Comparative Evaluation of Genetically Encoded Voltage Indicators | Zendy

Yuki Bando | Zendy; Masayuki Sakamoto | Zendy; Samuel Kim | Zendy; Inbal Ayzenshtat | Zendy; Rafael Yuste | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Comparative Evaluation of Genetically Encoded Voltage Indicators

Author(s) -

Yuki Bando,

Masayuki Sakamoto,

Samuel Kim,

Inbal Ayzenshtat,

Rafael Yuste

Publication year - 2019

Publication title -

cell reports

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 6.264

H-Index - 154

eISSN - 2639-1856

pISSN - 2211-1247

DOI - 10.1016/j.celrep.2018.12.088

Subject(s) - in vivo , signal (programming language) , two photon excitation microscopy , photon , voltage , fluorescence , computer science , biological system , physics , biophysics , biology , optics , genetics , quantum mechanics , programming language

Imaging voltage using fluorescent-based sensors could be an ideal technique to probe neural circuits with high spatiotemporal resolution. However, due to insufficient signal-to-noise ratio (SNR), imaging membrane potential in mammalian preparations is still challenging. In recent years, many genetically encoded voltage indicators (GEVIs) have been developed. To compare them and guide decisions on which GEVI to use, we have characterized side by side the performance of eight GEVIs that represent different families of molecular constructs. We tested GEVIs in vitro with 1-photon imaging and in vivo with 1-photon wide-field imaging and 2-photon imaging. We find that QuasAr2 exhibited the best performance in vitro, whereas only ArcLight-MT could be used to reliably detect electrical activity in vivo with 2-photon excitation. No single GEVI was ideal for every experiment. These results provide a guide for choosing optimal GEVIs for specific applications.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research