A systematic framework for using membrane metrics for strain engineering

Area of Science:

• Microbial biotechnology
• Synthetic biology
• Biochemical engineering

Background:

• The cell membrane is crucial for microbial cell factory performance and a key engineering target.
• Understanding membrane composition-performance relationships is vital for optimizing biocatalysts.
• Existing methods lack a systematic framework for identifying membrane engineering targets.

Purpose of the Study:

• To develop a systematic framework for identifying cell membrane features as engineering targets.
• To characterize the relationship between membrane lipid composition and cellular outcomes under various inhibitory conditions.
• To identify predictive metrics for microbial cell factory performance.

Main Methods:

• Generated microbial strains with altered membrane lipid composition by expressing des, fabA, and fabB genes.
• Characterized membrane lipid composition ('knobs') and cellular outcomes ('outcomes') across multiple inhibitory conditions.
• Analyzed correlations between lipid composition metrics (e.g., L/nL ratio, average lipid length) and membrane properties (e.g., permeability, hydrophobicity, fluidity, growth rate).

Main Results:

• Identified significant correlations between membrane lipid composition and physical properties, varying by inhibitor but also consistent across conditions.
• The ratio of linear to non-linear lipids (L/nL ratio) positively correlated with cell surface hydrophobicity across all conditions.
• Average lipid length positively correlated with specific growth rate across all conditions.
• The L/nL ratio and membrane hydrophobicity were identified as key predictors of cell growth under multiple inhibitors.
• Experimental validation confirmed membrane hydrophobicity as a significant predictor of ethanol production.

Conclusions:

• Cell membrane physical properties can predict biocatalyst performance under single and multiple inhibitory conditions.
• Identified membrane properties serve as potential engineering targets for microbial cell factories.
• Membrane properties can be utilized as screening or selection metrics for strain engineering libraries and evolution-based approaches.