Emerging biosensor platforms for the assessment of water-borne pathogens

Nishant Kumar ab, Yuan Hu c, Suman Singh *ab and Boris Mizaikoff *c
aCSIR-Central Scientific Instruments Organisation, Chandigarh, India. E-mail: ssingh@csio.res.in
bAcademy of Scientific and Innovative Research (AcSIR-CSIO), Chandigarh 160030, India
cUlm University, Institute of Analytical and Bioanalytical Chemistry, Ulm, Germany. E-mail: boris.mizaikoff@uni-ulm.de

Received 13th June 2017 , Accepted 13th November 2017

First published on 13th November 2017

Pathogens are key contaminants in water that are responsible for the generation of various water-borne diseases, and include viruses, fungi, bacteria, and protozoan parasites. The pathogenic effects of these species in water depend on their shape, size, composition, and structure. The resulting water-borne diseases are a serious threat to the environment, including to humans and animals, and are directly responsible for environmental deterioration and pollution. The potential presence of these pathogens requires sensitive, powerful, efficient, and ideally real-time monitoring methods for their reproducible quantification. Conventional methods for pathogen detection mainly rely on time-consuming enrichment steps followed by biochemical identification strategies, which require assay times ranging from 24 h to up to a week. However, in recent years, significant efforts have been made towards the development of biosensing technologies enabling rapid and close-to-real-time detection of water-borne pathogens. This review summarizes recent developments in biosensors and sensing systems based on a variety of transducer technologies for water-quality monitoring, with specific focus on rapid pathogen detection.

1 Introduction

Water-borne diseases are worldwide problems, which are estimated to bring about more than 2.2 million deaths per year, along with higher instances of ailments including cholera, diarrhea, giardiasis, cryptosporidiosis, and Hepatitis A and E.1,2 Globally, a monetary loss of about 12 billion US dollars per year is the associated economic effect.3 For example, estuarine and marine waters contain certain microorganisms which have toxic effects on humans.4 As of now, it is evaluated that there are >1400 types of pathogen with the potential to contaminate people, which include bacteria (538 species), viruses (208 types), parasitic protozoa (57 species), and a few species of fungi and helminths.1,5 The pathogenic effects of these species in water depend on their shape, size, composition, and structure. For example, in a seminal review Young detailed the role of bacterial morphology.6 Likewise, the shape of biological species/pathogens has biological relevance, as it assists in fighting against primary and secondary pressures, which include nutrient acquisition, cell division, predators, attachment to surfaces, passive dispersal, active motility, and internal or external differentiation.

The presence of pathogens in water is creating a threat to human survival. Table 1 provides general data on pathogens that are associated with different diseases, as well as those that are persistent in the drinking water supply.7 Despite the fact that water-borne outbreaks have been declining drastically since the 1900s, the worldwide impact of infectious water-borne diseases remains considerable. At least 1870 outbreaks were concerned with drinking water in the period 1920 to 2002. From 1991 to 2002, 433[thin space (1/6-em)]947 cases of illness were reported in the United States of America (USA) resulting from the protozoan agents Giardia, Naegleria fowleri, and Crytosporidium, and the bacteria Escherichia coli (E. coli) O157:H7, Salmonella typhimurium (S. typhimurium), Legionella spp., and Vibrio cholera.8 There were 134 water-associated outbreaks reported by 38 states in the USA and Puerto Rico between 2007 and 2009. This led to the occurrence of at least 13[thin space (1/6-em)]966 cases comprising 81 outbreaks of acute gastrointestinal illness, 24 of dermatological illness, and 17 of acute respiratory illness. The leading pathogens involved in these cases were Crytosporidium, E. coli O157:H7, Pseudomonas spp., Shigella sonnei, and Legionella spp. In 2010, approximately 25 outbreaks reported in the USA were concerned with drinking water.9 In Germany in 2011, E. coli (strain O104:H4) was responsible for severe cases of diarrhea, which resulted from the consumption of uncooked sprouts. Contaminated water was used for irrigation purposes, which caused the pathogenic infection.10 In 2012, 18 cases of cholera were reported from the United Kingdom, Austria, and Sweden. In the same year, the United Kingdom, Ireland, Belgium, and Germany faced 9591 cases of Cryptosporidium, largely due to Cryptosporidium parvum (C. parvum) gp60 subtype IIaA15GR1. In the same year, 10 water-borne outbreaks were reported in the EU, caused by E. coli O157:H7.11 In September 2013, an outbreak of acute gastroenteritis (AGE) was notified to the Gipuzkoa Epidemiology Unit at a domestic appliance factory in Spain (Basque Country), though first signs of outbreak were observed in June 2013.12 Analysis of water confirmed the presence of norovirus and rotavirus. This outbreak affected 238 people. In 2014, according to the World Health Organisation (WHO), approx. 94[thin space (1/6-em)]000 deaths occurred due to diarrhea in the Western Pacific Region via contaminated water.13 In 2015, the United Nations International Children's Emergency Fund (UNICEF) reported that around 884 million people across the world use some form of contaminated drinking water resource.14

Table 1 Water-borne pathogens and their significance in water supplies. Adapted from the WHO Guidelines for Drinking Water Quality.7
Pathogen Associated disease Health significance Persistence in water supplies Resistance to chlorine Relative infectivity
Burkholderia pseudomallei Melioidosis High May multiply Low Low
Campylobacter jejuni, C. coli Gastroenteritis High Moderate Low Moderate
Escherichia coli - Pathogenic Gastroenteritis High Moderate Low Low
E. coli – Enterohaemorrhagic Gastroenteritis, Hemolytic-uremia High Moderate Low High
Legionella spp. Legionnaires’ disease High May multiply Low Moderate
Non-tuberculous mycobacteria Pulmonary disease, skin infection Low May multiply High Low
Pseudomonas aeruginosa Pulmonary disease, skin infection Moderate May multiply Moderate Low
Salmonella typhi Typhoid Fever High Moderate Low Low
Salmonella enterica Salmonellosis High May multiply Low Low
Shigella spp. Shigellosis High Short Low High
Vibrio cholerae Cholera High Short to long Low Low
Yersinia enterocolitica Gastroenteritis Moderate Long Low Low
Adenoviruses Gastroenteritis, respiratory infection Moderate Long Moderate High
Enteroviruses Gastroenteritis High Long Moderate High
Astroviruses Gastroenteritis Moderate Long Moderate High
Hepatitis virus A, E Hepatitis High Long Moderate High
Noroviruses Gastroenteritis High Long Moderate High
Sapoviruses Gastroenteritis High Long Moderate High
Rotaviruses Gastroenteritis High Long Moderate High
Acanthamoeba spp. Keratitis, encephalitis High May multiply Low High
Cryptosporidium parvum Cryptosporidiosis High Long High High
Cyclospora cayetanensis Gastroenteritis High Long High High
Entamoeba histolytica Amoebic dysentery High Moderate High High
Giardia intestinalis Giardiasis (Beaver fever) High Moderate High High
Naegleria fowleri Primary amoebic meningoencephalitis High May multiply Low Moderate
Toxoplasma gondii Toxoplasmosis High Long High High
Dracunculus medinensis Dracunculiasis (Guinea worm disease) High Moderate Moderate High
Schistosoma spp. Schistosomiasis High Short Moderate High

The WHO has reported that enhancing water quality would decrease the worldwide effects of sickness by around 4%.15 Hence, there is a significant demand for the development of efficient, rapid, and sensitive analytical techniques for the detection of water-borne pathogens. Effective testing for the presence of water-borne pathogens requires methods of analysis that meet a number of challenging criteria in order to reduce outbreaks in the future. Pathogenic detection techniques are required to be rapid and sensitive, as the presence of even single pathogenic organisms in the water may cause severe infections. To meet this increasing demand, biosensors are being developed to offer user-friendly, rapid, selective, portable, and sensitive analytical platforms for the detection of water-borne pathogens.

Biosensors are devices or assays that consist of a biorecognition element, which is coupled to a signal transducer ideally capable of providing a quantitative analytical signal, resulting from the interaction between the biorecognition element and the target analyte/species.16 Among the more commonly applied biorecognition elements are enzymes, antibodies, oligonucleotide probes, aptamers, cell-surface molecules,17 and phages.18 The recognition elements are immobilized such that specific interactions with the target species – here, water-borne pathogens – are ensured, while the signal transduction process ideally remains free from interferences. The biochemical signal generated from chemical or enzyme-catalyzed reactions is converted into an electrical signal by the transducer. Some of the commonly used transducers will be discussed in the forthcoming sections.

This review focusses especially on biosensing methods for the detection of water-borne pathogens using various types of transducer platforms. It describes selected state-of-the-art application examples highlighting the particular benefits of each technology.

2 Classification of biosensors

Biosensors are usually classified based on their mode of physiochemical signal transduction. The transducer plays a vital role within a biosensor: it must reproducibly translate the (bio)chemical interaction/signal into a physical quantity. Transduction methods currently include predominantly electrochemical, optical, and piezoelectric principles, however, they are continuously expanding into utilizing other physical effects.

2.1. Electrochemical biosensors

An electrochemical biosensor, as defined by IUPAC in 1999, is a self-contained integrated device, which can perform quantitative or semi-quantitative analysis of biorecognition-catalyzed reactions using an electrochemical transduction element.19 Electrochemical biosensors measure the current produced from oxidation and reduction reactions; the current produced is directly related to the concentration of the electroactive species present/produced.

Despite the fact that biosensing devices may combine with an assortment of (bio)recognition elements, electrochemical detection techniques primarily take advantage of enzymes. This may be attributed not only to the specific binding capabilities of enzymes, but also to their (bio)catalytic activities which give rise to inherent signal enhancements.20–22 For electrochemical biosensors, the transducer needs to be a conductor, and conducive to appropriate surface modification steps for attachment of the biorecognition element. Electrochemical biosensors are further classified into voltammetric, potentiometric, amperometric, and impedance-based biosensors.

2.1.1. Voltammetric biosensors. Voltammetric biosensors detect an analyte by determining the change in current as a function of applied potential. For the analysis of environmental samples, different voltammetric techniques have been used, including cyclic voltammetry (CV), differential pulse voltammetry (DPV), and square wave voltammetry.23–25 Recently, Wang and Alocilja developed a state-of-the-art electrochemical biosensor using antibody-modified nanoparticles for the detection of E. coli O157:H7.26 For detection purposes, E. coli O157:H7 colonies from a frozen culture stored at −70 °C were grown on trypticase soy agar plates. Afterwards, a single colony was isolated, used to inoculate tryptic soy broth and grown overnight at 37 °C. Meanwhile, in another tube of tryptic soy broth, 1 mL of the liquid culture was transferred and incubated at 37 °C overnight. Before performing each experiment, 1 mL of this liquid culture was transferred again to a new broth tube and maintained at 37 °C for 6 h. Fig. 1 shows a schematic of the gold nanoparticle (AuNP)-labeled biosensor used for detection of the bacteria. In this study, two innovative nanoparticle approaches were applied for designing the biosensor: (i) polymer-coated magnetic nanoparticles (MNPs), which help to separate the bacteria from the sample matrix, and (ii) carbohydrate-capped AuNPs, which label the separated bacteria via formation of a sandwich structure during signal generation. The signals were generated due to interactions of the separated bacteria with the carbohydrate-capped AuNPs. The generated signals were determined by DPV using a screen-printed carbon electrode (SPCE) chip. The lower limit of detection was found to be 101 CFU (colony forming unit) mL−1 with a dynamic range of 101 to 106 CFU mL−1. The time required for the bacterial extraction and detection was less than 45 min
image file: c7an00983f-f1.tif
Fig. 1 Schematic of an AuNP-based biosensor. Target cells in a sample were captured by magnetic nanoparticle (MNP)-antibody (Ab) conjugates and separated by a magnet. Then, the cells were labeled with AuNPs. The MNP-Ab-cell-Ab-AuNP complexes were transferred onto a SPCE chip connected to a potentiostat for electrochemical analysis. Adapted from Wang and Alocilja26 with permission from BioMed Central.

Das et al. developed an electrochemical genosensor for the water-borne pathogen Salmonella typhi (S. typhi) using AuNP-mercaptosilane-modified screen-printed electrodes (SPEs).27 In this study, an integrated self-assembled layer of organosilane 3-mercaptopropyltrimethoxy silane (MPTES) was fabricated at the surface of the SPE, and AuNPs employing the Vi gene as a molecular marker for the detection of S. typhi were then electrochemically deposited on top (Fig. 2). A thiolated DNA probe was initially immersed in 1 mM 6-mercapto-hexanol (MCH) for 1 h to block the uncovered electrode surface. Subsequently, such thiolated DNA probe was immobilized on the AuNPs for a DNA hybridization assay using methylene blue (MB) as a redox (i.e., electroactive) hybridization indicator. The signal was evaluated using DPV. This biosensor was found to be linear in the range 1.0 × 10−11 to 0.5 × 10−8 M, and the detection limit was 50 (±2.1) pM. The as-developed electrochemical biosensor could be regenerated and reused for up to four times.

image file: c7an00983f-f2.tif
Fig. 2 Schematic representation of a MPTES-AuNPs modified SPE platform serving as a genosensor. Adapted from Das et al.27 (with minor changes in representation) with permission from Elsevier.
2.1.2. Potentiometric biosensors. Potentiometric biosensors determine the electrical potential difference between a working and reference electrode in an electrochemical cell, ideally without any significant current flowing in between. The potential of the reference electrode remains invariant during the measurement, whereas the working electrode undergoes significant changes in potential upon changes in analyte concentration. Such biosensors are usually based on so-called ion-selective electrodes (ISEs), and ion-sensitive field effect transistors (ISFETs).28 The output signal is generated due to the accumulation of ions at an ion-selective membrane interface. In other words, it can be said that these sensors/biosensors help in the determination of ion activity in an electrochemical reaction. Potentiometric sensors are good for measuring low concentrations of analytes in tiny sample volumes.29 Many reviews have been dedicated to potentiometric sensors/biosensors.30–32 Several studies have been reported on the detection of water-borne pathogens using potentiometric biosensors.33–35

Laczka et al. reported a novel electrochemical method for rapidly sensing the parasitic protozoan C. parvum.36 The detection of this water-borne protozoan is of specific interest for drinking water safety due to its resistance to standard methods of water disinfection.37–39 Using solid phase extraction (SPE) and horseradish peroxidase (HRP)-labeled antibodies to bind to the C. parvum, the species was detected potentiometrically. o-Phenylenediamine (OPD) acted as a proton donor, while HRP catalyzed the conversion of hydrogen peroxide to oxygen and water in its presence. The reduction of hydrogen peroxide involved a direct electron transfer, which generates an electrical potential difference between the working and reference electrodes. This potential difference is directly proportional to the rate of the enzymatic reaction, which is, in turn, related to the concentration of C. parvum oocysts (Fig. 3). This method allowed the detection of 5 × 102Cryptosporidium oocysts per mL in 60 min.

image file: c7an00983f-f3.tif
Fig. 3 Principle of a potentiometric immunosensor based on direct electron transfer resulting from the conversion of hydrogen peroxide to oxygen and water in the presence of the mediator and proton donor o-phenylenediamine (OPD). The oxidation of OPD by HRP results in the production of 2,3-diaminophenazine (DAP). Adapted from Laczka et al.36 with permission from Elsevier.

Karapetis et al. developed a miniaturized potentiometric cholera toxin (CT) sensor using graphene nanosheets with incorporated lipid films.40 CT is produced by the bacterium Vibrio cholera, which is responsible for epidemic diseases leading to rapid dehydration, and it causes death within a few hours of exposure. In this study, the natural CT receptor known as Ganglioside GM1 was immobilized onto the lipid film, providing excellent selectivity. The proposed sensor was reusable, reproducible, and selective across a wide range of concentrations (10 × 10−9 M to 10 × 10−6 M). The sensor displayed an adequate response even during the analysis of real water samples. A schematic of the experimental setup is shown in Fig. 4.

image file: c7an00983f-f4.tif
Fig. 4 Schematic of the experimental setup and detail of the bioelectrode surface of a potentiometric sensor for CT. Adapted from Karapetis et al.40 with permission from Wiley.
2.1.3. Amperometric biosensors. Amperometric biosensors detect an analyte by determining the changes in current after bioaffinity interactions occur at the surface of a working electrode. E. coli O157:H7 is the most common Shiga toxin-producing strain of E. coli, which causes severe bloody diarrhea, stomach cramps, vomiting, or even life-threatening hemolytic uremic syndrome.41 Xu et al. developed an electrochemical biosensor to detect E. coli O157:H7.42 This biosensor was fabricated by the integration of bifunctional glucose oxidase (GOx)-polydopamine (PDA)-based polymeric nanocomposites (PMNCs) and Prussian blue (PB)-modified screen-printed interdigitated microelectrodes (SP-IDMEs). Firstly, by the self-polymerization of dopamine (DA), core–shell magnetic bead (MB)-GOx@PDA PMNCs were synthesized. AuNPs were dispersed at the surface of the PMNCs via biochemical synthesis to achieve more efficient adsorption of antibodies (ABs) and GOx. Thereafter, using filtration, the unbound PMNCs were separated, and transferred into glucose solution to allow the enzymatic reaction to occur. The change in current response was measured using both CV and amperometric techniques via the PB-modified SP-IDMEs. The detection limit of this biosensor was found to be 102 CFU mL−1. A schematic of this biosensor principle is shown in Fig. 5.
image file: c7an00983f-f5.tif
Fig. 5 Electrochemical biosensor for the detection of E. coli O157:H7. Adapted from Xu et al.42 with permission from The Royal Society of Chemistry.

Davis et al. developed an enzyme-linked immunosorbent assay (ELISA)-based amperometric biosensing strip for the rapid and cost-effective detection of the water-borne pathogen Listeria monocytogenes (L. monocytogenes), using AuNP-modified SPCEs.43 The purpose of modifying the electrode surface using AuNPs was to create a larger electrode surface, to assist fast electron transfer and to contribute to the conductivity. The detection limit of the amperometric biosensing strip was determined at 102 CFU g−1 of food. The developed biosensor required one hour for an accurate determination, and revealed an excellent analytical response in real-world samples.

2.1.4. Impedance-based biosensors. Electrical impedance spectroscopy (EIS)-based biosensors are increasing in popularity. At different frequencies, low voltage sinusoidal potentials are applied to the electrochemical system. Via the resulting current, impedance changes are determined as a function of frequency.44 The results obtained from such impedance measurements are evaluated in terms of equivalent circuits.45 Due to the sensitivity and simplicity of the measurement, significant interest has emerged for the detection of water-borne pathogens using impedance-based techniques. Recently, Chen et al. reported an impedance-based biosensor for the sensitive detection of L. monocytogenes.46 Monoclonal antibodies (MAbs) were immobilized at the surface of magnetic nanoparticles (MNPs) using the biotin–streptavidin system, which assists in separating Listeria cells efficiently from the sample matrix. Moreover, at the surface of the AuNPs, polyclonal antibodies (PAbs) and urease were used to establish MNP-MAb-Listeria-PAb-AuNP-urease sandwich complexes. Subsequently, using 200 μL of PBST (0.5% Tween-20 in PBS) and deionized water, the complexes were washed sequentially three times to remove unbound PAb, urease-modified AuNPs, and conductive ions. Afterwards, the complexes were resuspended in 200 μL of 1 mM urea and incubated for 30 min. The magnetic separation of complexes was then carried out for 2 min, and 20 μL of supernatant was transferred onto the microelectrode for analysis. The lower detection limit of this biosensor for L. monocytogenes was found to be 30 CFU mL−1; the fundamental principle of the technique is shown in Fig. 6.
image file: c7an00983f-f6.tif
Fig. 6 Impedance-based biosensor using immunomagnetic separation and urease catalysis. Adapted from Chen et al.46 with permission from Elsevier.

Dong et al. designed a label-free electrochemical impedance immunosensor by immobilizing anti-Salmonella antibodies onto AuNPs and poly(amidoamine)-multiwalled carbon nanotube-chitosan nanocomposite film-modified glassy carbon electrodes (AuNPs/PAMAM-MWCNT-Chi/GCE) for the detection of S. typhimurium.47 A linear response function of the biosensor was found in the range of 1.0 × 103 to 1.0 × 107 CFU mL−1 with a detection limit of 5.0 × 102 CFU mL−1. A schematic is shown in Fig. 7.

image file: c7an00983f-f7.tif
Fig. 7 Schematic of an immunosensor fabrication process: (a) dropping of PAMAM-MWCNT-Chit membrane onto a glassy carbon electrode; (b) assembly of AuNPs; (c) assembly of mercaptoacetic acid; (d) activation of carboxyl groups with EDC/NHS; (e) capture of anti-Salmonella antibodies; (f) immunoreaction of anti-Salmonella antibodies with Salmonella cells. Adapted from Dong et al.47 with permission from Elsevier.

2.2. Optical biosensors

Optical biosensors, using a variety of optical sensing modalities, have been promoted as a promising alternative transducer platform for pathogen analysis. These types of biosensor are capable of detecting even minor changes in analytes, thus allowing sensitive and specific measurements. Herein, the most prominent types of optical biosensor are discussed, based on surface plasmon resonance (SPR), evanescent field sensing via optical fibers/waveguides, infrared (IR) and Raman spectroscopy, fluorescence, chemiluminescence (CL), and colorimetry.
2.2.1. Surface plasmon resonance (SPR) biosensors. SPR is an optical technique that uses the occurrence of surface waves propagating along noble metals under resonance conditions, and analyte-dependent changes in the refractive index adjacent to the noble metal (i.e., sensor) surface.48,49 In SPR biosensors, the bioreceptor is immobilized at the sensor surface, and the analyte solution usually passes via a microfluidic channel across the biomolecular recognition interface. The direct interaction between analyte and ligand results in a change in refractive index close to the sensor surface, which is determined as a change of the resonance angle of the surface plasmon. Thus, SPR is considered a label-free technique which even enables dynamic/kinetic measurements. The major benefits associated with this technique are that it simply responds to changes in refractive index induced by molecular binding events, and does not require additional reagents, assays, or laborious sample preparation steps. At the same time, the entire specificity of SPR-based sensors results from the biorecognition step. There are various reports on SPR-based biosensors for the detection of water-borne pathogens.50–52 Recently, Singh et al. developed an SPR-based biosensor for the detection of Salmonella.53 This biosensor was fabricated by generating self-assembled monolayers of 5′-thiolated single-stranded DNA (ssDNA) probes attached to the gold surface of an SPR chip. This DNA biosensor was investigated for label-free real-time monitoring of Salmonella with a detection limit of 2 fM. A schematic of this SPR-based biosensor scheme is shown in Fig. 8.
image file: c7an00983f-f8.tif
Fig. 8 SPR-based optical DNA biosensor. Adapted from Singh et al.53 with permission from Springer.

Nanduri et al. detected the pathogen L. monocytogenes with an SPR sensor using a phage-displayed single chain variable fragment (scFv) antibody to the virulence factor actin polymerization protein (ActA) as the biorecognition element.54 Via physical adsorption, the phage Lm P4:A8 expressing the scFv antibody bound to the pIII surface protein, and was immobilized at the sensor surface. The detection limit of this biosensor was estimated at 2 × 106 CFU mL−1. The dissociation constant (Kd) for the interaction of the phage-displayed scFv and soluble ActA was found to be 4.5 nM.

2.2.2. Evanescent field-based fiberoptic biosensors. When light propagates via a core-only high-index (i.e., nfiber > nsample) optical fiber on the basis of total internal reflection (TIR), an electromagnetic field (known as an evanescent field or evanescent wave) is generated at the waveguide/sample interface. This field decays exponentially with distance from the interface. An evanescent wave can thus be used to excite fluorescence in the proximity of a sensing surface, e.g., in fluorescently-labeled biomolecules bound to an optical sensor surface.55

In recent years optical fibers have been successfully used as biosensor platforms in various spectral regimes, as they are rapid in response, specific, sensitive, and cost-effective. Furthermore, they are suitable for close to real-time monitoring and on-site detection. Consequently, fiberoptic biosensors have been used in a wide range of applications.56,57 In the simplest form, evanescent field-based optical fiber or waveguide biosensors observe changes in refractive index due to analyte binding events via appropriate biorecognition elements, thus directly affecting the optical conditions for generating an evanescent field.58,59 Consequently, a variety of optical transduction schemes can be used to take advantage of evanescent field sensing concepts including fluorescence detection, monitoring of refractive index changes, absorbance spectroscopy via the evanescent field or the detection of spectroscopic shifts.

Evanescent field fiberoptic biosensors are increasingly being applied for the detection of pathogens in food and water supplies, food processing facilities, and homeland security operations.60 These biosensors can be used for the detection of multiple pathogens or to complement other analytical techniques. Bharadwaj et al. developed a U-shaped evanescent wave absorbance (EWA) fiberoptic biosensor for the label-free detection of E. coli at a wavelength of 280 nm.61 The penetration depth of the evanescent wave was enhanced by bending an unclad fiber segment into a U-shaped structure. The enhanced EWA response caused by the inherent optical absorbance properties of the biomolecules specifically bound to the surface of the sensor were used for the detection of pathogens. The detection limit of the proposed sensor was found to be 1000 CFU mL−1 and the sensor is schematically shown in Fig. 9.

image file: c7an00983f-f9.tif
Fig. 9 Enhancement of the penetration depth (DP) via a U-shaped fiber probe enabling the evanescent field detection of E. coli. Adapted from Bharadwaj et al.61 with permission from Elsevier.

This biosensor enabled the specific detection of proteins of the outer membranes of E. coli for the determination of E. coli in water. A portable evanescent wave fiber biosensor has been developed for Shigella detection using DNA as a biorecognition element.62 The DNA probe is capable of hybridization with a fluorescently-labeled complementary DNA strand that is covalently immobilized onto the fiberoptic biosensor. In a recent report, a fluorescent immunosensor has been developed using an optical waveguide for fast and sensitive detection of microcystin-LR (MC-LR) in lakes.63 MC-LR is one of the most toxic cyclic heptapeptide cyanotoxins released by cyanobacterial blooms in surface waters. 3-Mercaptopropyl trimethoxysilane/N-(4-maleimidobutyryloxy) succinimide (MTS/GMBS) was used to activate the surface of the waveguide chip to facilitate the immobilization of bovine serum albumin (BSA)-MC-LR conjugates.

2.2.3. Long-period grating (LPG)-based biosensors. Among the (bio)sensors using optical fibers, long-period gratings (LPG) are a particularly interesting platform.64 In an LPG, the refractive index of the fiber core is periodically modulated with a period (Λ) in the range of hundreds of micrometers.65 As a result of these modulations, coupling of the core mode into a series of cladding modes occurs, which results in the appearance of resonance peaks.66 The evanescent field of each cladding mode interacts with the environment surrounding the fiber. Hence, LPGs assist mode coupling at resonance wavelengths that are sensitive to variations in refractive index of the surrounding medium (i.e., sample). The advantages of LPG sensors include simple fabrication and ease of adjustment of the resonance wavelength within the spectrum emitted by the light source via the grating period. While LPG-based biosensors have demonstrated their generic utility, they appear less exploited to date for the detection of water-borne pathogens.

Tripathi et al. reported the label-free, bacteriophage-based detection of E. coli using particularly sensitive long-period fiber gratings (LPFGs).67 For this study, the bacteriophage T4 was covalently immobilized at the fiber surface. Binding of E. coli was subsequently monitored. An LPG-based biosensor was fabricated for the detection of E. coli outer membrane proteins (EcOMPs) via the generated evanescent field. For that purpose, a DNA-aptamer-based optical biosensor was applied and long-period gratings served as a refractometric platform.68 Via the functionalization of LPGs within a single-mode fiber, sensing areas were obtained using two types of immobilization: (i) electrostatic assembly, and (ii) covalent binding. The monitoring of changes in the resonance wavelength enabled the specific recognition of EcOMPs in water. The sensor displayed a linear response in the range of 0.1 nM to 10 nM.

2.2.4. Infrared (IR) and Raman spectroscopy-based biosensors. IR and Raman spectroscopies provide highly discriminatory vibrational fingerprints for a diversity of samples based on chemical composition. This enables long-term monitoring, high reproducibility, accurate determination and characterization of pathogens.69

Both vibrational spectroscopic techniques are effective and non-destructive. They enable the analysis of the phenotype of pathogen samples and detect dynamic changes in pathogen metabolism and structure occurring due to environmental stress.70 For example, Al-Qadiri et al. used Fourier transform infrared (FT-IR) absorbance spectroscopy to study the effect of chlorine-induced bacterial injury in a mixed bacterial culture of E. coli and Pseudomonas aeruginosa.71 Changes were found in the spectral features of injured bacterial cells between 1800 and 1300 cm−1, which revealed apparent denaturation concerning ester functional groups of lipids, structural proteins, and nucleic acids. Their study suggests that IR spectroscopy may be applicable for assessing the presence of injured and viable but not culturable (VBNC) water-borne pathogens, which can be underestimated or not discernible using traditional microbiological procedures. Lee-Montiel et al. developed a strategy for the detection and quantification of water-borne poliovirus using a combination of FT-IR spectroscopy and cell culture.72 Buffalo green monkey kidney (BGMK) cells infected with different virus titers were investigated at 1–12 hours post-infection utilizing FT-IR spectroscopy to monitor changes in the absorbance patterns of cell components (e.g., lipids, proteins, nucleic acids, and sugars) subsequent to poliovirus infection. An overview of this method is shown in Fig. 10.

image file: c7an00983f-f10.tif
Fig. 10 Schematic representation of a viral detection method using cell culture and FT-IR spectroscopy (not to scale). Adapted from Lee-Montiel et al.72 with permission from BioMed Central.

Raman scattering provides complementary information to IR spectroscopy, offering a wide range of potential analytical wavelengths as well as laser excitation sources (i.e., UV, near IR or visible). However, Raman signals are inherently much weaker, which renders surface enhanced Raman spectroscopy (SERS) relevant for ultrasensitive pathogen sensing. Therefore, considerable progress has been made in developing SERS biosensor platforms for pathogens.73 Currently, there are two types of SERS approach commonly used to detect pathogens. The first one is a label-based strategy using an immunosorbent assay format similar to ELISA, and a SERS tag as a quantitative reporter to produce sensitive and distinct signals. Biorecognition molecules such as antibodies and aptamers are necessary for specific binding of pathogens. Recently, Wang et al. proposed a SERS immunosensor for staphylococcal enterotoxin B (SEB) detection on a microplate by utilizing 4-nitrothiophenol (4-NTP)-modified Au@Ag core–shell NPs as the signal reporter/SERS tag coupled to an SEB MAb.74 The encoded 4-NTP in the Au@AgNP leads to substantial electromagnetic enhancement between the AuNPs and the Ag shell, and differentiates SERS signals from the sample and the microplate. A limit of detection of 1.3 pg mL−1 SEB was obtained with this method. The schematic of the working principle of this SERS-based immunoassay is given in Fig. 11.

image file: c7an00983f-f11.tif
Fig. 11 Schematic of an Au@Ag core–shell structure-based SERS immunosensor for SEB. Adapted from Wang et al.74 with permission from American Chemical. Society.

The second type of SERS biosensor, which directly detects the intrinsic vibrational fingerprint of pathogens in the vicinity of nanostructured noble metal surfaces, operates label-free and is able to simultaneously analyze various pathogens. Wang et al. synthesized positively charged polyethylenimine (PEI)-modified Au-coated magnetic microspheres (Fe3O4@Au@PEI) to capture, enrich, and separate negatively charged bacteria, which were then magnetically immobilized onto an Si substrate for establishing SERS substrates with a high density of hotspots.75 Au@Ag NPs in ethanol were further added and dried on the substrate to cover the blank surface. The SERS signal from the bacteria was then synergistically enhanced by the combination of Fe3O4@Au@PEI and Au@Ag NPs. Hence, a three-step, label-free SERS pathogen detection method termed capture–enrichment–enhancement (CEE) was established, and was verified by the detection of the Gram-negative bacterium E. coli and Gram-positive bacterium Staphylococcus aureus (S. aureus) from spiked tests in tap water and milk, at a detection limit as low as 103 cells per mL. Fig. 12 illustrates the general scheme of this concept.

image file: c7an00983f-f12.tif
Fig. 12 Schematic of (A) the synthesis of high-performance Fe3O4@Au@PEI microspheres, and (B) the CEE three-step procedure for the rapid SERS detection of bacterial pathogens. Adapted from Wang et al.75 with permission from The Royal Society of Chemistry.
2.2.5. Fluorescence and chemiluminescence (CL) biosensors. Optical biosensors for pathogens involving detection via luminescence (i.e., fluorescence and CL) represent a powerful analytical technique offering high sensitivity, flexibility, easy readout, and ease of operation. Furthermore, quantitative determination is enabled across a sizeable dynamic range. The vast majority of luminescence assays rely on appropriate labels, and the labeled components are predominantly antibodies, aptamers, proteins, amino acids, and peptides, which are then used as specific probes for the detection of a particular target. In recent decades, fluorophores (e.g., organic dyes), semiconductor quantum dots (QDs), and other fluorescent nanoparticles have been considered as effective labels in fluorescence-based biosensors. Most commonly, these reactive fluorescent labels selectively bind to a specific region or functional group on the target analyte. A sandwich assay was developed by Dogan et al. combining immunomagnetic separation (IMS) based on iron oxide-core, gold-shell (Fe3O4@Au) magnetic nanoparticles and chitosan-modified CdTe QDs as a fluorescence label for the quantitative detection of E. coli.76Fig. 13 gives a schematic illustration of the proposed method.
image file: c7an00983f-f13.tif
Fig. 13 Schematic illustration of the overall strategy using a fluorescence-based sandwich immunoassay for the enumeration of E. coli. Adapted from Dogan et al.76 with permission from Elsevier.

Apart from conventional fluorescence assays, Förster resonance energy transfer (FRET)-based techniques have been widely applied in ultrasensitive detection schemes, usually avoiding sample separation or washing steps. FRET describes the energy transfer process between fluorescent particles serving as energy donors, and quencher particles serving as acceptors whereby the fluorescence of the donor may be quenched by the acceptor if they are within a certain distance (i.e., Förster distance) of each other (usually <10 nm). The changes of fluorescence intensity during the FRET process may be used to monitor concentrations of target analytes. Jin et al. designed a FRET-based platform for bacteria detection, in which AuNPs (acceptor) were functionalized with bacteria-targeting aptamers, while upconversion nanoparticles (UCNPs, donor) were modified with corresponding complementary DNA (cDNA).77Via complementary pairing of the aptamers and cDNA, FRET occurred owing to the spectral overlap between the fluorescence emission of the UCNPs and the absorption of the AuNPs, thereby resulting in the quenching of the fluorescence of the UCNPs. When the target bacteria are present, the aptamers preferentially bind to the bacteria to form a three-dimensional structure, and induce aptamer dissociation from the cDNA leading to the liberation of the UCNPs, and to the subsequent recovery of the upconverted fluorescence. This aptasensor was tested by detecting E. coli in real-world food and water samples (e.g., tap/pond water, milk). A schematic illustration of the developed FRET biosensor is shown in Fig. 14.

image file: c7an00983f-f14.tif
Fig. 14 Schematic illustration of the UCNP-based FRET aptasensor for the rapid and ultrasensitive detection of bacteria. (A) The amino-modified cDNA of the aptamer is attached to the carboxyl-functionalized UCNPs by condensation reaction. (B) Thiol-modified aptamers are conjugated to the AuNPs via Au-S chemistry. (C) The FRET system is established between a donor–acceptor pair: UCNPs-cDNA hybridizes with an AuNPs-aptamer. (D) By introducing target bacteria into the FRET system, aptamers preferentially bind to the target bacteria resulting in the dissociation of the cDNA, thereby the aptamer–DNA pairs are destroyed and the green fluorescence recovers. Adapted from Jin et al.77 with permission from Elsevier.

Instead of labeling fluorophores to the target analyte, Zhang et al. reported a novel fluorescence system for sensing viable Salmonella enteritidis (S. enteritidis), on the basis of specific aptamer recognition and the target-induced assembly of G-quadruplex DNA.78 In the presence of the target S. enteritidis, the specific aptamer sequence in the designed capture probe complex binds to the bacterium, and meanwhile the hybridized signal target sequence is released such that finally it can generate G-quadruplex structures after a series of reactions. The fluorescent dye N-methyl mesoporphyrin IX (NMM) binds to the produced G-quadruplex structures, and then emits intensive fluorescent signals to achieve S. enteritidis detection. This biosensor was capable of discriminating viable S. enteritidis from dead bacteria. The principle of this sensor is illustrated in Fig. 15.

image file: c7an00983f-f15.tif
Fig. 15 Schematic illustration of a label-free, modification-free, and DNA extraction-free fluorescence detection strategy for S. enteritidis based on the cascaded two-stage toehold strand-displacement-driven assembly of G-quadruplex structures. The dashed arrows represent the two different products including the target sequences (TS) in the same reaction. Adapted from Zhang et al.78 with permission from Elsevier.

In contrast to fluorescence, CL biosensors promise an ultralow background, superior sensitivity, extended calibration range, and simple instrumentation, since no external light source or sophisticated optics are involved. CL sandwich ELISAs have been extensively exploited in clinical analysis. In a typical CL biosensor for pathogens—as presented for example by Wolter et al.—species-specific antibodies are immobilized onto a substrate.79 Target pathogens are then captured at the prepared substrate surface by the antibodies, and subsequently bound to specific secondary antibodies labeled with biotin. CL detection can be accomplished after the addition of an HRP-labeled streptavidin and CL substrates, due to the CL emitted during the HRP-catalyzed reaction of luminol and hydrogen peroxide. The CL can be recorded via a sensitive charge-coupled device (CCD) camera. Fig. 16 displays the principle of a typical CL assay.

image file: c7an00983f-f16.tif
Fig. 16 Schematic of a CL assay illustrated for the detection of three different bacteria at an antibody microarray surface. Adapted from Wolter et al.79 with permission from Elsevier.
2.2.6. Colorimetric biosensors. Colorimetry is an ideal method for developing low-cost biosensors applicable in sensing scenarios where the most likely pathogens are addressed, and read-out may be attained by simply monitoring visual color changes with the naked eye. Such methods do not require expert users and promise a straightforward, cost-efficient, and convenient strategy. For example, the pronounced localized SPR (LSPRs) of gold colloids occurs within the visible spectrum, and color changes depending on the inter-particle distance of nanoparticles have been exploited for designing colorimetric sensors.80,81 Similarly, Thakur et al. developed a polyaniline nanoparticle (PAni NP)-based colorimetric sensor for monitoring bacterial growth relying on estimates of metabolic products.82 Herein, the conducting polymer, i.e., polyaniline, is highly sensitive to the presence of protons in its microenvironment, and a visible color change can be observed if proton doping occurs. This can be triggered by the interaction of polyaniline with metabolic products released by the pathogens. Fig. 17 gives an overview of the fundamental mechanism of this colorimetric biosensor.
image file: c7an00983f-f17.tif
Fig. 17 Schematic representation of the mechanisms involved in monitoring bacterial growth using polyaniline nanoparticles (PAni NPs) as a colorimetric sensor. Adapted from Thakur et al.82 with permission from Elsevier.

Frequently, colorimetric bioassays are based on ELISA schemes. A conventional ELISA uses an enzyme as a label that catalyzes a chromogenic substrate, whereas in a plasmonic ELISA test, an immunocomplex is conjugated to a substrate that affects the growth/agglomeration/accumulation of AuNPs. Bui et al. introduced a sensitive enzyme-free immunoassay based on plasmonic colorimetry via AuNPs in conjunction with signal amplification via cysteine-loaded liposomes.83 In the presence of a pathogen, cysteine acted as a cross-linker, and aided the rapid aggregation of the AuNPs. The assembled nanoparticles absorbed light at higher wavelengths. Thus, a typical color shift of the solution from red to dark blue could be observed when aggregation was generated, and the detection of pathogens was accomplished even at 6.7 attomolar (600 molecules in 150 μL) concentration levels. The obtained results have been verified by visually detecting single-digit live pathogens of Salmonella, Listeria, and E. coli O157 in food samples. The entire analytical process is shown in Fig. 18.

image file: c7an00983f-f18.tif
Fig. 18 Schematic of a liposome-amplified plasmonic immunoassay (LAPIA). One bacterium, molecule, or antigen may rapidly trigger a chemical cascade leading to a chromogenic aggregation of AuNPs. The reaction proceeds in different steps: (a) The target (biomarker, pathogen, toxin) is captured using a sandwich immunoassay. (b) After washing steps, a biotinylated secondary antibody (polyclonal anti-IgG) interacts with the immunocomplex. (c) After incubation and washing, streptavidin is added to interact and bind to biotinylated IgG. (d) After washing steps, biotin-conjugated liposomes containing cysteine are added to the medium followed by addition of the AuNP solution. (e) Addition of PBS-Tween-20 1X to the medium causes the breakdown of the liposomes and the release of cysteine, leading to (f) the immediate aggregation of the AuNPs and a color shift from red to dark blue. Adapted from Bui et al.83 with permission from The American Chemical Society.

Furthermore, colorimetric dyes (e.g., hydroxynaphthol blue (HNB), calcein, etc.) have been used to indicate positive signals generated by the genetic-based detection of pathogens. A portable point-of-care (POC) device was thus assembled by Safavieh et al. for the identification of bacterial pathogens using isothermal DNA amplification and a colorimetric read-out.84E. coli (Gram-negative bacterium) was detected as well as S. aureus (Gram-positive bacterium) via the unambiguous color change of HNB and calcein dyes. The present POC device was fabricated using a flexible ribbon polyethylene substrate ensuring low manufacturing costs and a simple method. The detection limits of the resulting POC device were 30 CFU mL−1 for E. coli, and 200 CFU mL−1 for S. aureus.

2.3. Piezoelectric biosensors

Piezoelectric sensors are responsive to the binding of an analyte due to the induced increase in mass, which in turn changes the oscillation frequency of a piezoelectric material/crystal and produces an associated electric read-out.85 The transducer in piezoelectric biosensors is made from piezoelectric materials (e.g., quartz), and the biosensing interface is coated or immobilized onto the piezoelectric surface that oscillates at its natural frequency.19 If a target analyte binds to the sensing surface, a frequency shift is caused, which produces changes in piezoelectric current directly proportional to the induced mass change.

Regarding the application of piezoelectric biosensors for detecting water-borne pathogens, only a few reports have been published to date. Wang et al. developed a quartz crystal microbalance (QCM) based on the piezoelectric effect, for the detection of E. coli 0157:H7 DNA based on AuNP amplification.86 AuNPs were immobilized onto the thiolated surface of an Au electrode. Then, thiolated single-stranded DNA (ssDNA) was fixed via Au-SH bonding. This ssDNA probe was exposed to the complementary target DNA of E. coli 0157:H7 gene eaeA. Binding of target DNA caused a mass change, and a corresponding frequency shift of the QCM resonance. The outer avidin-coated AuNPs could combine with the target DNA to increase the mass. The detection limit of this biosensor was found to be 2.0 × 103 CFU mL−1. The fabrication scheme of such a QCM-based biosensor is shown in Fig. 19.

image file: c7an00983f-f19.tif
Fig. 19 Schematic showing the QCM DNA biosensor fabrication and detection procedure. Adapted from Wang et al.86 with permission from Springer.

Babacan et al. reported a piezoelectric-based biosensor for the detection of S. typhimurium.87 In this report, the piezoelectric biosensor protein A antibody was immobilized for the detection of S. typhimurium. The detection system consisted of an advanced design for the flow cell combined with a flow injection analysis system. The sensor had a response in the range of 5 to 65 Hz within 30 min with R2 = 0.95 for S. typhimurium concentrations of 107 to 109 CFU mL−1 under continuous flow conditions, and 3 to 75 Hz within 40 min with R2 = 0.96 for S. typhimurium concentrations of 106 to 1010 CFU mL−1 under stop-flow conditions.

The detection of E. coli O157:H7 was reported using a piezoelectric biosensor-QCM.88 Antibody-functionalized AuNPs were used as detection verifiers and amplifiers. The capture antibodies for E. coli O157:H7 were first immobilized onto the QCM chip. The sample containing E. coli O157:H7 was circulated through the system in the presence of 10 mL of brain heart infusion (BHI) broth for 18 h. The cells of E. coli O157:H7 that were specifically captured and enriched on the chip surface of the QCM were identified by QCM frequency changes. The authors claim that the real-time monitoring method for viable E. coli O157:H7 developed in this study can be used to simultaneously enrich and detect viable cells within 24 h.

3 Current challenges and future prospects

The main requirements for reliable pathogen analysis include the specificity, sensitivity, reproducibility, and reliability of the obtained results, as well as detection speed, automation, and ultimately, low cost. To date, even though a plethora of reports are available on biosensors for pathogen detection in the aqueous environment, there are many challenges for biosensor application to real-world environmental samples.

A major challenge is posed by the numerous and potentially interfering microbial species present, along with particulate matter, organic/inorganic constituents and contaminants, and molecular agglomerates and associates, e.g., from humic substances. Consequently, nonspecific interactions and adsorption at the biosensing interface limits the life time, specificity, and reliability of biosensors applied to complex environmental samples. In addition, biosensors used in pathogen detection frequently rely on the interaction of a natural receptor, usually an antibody, serving as the biorecognition element with its corresponding counterpart. Natural receptors themselves usually operate under comparatively stringent environmental conditions (i.e., pH, ionic strength, etc.), and if immobilized at a transducer surface they may be prone to accelerated degeneration resulting in a loss of selectivity, binding activity, and/or binding capacity. Hence, not only will the sensor performance in general degenerate with extended application time, but the robustness of the calibration will be detrimentally affected.

These challenges may be addressed by taking advantage of more robust molecular detection schemes such as the DNA signature of pathogens, given that DNA is an inherently robust molecule. Alternatively, natural receptors such as enzymes and antibodies may increasingly be replaced by advanced biomimetic recognition elements such as peptides, aptamers, and molecularly imprinted/templated polymers which provide similar recognition abilities yet increasingly robust sensing interfaces.

It is evident that electrochemical sensors/electrodes, in particular, have evolved into the biosensor ‘workhorse’ given their maturity, robustness, ease of preparation, and low cost. Electrochemical sensors are generally characterized by high sensitivity, low cost, and ease of use. However, most electrochemical detection schemes are of limited inherent molecular selectivity, and thus rely on the (bio)molecular recognition scheme. In addition, electroactive interferents may convolute the obtained signal by, e.g., unwanted redox reactions.

In contrast, optical biosensors—probably the main alternative transducer category—are still frequently challenged by the required limits of detection in pathogen analysis. Given the progress in photonics technologies including waveguides, light sources, detectors, and integrated optics, it appears that optical sensing platforms are becoming increasingly competitive with electrochemical transduction schemes. This holds true independent of the utilized spectral window (i.e., visible, near-IR, or mid-IR wavelength) or interaction principles (i.e., absorption, fluorescence, SPR, Raman scattering, etc.). It is noteworthy that some optical sensing schemes (e.g., in the mid-IR) have to deal with interferences by the aqueous matrix itself via appropriate surface functionalization strategies.

Optical sensing schemes that take advantage of evanescent fields/waves emanating at the interface of high-refractive-index waveguides and lower-index samples (e.g., aqueous media) are increasingly emerging. These provide an ideal optical sensing platform with tailorable surface chemistries for immobilizing chemo or bioreceptors.

Last but not least, optical amplification schemes including surface enhanced Raman, IR, and fluorescence enable the lowering of achievable limits of detection into the required range. Notwithstanding, more reliable and reproducible surfaces and interfaces—usually involving nanostructured noble metals—remain an issue for future research. Progress in this area could improve the quantification capabilities of surface enhanced optical techniques during pathogen detection in complex environments.

For the detection of water-borne pathogens, culture-dependent methods are still extensively used, despite limitations of low sensitivity and the excessive time required to obtain genuine results. In order to mitigate such problems in pathogen detection, advanced sample filtration and pre-concentration techniques, including the use of charged membrane filters to process large volumes of water, have been implemented. Here, microfluidic devices play an increasingly important role for pathogen detection because of their large surface to volume ratio, multiplexing possibilities and minute sample requirement. Easy, cost-effective, ultrasensitive and selective detection of water-borne pathogens is being conducted nowadays using nano-dielectrophoretic microfluidic devices integrated with, e.g., SERS.89,90 Microfluidic devices have the potential to shorten the assay time when combined with almost any transduction scheme.57,91 Liposomes are also being used in sensing applications, as liposome-tagged probes are capable of detecting the analyte selectively without enzymatic amplification.92 Upconverting phosphor technology (UPT) is another method which provides specific assay signals without amplification by enzymes.93 Moreover, the lack of auto-fluorescence in UPT produces signals with very low noise. Furthermore, ‘green nanotechnology’ is one of the most promising emerging research areas contributing to advanced pathogen sensing.94,95 This technology is capable of minimizing human health risks caused by water-borne pathogens. The use of biologically synthesized nanomaterials offers selective, sensitive and cost-effective detection of pathogens without the use of toxic chemicals which in turn deteriorate the environment.96 In addition to this, molecular imprinted polymers (MIPs) have the potential for specific detection of pathogens. These are artificial receptor ligands which can bind specifically to the target analyte. The target-specific MIP nanoparticles are more resistant to biological and chemical damage in comparison to antibodies, which makes them a potential candidate for detection of water-borne pathogens.97

Despite the remaining challenges, a wide variety of transduction technologies and molecular recognition schemes combined increasingly with integrated sampling/microfluidic concepts are evidently advancing biosensor platforms and their capabilities for detecting and monitoring water-borne pathogens in real-world aqueous environments. These advances will lead to the increasing usage of biosensors.

Conflicts of interest

There are no conflicts to declare.


The support and constant encouragement from the Directorate, CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh, India, is highly acknowledged. Yuan Hu gratefully acknowledges the Chinese Scholarship Council (CSC) for financial support.


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