Abstract

Neurons communicate through chemical neurotransmitter signals that either terminate at the postsynaptic process (“wired transmission”) or diffuse beyond the synaptic cleft to modulate the activity of larger neuronal networks (“volume transmission”). Molecules such as dopamine belong to the latter class of neurotransmitters, and have been the pharmacological targets of antidepressants and antipsychotics for decades. Owing to the central role of dopamine over a range of behaviors and psychiatric disorders, real-time imaging of the signal’s spatial propagation would constitute a valuable advance in neurochemical imaging. To this end, we present a nanoscale near-infrared fluorescent nanosensor for dopamine and demonstrate its efficacy for imaging dopamine volume transmission in the extracellular space of the brain striatum and prefrontal cortex (Beyene et al. ACS Chem. Neuro. 2017). The sensor is developed from polymers pinned to the surface of single wall carbon nanotubes (SWNT) in which the surface-adsorbed polymer is the recognition moiety and the carbon nanotube the fluorescence transduction element. Excitonic transitions in functionalized SWNT yield up to ΔF/F = 4500% near-infrared fluorescence emission in the presence of dopamine (Beyene et al. Nano Letters 2018). We next demonstrate imaging of evoked dopamine release in acute striatal slices, and show altered dopamine reuptake kinetics when brain tissue is exposed to dopamine receptor agonist and antagonist drugs (Beyene et al. Science Advances 2019). Lastly, we discuss how to evolve synthetic molecular recognition for other neuromodulators of interest, such as serotonin (Jeong et al. Science Advances 2019). We characterize our findings in the context of their utility for high spatial and temporal neuromodulator imaging in the brain, describe nanosensor exciton behavior from a molecular dynamics (MD) perspective, and validate nanosensor for use to elucidate dopaminergic signaling variability with disease or pharmacological perturbations at a synaptic scale.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.