Co-reactant-free self-enhanced solid-state electrochemiluminescence platform based on polyluminol-gold nanocomposite for signal-on detection of mercury ion

Development of a self-enhanced solid-state ECL platform creates a straightforward experimental design for the fabrication of point-of-care applications. Herein, we develop a promising method for self-enhanced solid-state ECL platform of polyluminol gold nanocomposite on glassy carbon electrode [(PL-Au)_nano/GCE] via simple one-step electrochemical deposition process without involving any additional co-reactants. The presence of gold nanoparticles (AuNPs) augments the electron transfer kinetics of PL (polyluminol) and enhances the solid-state ECL intensity and promotes label-free, excellent sensitivity, and selectivity to detect Hg²⁺ in physiological pH through signal-on mode. Unlike pristine PL/GCE, electrochemically co-deposited AuNPs in the (PL-Au)_nano/GCE composite, enable the co-reactant accelerator by improving the catalytic activity of PL towards oxygen reduction reaction (ORR) yielding in-situ ROS (co-reactant) generation. Further, the ECL intensity of (PL-Au)_nano/GCE composite, gradually increases with each addition of Hg²⁺ ion. This is because of the formation of an amalgamation of Au-Hg on (PL-Au)_nano/GCE composite surface which further accelerates the yield of in-situ ROS and enhances the intensity of ECL. Whereas no ECL signals changes were observed for PL/GCE composite. The proposed self-enhanced solid-state ECL platform is selectively sensing the Hg²⁺ ion in the linear range of 0.3–200 nM with a detection limit of 0.1 nM. The demonstrated (PL-Au)_nano/GCE platform might pave new avenues for further studies in the solid-state ECL platform which could be more useful in on-site monitoring of clinical bioassay and immunosensors.

Improving the accuracy of high-throughput protein-protein affinity prediction may require better training data

Background

One goal of structural biology is to understand how a protein’s 3-dimensional conformation determines its capacity to interact with potential ligands. In the case of small chemical ligands, deconstructing a static protein-ligand complex into its constituent atom-atom interactions is typically sufficient to rapidly predict ligand affinity with high accuracy (>70% correlation between predicted and experimentally-determined affinity), a fact that is exploited to support structure-based drug design. We recently found that protein-DNA/RNA affinity can also be predicted with high accuracy using extensions of existing techniques, but protein-protein affinity could not be predicted with >60% correlation, even when the protein-protein complex was available.

Methods

X-ray and NMR structures of protein-protein complexes, their associated binding affinities and experimental conditions were obtained from different binding affinity and structural databases. Statistical models were implemented using a generalized linear model framework, including the experimental conditions as new model features. We evaluated the potential for new features to improve affinity prediction models by calculating the Pearson correlation between predicted and experimental binding affinities on the training and test data after model fitting and after cross-validation. Differences in accuracy were assessed using two-sample t test and nonparametric Mann–Whitney U test.

Results

Here we evaluate a range of potential factors that may interfere with accurate protein-protein affinity prediction. We find that X-ray crystal resolution has the strongest single effect on protein-protein affinity prediction. Limiting our analyses to only high-resolution complexes (≤2.5 Å) increased the correlation between predicted and experimental affinity from 54 to 68% (p = 4.32x10⁻³). In addition, incorporating information on the experimental conditions under which affinities were measured (pH, temperature and binding assay) had significant effects on prediction accuracy. We also highlight a number of potential errors in large structure-affinity databases, which could affect both model training and accuracy assessment.

Conclusions

The results suggest that the accuracy of statistical models for protein-protein affinity prediction may be limited by the information present in databases used to train new models. Improving our capacity to integrate large-scale structural and functional information may be required to substantively advance our understanding of the general principles by which a protein’s structure determines its function.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1533-z) contains supplementary material, which is available to authorized users.

Rapid amperometric detection of trace metals by inhibition of an ultrathin polypyrrole-based glucose biosensor

A sensitive and reliable inhibitive amperometric glucose biosensor is described for rapid trace metal determination. The biosensor utilises a conductive ultrathin (55 nm thick) polypyrrole (PPy) film for entrapment of glucose oxidase (GOx) to permit rapid inhibition of GOx activity in the ultrathin film upon exposure to trace metals, resulting in reduced glucose amperometric response. The biosensor demonstrates a relatively fast response time of 20s and does not require incubation. Furthermore, a complete recovery of GOx activity in the ultrathin PPy-GOx biosensor is quickly achieved by washing in 2mM EDTA for only 10s. The minimum detectable concentrations achieved with the biosensor for Hg(2+), Cu(2+), Pb(2+) and Cd(2+) by inhibitive amperometric detection are 0.48, 1.5, 1.6 and 4.0 µM, respectively. Also, suitable linear concentration ranges were achieved from 0.48-3.3 µM for Hg(2+), 1.5-10 µM for Cu(2+), 1.6-7.7 µM for Pb(2+) and 4-26 µM for Cd(2+). The use of Dixon and Cornish-Bowden plots revealed that the suppressive effects observed with Hg(2+) and Cu(2+) were via non-competitive inhibition, while those of Pb(2+) and Cd(2+) were due to mixed and competitive inhibition. The stronger inhibition exhibited by the trace metals on GOx activity in the ultrathin PPy-GOx film was also confirmed by the low inhibition constant obtained from this analysis. The biosensor was successfully applied to the determination of trace metals in tap water samples.

Performance Evaluation of Monolith Based Immobilized Acetylcholinesterase Flow-Through Reactor for Copper(II) Determination with Spectrophotometric Detection

A monolith based immobilized acetylcholinesterase (AChE) flow-through reactor has been developed for the determination of copper(II) using flow injection spectrophotometric system. The bioreactor was prepared inside a microcapillary column byin situpolymerization of butyl methacrylate, ethylene dimethacrylate, and 2,2-dimethoxy-1,2-diphynyletane-1-one in the presence of 1-decanol, followed by vinyl azlactone functionalization and AChE immobilization. The behavior of AChE before and after being immobilized on the monolith was evaluated by kinetic parameters from Lineweaver and Burk equation. The detection was based on measuring inhibition effect on the enzymatic activity of AChE by copper(II) using Ellman’s reaction with spectrophotometric detection at 410 nm. The linear range of the calibration graph was obtained over the range of 0.02–3.00 mg L−1. The detection limit, defined as 10% inhibition (I10), was found to be 0.04 mg L−1. The repeatability was 3.35 % (n=5) for 1.00 mg L−1of copper(II). The proposed method was applied to the determination of copper(II) in natural water samples with sampling rate of 4 h−1.

Indirect determination of mercury ion by inhibition of a glucose biosensor based on ZnO nanorods

A potentiometric glucose biosensor based on immobilization of glucose oxidase (GOD) on ZnO nanorods (ZnO-NRs) has been developed for the indirect determination of environmental mercury ions. The ZnO-NRs were grown on a gold coated glass substrate by using the low temperature aqueous chemical growth (ACG) approach. Glucose oxidase in conjunction with a chitosan membrane and a glutaraldehyde (GA) were immobilized on the surface of the ZnO-NRs using a simple physical adsorption method and then used as a potentiometric working electrode. The potential response of the biosensor between the working electrode and an Ag/AgCl reference electrode was measured in a 1mM phosphate buffer solution (PBS). The detection limit of the mercury ion sensor was found to be 0.5 nM. The experimental results provide two linear ranges of the inhibition from 0.5 × 10⁻⁶ mM to 0.5 × 10⁻⁴ mM, and from 0.5 × 10⁻⁴ mM to 20 mM of mercury ion for fixed 1 mM of glucose concentration in the solution. The linear range of the inhibition from 10⁻³ mM to 6 mM of mercury ion was also acquired for a fixed 10 mM of glucose concentration. The working electrode can be reactivated by more than 70% after inhibition by simply dipping the used electrode in a 10 mM PBS solution for 7 min. The electrodes retained their original enzyme activity by about 90% for more than three weeks. The response to mercury ions was highly sensitive, selective, stable, reproducible, and interference resistant, and exhibits a fast response time. The developed glucose biosensor has a great potential for detection of mercury with several advantages such as being inexpensive, requiring minimum hardware and being suitable for unskilled users.

Electrochemical biosensors

Electrochemical biosensors combine the sensitivity of electroanalytical methods with the inherent bioselectivity of the biological component. The biological component in the sensor recognizes its analyte resulting in a catalytic or binding event that ultimately produces an electrical signal monitored by a transducer that is proportional to analyte concentration. Some of these sensor devices have reached the commercial stage and are routinely used in clinical, environmental, industrial, and agricultural applications. The two classes of electrochemical biosensors, biocatalytic devices and affinity sensors, will be discussed in this critical review to provide an accessible introduction to electrochemical biosensors for any scientist (110 references).

Recent biosensing developments in environmental security

Environmental security is one of the fundamental requirements of our well being. However, it still remains a major global challenge. Therefore, in addition to reducing and/or eliminating the amounts of toxic discharges into the environment, there is need to develop techniques that can detect and monitor these environmental pollutants in a sensitive and selective manner to enable effective remediation. Because of their integrated nature, biosensors are ideal for environmental monitoring and detection as they can be portable and provide selective and sensitive rapid responses in real time. In this review we discuss the main concepts behind the development of biosensors that have most relevant applications in the field of environmental monitoring and detection. We also review and document recent trends and challenges in biosensor research and development particularly in the detection of species of environmental significance such as organophosphate nerve agents, heavy metals, organic contaminants, pathogenic microorganisms and their toxins. Special focus will be given to the trends that have the most promising applications in environmental security. We conclude by highlighting the directions towards which future biosensors research in environmental security sector might proceed.

Enzyme inhibition-based biosensors for food safety and environmental monitoring

Analytical technology based on sensors is an extremely broad field which impacts on many major industrial sectors such as the pharmaceutical, healthcare, food, and agriculture industries as well as environmental monitoring. This review will highlight the research carried out during the last 5 years on biosensors that are based on enzyme inhibition for determination of pollutants and toxic compounds in a wide range of samples. Here the different enzymes implicated in the inhibition, different transducers forming the sensing devices, and the different contaminants analyzed are considered. The general application of the various biosensors developed, with emphasis on food and environmental applications, is reviewed as well as the general approaches that have been used for enzyme immobilization, the enzyme catalysis, and the inhibition mechanism.