Super-resolution imaging of biological organisms: seeing below the classical limits

超分辨率成像技术可以研究比传统限制小得多的结构，即大约一半的光波长。2014年诺贝尔化学奖强调了它对生物科学的根本重要性。已经开发了两大类超分辨率成像技术，基于扫描的(例如STED、GSD)和定位显微镜(例如Palm、Storm、Paint)。两者都提供了在生物样本中成像小于30纳米的结构的能力；然而，成功的成像仍然面临许多挑战，例如光学不均匀对成像过程的影响，由定位成像产生的大数据集的有效处理，使用合适的染料对感兴趣的结构进行有效的标记，以及进一步提高采集速度、视野、分辨率和在3D中执行多色成像的需求。该项目专注于开发关键的使能技术，以便在活组织中进行大光学深度的超分辨率成像。学生将有机会发展进行下一代显微镜研究所必需的广泛技能，例如开发纳米钻石作为活脑组织神经活动的标志，以及使用自适应光学增强型超分辨率显微镜。学生将获得广泛的技能方面的经验，如：光学硬件设计和对准，开发硬件控制和数据处理软件，标记成像样品，以及与生物科学同行合作，以确保我们的研究也使新的生物科学成为可能。

Super-resolution imaging techniques allow studying of structures much smaller than the traditional limit of approximately half the wavelength of the light. The 2014 Nobel Prize in Chemistry has emphasised its fundamental importance to the biological sciences. Two broad classes of techniques for super-resolution imaging have been developed, scanning-based (e.g. STED, GSD) and localisation microscopy (e.g. PALM, STORM, PAINT). Both offer the ability to image structures smaller than 30 nm within biological samples; however there are still numerous challenges to successful imaging such as the effects of optical inhomogeneities on the imaging process, the efficient processing of the large data sets generated by localisation imaging, effective labelling of structures of interest with suitable dyes and the desire to further increase speed of acquisition, field of view, resolution and perform multi-colour imaging in 3D.This project focusses on developing key enabling technologies for performing super-resolution imaging at large optical depths in living tissue. The student will have the opportunity to develop a wide range of skills that are essential for performing research into next-generation microscopy, e.g. developing nanodiamond as a marker for neural activity in living brain tissue and working with adaptive-optics enhanced super-resolution microscopes. The student will gain a wide range of experience in skills such as: Optical hardware design and alignment, developing software for hardware control and data processing, labelling samples for imaging and collaboration with colleagues in the biological sciences to ensure our research also enables new biological science.