Long-duration environmental biosensing by recording analyte detection in DNA using recombinase memory

Area of Science:

• Synthetic biology
• Microbial engineering
• Environmental monitoring

Background:

• Traditional microbial biosensors struggle with optical inaccessibility in complex environments like soil and wastewater.
• A promising solution involves biosensors that record transient analyte exposure over extended periods for later retrieval.
• Recombinase-based genetic memory systems offer a strategy for stable, long-term recording of microbial environmental interactions.

Purpose of the Study:

• To engineer and test recombinase-memory biosensors for stable recording of analyte exposure in microbes.
• To overcome limitations of initial designs, including unintended DNA flipping and loss of memory.
• To apply and validate these improved memory biosensors in environmental isolates for in situ applications.

Main Methods:

• Development of recombinase-memory biosensors to detect arabinose and 3-oxo-C12-L-homoserine lactone.
• Iterative optimization of biosensor design by adjusting recombinase expression and output mechanisms.
• Utilizing quantitative PCR for readout of stored genetic memory.
• Testing biosensor performance in wastewater microbial isolates over an 8-day period.

Main Results:

• Initial biosensor designs exhibited instability, with unintended DNA flipping and memory loss.
• Optimized designs, featuring reduced recombinase expression and quantitative PCR readout, demonstrated improved performance.
• The memory biosensor successfully recorded analyte exposure in an uncharacterized *Pseudomonas* isolate from wastewater.
• The system demonstrated stable memory over approximately 70 generations.

Conclusions:

• Recombinase-memory biosensors can be engineered for stable, long-term recording of microbial analyte exposure.
• Optimization strategies are crucial for reliable performance in complex environmental conditions.
• These engineered microbes offer a powerful tool for in situ investigation of microbial signaling, community dynamics, and ecological processes.