Novel microbial rhodopsins for optogenetics
Engineering, optimization and application ofmicroscopes, software, screening pipelines, and genetically encoded voltage indicators towards imaging neural dynamics
More Info
expand_more
Abstract
Optogenetics has revolutionized neuroscience in the last decade. In contrast to traditional electrode-based electrophysiology, optogenetics increases the throughput of targeted neurons by orders of magnitude. Genetically targeted populational neuron activities can thus be monitored and manipulated with high temporal and spatial resolution, thanks to joint efforts from both biological and optical sides. Optogenetics has become an attractive and reliable method for studying neuroscience problems.
In optogenetics, the most widely used protein to report action potentials (AP) is genetically encoded calcium indicators (GECI), which change the green fluorescence level when there is a calcium influx in the neuron. However, it is not a directmeasure ofmembrane potential, which makes them incapable of reporting sub-threshold events. Moreover, they have slow kinetics that can not distinguish a single AP.
To truly report membrane voltage dynamics, genetically encoded voltage indicators (GEVIs) were developed. GEVIs use either voltage-sensing domains (VSD) or microbial rhodopsins to detect the change in membrane potential. This change is reflected through the fluorescence emission difference from the linked fluorescent proteins or the microbial rhodopsins themselves. GEVIs based on different scaffolds have evolved through several iterations to make them brighter and faster, and voltage imaging using GEVIs has provided insights into neuroscience problems in vivo. However, the performance is still quite limited: although the VSD-based GEVIs are bright, they require blue laser excitation for the fluorescent proteins. Because of this, they suffer more from scattering in deep tissue, and their transduction time from VSD to fluorescence emission limits the speed; The microbial rhodopsin based GEVIs show a sub-millisecond response. On the other side, the biggest issue is their orders of magnitude lower fluorescence. These drawbacks would result in a poor signal-to-noise ratio (SNR) of measured signals, which is discussed in Chapter 1.
The goal of my PhD is to develop better tools to increase the SNR of voltage imaging. This dissertation achieves this goal from different disciplinary perspectives: optical engineering, software development, and protein engineering through rational design and directed evolution…