Neurotransmitter-Responsive Nanosensors for T2-Weighted Magnetic Resonance Imaging
Author(s)
Hsieh, Vivian
Okada, Satoshi
Wei, He
Garcia Alvarez, Isabel
Barandov, Ali
Alvarado, Santiago Recuenco
Ohlendorf, Robert
Fan, Jingxuan
Ortega, Athena
Jasanoff, Alan Pradip
Date Issued
September 2019
Journal
Journal of the American Chemical Society
Publisher
American Chemical Society (ACS)
Citation
Hsieh, Vivian et al. "Neurotransmitter-Responsive Nanosensors for T2-Weighted Magnetic Resonance Imaging." Journal of the American Chemical Society 141, 40 (September 2019): 15751–15754 © 2019 American Chemical Society
Version
Author's final manuscript
Abstract
Neurotransmitter-sensitive contrast agents for magnetic resonance imaging (MRI) have recently been used for mapping signaling dynamics in live animal brains, but paramagnetic sensors for T1-weighted MRI are usually effective only at micromolar concentrations that themselves perturb neurochemistry. Here we present an alternative molecular architecture for detecting neurotransmitters, using superparamagnetic iron oxide nanoparticles conjugated to tethered neurotransmitter analogs and engineered neurotransmitter binding proteins. Interactions between the nanoparticle conjugates result in clustering that is reversibly disrupted in the presence of neurotransmitter analytes, thus altering T2-weighted MRI signals. We demonstrate this principle using tethered dopamine and serotonin analogs, together with proteins selected for their ability to competitively bind either the analogs or the neurotransmitters themselves. Corresponding sensors for dopamine and serotonin exhibit target-selective relaxivity changes of up to 20%, while also operating below endogenous neurotransmitter concentrations. Semisynthetic magnetic particle sensors thus represent a promising path for minimally perturbative studies of neurochemical analytes.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Terms of Use
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DOI of Published Version
https://doi.org/10.1021/jacs.9b08744
