Rapid detection of nitrite based on nitrite-oxidizing bacteria biosensor and its application in surface water monitoring

Electrochemical nitrite sensing using mass transfer signal with a catalyst-free small-sized rotating disk electrode for wastewater monitoring

Electrochemical nitrite sensing (ENS) is a competitive method for online monitoring in the intelligent control of biological nitrogen removal process. However, its popularity is extremely low due to complex wastewater interference and low sensor durability. Here, we developed a novel ENS method that utilizes the mass transfer signal (MTS) of the nitrite oxidation reaction (NOR), making detection accuracy dependent solely on mass transfer process. These features enabled us to design a catalyst-free, small-sized glassy carbon rotating disk electrode for accurate MTS determination with exceptional durability. The linearity of MTS versus nitrite concentration surpasses that of conventional differential pulse voltammetry and amperometry. The method has a wide linear range of 100 μM-100 mM, a detection limit of 28 μM, and a high sensitivity of 1638 μA mM-1 cm-2. Importantly, solution pH and coexisting buffers show no significant effect on MTS determinations as long as pH does not exceed 10. Excellent immunity to interference from ionic strength, temperature, COD, inert salts, metal ions, dissolved oxygen, and hydrogen peroxide was observed. While reducing substances capable of oxidation reactions do cause interference, they are not common in environmental samples. Finally, a self-designed detection system requiring a sample volume of 4 mL was used for wastewater testing. The results demonstrate good capability for nitrite detection during practical wastewater treatment processes, although relative error increases with the complexity and content of organic pollutants in the wastewater. Overall, this ENS method holds great potential for achieving rapid, stable, and low-cost nitrite sensing in environmental applications.

A Co(II)-Organic Coordination Polymer and Its Hydroxyl Multiwalled Carbon Nanotube Composite Incorporating 2-Iodo-4-sulfobenzoate Exhibiting Dual Electrochemical Sensing Performance for NO2- and Fe3

The novel Co(II) coordination polymer incorporating 2-iodo-4-sulfobenzoic acid (H2isba) and a pliable 1,4-bis(benzimidazole-1-methyl) benzene (bdbmb) ligand, {[Co(bdbmb)(H2O)4]·isba·2H2O·2DMA}n (Co(II)-CP), was synthesized. In addition, the composite of Co(II)-CP with the short hydroxyl multiwalled carbon nanotubes (Co(II)-CP@HCNTs) was prepared via an in situ preparation strategy. Amperometric current response reveals that the glass carbon electrodes (GCEs) of Co(II)-CP and Co(II)-CP@HCNTs exhibit highly sensitive electrochemical sensing toward NO2- and Fe3+ in the corresponding electrolytes. Co(II)-CP@HCNTs demonstrate superior electrocatalytic performance toward NO2- oxidation and Fe3+reduction to Co(II)-CP. The sensing mechanisms for NO2- and Fe3+ were illustrated with Hirshfeld surface analysis and density of states calculations. Furthermore, this methodology was successfully implemented on a miniaturized screen-printed electrode (SPE) platform. Among the three tested electrodes, the Co(II)-CP@HCNT-modified SPEs exhibited superior sensing capabilities, showing response ranges of 0.002-20 mM for nitrite and 0.002-38 mM for ferric ions, respectively. The calculated detection limits reached 0.12 μM for NO2- (δ = 0.00396 μA, N = 10) and 0.30 μM for Fe3+ (δ = 0.00201 μA, N = 10). Moreover, Co(II)-CP@HCNTs/SPE was further validated through practical applications for the detection of both analytes in real-world samples in the respective electrolytes.

Machine learning-assisted nitrite detection on smartphone-integrated μPAD using lychee-like perovskite nanocomposites

A reliable and convenient nitrite detection method is crucial for environmental monitoring and food safety. This study presents a novel dual-response nitrite detection platform utilizing monodisperse, water-stable, and lychee-like CsPbCl3: Mn2+@MSN@MnO2 (ClMnM@MnO2) nanocomposites. The in-situ growth of perovskite nanocrystals within mesoporous silica nano-templates (MSN) significantly enhances the dispersion and stability of the nanocomposites in water. Mn2+ doping introduces a second emission center, enabling potential post-synthetic designability. The MnO2 shell, synthesized through NaClO-mediated oxidation, exhibits excellent oxidase (OXD)-like activity. By integrating the nanocomposites with a microfluidic paper-based device (μPAD), we developed a portable system for quantitative nitrite detection by analyzing smartphone-captured images under both room and UV light. With the aid of machine learning (ML) through the ANN algorithm, this platform achieves nitrite concentration prediction and antioxidant additive discrimination, thereby expanding perovskite applications in biosensing and offering innovative solutions for nitrite detection in complex matrices.

Selectively Quantify Toxic Pollutants in Water by Machine Learning Empowered Electrochemical Biosensors

Electroactive biofilm (EAB) sensors have become pivotal in water quality detection and early ecological risk warnings due to their remarkable sensitivity. However, it is challenging to identify multiple toxicants in complex water bodies concurrently. This research developed an innovative biosensor detection strategy combined with machine learning. To simultaneously quantify and qualitatively predict the presence of each toxin in a multitoxic system, we developed a prediction model (MEA-ANN) based on machine learning analysis of EABs by analyzing the electrochemical toxicity response parameters of various toxicants (Cd2+, Cr6+, triclosan, and trichloroacetic acid). Furthermore, the mean impact value was utilized to filter the characteristic response parameters of toxicants, enhancing the prediction accuracy and efficiency of the model. The optimized model (OMEA-ANN) demonstrated strong performance in predicting target toxicants within interference systems containing analogs. The practicability and feasibility of this model were validated using seven real water samples and spiked natural water samples, achieving R2 > 0.9. The novel, eco-friendly, and intelligent water ecological risk early warning strategy presented in this paper addresses the limitations of traditional EAB sensors. It expands the applicability of EAB sensors for detecting multiple toxicants in water, significantly advancing their role in water quality monitoring. This approach provides valuable insights for the intelligent management of sewage.

Recent advances in electrochemical approaches for detection of nitrite in food samples

Nitrite is a common ingredient in the industry and agriculture; it is everywhere, like water, food, and surroundings. Recently, several approaches have been developed to measure the nitrite levels. So, this review was presented as a summary of many approaches utilized to detect the nitrite. Furthermore, the types of information that may be acquired using these methodologies, including optic and electrical signals, were discussed. In electrical signal methods, electrochemical sensors are usually developed using different materials, including carbon, polymers, oxides, and hydroxides. At the same time, optic signals receiving techniques involve utilizing fluorescence chromatography, absorption, and spectrometry instruments. Furthermore, these methodologies' benefits, drawbacks, and restrictions are examined. Lastly, due to the efficiency and fast means of electrochemical detectors, it was suggested that they can be used for detecting nitrite in food safety. Futuristic advancements in the techniques used for nitrite determination are subsequently outlined.

Fast preparing bioelectrode with conductive bioink for nitrite detection in high sensitivity and stability

Electrochemically active biofilms (EABs) for nitrite detection have high specificity, rapid response, operational simplicity, and extended lifespan advantages. However, their scale production remains challenging due to time-consuming and uniform preparation. In this study, a novel approach was proposed to fast fabricate an EAB biosensor with a synthetic biofilm electrode for nitrite detection. The biofilm electrode was prepared by coating bioinks with varying conductive materials onto the surface of the graphite sheets, showing short incubation time and good reproducibility. Incorporating conductive materials into the bioinks remarkably enhanced the maximum voltage of the first cycle of bioelectrode incubation, with an increase of up to 633% for carbon nanofibers. The nitrite reduction current was amplified by a factor of 2.97, due to the enhancement of extracellular electron transfer (EET). The developed nitrite biosensor exhibited a detection range of 0.1-15 mg NO2--N L-1, with a high sensitivity of 610.8 μA mM-1 cm-2, and a stabilization operation time of at least 280 cycles. This study not only provided valuable insights into conductive materials for synthetic biofilms but also presented a practical approach for the rapid preparation, scale production, and optimization of highly sensitive and stable EAB sensors.

Portable Mini-Electrochemical Cell: Integrating Microsampling and Micro-Electroanalysis for Multipurpose On-Site Nitrite Sensing

In modern analytical chemistry, one of the primary goals is to develop miniaturized, easy-to-use sensing tools, particularly those with multitasking capabilities. In this work, we designed a mini-voltammetric cell that integrates a modified Au microelectrode (Au/Au NPs as the working electrode) and an Ag/AgCl reference electrode installed within a micropipette tip. This combined tool not only enables portable and on-site microvolume sampling─requiring only a microvolume (around 20-40 μL) or a single droplet─but also facilitates direct micro-electroanalysis in a short time. To evaluate its capabilities, the mini-voltammetric cell was optimized for trace analysis of nitrite ions and demonstrated linear responses in the ranges of 20-150 and 150-1200 μM, with an acceptable limit of detection (LOD) of 18.40 μM, meeting both WHO and EPA standards for nitrite levels. Furthermore, it exhibited high selectivity, stability (up to 36 continuous measurements with only a 3.24% signal drop), and acceptable repeatability (RSD of 2.98%, n = 15). The analytical performance of this miniaturized tool was further assessed through the sampling and detection of nitrite ions in various real samples with different matrixes: (1) urine samples, for the fast diagnosis of urinary tract infections (UTIs), where nitrite ions are detected as biomarkers of UTIs; (2) river water polluted with agricultural waste, where nitrite ions serve as pollutants from nitrogen fertilizers; and (3) on the hands and in forensic investigations, where nitrite ions are detected as indicators of gunshot residue, crucial in crime scene examinations. All real samples were analyzed using the standard addition method and recovery tests, yielding acceptable results. Additionally, the proposed mini-analytical tool was evaluated for its sustainability and applicability using two recognized metrics: The Green Analytical Procedure Index (GAPI) and the Blue Applicability Grade Index (BAGI). The results confirmed that this method can be classified as both a green analytical method and highly applicable. Finally, the practical results demonstrated that the proposed miniaturized electroanalytical tool exhibits reliable performance, high sensitivity and selectivity, and fast response in the on-site microanalysis of nitrite, without the need for any reagents or complex sampling steps, across different real samples (such as clinical, forensic, and environmental samples). We believe the proposed mini-voltammetric cell could be used as an alternative to current detection methods, and with suitable modifications, it could be adapted for the microanalysis of other applications and (bio)targets with small volumes in the near future.

A Simultaneous Calibration and Detection Strategy for Electrochemical Sensing with High Accuracy in Complex Water

The electrochemical sensors loaded with nanomaterials have exhibited a great sensitivity. Nonetheless, the field detection for complex waterbodies can be affected by cross-sensitivity, environmental conditions such as temperature and pH value, as well as the relatively low reproducibility and stability of nanomaterials. In this paper, a simultaneous calibration and detection (SCD) strategy is proposed to introduce a simultaneous and precise calibration during field electrochemical detection, which is composed of a linear regression algorithm and a compact electrochemical sensor containing a series of identical sensing cells. This design can significantly mitigate cross-sensitivity in complex water and the inconsistency of sensing materials. Applied in the NO2- detection for practical waterbodies, the SCD strategy has exhibited a relative error of no more than 9.6% for the measurement compared to the results obtained by the standard Griess method and higher accuracy than the normal electrochemical method. The SCD strategy is independent of sensing materials, indicating that it can be widely applied to various detections by just switching the corresponding sensing material.

Continuous Flow with Reagent Injection on an Inlaid Microfluidic Platform Applied to Nitrite Determination

A continuous flow with reagent injection method on a novel inlaid microfluidic platform for nitrite determination has been successfully developed. The significance of the high-frequency monitoring of nutrient fluctuations in marine environments is crucial for understanding our impacts on the ecosystem. Many in-situ systems face limitations in high-frequency data collection and have restricted deployment times due to high reagent consumption. The proposed microfluidic device employs automatic colorimetric absorbance spectrophotometry, using the Griess assay for nitrite determination, with minimal reagent usage. The sensor incorporates 10 solenoid valves, four syringes, two LEDs, four photodiodes, and an inlaid microfluidic technique to facilitate optical measurements of fluid volumes. In this flow system, Taylor-Aris dispersion was simulated for different injection volumes at a constant flow rate, and the results have been experimentally confirmed using red food dye injection into a carrier stream. A series of tests were conducted to determine a suitable injection frequency for the reagent. Following the initial system characterization, seven different standard concentrations ranging from 0.125 to 10 µM nitrite were run through the microfluidic device to acquire a calibration curve. Three different calibrations were performed to optimize plug length, with reagent injection volumes of 4, 20, and 50 µL. A straightforward signal processing method was implemented to mitigate the Schlieren effect caused by differences in refractive indexes between the reagent and standards. The results demonstrate that a sampling frequency of at least 10 samples per hour is achievable using this system. The obtained attenuation coefficients exhibited good agreement with the literature, while the reagent consumption was significantly reduced. The limit of detection for a 20 µL injection volume was determined to be 94 nM from the sample intake, and the limit of quantification was 312 nM. Going forward, the demonstrated system will be packaged in a submersible enclosure to facilitate in-situ colorimetric measurements in marine environments.

A microfluidic concentration gradient colorimetric system for rapid detection of nitrite in surface water

A microfluidic concentration gradient colorimetric detection system consisting of a microfluidic concentration gradient colorimetric detection chip, a self-built colorimetric signal acquisition box and a self-written smartphone APP was constructed for the rapid, in-field and visual quantitative detection of nitrite. Specifically, nitrite with initial concentration of C0 can be automatically diluted into 8 concentration gradients characterized by arithmetic series, and the concentrations are 0, 0.20 C0, 0.33 C0, 0.46 C0, 0.59 C0, 0.72 C0, 0.86 C0 and C0. The colorimetric signal acquisition box avoided the interference of light spots on data acquisition. Under the optimal experimental conditions, the quantitative detection of nitrite was achieved by the proposed two-step colorimetric method based on the inhibition of AuNPs signal amplification, and the limit of detection (LOD) was 0.14 mg/L. The microfluidic concentration gradient colorimetric detection system was able to detect nitrite as low as 0.43 mg/L and showed a good specificity. The practical application was investigated by analyzing 10 actual samples of river and lake water, pure water and tap water. The recoveries of the microfluidic concentration gradient colorimetric detection system ranged from 94.92% to 105.60%, which indicates that the method had a good application prospect in the detection of practical samples.

Highly sensitive and ratiometric detection of nitrite in food based on upconversion-carbon dots nanosensor

Nitrite (NO₂^-) is extensively found in the daily dietary environment. However, consuming too much NO₂^- can pose serious health risks. Thus, we designed a NO₂^--activated ratiometric upconversion luminescence (UCL) nanosensor which could realize NO₂^- detection via the inner filter effect (IFE) between NO₂^--sensitive carbon dots (CDs) and upconversion nanoparticles (UCNPs). Due to the exceptional optical properties of UCNPs and the remarkable selectivity of CDs, the UCL nanosensor exhibited a good response to NO₂^-. By taking advantage of NIR excitation and ratiometric detection signal, the UCL nanosensor could eliminate the autofluorescence thereby increasing the detection accuracy effectively. Additionally, the UCL nanosensor proved successful in detecting NO₂^- quantitatively in actual samples. The UCL nanosensor provides a simple as well as sensitive sensing strategy for NO₂^- detection and analysis, which is anticipated to extend the utilization of upconversion detection in food safety.

Environmental ammonia analysis based on exclusive nitrification by nitrifying biofilm screened from natural bioresource

Biofilm-based biological nitrification is widely used for ammonia removal, while hasn't been explored for ammonia analysis. The stumbling block is the coexist of nitrifying and heterotrophic microbes in real environment resulting in non-specific sensing. Herein, an exclusive ammonia sensing nitrifying biofilm was screened from natural bioresource, and a bioreaction-detection system for the on-line analysis of environmental ammonia based on biological nitrification was reported. The nitrifying microbes were aggregated into a nitrifying biofilm through a result-oriented bioresource enrichment strategy. The predominant nitrifying population and progressive surface reaction in the plug flow bioreactor led to the exclusive and exhaustive ammonia biodegradation for the establishment of a novel analytical method. The on-line ammonia monitoring prototype achieved complete biodegradation for determining ammonium nitrogen within 5 min and showed exceptional reliability in long-term real sample measurements without frequent calibration. This work offers a low-threshold natural screening paradigm for developing sustainable bioresource-based analytical technologies.

In situ and self-adaptive BOD bioreaction sensing system based on environmentally domesticated microbial populations

Biochemical oxygen demand (BOD) is a water quality parameter of vital importance. Rapid BOD analysis methods have emerged to simplify the five-day BOD (BOD₅) measurement protocol. However, their universal implementations are restricted by the tricky environmental matrix (including environmental microbes, contaminants, ionic compositions, etc.). Here, an in situ and self-adaptive BOD bioreaction sensing system consisting of a "gut-like" microfluidic coil bioreactor with self-renewed biofilm was proposed for the establishment of a rapid, resilient and reliable BOD determination method. With the spontaneous surface adhesion of environmental microbial populations, the biofilm was colonized in situ on the inner surface of the microfluidic coil bioreactor. Exploiting the environmental domestication during every real sample measurement, the biofilm was capable of self-renewal to adapt to the environmental changes and exhibited representative biodegradation behaviors. The aggregated abundant, adequate and adapted microbial populations in the BOD bioreactor rendered a total organic carbon (TOC) removal rate of 67.7% within a short hydraulic retention time of 99 s. As validated by an online BOD prototype, exceptional analytical performance was achieved in terms of reproducibility (relative standard deviation of 3.7%), survivability (inhibition by pH and metal ion interference of <20%) and accuracy (relative error of -5.9% to 9.7%). This work rediscovered the interactive effects of the environmental matrix on BOD assays and demonstrated an instructive attempt by making use of the environment to develop practical online BOD monitoring devices for water quality assessments.

Innovative electrochemical biosensor with nitrifying biofilm and nitrite oxidation signal for comprehensive toxicity detection in Tuojiang River

Water toxicity detection, as a valuable supplement to conventional water quality measurement, is an important method for evaluating water environmental quality standards. However, the toxicity of composite pollutants is more complicated due to their mixture effects. This study developed a novel, rapid and interference-resistant detection method for water toxicity based on an electrochemical biosensor using peak current from nitrite oxidation as a signal. Toxicants could weaken the characteristic peak current of nitrite to indicate the magnitude of toxicity. The proof-of-concept study was first conducted using a synthetic water sample containing trichloroacetic acid (TCAA), and then the results were compared with those of the traditional toxicity colorimetric method (CCK-8 kit) and laser confocal microscopy (CLSM). The accuracy of the biosensor was further verified with water samples containing individual pollutants such as Cd²⁺ (50-150 μg/L), Cr⁶⁺ (20-80 μg/L) mixture, triclosan (TCS; 0.1-1.0 μg/L) and TCAA (10-80 μg/L), or a mixture of the above. The viability of the sensor was further validated with the actual water sample from the Tuojiang River. The results demonstrated that although the concentration of a single conventional pollutant in water did not exceed the discharge standard for surface water, the comprehensive toxicity of natural water should not be ignored. This method could be a beneficial supplement to conventional water quality detection to understand the characteristics of the water, and thus contribute to the next stage of water treatment.

Bionic Enzyme-Assisted Ion-Selective Amperometric Biosensor Based on 3D Porous Conductive Matrix for Point-of-Care Nitrite Testing

Nitrite plays a critical role in a variety of physiological processes and maintaining the nitrite level in an appropriate range is vital to keep healthy. Current nitrite analysis methods lack sensitivity and require tedious operations, which could not meet the need of point-of-care (POC) nitrite detection in precision medicine. Here we present a cyanocobalamin (VB₁₂) bionic enzyme-assisted ion-selective amperometric biosensor based on 3D porous conductive matrix (PCM), which can facilitate rapid and accurate POC nitrite monitoring in complex biofluids. The experimental findings quantitatively demonstrate that the biosensor has a sensitivity of 64.08 μA/(mM·cm²), a wide linear range of 0.025-45 mM, and low limit of detection of 1 nM. Moreover, the developed VB₁₂/BSA-PCM biosensor shows outstanding stability after 21 days with 2% decline in current signal, and high repeatability between batches with RSD of only 1.29%. Real salivary nitrite detection has been evaluated, and the results match well with the commercial nitrite analyzer. Thus, the bionic enzyme-assisted ion-selective amperometric biosensor proposed herein has potential utility as an affordable tool for POC detection and home-based healthcare.