically modified enzyme substrates is a convenient approach to detect bacteria in a specific, economic and rapid manner. The method is based on the use of specific enzyme substrates for a given bacterial marker enzyme, conjugated to a signalogenic moiety. Following enzymatic reaction, the signalophor is released from the synthetic substrate, generating a specific and measurable signal. Several types of signalophors have been described and are defined by the type of signal they generate, such as chromogenic, fluorogenic, luminogenic, electrogenic and redox. Signalophors are further subdivided into groups based on their solubility in water, which is key in defining their application on solid or liquid media for bacterial culturing. This comprehensive review describes synthetic enzyme substrates and their applications for bacterial detection, showing their mechanism of action and their synthetic routes.

Simple and reliable enumeration of Escherichia coli concentrations in wastewater samples by measuring β-d-glucuronidase (GUS) activities via a microplate reader

Monitoring of Escherichia coli concentrations at wastewater treatment plants (WWTPs) is important to ensure process performance and protect public health. However, conventional E. coli enumeration methods are complicated and time- and labor-consuming. Here, we report a novel simple and reliable method based on β-d-glucuronidase (GUS) activity assay to enumerate E. coli concentrations in wastewater (WW) samples. An aliquot (20 μL) of the medium with fluorogenic enzyme substrate for E. coli and 180 μL of a WW sample were added to one well of a 96-well microplate. The microplate was placed in a microplate reader at 37 °C. To this end, the fluorescence intensity of a fluorogenic enzyme substrate for E. coli was measured every 10 min over 3 h to determine GUS activity. The linear increase in the fluorescence intensity representing the GUS activities showed a positive correlation with E. coli concentrations in wastewater samples. However, the correlation equations were specific to WWTPs, which could be due to the difference in the E. coli population structures among WWTPs. We observed that the wastewater matrix is not a limitation to measure the GUS activity, and a WWTP-specific correlation equation can be used as a calibration curve to estimate the E. coli concentrations in the samples collected from that site. A comparison of the results with those of culture-dependent Colilert method proved that the current method is simple and useful for the enumeration of E. coli concentrations in wastewater samples reliably.

Online microbial fingerprinting for quality management of drinking water: Full-scale event detection

Microbial regrowth during drinking water distribution can result in a variety of problems such as a deviating taste and odor, and may even pose a risk to public health. Frequent monitoring is essential to anticipate events of biological instability, and relevant microbial parameters for operational control of biostability of drinking water should be developed. Here, online flow cytometry and derived biological metrics were used to assess the biological stability of a full-scale drinking water tower during normal and disturbed flow regime. Pronounced operational events, such as switching from drinking water source, and seasonal changes, were detected in the total cell counts, and regrowth was observed despite the short hydraulic residence time of 6-8 h. Based on the flow cytometric fingerprints, the Bray-Curtis dissimilarity was calculated and was developed as unambiguous parameter to indicate or warn for changing microbial drinking water quality during operational events. In the studied water tower, drastic microbial water quality changes were reflected in the Bray-Curtis dissimilarity, which demonstrates its use as an indicator to follow-up and detect microbial quality changes in practice. Hence, the Bray-Curtis dissimilarity can be used in an online setup as a straightforward parameter during full-scale operation of drinking water distribution, and combined with the cell concentration, it serves as an early-warning system for biological instability.

Biological Biosensors for Monitoring and Diagnosis

Quantification and detection of various contaminants in the ecosystem have become critically important in the past few decades due to their exhaustive use in soil and aquatic ecosystems. The contamination by both organic and inorganic contaminants in the ecosystem has drawn attention due to their persistence, biological accumulation, and toxicity. Organic contaminants reach the air, water, food, soil, and other systems through drift mechanism and have detrimental effect on various life systems after entering the food chain, thus interfering the normal biological process of the ecosystem. Inorganic contaminants have less solubility, primarily get adsorbed, and accumulate on lower sediments. The sources of both organic and inorganic contaminants include anthropogenic activities which dispose industrial and sewage effluent directly into water bodies. Most of the contaminants are very much toxic and have tumorigenic, carcinogenic, and mutagenic effect on various life-forms. Biosensors have various prospective and existing applications in the detection of these compounds in the environment by transducing a signal. It also has immense applications in the detection of different contaminants in the food industry, environmental monitoring, disease diagnosis, etc. where reliable and precise analyses are required. This chapter points out a comprehensive glimpse on different biosensors and their characteristics, operating principles, and their designs, based on transduction types and biological components. Efforts have been made to summarize various applications of biosensors in food industry, environmental monitoring, drug delivery systems, and clinical diagnostics etc.

Early detection of E. coli and total coliform using an automated, colorimetric and fluorometric fiber optics-based device

Lack of access to clean water is a major global issue that affects millions of people worldwide. Drinking contaminated water can be extremely hazardous, so it is imperative that it is tested sufficiently. One method commonly used to determine the quality of water is testing for both E. coli and total coliform. Here, we present a cost-effective and automated device which can concurrently test drinking water samples for both E. coli and total coliform using an EPA-approved reagent. Equipped with a Raspberry Pi microcontroller and camera, we perform automated periodic measurements of both the absorption and fluorescence of the water under test over 24 hours. In each test, 100 mL of the water sample is split into a custom designed 40-well plate, where the transmitted blue light and the fluorescent light (under UV excitation) are collected by 520 individual optical fibers. Images of these fiber outputs are then acquired periodically, and digitally processed to determine the presence of the bacteria in each well of the 40-well plate. We demonstrate that this cost-effective device, weighing 1.66 kg, can automatically detect the presence of both E. coli and total coliform in drinking water within ∼16 hours, down to a level of one colony-forming unit (CFU) per 100 mL. Furthermore, due to its automated analysis, this approach is also more sensitive than a manual count performed by an expert, reducing the time needed to determine whether the water under test is safe to drink or not.

Phage based electrochemical detection of Escherichia coli in drinking water using affinity reporter probes

The monitoring of drinking water for indicators of fecal contamination is crucial for ensuring a safe supply. In this study, a novel electrochemical method was developed for the rapid and sensitive detection of Escherichia coli (E. coli) in drinking water. This strategy is based on the use of engineered bacteriophages (phages) to separate and concentrate target E. coli when conjugated with magnetic beads, and to facilitate the detection by expressing gold binding peptides fused alkaline phosphatase (GBPs-ALP). The fusion protein GBPs-ALP has both the enzymatic activity and the ability to directly bind onto a gold surface. This binding-peptide mediated immobilization method provided a novel and simple approach to immobilize proteins on a solid surface, requiring no post-translational modifications. The concentration of E. coli was determined by measuring the activity of the ALP on gold electrodes electrochemically using linear sweep voltammetry (LSV). This approach was successfully applied in the detection of E. coli in drinking water. We were able to detect 105 CFU mL-1 of E. coli within 4 hours. After 9 hours of preincubation, 1 CFU of E. coli in 100 mL of drinking water was detected with a total assay time of 12 hours. This approach compares favorably to the current EPA method and has the potential to be applied to detect different bacteria in other food matrices.

Rapid generation of chemical combinations on a magnetic digital microfluidic array

Combinatorial screening is frequently used to identify chemicals with synergistic effects by measuring the response of biological entities exposed to various chemical-dose combinations. Conventional microwell-based combinatorial screening is resource-demanding, and the closed microfluidics-based screening requires sophisticated fluidic control systems. In this work, we present a novel combinatorial screening platform based on the surface energy trap (SET)-assisted magnetic digital microfluidics. This platform, known as FlipDrop, rapidly generates chemical combinations by coupling two droplet arrays with orthogonal chemical concentration gradients with a simple flip. We have illustrated the working principle of FlipDrop by generating combinations of quantum dots. We have also successfully demonstrated the screening of quantum dot fluorescence resonance energy transfer (QD-FRET) on the FlipDrop platform by measuring the FRET response. This report demonstrates that FlipDrop is capable of rapidly generating chemical combinations with unprecedented ease for combinatorial screening.

FlipDrop is a combinatorial screening platform. It enables rapid generation of chemical combinations by flipping and coupling two droplet arrays generated by surface energy traps on the magnetic digital microfluidic platform.

Multi-Drug Resistant Coliform: Water Sanitary Standards and Health Hazards

Water constitutes and sustains life; however, its pollution afflicts its necessity, further worsening its scarcity. Coliform is one of the largest groups of bacteria evident in fecally polluted water, a major public health concern. Coliform thrive as commensals in the gut of warm-blooded animals, and are indefinitely passed through their feces into the environment. They are also called as model organisms as their presence is indicative of the prevalence of other potential pathogens, thus coliform are and unanimously employed as adept indicators of fecal pollution. As only a limited accessible source of fresh water is available on the planet, its contamination severely affects its usability. Coliform densities vary geographically and seasonally which leads to the lack of universally uniform regulatory guidelines regarding water potability often leads to ineffective detection of these model organisms and the misinterpretation of water quality status. Remedial measures such as disinfection, reducing the nutrient concentration or re-population doesn’t hold context in huge lotic ecosystems such as freshwater rivers. There is also an escalating concern regarding the prevalence of multi-drug resistance in coliforms which renders antibiotic therapy incompetent. Antimicrobials are increasingly used in household, clinical, veterinary, animal husbandry and agricultural settings. Sub-optimal concentrations of these antimicrobials are unintentionally but regularly dispensed into the environment through seepages, sewages or runoffs from clinical or agricultural settings substantially adding to the ever-increasing pool of antibiotic resistance genes. When present below their minimum inhibitory concentration (MIC), these antimicrobials trigger the transfer of antibiotic-resistant genes that the coliform readily assimilate and further propagate to pathogens, the severity of which is evidenced by the high Multiple Antibiotic Resistance (MAR) index shown by the bacterial isolates procured from the environmental. This review attempts to assiduously anthologize the use of coliforms as water quality standards, their existent methods of detection and the issue of arising multi-drug resistance in them.

Electrically-receptive and thermally-responsive paper-based sensor chip for rapid detection of bacterial cells

Although significant technological advancements have been made in the development of analytical biosensor chips for detecting bacterial strains (E. coli, S. Mutans and B. Subtilis), critical requirements i.e. limit of detection (LOD), fast time of response, ultra-sensitivity with high reproducibility and good shelf-life with robust sensing capability have yet to be met within a single sensor chip. In order to achieve these criteria, we present an electrically-receptive thermally-responsive (ER-TR) sensor chip comprised of simple filter paper used as substrate coated with composite of poly(N-isopropylacrylamide) polymer (PNIPAm) - graphene nanoplatelet (GR) followed by evaporation of Au electrodes for capturing both Gram-positive (S. mutans and B. subtilis) and Gram-negative (E. coli) bacterial cells in real-time. Autoclave water, tap water, lake water and milk samples were tested with ER-TR chip with and without bacterial strains at varying concentration range 10¹-10⁵ cells/mL. The sensor was integrated with in-house built printed circuit board (PCB) to transmit/receive electrical signals. The interaction of E. coli, S. mutans and B. subtilis cells with fibers of PNIPAm-GR resulted in a change of electrical resistance and the readout was monitored wirelessly in real-time using MATLAB algorithm. Finally, prepared ER-TR chip exhibited the reproducibility of 85-97% with shelf-life of up to four weeks after testing with lake water sample.

Bluephage: A rapid method for the detection of somatic coliphages used as indicators of fecal pollution in water

The use of somatic coliphages as indicators of fecal and viral pollution in water and food has great potential due to the reliability, reproducibility, speed and cost effectiveness of methods for their detection. Indeed, several countries already use this approach in their water management policies. Although standardized protocols for somatic coliphage detection are available, user-friendly commercial kits would facilitate their routine implementation in laboratories. The new method presented here allows detection of up to 1 somatic coliphage in under 3.5 h, well within one working day. The method is based on a modified Escherichia coli strain with knocked-out uidB and uidC genes, which encode the transport of glucuronic acid inside cells, and overexpressing uidA, which encodes the enzyme β-glucuronidase. The enzyme accumulated in the bacterial cells only has contact with its substrate after cell lysis, such as that caused by phages, since the strain cannot internalize the substrate. When the enzyme is released into the medium, which contains a chromogen analogous to glucuronic acid, it produces a change of color from yellow to dark blue. This microbiological method for the determination of fecal pollution via the detection of culturable microorganisms can be applied to diverse sample types and volumes for qualitative (presence/absence) and quantitative analysis and is the fastest reported to date.

A Strategy to Establish a Quality Assurance/Quality Control Plan for the Application of Biosensors for the Detection of E. coli in Water

Rapid bacterial detection using biosensors is a novel approach for microbiological testing applications. Validation of such methods is an obstacle in the adoption of new bio-sensing technologies for water testing. Therefore, establishing a quality assurance and quality control (QA/QC) plan is essential to demonstrate accuracy and reliability of the biosensor method for the detection of E. coli in drinking water samples. In this study, different reagents and assay conditions including temperatures, holding time, E. coli strains and concentrations, dissolving agents, salinity and pH effects, quality of substrates of various suppliers of 4-methylumbelliferyl glucuronide (MUG), and environmental water samples were included in the QA/QC plan and used in the assay optimization and documentation. Furthermore, the procedural QA/QC for the monitoring of drinking water samples was established to validate the performance of the biosensor platform for the detection of E. coli using a culture-based standard technique. Implementing the developed QA/QC plan, the same level of precision and accuracy was achieved using both the standard and the biosensor methods. The established procedural QA/QC for the biosensor will provide a reliable tool for a near real-time monitoring of E. coli in drinking water samples to both industry and regulatory authorities.