Engineering a split-GFP system for direct pathogen detection

Abstract

The process often requires mutations of residues surrounding the chromophore and could lead to a loss of function and destabilization. Therefore, four different studies were initiated and are described. The first set of studies was to test the effects of restoring an internal hydrogen bonding network, disulfide engineering and introducing insertions and deletions in GFP. The second study was to test the tolerance of the protein’s chromophore’s micro-environment to point mutations. The saturation mutagenesis studies thus performed, revealed that the microenvironment is surprisingly robust. The third study, was to develop several biosensor prototypes. Two of these produced promising results and are described in detail. A good LOO-GFP biosensor should ideally have no fluorescence in the absence of the target but the prototypes developed thus far show high levels of background fluorescence due to oligomerization of unbound LOO-GFP. One way to mitigate this is to use a genetic fusion based immobilization approach to tether LOO-GFPs to a self-assembled protein matrix. This was the subject of the fourth study. Preliminary results showed that the genetic fusion did not compromise fluorescent functionality in the LOO-GFP. Thus in summary, the results of the four studies outlined above, produced results showing good promise for the engineering of LOO-GFPs to directly interact with protein targets of interest.

The green fluorescent protein (GFP) has seen widespread use in biological research. It can be split into two or three fragments, which self-assemble and reconstitute structure and function. A particular type of split GFP is called Leave-one-out-GFP (LOO-GFP). A LOO-GFP is designed to reconstitute fluorescent function upon exogenous addition of its left-out piece. In this work, efforts toward modifying LOO-GFPs to reconstitute function upon binding specifically to a protein of interest are described. This could enable the use of LOO-GFPs as versatile biosensors for direct pathogen detection. Computational protein design algorithms were used to calculate the set of mutations required to enable the LOO-GFP-target interaction.