Pushing the boundaries of super-resolution optical microscopy for molecular imaging in live tissue

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Optical microscopy methods have transformed the way we study biological processes in living organisms, enabling researchers to study how cells grow, differentiate, communicate and how they are altered to support cellular plasticity. Those techniques offer a very high spatio-temporal precision combined with very low invasiveness, which is essential to observe molecular dynamics and interactions in cells at their scale: the nanoscale. This requirement is particularly relevant for studying the mechanisms that support communication in our brain that is mediated by tiny (<1um3) subcellular compartments of neurons, the synapses. With novel optical nanoscopy methods we can begin to study molecular mechanisms at the nanoscale. However, as they are further developed, along with the continuous evolution of bio-imaging tools and experimental paradigms, those methods come with several layers of complexity in their implementation. This has limited their adoption as well as their adaptability to multi-color, multi-modal in living cells, tissues or in vivo. There is a critical need to develop imaging strategies to increase the accessibility and the achievable performance of optical nanoscopy to study complex biological paradigms. Progress in this direction has the potential to make optical nanoscopy truly transformative in life sciences. The long-term objectives of my programs are: 1. To establish my team and laboratory as a leading research group on novel intelligent super-resolution methods combining optical nanoscopy and machine learning to improve our understanding of synaptic communication. 2. To develop an intelligent nanoscopy platform that will allow to dynamically adapt the image acquisition to the biological sample and experimental conditions. It will integrate multi-modal imaging capabilities to enhance our ability to probe synaptic structures and function in living neurons. The Program will articulate around five short term objectives: 1.The development of online feature recognition approaches based on deep learning 2.The implementation of an intelligent scanning system 3.The combination of intelligent nanoscopy with hyperspectral imaging, 4.The investigation of novel markers for hyperspectral nanoscopy in living tissue 5.The application of adaptive photostimulation for functional synaptic imaging My transdisciplinary program is at the interface of Optics, Chemistry, Machine learning and Neurosciences. The proposed development of intelligent optical nanoscopy will build on our recent integration of a fully-automated microscopy optimization platform. My proposed NSERC research program will contribute to a new generation of intelligent imaging devices that will transform the applicability and the impact of optical nanoscopy. The trainees of my Program will develop a unique expertise at the interface of Biophotonics, Chemistry, Neurosciences and Artificial Intelligence.