Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2021
    In:  Proceedings of the National Academy of Sciences Vol. 118, No. 6 ( 2021-02-09)
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 118, No. 6 ( 2021-02-09)
    Abstract: Voltage sensing with genetically expressed optical probes is highly desirable for large-scale recordings of neuronal activity and detection of localized voltage signals in single neurons. Most genetically encodable voltage indicators (GEVI) have drawbacks including slow response, low fluorescence, or excessive bleaching. Here we present a dark quencher GEVI approach (dqGEVI) using a Förster resonance energy transfer pair between a fluorophore glycosylphosphatidylinositol–enhanced green fluorescent protein (GPI-eGFP) on the outer surface of the neuronal membrane and an azo-benzene dye quencher (D3) that rapidly moves in the membrane driven by voltage. In contrast to previous probes, the sensor has a single photon bleaching time constant of ∼40 min, has a high temporal resolution and fidelity for detecting action potential firing at 100 Hz, resolves membrane de- and hyperpolarizations of a few millivolts, and has negligible effects on passive membrane properties or synaptic events. The dqGEVI approach should be a valuable tool for optical recordings of subcellular or population membrane potential changes in nerve cells.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2021
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages