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      A toolbox of Cre-dependent optogenetic transgenic mice for light-induced activation and silencing

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          Abstract

          Cell-type-specific expression of optogenetic molecules allows temporally precise manipulation of targeted neuronal activity. Here we present a toolbox of 4 knock-in mouse lines engineered for strong, Cre-dependent expression of channelrhodopsins ChR2-tdTomato and ChR2-EYFP, halorhodopsin eNpHR3.0, and archaerhodopsin Arch-ER2. All 4 transgenes mediate Cre-dependent, robust activation or silencing of cortical pyramidal neurons in vitro and in vivo upon light stimulation, with ChR2-EYFP and Arch-ER2 demonstrating light sensitivity approaching that of in utero or virally transduced neurons. We further show specific photoactivation of parvalbumin-positive interneurons in behaving ChR2-EYFP reporter mice. The robust, consistent, and inducible nature of our ChR2 mice represents a significant advancement over previous lines, whereas the Arch-ER2 and eNpHR3.0 mice are the first demonstration of successful conditional transgenic optogenetic silencing. When combined with the hundreds of available Cre-driver lines, this optimized toolbox of reporter mice will enable widespread investigations of neural circuit function with unprecedented reliability and accuracy.

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          Most cited references26

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          A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex.

          A key obstacle to understanding neural circuits in the cerebral cortex is that of unraveling the diversity of GABAergic interneurons. This diversity poses general questions for neural circuit analysis: how are these interneuron cell types generated and assembled into stereotyped local circuits and how do they differentially contribute to circuit operations that underlie cortical functions ranging from perception to cognition? Using genetic engineering in mice, we have generated and characterized approximately 20 Cre and inducible CreER knockin driver lines that reliably target major classes and lineages of GABAergic neurons. More select populations are captured by intersection of Cre and Flp drivers. Genetic targeting allows reliable identification, monitoring, and manipulation of cortical GABAergic neurons, thereby enabling a systematic and comprehensive analysis from cell fate specification, migration, and connectivity, to their functions in network dynamics and behavior. As such, this approach will accelerate the study of GABAergic circuits throughout the mammalian brain. Copyright © 2011 Elsevier Inc. All rights reserved.
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            High-Performance Genetically Targetable Optical Neural Silencing via Light-Driven Proton Pumps

            The ability to silence the activity of genetically specified neurons in a temporally precise fashion would open up the ability to investigate the causal role of specific cell classes in neural computations, behaviors, and pathologies. Here we show that members of the class of light-driven outward proton pumps can mediate very powerful, safe, multiple-color silencing of neural activity. The gene archaerhodopsin-31 (Arch) from Halorubrum sodomense enables near-100% silencing of neurons in the awake brain when virally expressed in mouse cortex and illuminated with yellow light. Arch mediates currents of several hundred picoamps at low light powers, and supports neural silencing currents approaching 900 pA at light powers easily achievable in vivo. In addition, Arch spontaneously recovers from light-dependent inactivation, unlike light-driven chloride pumps that enter long-lasting inactive states in response to light. These properties of Arch are appropriate to mediate the optical silencing of significant brain volumes over behaviourally-relevant timescales. Arch function in neurons is well tolerated because pH excursions created by Arch illumination are minimized by self-limiting mechanisms to levels comparable to those mediated by channelrhodopsins2,3 or natural spike firing. To highlight how proton pump ecological and genomic diversity may support new innovation, we show that the blue-green light-drivable proton pump from the fungus Leptosphaeria maculans 4 (Mac) can, when expressed in neurons, enable neural silencing by blue light, thus enabling alongside other developed reagents the potential for independent silencing of two neural populations by blue vs. red light. Light-driven proton pumps thus represent a high-performance and extremely versatile class of “optogenetic” voltage and ion modulator, which will broadly empower new neuroscientific, biological, neurological, and psychiatric investigations.
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              Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements.

              Simultaneous recording from large numbers of neurons is a prerequisite for understanding their cooperative behavior. Various recording techniques and spike separation methods are being used toward this goal. However, the error rates involved in spike separation have not yet been quantified. We studied the separation reliability of "tetrode" (4-wire electrode)-recorded spikes by monitoring simultaneously from the same cell intracellularly with a glass pipette and extracellularly with a tetrode. With manual spike sorting, we found a trade-off between Type I and Type II errors, with errors typically ranging from 0 to 30% depending on the amplitude and firing pattern of the cell, the similarity of the waveshapes of neighboring neurons, and the experience of the operator. Performance using only a single wire was markedly lower, indicating the advantages of multiple-site monitoring techniques over single-wire recordings. For tetrode recordings, error rates were increased by burst activity and during periods of cellular synchrony. The lowest possible separation error rates were estimated by a search for the best ellipsoidal cluster shape. Human operator performance was significantly below the estimated optimum. Investigation of error distributions indicated that suboptimal performance was caused by inability of the operators to mark cluster boundaries accurately in a high-dimensional feature space. We therefore hypothesized that automatic spike-sorting algorithms have the potential to significantly lower error rates. Implementation of a semi-automatic classification system confirms this suggestion, reducing errors close to the estimated optimum, in the range 0-8%.
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                Author and article information

                Journal
                9809671
                21092
                Nat Neurosci
                Nat. Neurosci.
                Nature neuroscience
                1097-6256
                1546-1726
                1 March 2012
                25 March 2012
                01 November 2012
                : 15
                : 5
                : 793-802
                Affiliations
                [1 ]Allen Institute for Brain Science, Seattle, WA, USA
                [2 ]Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, VA, USA
                [3 ]Center for Integrative Brain Research, Seattle Children’s Research Institute, Seattle, WA USA
                [4 ]Boston University, Boston, MA, USA
                [5 ]Rutgers University, Newark, NJ, USA
                [6 ]Massachusetts Institute of Technology, Cambridge, MA, USA
                [7 ]Vollum Institute, Oregon Health and Science University, Portland, OR, USA
                Author notes
                [* ]Correspondence should be addressed to Hongkui Zeng ( hongkuiz@ 123456alleninstitute.org )
                Article
                NIHMS360099
                10.1038/nn.3078
                3337962
                22446880
                a9fb9f30-98b2-4e32-8a5b-00cfc8597560
                History
                Funding
                Funded by: National Institute on Drug Abuse : NIDA
                Award ID: R01 DA028298-02 || DA
                Categories
                Article

                Neurosciences
                Neurosciences

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