A high-throughput multiparameter screen for accelerated development and optimization of soluble genetically encoded...

Area of Science:

• Biotechnology
• Molecular Biology
• Chemical Biology

Background:

• Genetically encoded fluorescent biosensors are crucial for monitoring biological processes.
• Current biosensor development is hindered by slow, labor-intensive screening methods.
• Existing techniques often screen only one biosensor characteristic at a time.

Purpose of the Study:

• To develop a novel, high-throughput screening modality for biosensor optimization.
• To enable parallel evaluation of multiple biosensor features.
• To generate an improved biosensor for intracellular lactate detection.

Main Methods:

• Integration of droplet microfluidics with automated fluorescence imaging.
• Development of a screening platform for enhanced throughput and multi-feature analysis.
• Application of the system to engineer a lactate biosensor.

Main Results:

• Achieved an order of magnitude increase in screening throughput.
• Enabled parallel assessment of biosensor brightness, contrast, affinity, and specificity.
• Successfully generated a high-performance lactate biosensor, named LiLac.
• Demonstrated the capability to quantify intracellular lactate concentrations.

Conclusions:

• The described screening modality significantly accelerates biosensor development and optimization.
• The LiLac biosensor represents a substantial advancement in metabolite sensing.
• This approach highlights the potential of microfluidics and automated imaging in biological tool development.