Issue 48, 2020

Lignin nanoparticles are renewable and functional platforms for the concanavalin a oriented immobilization of glucose oxidase–peroxidase in cascade bio-sensing

Abstract

Lignin nanoparticles (LNPs) acted as a renewable and efficient platform for the immobilization of horseradish peroxidase (HRP) and glucose oxidase (GOX) by a layer by layer procedure. The use of concanavalin A as a molecular spacer ensured the correct orientation and distance between the two enzymes as confirmed by Förster resonance energy transfer measurement. Layers with different chemo–physical properties tuned in a different way the activity and kinetic parameters of the enzymatic cascade, with cationic lignin performing as the best polyelectrolyte in the retention of the optimal Con A aggregation state. Electrochemical properties, temperature and pH stability, and reusability of the novel systems have been studied, as well as their capacity to perform as colorimetric biosensors in the detection of glucose using ABTS and dopamine as chromogenic substrates. A boosting effect of LNPs was observed during cyclovoltammetry analysis. The limit of detection (LOD) was found to be better than, or comparable to, that previously reported for other HRP–GOX immobilized systems, the best results being again obtained in the presence of a cationic lignin polyelectrolyte. Thus renewable lignin platforms worked as smart and functional devices for the preparation of green biosensors in the detection of glucose.

Graphical abstract: Lignin nanoparticles are renewable and functional platforms for the concanavalin a oriented immobilization of glucose oxidase–peroxidase in cascade bio-sensing

Supplementary files

Article information

Article type
Paper
Submitted
20 May 2020
Accepted
23 Jul 2020
First published
05 Aug 2020
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2020,10, 29031-29042

Lignin nanoparticles are renewable and functional platforms for the concanavalin a oriented immobilization of glucose oxidase–peroxidase in cascade bio-sensing

E. Capecchi, D. Piccinino, E. Tomaino, B. M. Bizzarri, F. Polli, R. Antiochia, F. Mazzei and R. Saladino, RSC Adv., 2020, 10, 29031 DOI: 10.1039/D0RA04485G

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