Seeing the virus with topological optical microscopy

用拓扑光学显微镜观察病毒

• 批准号: BB/X003477/1
• 负责人: Peter Smith
• 金额: $ 22.94万
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FX003477%2F1
• 关键词: Seeing; virus; topological; optical; microscopy

The Problem: This project will develop a new optical approach to seeing small, unlabelled, living viruses and will deliver new ways of describing their interactions with surfaces. Surface treatments with various substances, notably copper, is a first line of defence against viral spread. Effective treated surfaces have been shown to cause structural damage when observed using an electron microscope (EM). However, assaying the effectiveness of coatings is difficult. Delivering a quick and generally usable assessment of viability through structural integrity would deliver a transformative and rapid assay. Current assays for capacity to infect form a bottleneck to designing suitable surfaces for placement in public spaces, hospital environments or on PPE, particularly when faced with rapid spread, as with SARS-CoV-2. Rapid PCR-based or immunological assays can provide information on viral presence/absence, but determination of viral viability still often relies on cell culture assays. EM is time consuming, expensive and can only be used on dead material. These are all laborious processes, only available to specialised labs and as indirect methods are at best semi-quantitative. An optical approach that can be fitted to a standard microscope platform to allow the study of viral responses and disruption on surfaces, will be a transformative step.The Solution: Here, we propose to develop a label-free, non-invasive optical imaging method with spatial resolution at one millionth of a millimetre (a nanometre) or a thousandth of the diameter of a human hair. Such microscopy is theoretically out of reach due to the Abbe diffraction limit. This would restrict resolution to approximately 190 nm for visible light. Viruses of interest are frequently only 10s of nanometres in diameter. However, our new approach will draw on recent developments in structuring light and artificial intelligence to address the challenge of single virus imaging while observing their interactions with surfaces. This proposal has two aims: 1. To develop an optical method for imaging biological systems that bridges the gap between conventional unlabelled optical imaging and electron microscopy.2. To study viruses with the method, pushing its development and resolution, while exploring its use as a method for directly observing viral structure and disruption on antimicrobial surfaces.Success will not only deliver new ways of studying viruses but will open a transformational pathway to unlabelled live cell imaging at the nanoscale.Our approach is based on the recently introduced concept of imaging by manipulating the physics of light. The target is illuminated with a structured light field and the corresponding scatter patterns are analysed with artificial intelligence. When these structured fields illuminate a small object, the scattered fields carry information about the geometry of the object at the subwavelength-scale. This has been shown to lead to orders of magnitude improvements in metrology. More recently, the applicants have implemented new imaging methods based on structured light. The step from metrology to imaging is, however, a non-trivial one, and to date only one-dimensional apertures have been imaged by this approach. However, the resolution improved conventional microscopy by an order of magnitude, and we anticipate that our new method will allow for another 10-fold enhancement. We propose to translate our method from nanoscale metrology to nanoscale biological imaging of 'living viruses'. A key challenge in extending to biological imaging involves the extraction of information from the complex scattered field patterns. To this end, we will use neural network-based deconvolution algorithms to perform image reconstruction, as demonstrated in the recent work of the Solution Providers. We are thus well placed to adapt the methodology to viral imaging, viability assays and further biological applications.

问题：该项目将开发一种新的光学方法来观察小的、未标记的活病毒，并将提供描述它们与表面相互作用的新方法。用各种物质（特别是铜）进行表面处理是防止病毒传播的第一道防线。有效处理的表面已被证明会导致结构损伤时，使用电子显微镜（EM）观察。然而，测定涂层的有效性是困难的。通过结构完整性提供快速且普遍可用的生存力评估将提供变革性和快速测定。目前对感染能力的测定形成了设计用于放置在公共场所、医院环境或PPE上的合适表面的瓶颈，特别是当面临快速传播时，如SARS-CoV-2。基于PCR的快速检测或免疫学检测可以提供有关病毒存在/不存在的信息，但病毒活力的测定通常仍依赖于细胞培养检测。EM是耗时的，昂贵的，只能用于死材料。这些都是费力的过程，只有专门的实验室才能使用，而且间接方法充其量只能是半定量的。一种可以安装在标准显微镜平台上的光学方法，可以研究表面上的病毒反应和破坏，这将是一个变革性的步骤。解决方案：在这里，我们建议开发一种无标记的非侵入性光学成像方法，其空间分辨率为百万分之一毫米（一纳米）或人类头发直径的千分之一。由于阿贝衍射极限，这种显微镜在理论上是无法达到的。这将把可见光的分辨率限制在约190 nm。感兴趣的病毒直径通常只有几十纳米。然而，我们的新方法将利用结构化光和人工智能的最新发展来解决单个病毒成像的挑战，同时观察它们与表面的相互作用。这项建议有两个目的：1。发展一种生物系统成像的光学方法，弥补传统无标记光学成像和电子显微镜之间的差距.利用该方法研究病毒，推动其发展和分辨率，同时探索其作为直接观察抗菌表面上病毒结构和破坏的方法的用途。成功不仅将提供研究病毒的新方法，还将打开纳米级未标记活细胞成像的变革途径。我们的方法基于最近引入的通过操纵光物理成像的概念。用结构光场照明目标，并用人工智能分析相应的散射模式。当这些结构化的领域照亮一个小的对象，散射场携带的信息的几何形状的对象在亚波长尺度。这已被证明导致计量学的数量级改进。最近，申请人已经实现了基于结构光的新成像方法。然而，从计量到成像的步骤是不平凡的步骤，并且迄今为止仅一维孔径已经通过这种方法成像。然而，分辨率将传统显微镜提高了一个数量级，我们预计我们的新方法将允许另一个10倍的增强。我们建议将我们的方法从纳米计量学翻译为“活病毒”的纳米生物成像。扩展到生物成像的一个关键挑战涉及从复杂的散射场模式中提取信息。为此，我们将使用基于神经网络的反卷积算法来执行图像重建，正如解决方案提供商最近的工作所证明的那样。因此，我们处于有利地位，以适应病毒成像，活力测定和进一步的生物学应用的方法。