Amperometric detection of lignin-degrading peroxidase activities from Phanerochaete chrysosporium

A Comprehensive Review on Biopolymer Mediated Nanomaterial Composites and Their Applications in Electrochemical Sensors

Biopolymers are an attractive green alternative to conventional polymers, owing to their excellent biocompatibility and biodegradability. However, their amorphous and nonconductive nature limits their potential as active biosensor material/substrate. To enhance their bio-analytical performance, biopolymers are combined with conductive materials to improve their physical and chemical characteristics. We review the main advances in the field of electrochemical biosensors, specifically the structure, approach, and application of biopolymers, as well as their conjugation with conductive nanoparticles, polymers and metal oxides in green-based noninvasive analytical biosensors. In addition, we reviewed signal measurement, substrate bio-functionality, biochemical reaction, sensitivity, and limit of detection (LOD) of different biopolymers on various transducers. To date, pectin biopolymer, when conjugated with either gold nanoparticles, polypyrrole, reduced graphene oxide, or multiwall carbon nanotubes forming nanocomposites on glass carbon electrode transducer, tends to give the best LOD, highest sensitivity and can detect multiple analytes/targets. This review will spur new possibilities for the use of biosensors for medical diagnostic tests.

Effects of environmental variation on stable isotope abundances during typical seasonal floodplain dry season litter decomposition

Unique hydrological characteristics and complex topography can create wide-ranging dry season environmental heterogeneity in response to groundwater level across China's Jiangxi Province Poyang Lake wetland. Soil traits are one of several fluctuating environmental variables. To determine the effects of soil variables on stable isotope (δ¹³C and δ¹⁵N) abundances during decomposition, we performed a field experiment using Carex cinerascens along a groundwater level gradient (GT-L: -25 to -50cm, GT-LM: -15 to -25cm, GT-MH: -5 to -15cm, GT-H: 5 to -5cm) in a shallow lake. Twelve soil properties-including total organic carbon (TOC), nitrogen (N), pH, moisture, bulk density, clay, silt, sand, peroxidase, cellulase, microbial biomass carbon (MBC), and microbial biomass nitrogen-were measured in surface soil samples to assess soil environmental conditions. Analyses were performed to determine the effects of soil traits and lignin degradation on changes in stable isotope abundances. This study revealed that stable isotope abundances were significantly lower at high groundwater levels than at low groundwater levels. Lignin degradation was associated with a decrease in both δ¹³C and δ¹⁵N abundances. These two stable isotopes were positively related with soil N and bulk density, but negatively with pH and microbial quotient (MBC/TOC). Variation partitioning analysis (VPA) showed that soil variables and lignin decay rates explained 80.1% of the δ¹³C variation and 42.8% of the δ¹⁵N variation. Soil chemical and biological variables exhibited significant interactions with lignin decay rates, indicating they may affect stable isotope abundances via complex mechanisms. Our results indicate that the change in stable isotope abundances during decomposition may be affected directly by soil variables or indirectly through lignin degradation. Our results provide useful insight for understanding the roles of litter decomposition and soil traits in changing environmental conditions of seasonal floodplain wetlands.

Optical detection of NADH based on biocatalytic growth of Au-Ag core-shell nanoparticles

We have developed an optical assay for NADH (Dihydronicotinamide adenine dinucleotide) based on the catalytic growth of gold-silver core-shell nanoparticles (Au-Ag-CSNPs). The nanoparticles were immobilized on pretreated glass slide and are shown to catalyze the NADH-mediated reduction of Ag(I) ions in the presence of 1,4-benzoquinone and cetyltrimethyl ammonium ion. This leads to the formation of Au-Ag-CSNPs on the glass. The absorption peak of the Au-Ag-CSNPs at 415 nm increases with the concentration of NADH in the solution used, and this can be measured by UV-vis photometry. High-resolution scanning electron microscopy analysis of the morphology of the surface of the Au-Ag-CSNPs before and after the catalytic reaction revealed a growth of their diameter. Under optimal conditions, NADH can be determined in the concentration range from 0.2 to 3.2mM, and the detection limit is 15.6 μM. The sensor has good precision and good storage stability, simple in operation, and can be fabricated at low costs, which made it suitable for the determination of NADH in complex biological systems and in related degradation processes of contaminants.

Understanding lignin-degrading reactions of ligninolytic enzymes: binding affinity and interactional profile

Previous works have demonstrated that ligninolytic enzymes mediated effective degradation of lignin wastes. The degrading ability greatly relied on the interactions of ligninolytic enzymes with lignin. Ligninolytic enzymes mainly contain laccase (Lac), lignin peroxidase (LiP) and manganese peroxidase (MnP). In the present study, the binding modes of lignin to Lac, LiP and MnP were systematically determined, respectively. Robustness of these modes was further verified by molecular dynamics (MD) simulations. Residues GLU460, PRO346 and SER113 in Lac, residues ARG43, ALA180 and ASP183 in LiP and residues ARG42, HIS173 and ARG177 in MnP were most crucial in binding of lignin, respectively. Interactional analyses showed hydrophobic contacts were most abundant, playing an important role in the determination of substrate specificity. This information is an important contribution to the details of enzyme-catalyzed reactions in the process of lignin biodegradation, which can be used as references for designing enzyme mutants with a better lignin-degrading activity.

Highly sensitive sensor for detection of NADH based on catalytic growth of Au nanoparticles on glassy carbon electrode

In this work, an electrochemical dihydronicotinamide adenine dinucleotide (NADH) sensor based on the catalytic growth of Au nanoparticles (Au NPs) on glassy carbon electrode was developed. Catalyzed by Au NPs immobilized on pretreated glassy carbon electrode, the reduction of AuCl(4)(-) in the presence of hydroquinone and cetyltrimethyl ammonium chloride led to the formation of enlarged Au NPs on the electrode surface. Spectrophotometry and high-resolution scanning electronic microscope (SEM) analysis of the sensor morphologies before and after biocatalytic reaction revealed a diameter growth of the nanoparticles. The catalytic growth of Au NPs on electrode surface remarkably facilitated the electron transfer and improved the performance of the sensor. Under optimal conditions, NADH could be detected in the range from 1.25 x 10(-6) to 3.08 x 10(-4) M, and the detection limit was 2.5 x 10(-7) M. The advantages of the proposed sensor, such as high precision and sensitivity, fast response, low cost, and good storage stability, made it suitable for on-line detection of NADH in complex biological systems and contaminant degradation processes.

An electrochemical sensor for detection of laccase activities from Penicillium simplicissimum in compost based on carbon nanotubes modified glassy carbon electrode

An electrochemical sensor for detection of the activity of laccase from Penicillium simplicissimum isolated from the composting has been developed. The sensor is based on glassy carbon electrode modified with multi-wall carbon nanotubes (CNTs). The introduction of CNTs into this system can greatly enhance the electrochemical signal in this assay more sensitively, selectively and rapidly than that in conventional spectrophotometric assays. It was found that the optimal pH value of the electrolyte was 5.6. The results showed a good linear correlation between the current and the concentration of laccase activities measured by spectrophotometry, where the current slope was measured by chronoamperometry with a coefficient of 0.9835. Therefore, this electrochemical sensor can be used for rapid detection of laccase activity from P. simplicissimum. Furthermore, it may be potentially used for rapid quantification of P. simplicissimum according to the relationship between the laccase activities and the biomass.

Sensitive detection of lip genes by electrochemical DNA sensor and its application in polymerase chain reaction amplicons from Phanerochaete chrysosporium

An electrochemical DNA sensor based on the sandwich hybridization recognition of target sequence of lignin peroxidase (lip) genes on a gold electrode was developed. A monolayer of thiolated capture probe was formed on a gold electrode through self-assembling. Following hybridizations with target nucleic acid and biotinylated detection probe, streptavidin-horseradish peroxidase (HRP) conjugate was applied to the electrode. The DNA conformation and surface coverage on electrode were characterized by impedance spectroscopy and square wave voltammetry. The experimental variables were optimized to maximize the hybridization efficiency, detection sensitivity and speed up the assay time. The amperometric current response to HRP-catalyzed reaction was linearly related to the natural logarithm of the target nucleic acid concentration in the range from 0.6 to 30 nM, with the correlation coefficient of 0.9722. The detection limit was 0.03 nM. Synthesized oligonucleotide as well as Phanerochaete chrysosporium lip gene fragments amplified using polymerase chain reaction and digested by restriction endonucleases were tested. The DNA sensor exhibited good precision, stability, sensitivity, and selectivity, and discriminated satisfactorily against mismatched nucleic acid samples of similar lengths.

A hydroquinone biosensor using modified core–shell magnetic nanoparticles supported on carbon paste electrode

A hydroquinone biosensor was developed and used to determine hydroquinone concentration in compost extracts based on the immobilization of laccase on the surface of modified magnetic core-shell (Fe(3)O(4)-SiO2) nanoparticles. Laccase was covalently immobilized on the magnetic nanoparticles by glutaraldehyde, which was modified with amino groups on its surface. The obtained magnetic bio-nanoparticles were attached to the surface of carbon paste electrode with the aid of a permanent magnet to determine hydroquinone. A good microenvironment for retaining the bioactivity of laccase was provided by the immobilization matrix. The linear range for hydroquinone determination was 1 x 10(-7) to 1.375 x 10(-4)M, with a detection limit of 1.5 x 10(-8)M. The current reached 95% of the steady-state current within about 60s. Hydroquinone concentration in compost extracts was determined by laccase biosensor and HPLC, the results of the two methods were approximately the same.

Simultaneous amperometric determination of lignin peroxidase and manganese peroxidase activities in compost bioremediation using artificial neural networks

The activities of lignin-degrading peroxidases are the primary decomposition indexes in compost bioremediation. In this paper, artificial neural networks (ANNs) have been combined with an enzyme sensor for simultaneous determination of lignin peroxidase (LiP) and manganese peroxidase (MnP) activities secreted by Phanerochaete chrysosporium in composting of municipal solid waste. The LiP and MnP activities were detected through catalytic redox of H2O2, hydroquinone and veratryl alcohol as substrates by an amperometric sensor immersed in the culture filtrate solution. Due to the dynamic, nonlinear and uncertain characteristics of the complex composting system, ANNs have been used as a chemometric tool for overlapping signal deconvolution and modelling to quantify the two enzyme activities separately. Feedforward backpropagation network was used for the training process. The effects of the transfer functions, the amount of current values, the number of hidden neurons and the optimization algorithm were investigated. The LiP activities in the filtrate varied from 8.14 to 29.79 U L(-1), and from 0.36 to 1.37 U L(-1) for MnP activities. A good prediction capability was obtained, with correlation coefficients of 0.9936 for LiP activity and 0.9976 for MnP activity between the expected and predicted values of the external test samples. The performance of the ANN model was compared with the linear regression model in respect to simulation accuracy, adaptability to uncertainty, etc. All the results show that the combination of amperometric enzyme sensor and artificial neural networks is a rapid, sensitive and robust method in the quantitative study of composting system.