The overall goals of the St-Pierre lab are to design, characterize, and deploy molecular tools to enable neuroscience research.
The brain of the mouse, a commonly-used animal model in neuroscience, is challenging to study for multiple reasons:
It is complex. For example, it contains 108 neurons and as many (or more) glia. Neurons in the mouse cortex receive on average ~8,000 inputs (synapses) from other cells (link: https://www.ncbi.nlm.nih.gov/pubmed/2778101).
Neurons can process information extremely quickly, on a millisecond timescale.
Brain tissue is opaque, challenging the use of optical techniques to image activity and structures deep in the brain in living mice.
These challenges motivate the development of tools optimized for brain imaging.
Our current projects focus on three broad themes:
1. Novel probes for imaging rapid neural activity. Given that membrane potential (voltage) is a key informational carrier in the brain, there is a large demand in neuroscience for monitoring voltage dynamics at high spatiotemporal resolution and in genetically-defined cell types. We are addressing this need by developing improved genetically encoded voltage indicators (GEVIs). To facilitate their adoption, we are also developing standardized assays for benchmarking GEVIs across all key performance criteria. Finally, we are deploying novel GEVIs for biological discovery. We also share novel GEVIs with the broader neuroscience community.
2. Accelerating protein engineering. Engineering biosensors and other classes of proteins remains often time-consuming and labor intensive, often more akin to an art project than true engineering. To facilitate and accelerate protein engineering, we are developing new integrated pipelines combining innovations in hardware, software, and wetware.
3. Synthetic biology and synthetic neurobiology. We are using synthetic biological approaches to develop new transcriptional interfaces with neurons. These interfaces could either be used for perturbing neurons or for monitoring neuronal activity without impacting cellular physiology.
We adopt multidisciplinary approaches, combining techniques from synthetic biology, electrical engineering, optics, and computational biology, and neuroscience. We focus on integrated solutions that combine wetware (e.g. new biosensors or cell lines), hardware (e.g. custom microscopes) and software (e.g. new signal/image analysis software). Our multidisciplinary approaches are reflected in the diverse backgrounds of our team members.