High relaxivity biomolecule based contrast agents engineered for molecular functional magnetic resonance imaging
[摘要] Magnetic resonance imaging (MRI) is a powerful neuroimaging tool that allows non-invasive visualization of the brain with high spatial and temporal resolution. Research on MRI contrast agents and their application to problems in neuroscience is burgeoning, and there is particular interest in developing MRI agents that are sensitive to time varying components of neurophysiology. Relatively recent advances in biomolecular probes has demonstrated the potential and versatility of bioengineered MRI sensors for molecular imaging. However, a major limitation of these probes is the high concentration needed for imaging, which can lead to issues such as analyte buffering and toxicity, and restrict the applicability of the sensors. In this work, we explore two approaches for developing high relaxivity protein-based contrast agents to address the issues of low detectability. First, we coupled monoamine sensing with the disaggregation of superparamagnetic iron oxide nanoparticles (SPIOs). Ligand detection was imparted by integration of a monoamine sensing protein-based contrast agent derived from P450- BM3h (BM3). We demonstrated that this mechanism can produce robust signal changes of approximately 2-fold, while reducing the concentration of BM3 needed by 100-fold compared to the amount needed when only the protein is used for imaging. The second method demonstrated the feasibility of using semi-rational protein design to engineer a high relaxivity metalloprotein by tuning phenylalanine hydroxylase to bind gadolinium at high affinity. Mutations were found that increased the protein affinity by two orders of magnitude and enhanced relaxivity. The results of this thesis advance approaches for creating high relaxivity contrast agents which can be applied to the development of probes for other analytes, ultimately advancing and broadening the applicability of bioengineered probes in molecular functional neuroimaging.
[发布日期] [发布机构] Massachusetts Institute of Technology
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