Development and optimization of a novel conductometric bi-enzyme biosensor for L-arginine determination.
Abstract
A highly sensitive conductometric biosensor for l-arginine determination was developed by exploiting the unique biorecognition capacities of two enzymes of urea cycle - arginase (E.C. 3.5.3.1) and urease (E.C. 3.5.1.5). The enzymes were co-immobilized in a single bioselective membrane on the working sensor, while a lysine rich bovine serum albumin (BSA) membrane was immobilized on the reference sensor, allowing differential measurements. The optimum percentage ratio of arginase and urease within the bioselective membrane was determined when the biosensor sensitivity to l-arginine and urea was optimum. Analytical characteristics of the conductometric biosensor for l-arginine determination were compared for two types of enzyme immobilization (cross-linking with glutaraldehyde (GA) and entrapment in the polymeric membrane). The optimum features in terms of the sensitivity, the linear range, and the detection limit (4.2 μS/mM, 0.01-4mM, and 5.0 × 10(-7)M, respectively) were found for l-arginine biosensor based on enzyme cross-linking with GA. A quantitative determination of l-arginine in the real sample (a drinkable solution "Arginine Veyron") gave a satisfactory result compared to the data provided by the producer (a relative error was 4.6%). The developed biosensor showed high operational and storage stability.
Links
Authors
Saiapina OY, Dzyadevych SV, Jaffrezic-Renault N, Soldatkin OP
Institution
Laboratory of Biomolecular Electronics, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, 150 Zabolotnogo St., Kyiv 03680, Ukraine. osayapina4@gmail.com
Source
Talanta 92: 2012 Apr 15 pg 58-64MeSH
AnimalsArginase
Arginine
Biosensing Techniques
Cattle
Conductometry
Cross-Linking Reagents
Electrodes
Enzymes, Immobilized
Glutaral
Hydrogen-Ion Concentration
Limit of Detection
Membranes, Artificial
Serum Albumin, Bovine
Urease
Pub Type(s)
Journal ArticleResearch Support, Non-U.S. Gov't
Language
eng
PubMed ID
22385808
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