A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors

Area of Science:

• Biochemistry
• Molecular Biology
• Cell Biology

Background:

• Fluorescent protein (FP)-based biosensors utilize intramolecular Förster resonance energy transfer (FRET) for visualizing biochemical events in living cells.
• Biosensor sensitivity relies on ratiometric emission changes, necessitating methods to maximize signal output.
• Optimizing biosensor constructs is crucial for expanding their utility in cellular research.

Purpose of the Study:

• To develop a high-throughput screening method for optimizing FRET-based biosensor variants.
• To enhance the detection of specific biochemical events, such as histone methylation.
• To improve the sensitivity and ratiometric change of existing biosensor designs.

Main Methods:

• Developed a function-based, high-throughput screening approach for biosensor variants in Escherichia coli colonies.
• Constructed and screened three distinct libraries: domain, lower-resolution linker, and higher-resolution linker libraries.
• Applied screening methodology to optimize a biosensor for detecting histone H3 lysine 27 (H3K27) methylation.

Main Results:

• Successfully optimized a biosensor for H3K27 trimethylation detection.
• The optimized biosensor demonstrated a 66% emission ratio change.
• This represents a 2.3-fold improvement compared to the initial biosensor's 29% emission ratio change.

Conclusions:

• The developed library screening methodology is effective for accelerating biosensor optimization.
• Significant improvements in biosensor performance, specifically for H3K27 trimethylation, were achieved.
• This approach enhances the visualization of biochemical events through improved biosensor sensitivity.