Issue 24, 2022

A two-step screening to optimize the signal response of an auto-fluorescent protein-based biosensor

Abstract

Auto-fluorescent protein (AFP)-based biosensors transduce the structural change in their embedded recognition modules induced by recognition/reaction events to fluorescence signal changes of AFP. The lack of detailed structural information on the recognition module often makes it difficult to optimize AFP-based biosensors. To enhance the signal response derived from detecting the putative structural change in the nitric oxide (NO)-sensing segment of transient receptor potential canonical 5 (TRPC5) fused to enhanced green fluorescent protein (EGFP), EGFP-TRPC5, a facile two-step screening strategy, in silico first and in vitro second, was applied to variants of EGFP-TRPC5 deletion-mutated within the recognition module. In in silico screening, the structural changes of the recognition modules were evaluated as root-mean-square-deviation (RMSD) values, and 10 candidates were efficiently selected from 47 derivatives. Through in vitro screening, four mutants were identified that showed a larger change in signal response than the parent EGFP-TRPC5. One mutant in particular, 551-575, showed four times larger change upon reaction with NO and H2O2. Furthermore, mutant 551-575 also showed a signal response upon reaction with H2O2 in mammalian HEK293 cells, indicating that the mutant has the potential to be applied as a biosensor for cell measurement. Therefore, this two-step screening method effectively allows the selection of AFP-based biosensors with sufficiently enhanced signal responses for application in mammalian cells.

Graphical abstract: A two-step screening to optimize the signal response of an auto-fluorescent protein-based biosensor

Supplementary files

Article information

Article type
Paper
Submitted
06 apr. 2022
Accepted
15 maí 2022
First published
20 maí 2022
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2022,12, 15407-15419

A two-step screening to optimize the signal response of an auto-fluorescent protein-based biosensor

S. Tajima, E. Nakata, R. Sakaguchi, M. Saimura, Y. Mori and T. Morii, RSC Adv., 2022, 12, 15407 DOI: 10.1039/D2RA02226E

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