Selected publications

Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator

Published in Neuron, 2023

The ability to optically image cellular transmembrane voltage at millisecond-timescale resolution can offer unprecedented insight into the function of living brains in behaving animals. The chemigenetic voltage indicator Voltron is bright and photostable, making it a favorable choice for long in vivo imaging of neuronal populations at cellular resolution. Improving the voltage sensitivity of Voltron would allow better detection of spiking and subthreshold voltage signals. We performed site saturation mutagenesis at 40 positions in Voltron and screened for increased ΔF/F0 in response to action potentials (APs) in neurons. Using a fully automated patch-clamp system, we discovered a Voltron variant (Voltron.A122D) that increased the sensitivity to a single AP by 65% compared to Voltron. This variant (named Voltron2) also exhibited approximately 3-fold higher sensitivity in response to sub-threshold membrane potential changes. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, with lower baseline fluorescence. Introducing the same A122D substitution to other Ace2 opsin-based voltage sensors similarly increased their sensitivity. We show that Voltron2 enables improved sensitivity voltage imaging in mice, zebrafish and fruit flies. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.

Recommended citation: Abdelfattah, A.S., Zheng, J., Singh, A., Huang, Y.-C., Reep, D., Tsegaye, G., Tsang, A., Arthur, B.J., Rehorova, M., Olson, C.V.L., Shuai, Y., Zhang, L., Fu, T.-M., Milkie, D.E., Moya, M.V., Weber, T.D., Lemire, A.L., Baker, C.A., Falco, N., Zheng, Q., Grimm, J.B., Yip, M.C., Walpita, D., Chase, M., Campagnola, L., Murphy, G.J., Wong, A.M., Forest, C.R., Mertz, J., Economo, M.N., Turner, G.C., Koyama, M., Lin, B.-J., Betzig, E., Novak, O., Lavis, L.D., Svoboda, K., Korff, W., Chen, T.-W., Schreiter, E.R., Hasseman, J.P., Kolb, I., 2023. Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator. Neuron. https://doi.org/10.1016/j.neuron.2023.03.009 [PDF]

Fast and sensitive GCaMP calcium indicators for imaging neural populations

Published in Nature, 2023

Calcium imaging with protein-based indicators1,2 is widely used to follow neural activity in intact nervous systems, but current protein sensors report neural activity at timescales much slower than electrical signalling and are limited by trade-offs between sensitivity and kinetics. Here we used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators3–8. The resulting ‘jGCaMP8’ sensors, based on the calcium-binding protein calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (half-rise times of 2 ms) and the highest sensitivity for neural activity reported for a protein-based calcium sensor. jGCaMP8 sensors will allow tracking of large populations of neurons on timescales relevant to neural computation. [[News and Views]

Recommended citation: Zhang, Yan, Márton Rózsa, Yajie Liang, Daniel Bushey, Ziqiang Wei, Jihong Zheng, Daniel Reep, et al. “Fast and Sensitive GCaMP Calcium Indicators for Imaging Neural Populations.” Nature 615, no. 7954 (March 2023): 884–91. https://doi.org/10.1038/s41586-023-05828-9. [PDF]

Improved GABA (γ-aminobutyric acid) Indicators for Synaptic Imaging

Published in Figshare, 2022

iGABASnFR2 is the current (2022) generation of GABA-Sensing Fluorescent Reporters developed at HHMI’s Janelia Research Campus. Other sensor technologies such as SF-iGluSnFR, jGCaMP8, and jRGECO are optimized for excitatory synaptic transmission and action potentials. iGABASnFr complements these technologies with the ability to detect inhibitory synaptic transmission and inhibitory post-synaptic currents. iGABASnFr2 has the best performance among GABA indicators and is completely genetically coded, which is optimal for in vivo use.

Recommended citation: Kolb, Ilya; Hasseman, Jeremy; Tsegaye, Getahun; Tsang, Arthur; Reep, Daniel; Zheng, Jihong; et al. (2022). Optimization of genetically encoded GABA indicator. Janelia Research Campus. Dataset. https://doi.org/10.25378/janelia.19709311.v3 [PDF]

PatcherBot: a single-cell electrophysiology robot for adherent cells and brain slices

Published in Journal of Neural Engineering, 2019

Intracellular patch-clamp electrophysiology, one of the most ubiquitous, high-fidelity techniques in biophysics, remains laborious and low-throughput. While previous efforts have succeeded at automating some steps of the technique, here we demonstrate a robotic ‘PatcherBot’ system that can perform many patch-clamp recordings sequentially, fully unattended. Comprehensive automation is accomplished by outfitting the robot with machine vision, and cleaning pipettes instead of manually exchanging them. The PatcherBot can obtain data at a rate of 16 cells per hour and work with no human intervention for up to 3 h. We demonstrate the broad applicability and scalability of this system by performing hundreds of recordings in tissue culture cells and mouse brain slices with no human supervision. Using the PatcherBot, we also discovered that pipette cleaning can be improved by a factor of three. The system is potentially transformative for applications that depend on many high-quality measurements of single cells, such as drug screening, protein functional characterization, and multimodal cell type investigations. Featured article. Media: [PhysicsWorld, GaTech]

Recommended citation: Kolb, Ilya, Corey R. Landry, Mighten C. Yip, Colby F. Lewallen, William A. Stoy, John Lee, Amanda Felouzis, et al. "PatcherBot: A Single-Cell Electrophysiology Robot for Adherent Cells and Brain Slices." Journal of Neural Engineering 16, no. 4 (May 2019) [PDF]

Evidence for Long-Timescale Patterns of Synaptic Inputs in CA1 of Awake Behaving Mice

Published in Journal of Neuroscience, 2018

Repeated sequences of neural activity are a pervasive feature of neural networks in vivo and in vitro. In the hippocampus, sequential firing of many neurons over periods of 100–300 ms reoccurs during behavior and during periods of quiescence. However, it is not known whether the hippocampus produces longer sequences of activity or whether such sequences are restricted to specific network states. Furthermore, whether long repeated patterns of activity are transmitted to single cells downstream is unclear. To answer these questions, we recorded intracellularly from hippocampal CA1 of awake, behaving male mice to examine both subthreshold activity and spiking output in single neurons. In eight of nine recordings, we discovered long (900 ms) reoccurring subthreshold fluctuations or “repeats.” Repeats generally were high-amplitude, nonoscillatory events reoccurring with 10 ms precision. Using statistical controls, we determined that repeats occurred more often than would be expected from unstructured network activity (e.g., by chance). Most spikes occurred during a repeat, and when a repeat contained a spike, the spike reoccurred with precision on the order of ≤20 ms, showing that long repeated patterns of subthreshold activity are strongly connected to spike output. Unexpectedly, we found that repeats occurred independently of classic hippocampal network states like theta oscillations or sharp-wave ripples. Together, these results reveal surprisingly long patterns of repeated activity in the hippocampal network that occur nonstochastically, are transmitted to single downstream neurons, and strongly shape their output. This suggests that the timescale of information transmission in the hippocampal network is much longer than previously thought.

Recommended citation: Kolb, Ilya, Giovanni Talei Franzesi, Michael Wang, Suhasa B. Kodandaramaiah, Craig R. Forest, Edward S. Boyden, and Annabelle C. Singer. "Evidence for Long-Timescale Patterns of Synaptic Inputs in CA1 of Awake Behaving Mice." Journal of Neuroscience 38, no. 7 (February 14, 2018): 1821–34 [PDF]

Cleaning patch-clamp pipettes for immediate reuse

Published in Scientific Reports, 2016

Patch-clamp recording has enabled single-cell electrical, morphological and genetic studies at unparalleled resolution. Yet it remains a laborious and low-throughput technique, making it largely impractical for large-scale measurements such as cell type and connectivity characterization of neurons in the brain. Specifically, the technique is critically limited by the ubiquitous practice of manually replacing patch-clamp pipettes after each recording. To circumvent this limitation, we developed a simple, fast, and automated method for cleaning glass pipette electrodes that enables their reuse within one minute. By immersing pipette tips into Alconox, a commercially-available detergent, followed by rinsing, we were able to reuse pipettes 10 times with no degradation in signal fidelity, in experimental preparations ranging from human embryonic kidney cells to neurons in culture, slices, and in vivo. Undetectable trace amounts of Alconox remaining in the pipette after cleaning did not affect ion channel pharmacology. We demonstrate the utility of pipette cleaning by developing the first robot to perform sequential patch-clamp recordings in cell culture and in vivo without a human operator. Media: [Phys.org, top 5% on Altmetric]

Recommended citation: Kolb, I., W. A. Stoy, E. B. Rousseau, O. A. Moody, A. Jenkins, and C. R. Forest. "Cleaning Patch-Clamp Pipettes for Immediate Reuse." Scientific Reports 6, no. 1 October 11, 2016): 35001. [PDF]

Ilya Kolb, PhD