Sorting for secreted molecule production using a biosensor-in-microdroplet approach.

Area of Science:

• Synthetic biology
• Metabolic engineering
• High-throughput screening

Background:

• Cellular production and secretion of small molecules are crucial for various industries.
• Current screening methods for optimizing these processes are often slow and labor-intensive.
• Developing efficient platforms to sort large cell libraries is essential for advancing metabolic engineering.

Purpose of the Study:

• To establish a versatile microfluidic workflow for high-throughput screening of cell libraries for enhanced small molecule secretion.
• To demonstrate the adaptability of this workflow across different cell types, genetic engineering methods, and target molecules.

Main Methods:

• Integration of producer/secretor cell libraries with whole-cell biosensors within a microfluidic platform.
• Utilizing coencapsulation or pico-injection for flexible biosensor integration.
• Application of diverse mutagenesis libraries (single-guide RNA, transposon, ethyl-methyl sulfonate) in multiple microbial hosts (Escherichia coli, Saccharomyces cerevisiae, Yarrowia lipolytica).

Main Results:

• Demonstrated a cell type and library-agnostic screening workflow.
• Successfully screened libraries across three distinct microbes and employed biosensors from two different organisms.
• Identified targets for improving the production and secretion of three different molecules: triacetic acid lactone, naringenin, and L-DOPA.

Conclusions:

• The developed microfluidic workflow significantly enhances the throughput for sorting cell libraries for improved small molecule secretion.
• This adaptable platform accelerates the discovery of novel microbial strains with optimized production capabilities.
• The demonstrated versatility paves the way for broader applications in synthetic biology and metabolic engineering.