A GENETIC PROGRAMMING TECHNIQUE FOR PROTEIN OPTIMIZATION DEMONSTRATED IN MRI REPORTER GENES

Reporter genes are important tools for researchers studying molecular and cellular biology as they give location and measurable values to the expression level of a given gene, by linking the activation of a gene to a detectable phenomenon. Reporter genes for MRI, allow these functions to be done noninvasively at arbitrary tissue depth. Chemical Exchange Saturation Transfer (CEST) based reporter genes have shown promise in acting as reliable reporters in MRI, but the relatively low sensitivity of the method has limited its utility in research situations. Initial attempts to optimize existing CEST reporter genes proved difficult due to a series of technical challenges. This led to the development of a new machine learning tool for protein engineering, the Protein Optimization Engineering Tool (POET). Using POET and experimentation to develop improved CEST reporter genes resulted in new peptides that produce nearly a fourfold increase in contrast over prior art. Additionally POET is used to generate a reporter gene that produces significant contrast at a farther downfield frequency than prior CEST reporter genes.