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

光学显微镜方法改变了我们研究生物体中生物过程的方式，使研究人员能够研究细胞如何生长，分化，交流以及它们如何改变以支持细胞可塑性。这些技术提供了非常高的时空精度，同时具有非常低的侵入性，这对于在纳米尺度上观察细胞中的分子动力学和相互作用至关重要。这一要求对于研究支持我们大脑中由神经元（突触）的微小（<1 μ m 3）亚细胞区室介导的通信的机制特别相关。有了新的光学纳米方法，我们可以开始研究纳米尺度的分子机制。然而，随着它们的进一步发展，沿着生物成像工具和实验范例的不断发展，这些方法在其实现中具有几层复杂性。这限制了它们的采用以及它们对活细胞、组织或体内的多色、多模态的适应性。 有一个迫切需要开发成像策略，以增加可访问性和可实现的性能的光学纳米研究复杂的生物范例。这一方向的进展有可能使光学纳米技术在生命科学中真正具有变革性。我们的长期目标是：1。将我的团队和实验室建立为结合光学纳米镜和机器学习的新型智能超分辨率方法的领先研究小组，以提高我们对突触通信的理解。2.开发一个智能纳米平台，将允许动态适应生物样品和实验条件的图像采集。它将整合多模态成像能力，以增强我们探测活神经元中突触结构和功能的能力。该计划将围绕五个短期目标进行阐述：1.基于深度学习的在线特征识别方法的开发2.智能扫描系统的实现3.智能纳米显微镜与高光谱成像的结合，4.活体组织高光谱纳米显微镜新标记物的研究5.自适应光刺激在功能性突触成像中的应用在光学、化学、机器学习和神经科学的界面上。 智能光学纳米显微镜的拟议发展将建立在我们最近集成的全自动显微镜优化平台的基础上。我提出的NSERC研究计划将有助于新一代智能成像设备，这将改变光学纳米显微镜的适用性和影响。我的计划的学员将在生物光子学，化学，神经科学和人工智能的接口开发一个独特的专业知识。

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.