(Invited) Evolution of Synthetic Molecular Recognition on Single Walled Carbon Nanotubes

Abstract

Molecular recognition is fundamental to the design of therapeutics, diagnostics, and sensors. Many of these sensor technologies rely on natural or synthetic molecular recognition elements such as antibodies and aptamers, which have evolved to be highly selective for their molecular targets. However, there are numerous applications for which existing approaches to molecular recognition have been unable to generate optical probes, particularly for neuromodulators and neuropeptides. Herein, we describe a polymer evolution-based platform, in which 10^12 unique polynucleotide polymers are adsorbed to single-walled carbon nanotubes (SWNT). The SWNT-pinned polynucleotide polymers can be screened for their ability to bind a target analyte and provide a selective near-infrared fluorescence signal. Iterative selection of analyte-binding polymers that form a SWNT-surface-adsorbed phase for target recognition are identified through ionic desorption of sub-optimal polymers, and exponential amplification of synthetic polymers that recognize the target analyte. Next-generation sequencing identifies SWNT-polynucleotide conjugates with sequences selective and sensitive for the desired analyte. We demonstrate the utility of this platform for the evolution of SWNT-polymer nanosensors for neuromodulators [1] and neuropeptides, and discuss its potential for identification of chirality-specific SWNT separation. Our results suggest our platform is fundamentally generic in enabling the evolution of nanosensors from synthetic polymer-nanoparticle conjugates for any desired analyte. 1. Jeong, S., Yang, D., Beyene, A.G., O’Donnell, J.T.D., Gest, A. M., Navarro, N., Sun, X., Landry, M.P. High Throughput Evolution of Near Infrared Serotonin Nanosensors. Science Advances (2019). DOI: 10.1101/673152