No abstract

Nitrite ions have emerged as one of the major problems in environmental and pollution issuesnowadays. Food products are the major source of these ions to preserve color. However, thereis a maximum permissible limit (MPL) for the use of nitrite in food. A lot of works in theliterature have been carried out on nitrite quantification and most of them are using simple andquick analysis methods. Recently, the advent of biosensor has allowed the fabrication ofsensors for the detection of nitrite. This paper specifically reviews the interest in the usage ofthe nitrite reductase enzyme as a biorecognition element for the application of nitritebiosensors.

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A microbial optosensor for nitrite was constructed based on biomimetic silica nanoparticles, which were doped with R5, a polypeptide component of silaffin, as a robust biosilica immobilization matrix entrapped with Raoultella planticola and NAD(P)H cofactor during the in vitro biosilicification process of silica nanoparticles. Ruthenium(II)(bipy)2(phenanthroline-benzoylthiourea), the chromophoric pH probe, was physically adsorbed on the resulting biogenic nanosilica. Optical quantitation of the nitrite concentration was performed via reflectance transduction of the bio-doped microbial nanosilica at a maximum reflectance of 608 nm, due to the deprotonation of phen-BT ligands in the ruthenium complex, while the intracellular enzyme expression system catalyzed the enzymatic reduction of nitrite. Reflectance enhancement of the microbial optosensor was linearly proportional to the nitrite concentration from 1–100 mg L−1, with a 0.25 mg L−1 limit of detection and a rapid response time of 4 min. The proposed microbial optosensor showed good stability of >2 weeks, great repeatability for 5 repetitive assays (relative standard deviation, (RSD) = 0.2–1.4%), high reproducibility (RSD = 2.5%), and a negligible response to common interferents found in processed meats, such as NO3−, NH4+, K+, Ca2+, and Mg2+ ions, was observed. The microbial biosensor demonstrated an excellent capacity to provide an accurate estimation of nitrite in several cured meat samples via validation using a standard UV-vis spectrophotometric Griess assay.