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Bricco, A. R.

Publications and source records attributed to Bricco, A. R..

2 recordsLinked to original sources

Development of a Synthetic Biosensor for Chemical Exchange MRI Utilizing In Silico Optimized Peptides

1Chemical Exchange Saturation Transfer (CEST) magnetic resonance imaging (MRI) has been identified as a novel alternative to classical diagnostic imaging. Over the last several decades, many studies have been conducted to determine possible CEST agents, such as endogenously expressed compounds or proteins, that can be utilized to produce contrast with minimally invasive procedures and reduced or non-existent levels of toxicity. In recent years there has been an increased interest in the generation of genetically engineered CEST contrast agents, typically based on existing proteins with CEST contrast or modified to produce CEST contrast. We have developed an in-silico method for the evolution of peptide sequences to optimize CEST contrast and showed that these peptides could be combined to create de novo biosensors for CEST MRI. A single protein, superCESTide 2.0, was designed to be 198 amino acids. SuperCESTide 2.0 was expressed in E. coli and purified with size-exclusion chromatography. The magnetic transfer ratio asymmetry (MTRasym) generated by superCESTide 2.0 was comparable to levels seen in previous CEST reporters, such as protamine sulfate (salmon protamine, SP), Poly-L-Lysine (PLL), and human protamine (hPRM1). This data shows that novel peptides with sequences optimized in silico for CEST contrast that utilizes a more comprehensive range of amino acids can still produce contrast when assembled into protein units expressed in complex living environments.

synthetic biology↗

Protein Optimization Evolving Tool (POET) based on Genetic Programming

Proteins are used by scientists to serve a variety of purposes in clinical practice and laboratory research. To optimize proteins for greater function, a variety of techniques have been developed. For the development of reporter genes used in Magnetic Resonance Imaging (MRI) based on Chemical Exchange Saturation Transfer (CEST), these techniques have encountered a variety of challenges. Here we develop a mechanism of protein optimization using a computational approach known as "genetic programming". We developed an algorithm called Protein Optimization Evolving Tool (POET). Starting from a small library of literature values, use of this tool allowed us to develop proteins which produce four times more MRI contrast than what was previously state-of-the-art. Next, we used POET to evolve peptides that produced CEST-MRI contrast at large chemical shifts where no other known peptides have previously demonstrated contrast. This demonstrated the ability of POET to evolve new functions in proteins. Interestingly, many of the peptides produced using POET were dramatically different with respect to their sequence and chemical environment than existing CEST producing peptides, and challenge prior understandings of how those peptides function. This suggests that unlike existing algorithms for protein engineering that rely on divergent evolution, POET relies on convergent evolution.

synthetic biology↗