(627e) Membrane Protein Engineering for Selective Uptake of MRI Contrast Agents | AIChE

(627e) Membrane Protein Engineering for Selective Uptake of MRI Contrast Agents

Authors 

Woldring, D. - Presenter, HHMI/Brandeis University
Gilad, A. A., Johns Hopkins University
VanAntwerp, J., Michigan State University
Mardikoraem, M., Michigan State University
Pratx, G., Stanford University
Hagenbuch, B., University of Kansas Medical Center
Mir, F., Michigan State University
Latourette, M., Michigan State University
In this project we use ancestral sequence reconstruction and computational modeling to evolve novel transport function in a human solute carrier (SLC) protein for enhanced uptake of an inert MRI contrast agent. Our newly engineered, non-immunogenic proteins provide exciting opportunities for immune and stem cell therapy – enabling cells to be precisely tracked through space and time with minimal background signal. These membrane transport proteins are moderately conserved throughout mammals (60-80% sequence identity), yet demonstrate diverse and promiscuous substrate activity among closely related species. Substrate preferences are known to be critical for regulating the uptake of hormones, toxins, and drugs throughout the liver, brain, and heart. Unfortunately, the community lacks a mechanistic understanding of this promiscuous transport function. In this study, we explore the individual positions and domains that drive transport activity and specificity by computationally predicting and experimentally testing key mutations. To accomplish this, we functionally characterize transport activity of numerous mammalian SLCs against a panel of imaging agents and, in parallel, compute the phylogenetic relationships between each of these SLCs. Using a Bayesian approach, we then infer the protein sequences for each common ancestor. The experimental substrate transport data are then paired with the phylogenetic analysis resulting in a mutational road map showing a tractable number of mutations necessary for one species to adopt the functional attributes of a distantly related species. Our results showcase a powerful high throughput approach for evolving new function in notoriously challenging membrane proteins.