A variety of genetically encoded reporters use changes in fluorescence (or Förster) resonance energy transfer (FRET) to report on biochemical processes in living cells. The standard genetically encoded FRET pair consists of cyan and yellow fluorescent proteins (CFP and YFP), but many CFP-YFP reporters suffer from low FRET dynamic range, phototoxicity from the CFP excitation light, and complex photokinetic events such as reversible photobleaching and photoconversion. Here, we engineered two fluorescent proteins, Clover and mRuby2, which are the brightest green and red fluorescent proteins to date, and have the highest Förster radius of any ratiometric FRET pair yet described. Replacement of CFP and YFP in reporters of kinase activity, small GTPase activity, and transmembrane voltage significantly improves photostability, FRET dynamic range, and emission ratio changes. These improvements enhance detection of transient biochemical events such as neuronal action potential firing and RhoA activation in growth cones.

Genetically encoded voltage indicators (GEVIs) are a promising technology for fluorescence readout of millisecond-scale neuronal dynamics. Previous GEVIs had insufficient signaling speed and dynamic range to resolve action potentials in live animals. We coupled fast voltage-sensing domains from a rhodopsin protein to bright fluorophores through resonance energy transfer. The resulting GEVIs are sufficiently bright and fast to report neuronal action potentials and membrane voltage dynamics in awake mice and flies, resolving fast spike trains with 0.2-millisecond timing precision at spike detection error rates orders of magnitude better than previous GEVIs. In vivo imaging revealed sensory-evoked responses, including somatic spiking, dendritic dynamics, and intracellular voltage propagation. These results empower in vivo optical studies of neuronal electrophysiology and coding and motivate further advancements in high-speed microscopy.

Accurate optical reporting of electrical activity in genetically defined neuronal populations is a long-standing goal in neuroscience. Here we describe Accelerated Sensor of Action Potentials 1 (ASAP1), a novel voltage sensor design in which a circularly permuted green fluorescent protein is inserted within an extracellular loop of a voltage-sensing domain, rendering fluorescence responsive to membrane potential. ASAP1 demonstrates on- and off- kinetics of 2.1 and 2.0 ms, reliably detects single action potentials and subthreshold potential changes, and tracks trains of action potential waveforms up to 200 Hz in single trials. With a favorable combination of brightness, dynamic range, and speed, ASAP1 enables continuous monitoring of membrane potential in neurons at KHz frame rates using standard epifluorescence microscopy.

No abstract

Genetically encoded fluorescence voltage sensors offer the possibility of directly visualizing neural spiking dynamics in cells targeted by their genetic class or connectivity. Sensors of this class have generally suffered performance-limiting tradeoffs between modest brightness, sluggish kinetics, and limited signaling dynamic range in response to action potentials. Here we describe sensors that use fluorescence resonance energy transfer (FRET) to combine the rapid kinetics and substantial voltage-dependence of rhodopsin family voltage-sensing domains with the brightness of genetically engineered protein fluorophores. These FRET-opsin sensors significantly improve upon the spike detection fidelity offered by the genetically encoded voltage sensor, Arclight, while offering faster kinetics and higher brightness. Using FRET-opsin sensors we imaged neural spiking and sub-threshold membrane voltage dynamics in cultured neurons and in pyramidal cells within neocortical tissue slices. In live mice, rates and optical waveforms of cerebellar Purkinje neurons’ dendritic voltage transients matched expectations for these cells’ dendritic spikes.

Calcium imaging records large-scale neuronal activity with cellular resolution in vivo. Automated, fast, and reliable active neuron segmentation is a critical step in the analysis workflow of utilizing neuronal signals in real-time behavioral studies for discovery of neuronal coding properties. Here, to exploit the full spatiotemporal information in two-photon calcium imaging movies, we propose a 3D convolutional neural network to identify and segment active neurons. By utilizing a variety of two-photon microscopy datasets, we show that our method outperforms state-of-the-art techniques and is on a par with manual segmentation. Furthermore, we demonstrate that the network trained on data recorded at a specific cortical layer can be used to accurately segment active neurons from another layer with different neuron density. Finally, our work documents significant tabulation flaws in one of the most cited and active online scientific challenges in neuron segmentation. As our computationally fast method is an invaluable tool for a large spectrum of real-time optogenetic experiments, we have made our open-source software and carefully annotated dataset freely available online.

A longstanding goal in neuroscience has been to develop techniques for imaging the voltage dynamics of genetically defined subsets of neurons. Optical sensors of transmembrane voltage would enhance studies of neural activity in contexts ranging from individual neurons cultured in vitro to neuronal populations in awake-behaving animals. Recent progress has identified Archaerhodopsin (Arch) based sensors as a promising, genetically encoded class of fluorescent voltage indicators that can report single action potentials. Wild-type Arch exhibits sub-millisecond fluorescence responses to trans-membrane voltage, but its light-activated proton pump also responds to the imaging illumination. An Arch mutant (Arch-D95N) exhibits no photocurrent, but has a slower, ~40 ms response to voltage transients. Here we present Arch-derived voltage sensors with trafficking signals that enhance their localization to the neural membrane. We also describe Arch mutant sensors (Arch-EEN and -EEQ) that exhibit faster kinetics and greater fluorescence dynamic range than Arch-D95N, and no photocurrent at the illumination intensities normally used for imaging. We benchmarked these voltage sensors regarding their spike detection fidelity by using a signal detection theoretic framework that takes into account the experimentally measured photon shot noise and optical waveforms for single action potentials. This analysis revealed that by combining the sequence mutations and enhanced trafficking sequences, the new sensors improved the fidelity of spike detection by nearly three-fold in comparison to Arch-D95N.

Electrophysiological field potential dynamics are of fundamental interest in basic and clinical neuroscience, but how specific cell types shape these dynamics in the live brain is poorly understood. To empower mechanistic studies, we created an optical technique, TEMPO, that records the aggregate trans-membrane voltage dynamics of genetically specified neurons in freely behaving mice. TEMPO has >10-fold greater sensitivity than prior fiber-optic techniques and attains the noise minimum set by quantum mechanical photon shot noise. After validating TEMPO’s capacity to track established oscillations in the delta, theta and gamma frequency-bands, we compared the D1- and D2-dopamine-receptor-expressing striatal medium spiny neurons (MSNs), which are interspersed and electrically indistinguishable. Unexpectedly, MSN population dynamics exhibited two distinct coherent states that were commonly indiscernible in electrical recordings and involved synchronized hyperpolarizations across both MSN subtypes. Overall, TEMPO allows the deconstruction of normal and pathologic neurophysiological states into trans-membrane voltage activity patterns of specific cell types.