Biophysical Society Thematic Meeting - June 28-July 1, 2015

New Biological Frontiers Illuminated by Molecular Sensors and Actuators

Poster Abstracts

41-POS Board 41 Imaging Subcellular Voltage Dynamics in vivo with Improved Genetically Encoded Indicators Francois St-Pierre , Helen H. Yang, Xiaozhe Ding, Ying Yang, Thomas R. Clandinin, Michael Z. Lin. Stanford University, Stanford, CA, USA. Nervous systems encode information as spatiotemporal patterns of membrane voltage transients, so accurate measurement of electrical activity has been of long-standing interest. Recent engineering efforts have improved our ability to monitor membrane voltage dynamics using genetically encoded voltage indicators. In comparison with electrophysiological approaches, such indicators can monitor many genetically defined neurons simultaneously; they can also more easily measure voltage changes from subcellular compartments such as axons and dendrites. Compared with genetically encoded calcium indicators, voltage sensors enable a more direct, accurate, and rapid readout of membrane potential changes. However, several challenges remain for in vivo voltage imaging with genetically encoded indicators. In particular, current voltage sensors are characterized by insufficient sensitivity, kinetics, and/or brightness to be true optical replacements for electrodes in vivo . As a first step towards addressing these challenges, we developed new voltage indicators, ASAP2f and ASAP2s, that further improve upon the sensitivity of the fast voltage sensor Accelerated Sensor of Action Potentials 1 (ASAP1). We also describe here how these novel sensors are able to report stimulus-evoked voltage responses in axonal termini of the fly visual interneuron L2. In this system, ASAP sensors enabled the monitoring of neural activity with greater temporal resolution than three recently reported calcium and voltage sensors. Overall, our study reports novel voltage indicators with improved performance, illustrates the importance of sensor kinetics for accurately reporting neural activity, and suggests L2 as an in vivo platform for benchmarking neural activity sensors. We anticipate that ASAP2f and ASAP2s will facilitate current and future efforts to understand how neural circuits represent and transform information.

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