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Bioluminescent enzyme inhibition-based assay to predict the potential toxicity of carbon nanomaterials
A bioluminescent enzyme inhibition-based assay was applied to predict the potential toxicity of carbon nanomaterials (CNM) presented by single- and multi-walled nanotubes (SWCNT and MWCNT) and aqueous solutions of hydrated fullerene С60 (C60HyFn). This assay specifically detects the influence of sub...
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Published in: | Toxicology in vitro 2017-12, Vol.45 (Pt 1), p.128-133 |
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Main Authors: | , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | A bioluminescent enzyme inhibition-based assay was applied to predict the potential toxicity of carbon nanomaterials (CNM) presented by single- and multi-walled nanotubes (SWCNT and MWCNT) and aqueous solutions of hydrated fullerene С60 (C60HyFn). This assay specifically detects the influence of substances on parameters of the soluble or immobilised coupled enzyme system of luminescent bacteria: NAD(P)Н:FMN-oxidoreductase+luciferase (Red+Luc). A protocol based on the optical properties of CNM for correcting the results of the bioluminescent assay was also developed. It was shown that the inhibitory activity of CNM on Red+Luc decreased in the following order: MWCNT>SWCNT>C60HyFn. The soluble enzyme system Red+Luc had high sensitivity to MWCNT and SWCNT, with values of the inhibition parameter IC50 equal to 0.012 and 0.16mg/L, respectively. The immobilised enzyme system was more vulnerable to C60HyFn than its soluble form, with an IC50 equal to 1.4mg/L. Due to its technical simplicity, rapid response time and high sensitivity, this bioluminescent method has the potential to be developed as a general enzyme inhibition-based assay for a wide variety of nanomaterials.
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•Bioluminescent enzymatic assay for CNM potential toxicity was proposed.•The assay predicts toxicity decreasing in the following order: MWCNT>SWCNT>C60HyFn.•Soluble and immobilised enzymes differ qualitatively in CNM toxicity prediction. |
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ISSN: | 0887-2333 1879-3177 |
DOI: | 10.1016/j.tiv.2017.08.022 |