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© 2016, Dana et al. This work is licensed under the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/3.0/ ) (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Genetically encoded calcium indicators (GECIs) allow measurement of activity in large populations of neurons and in small neuronal compartments, over times of milliseconds to months. Although GFP-based GECIs are widely used for in vivo neurophysiology, GECIs with red-shifted excitation and emission spectra have advantages for in vivo imaging because of reduced scattering and absorption in tissue, and a consequent reduction in phototoxicity. However, current red GECIs are inferior to the state-of-the-art GFP-based GCaMP6 indicators for detecting and quantifying neural activity. Here we present improved red GECIs based on mRuby (jRCaMP1a, b) and mApple (jRGECO1a), with sensitivity comparable to GCaMP6. We characterized the performance of the new red GECIs in cultured neurons and in mouse, Drosophila, zebrafish and C. elegans in vivo. Red GECIs facilitate deep-tissue imaging, dual-color imaging together with GFP-based reporters, and the use of optogenetics in combination with calcium imaging.

DOI: http://dx.doi.org/10.7554/eLife.12727.001

Details

Title
Sensitive red protein calcium indicators for imaging neural activity
Author
Hod, Dana; Mohar Boaz; Sun, Yi; Narayan Sujatha; Gordus, Andrew; Hasseman, Jeremy P; Getahun, Tsegaye; Holt, Graham T; Hu, Amy; Walpita Deepika; Patel, Ronak; Macklin, John J; Bargmann, Cornelia I; Ahrens, Misha B; Schreiter, Eric R; Jayaraman Vivek; Looger, Loren L; Svoboda Karel; Kim, Douglas S
University/institution
U.S. National Institutes of Health/National Library of Medicine
Publication year
2016
Publication date
2016
Publisher
eLife Sciences Publications Ltd.
e-ISSN
2050084X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1953747695
Copyright
© 2016, Dana et al. This work is licensed under the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/3.0/ ) (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.