Attaining effective genetically encoded optical voltage-indicators has been a longstanding goal in neuroscience research and is a key near-term aim of the BRAIN Initiative. Unlike small molecule sensors or hybrids of fluorescent proteins with organic molecules, optical voltage-indicators that can be fully encoded genetically are readily combined with genetic tools and viral delivery methods that enable long-term expression and chronic imaging studies without addition of exogenous agents. Genetically encoded Ca2+-sensors offer similar targeting advantages, but Ca2+-imaging fails to reveal individual spikes in many neuron types, poorly captures sub- threshold membrane dynamics, and has insufficient temporal resolution to capture spike timing to better than ~50-100 ms. Voltage-indicators directly sense the membrane potential and promise faithful reporting of spike waveforms, spike bursts and sub-threshold dynamics, in cells targeted by their genetic class or connectivity. An ideal voltage-indicator would produce large fluorescence responses, to facilitate spike detection, and have millisecond-scale kinetics, to study synchrony and spike-timing aspects of neural coding. However, prior protein voltage-indicators have generally suffered performance-limiting tradeoffs between modest brightness, sluggish kinetics, and limited signaling dynamic range in response to action potentials. To date, no protein voltage-indicator combines the attributes needed for accurate reporting of voltage activity in behaving animals. However, if such a sensor emerged, this would likely have even greater impact on brain science than the surge in research enabled by recent advanced versions of the GCaMP Ca2+-indicator. This proposal seeks to create broad voltage-imaging capabilities and involves two Co-PDs who are highly experienced in fluorescence imaging of neural activity. Working collaboratively, we recently created two new classes of voltage-indicators, of distinct colors and voltage-sensing mechanisms, each of which has substantially superior signaling fidelity than earlier protein voltage-indicators while offering faster kinetics and higher brightness. Using thes two sensor types, we have imaged fast spike trains in cultured neurons and brain slices. Calculations using signal detection theory show our indicators are now on the brink of transitioning into a mainstay approach to monitor large numbers of individual neurons in behaving animals. To enact this, we will use novel massively parallel methods to screen variants of our protein indicators at 100-1000 greater throughput than screening methods used previously in the field. We will validate and iteratively optimize the resulting indicators in cultred neurons, mammalian brain slices, and behaving flies, nematodes and mice, by using signal detection theory to benchmark indicator performance. To accompany these voltage-indicators, we will also create imaging instrumentation custom-designed for high-speed (~1 kHz) voltage-imaging in awake head-restrained and freely behaving mice. If our work succeeds, it will be a game-changer for brain research, propelling studies of how cells and circuits function normally and go awry in disease.

Public Health Relevance

Attaining a rich understanding of how neural circuits convey and process information will require new technologies for high-fidelity recordings of electrical activity, including high-frequency and sub-threshold events, in genetically defined ensembles of neurons. Having recently developed two new classes of genetically encoded optical voltage-indicators with fast kinetics and large dynamic range, here we will use novel massively high-throughput protein screening methods to further improve their signaling capabilities, which we will validate and iteratively optimize in behaving nematodes, fruit flies and mice. To accompany these voltage-indicators, we will also create imaging instrumentation custom-designed for high-speed (~1 kHz) voltage-imaging in awake head-restrained and freely behaving mice.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01NS090600-02
Application #
8934235
Study Section
Special Emphasis Panel (ZNS1-SRB-G (77))
Program Officer
Talley, Edmund M
Project Start
2014-09-30
Project End
2017-07-31
Budget Start
2015-08-01
Budget End
2016-07-31
Support Year
2
Fiscal Year
2015
Total Cost
$967,044
Indirect Cost
$259,730
Name
Stanford University
Department
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Chamberland, Simon; Yang, Helen H; Pan, Michael M et al. (2017) Fast two-photon imaging of subcellular voltage dynamics in neuronal tissue with genetically encoded indicators. Elife 6:
Ng, Ho-Leung; Lin, Michael Z (2016) Structure-guided wavelength tuning in far-red fluorescent proteins. Curr Opin Struct Biol 39:124-133
Lin, Michael Z; Schnitzer, Mark J (2016) Genetically encoded indicators of neuronal activity. Nat Neurosci 19:1142-53
Marshall, Jesse D; Li, Jin Zhong; Zhang, Yanping et al. (2016) Cell-Type-Specific Optical Recording of Membrane Voltage Dynamics in Freely Moving Mice. Cell 167:1650-1662.e15
Chu, Jun; Oh, Younghee; Sens, Alex et al. (2016) A bright cyan-excitable orange fluorescent protein facilitates dual-emission microscopy and enhances bioluminescence imaging in vivo. Nat Biotechnol 34:760-7
Bajar, Bryce T; Wang, Emily S; Lam, Amy J et al. (2016) Improving brightness and photostability of green and red fluorescent proteins for live cell imaging and FRET reporting. Sci Rep 6:20889
Bajar, Bryce T; Wang, Emily S; Zhang, Shu et al. (2016) A Guide to Fluorescent Protein FRET Pairs. Sensors (Basel) 16:
Yang, Helen H; St-Pierre, François; Sun, Xulu et al. (2016) Subcellular Imaging of Voltage and Calcium Signals Reveals Neural Processing In Vivo. Cell 166:245-57
Laviv, Tal; Kim, Benjamin B; Chu, Jun et al. (2016) Simultaneous dual-color fluorescence lifetime imaging with novel red-shifted fluorescent proteins. Nat Methods 13:989-992
Gong, Yiyang; Huang, Cheng; Li, Jin Zhong et al. (2015) High-speed recording of neural spikes in awake mice and flies with a fluorescent voltage sensor. Science 350:1361-6

Showing the most recent 10 out of 11 publications