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Development of an miRFP680-Based Fluorescent Calcium Ion Biosensor Using End-Optimized Transposons
Fu Chai1, Hajime Fujii2, Giang N T Le3
1Department of Chemistry, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan.
ACS Sensors
|June 1, 2024
Summary
Researchers developed novel transposon tools to create advanced single fluorescent protein biosensors (SFPBs). This accelerates the discovery of near-infrared biosensors for improved biological imaging and calcium ion (Ca2+) detection.
Area of Science:
- Biotechnology
- Molecular Biology
- Bioimaging
Background:
- Advancements in biological imaging rely on novel single fluorescent protein biosensors (SFPBs).
- Near-infrared (NIR) SFPBs are particularly valuable for deep-tissue imaging and reduced phototoxicity.
- Efficient methods for developing SFPBs with optimized allosteric coupling are needed.
Purpose of the Study:
- To develop and validate modified transposons for accelerated creation of SFPB libraries.
- To discover novel SFPBs, including those operating at near-infrared wavelengths.
- To engineer highly optimized calcium ion (Ca2+) biosensors for biological applications.
Main Methods:
- Utilized modified transposons for random insertion of fluorescent proteins (FPs) into analyte-binding domains, and vice versa.
- Employed end-modified Mu transposons to create SFPB prototypes for l-lactate, spermidine, and Ca2+.
- Applied directed evolution, including under biliverdin (BV)-deficient conditions, to optimize Ca2+ biosensors.
Main Results:
- Successfully generated SFPB prototypes for l-lactate, spermidine, and Ca2+ using the transposon system.
- Discovered Ca2+-specific SFPBs by inserting calmodulin into a NIR FP (miRFP680).
- Developed the highly optimized NIR-GECO3 series of Ca2+ biosensors through directed evolution.
Conclusions:
- Modified transposons significantly accelerate the development of diverse SFPBs.
- The NIR-GECO3 series represents a significant advancement in Ca2+ biosensor technology for biological imaging.
- This methodology provides a versatile platform for future SFPB discovery and optimization.
