Seeing the virus with topological optical microscopy
Seeing the virus with topological optical microscopy
批准号:
BB/X003477/1
负责人:
Peter Smith
金额:
$22.94万
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
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
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.
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