Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by...

Area of Science:

• Microbiology
• Synthetic Biology
• Metabolic Engineering

Background:

• Adaptive laboratory evolution (ALE) is a powerful technique for microbial strain engineering and genomics.
• ALE is well-suited for adapting microorganisms to new environments and substrates.
• Long ALE experiments require frequent cell proliferation, ideally without duration constraints.

Purpose of the Study:

• To develop an extended robotic workflow for long-term evolution experiments using automated repetitive batch cultures (rbALE).
• To improve ethanol utilization in Corynebacterium glutamicum using the established rbALE workflow.
• To identify genetic modifications responsible for enhanced ethanol assimilation.

Main Methods:

• Implemented a fully automated repetitive batch culture (rbALE) workflow in a microbioreactor system.
• Utilized a microtiter plate recycling approach for unlimited batch cultures and cell generations.
• Performed genome sequencing and re-engineering to identify key genetic variations.

Main Results:

• The rbALE workflow successfully improved ethanol utilization in Corynebacterium glutamicum.
• The evolved strain (WT_EtOH-Evo) exhibited significantly higher ethanol uptake and growth rates.
• A single nucleotide variation upstream of the acetaldehyde dehydrogenase (ALDH) gene was identified as crucial for enhanced ethanol assimilation by affecting GlxR binding and ALDH synthesis.

Conclusions:

• The developed rbALE technology is broadly applicable to various microbial strains and selection pressures.
• The findings enable improved production processes using C. glutamicum with ethanol as a substrate.
• This advancement is particularly relevant for the production of acetyl-CoA-derived products.