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In vivo glucose imaging in multiple model organisms with an engineered single-wavelength sensor.
- Source :
-
Cell reports [Cell Rep] 2021 Jun 22; Vol. 35 (12), pp. 109284. - Publication Year :
- 2021
-
Abstract
- Glucose is arguably the most important molecule in metabolism, and its dysregulation underlies diabetes. We describe a family of single-wavelength genetically encoded glucose sensors with a high signal-to-noise ratio, fast kinetics, and affinities varying over four orders of magnitude (1 μM to 10 mM). The sensors allow mechanistic characterization of glucose transporters expressed in cultured cells with high spatial and temporal resolution. Imaging of neuron/glia co-cultures revealed ∼3-fold faster glucose changes in astrocytes. In larval Drosophila central nervous system explants, intracellular neuronal glucose fluxes suggested a rostro-caudal transport pathway in the ventral nerve cord neuropil. In zebrafish, expected glucose-related physiological sequelae of insulin and epinephrine treatments were directly visualized. Additionally, spontaneous muscle twitches induced glucose uptake in muscle, and sensory and pharmacological perturbations produced large changes in the brain. These sensors will enable rapid, high-resolution imaging of glucose influx, efflux, and metabolism in behaving animals.<br />Competing Interests: Declaration of interests L.L.L., J.S.M., and R.T.L. are holders of US Patent US9939437B2, which covers iGlucoSnFR. The remaining authors declare no competing interests.<br /> (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Animals
Biological Transport
Central Nervous System metabolism
Drosophila metabolism
HEK293 Cells
Humans
Imaging, Three-Dimensional
Larva metabolism
Muscles metabolism
Neuroglia metabolism
Proteins metabolism
Rats, Sprague-Dawley
Zebrafish metabolism
Rats
Genetic Engineering
Glucose metabolism
Models, Biological
Subjects
Details
- Language :
- English
- ISSN :
- 2211-1247
- Volume :
- 35
- Issue :
- 12
- Database :
- MEDLINE
- Journal :
- Cell reports
- Publication Type :
- Academic Journal
- Accession number :
- 34161775
- Full Text :
- https://doi.org/10.1016/j.celrep.2021.109284