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Fast GCaMPs for improved tracking of neuronal activity

Author

Listed:
  • Xiaonan R. Sun

    (Princeton University
    Neuroscience Institute, Princeton University)

  • Aleksandra Badura

    (Princeton University
    Neuroscience Institute, Princeton University)

  • Diego A. Pacheco

    (Princeton University
    Neuroscience Institute, Princeton University)

  • Laura A. Lynch

    (Princeton University
    Neuroscience Institute, Princeton University)

  • Eve R. Schneider

    (Princeton University
    Neuroscience Institute, Princeton University)

  • Matthew P. Taylor

    (Princeton University
    Neuroscience Institute, Princeton University)

  • Ian B. Hogue

    (Princeton University
    Neuroscience Institute, Princeton University)

  • Lynn W. Enquist

    (Princeton University
    Neuroscience Institute, Princeton University)

  • Mala Murthy

    (Princeton University
    Neuroscience Institute, Princeton University)

  • Samuel S. -H. Wang

    (Princeton University
    Neuroscience Institute, Princeton University)

Abstract

The use of genetically encodable calcium indicator proteins to monitor neuronal activity is hampered by slow response times and a narrow Ca2+-sensitive range. Here we identify three performance-limiting features of GCaMP3, a popular genetically encodable calcium indicator protein. First, we find that affinity is regulated by the calmodulin domain’s Ca2+-chelating residues. Second, we find that off-responses to Ca2+ are rate-limited by dissociation of the RS20 domain from calmodulin’s hydrophobic pocket. Third, we find that on-responses are limited by fast binding to the N-lobe at high Ca2+ and by slow binding to the C-lobe at lower Ca2+. We develop Fast-GCaMPs, which have up to 20-fold accelerated off-responses and show that they have a 200-fold range of KD, allowing coexpression of multiple variants to span an expanded range of Ca2+ concentrations. Finally, we show that Fast-GCaMPs track natural song in Drosophila auditory neurons and generate rapid responses in mammalian neurons, supporting the utility of our approach.

Suggested Citation

  • Xiaonan R. Sun & Aleksandra Badura & Diego A. Pacheco & Laura A. Lynch & Eve R. Schneider & Matthew P. Taylor & Ian B. Hogue & Lynn W. Enquist & Mala Murthy & Samuel S. -H. Wang, 2013. "Fast GCaMPs for improved tracking of neuronal activity," Nature Communications, Nature, vol. 4(1), pages 1-10, October.
    • Handle: RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms3170
    DOI: 10.1038/ncomms3170
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    Cited by:

    1. Sine Yaganoglu & Konstantinos Kalyviotis & Christina Vagena-Pantoula & Dörthe Jülich & Benjamin M. Gaub & Maaike Welling & Tatiana Lopes & Dariusz Lachowski & See Swee Tang & Armando Del Rio Hernandez, 2023. "Highly specific and non-invasive imaging of Piezo1-dependent activity across scales using GenEPi," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Omer Mano & Damon A Clark, 2017. "Graphics Processing Unit-Accelerated Code for Computing Second-Order Wiener Kernels and Spike-Triggered Covariance," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-11, January.

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