Being able to both control and monitor neuronal activity is critical for learning how neuronal circuits process information and make decisions. However, while powerful tools to control neuronal firing using genetically encoded light-activated channels have recently been developed, limitations of current genetically encoded sensors of neuronal activity severely restrict their use for monitoring brain function. In particular, calcium sensors are slow and cannot report on subthreshold depolarizations. While voltage sensors could in principle be used to follow fast trains of action potentials and monitor subthreshold depolarizations, the low dynamic range of existing sensors makes them unsuitable for most experiments in vivo. Moreover, there are presently no calcium or voltage sensors that are efficiently excited by red (>550nm) wavelengths, a region of the spectrum that would enable their concurrent use with blue/greenabsorbing light-activated channels. The goal of this proposal is to address these needs by developing a new generation of genetically encoded voltage biosensors with significantly improved dynamic range and speed and the ability to be used concurrently with light-activated channels. This work will enable finer and more powerful functional dissection of the nervous system, while also establishing new protein engineering methods. The expertise of the lab in fluorescent proteins engineering will be leveraged to educate future scientists and engineers about research in protein engineering, and to introduce educators to the utility of genetically encoded biosensors for teaching scientific concepts in laboratory courses.

Intellectual Merit The engineering objective of this proposal is to apply knowledge of fluorescence spectroscopy and protein structure to quantitatively improve the performance of an existing class of voltage sensors (Aim 1) and to develop an entirely new class of voltage sensors (Aim 2). In the first aim, we will increase dynamic range via rational optimization of Förster resonance energy transfer (FRET) between fluorescent proteins linked to a voltage sensing domain. In the second aim, we will use a conformationally sensitive red fluorescent protein to report on movements of a voltage sensing domain with rapid kinetics. For both aims, we will employ rational design combined with comprehensive saturation mutagenesis and screening of important sites. This project will be a pioneering study in molecular engineering in two ways. It will be the first to rationally apply predictions from modeling of Förster resonance energy transfer to identify the factors limiting the fluorescence output response, and then to perform protein engineering to comprehensively address those factors. Second, this project will be the first to combine comprehensive screening with atomic-level structural knowledge of sensing domains and fluorescent proteins in order to create an entirely new class of allosteric voltage sensors; this research will thus give insight on the relative usefulness of prior knowledge and screening to the engineering of genetically encoded biosensors.

Broader Impacts Voltage sensors developed through this project will be promptly disseminated to the larger scientific community. These sensors will have a broad impact on the field of neuroscience by enabling robust voltage sensing and concurrent control and readout of neuronal activity. Our work will also impact the field of bioengineering by validating concepts and establishing strategies for how to optimize the design of fluorescent protein-based sensors using energy transfer or allostery. The proposed project will provide an excellent opportunity to introduce undergraduates and high school students, including students from disadvantaged backgrounds, to research in molecular bioengineering. It will also provide the opportunity to introduce educators to the use of genetically encoded biosensing to create exciting laboratory lessons that teach important basic concepts while demonstrating the results of recent research in protein engineering.

Project Start
Project End
Budget Start
2011-10-01
Budget End
2014-09-30
Support Year
Fiscal Year
2011
Total Cost
$319,996
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
City
Palo Alto
State
CA
Country
United States
Zip Code
94304