Multidomain DNA-Protein Mining Reveals Polymorphic Variations in RhlB Enhancing Monorhamnolipid Biosynthesis.

Area of Science:

• Biotechnology
• Enzyme Engineering
• Microbial Biosynthesis

Background:

• Rhamnolipids are biodegradable glycolipid biosurfactants with green chemistry applications.
• The RhlB enzyme is crucial for rhamnolipid biosynthesis, and enhancing its activity is key to increasing production.
• Natural enzyme diversity offers potential for optimizing catalytic efficiency.

Purpose of the Study:

• To identify and characterize novel RhlB enzyme variants with enhanced catalytic activity for monorhamnolipid production.
• To develop and apply a computational-experimental pipeline for enzyme discovery and engineering.
• To investigate the structural and functional basis of improved RhlB activity.

Main Methods:

• A multilayer DNA-protein mining pipeline integrating sequence, structure, and stability analyses.
• Phylogenetic analysis to identify evolutionary divergence and hypermutator phylogroups.
• Experimental validation of selected rhlB variants in Escherichia coli using a modular rhlAB construct.
• High-throughput screening for quantifying monorhamnolipid production.

Main Results:

• Identified two hypermutator phylogroups within RhlB, indicating evolutionary divergence.
• Validated three rhlB variants (rhlB1, rhlB2, rhlB3) for monorhamnolipid biosynthesis.
• Achieved a 2.76-fold increase in monorhamnolipid production using the RhlB3 variant (55.51 μg mL^-1).
• Determined that mutation H263R in RhlB2 impairs activity, while loop mutations (I234V, P238R) in RhlB3 enhance substrate binding and catalysis.

Conclusions:

• The integrated computational and experimental approach successfully identified naturally optimized RhlB variants.
• Enzyme engineering through mining natural diversity is a viable strategy for enhancing biosurfactant production.
• This framework accelerates enzyme discovery for sustainable bioprocess development.