A Novel Biosensor for Ferrous Iron Developed via CoBiSe: A Computational Method for Rapid Biosensor Design.

Area of Science:

• Biotechnology
• Molecular Biology
• Systems Biology

Background:

• Genetically encoded biosensors are crucial for monitoring metabolite dynamics in living systems.
• Designing effective biosensors often involves complex and labor-intensive screening processes.

Purpose of the Study:

• To present CoBiSe, a computational biosensor design approach.
• To develop a novel ratiometric biosensor for ferrous iron (Fe2+) detection.

Main Methods:

• Utilized Constraint Network Analysis within the CoBiSe framework to identify optimal reporter module insertion sites in molecular recognition elements (MREs).
• Applied CoBiSe to the DtxR protein from Corynebacterium glutamicum to engineer the IronSenseR biosensor.

Main Results:

• CoBiSe identified a flexible loop (residues 138-150) in DtxR for reporter insertion, creating the IronSenseR biosensor.
• IronSenseR exhibited high specificity for Fe2+ with low dissociation constants (1.78 ± 0.03 μM for FeSO4, 2.90 ± 0.12 μM for FeCl2) and no cross-reactivity with Fe3+ or other divalent cations.
• In vivo studies in E. coli, P. putida, and C. glutamicum demonstrated IronSenseR's ability to track intracellular iron pool fluctuations.

Conclusions:

• CoBiSe significantly streamlines biosensor development by reducing search space and eliminating manual screening.
• The successful creation of IronSenseR validates CoBiSe as a powerful tool for precise engineering of next-generation biosensors for various metabolites.