High-Throughput Evolution of Near-Infrared Oxytocin Nanosensors

Abstract

Neuropeptide oxytocin is known for its crucial regulatory role in various social behaviors, yet our understanding of its function in the brain remains incomplete. There is a demonstrable need for an imaging probe with the requisite specificity and resolution to image endogenous oxytocin signaling. Here, we leverage an evolution-based molecular recognition platform called Systematic Evolution of Ligands by Exponential Enrichment on Carbon Nanotubes (SELEC).1 With an initial library of over 1010 DNA sequences, we conducted six iterative rounds of competitive DNA-SWNCT binding in the presence and absence of oxytocin, respectively termed experimental and control SELEC, followed by adsorbed DNA isolation and enzymatic amplification to prepare the aptamer library for the subsequent round. Deep sequencing analysis and oxytocin sensitivity screening of the most enriched constructs per round revealed that oxytocin incubation enhanced the appearance of highly responsive DNA-SWCNT; only top nanosensors from SELEC experimental rounds 5 and 6 demonstrated a normalized ΔF/F0 greater than 60% in response to 100 µM oxytocin. Furthermore, the most oxytocin-sensitive aptamer was identified as E6#4, the 4th most-enriched sequence from the 6th experimental round. We briefly discuss how machine learning approaches can mine sequencing data from our SELEC experimental rounds to identify top-performing oxytocin nanosensors.Lastly, we characterize the top nanosensor candidates for sensitivity, selectivity, and reversibility, prior to demonstrating their use to image endogenous oxytocin release in acute brain slices. Our results indicate SELEC can serve as a general approach to evolving molecular recognition and developing imaging probes for complex targets such as oxytocin.1. Jeong, S.; Yang, D.; Beyene, A. G.; Travis, J.; Bonis-O’donnell, D.; Gest, A. M. M.; Navarro, N.; Sun, X.; Landry, M. P. High-Throughput Evolution of near-Infrared Serotonin Nanosensors; 2019; Vol. 5, pp 3771–3789. Figure 1