TartanSW: a new method for spectrally-resolved standing wave cell microscopy and mesoscopy

TartanSW：光谱分辨驻波细胞显微镜和介观镜检查的新方法

• 批准号: BB/P02565X/1
• 负责人: Gail McConnell
• 金额: $ 20.19万
• 依托单位: University of Strathclyde
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FP02565X%2F1
• 关键词: TartanSW; new; method; spectrally; resolved

Important biological processes such as cell movement depend on dynamic changes in the shape of the cell surface. As well as in motility and the ingestion of bacterial pathogens, the cell membrane changes shape actively in the formation of synapses between nerve cells and the handling of antigens by cells of the immune system. The neuronal growth cone shows protrusions occurring over a time scale of seconds and much faster movements are seen in many motile cells.Unfortunately, conventional microscope methods fail to provide exact answers to one of the basic questions: 'what is the shape of the cell membrane and how high is it above the substrate in the case of attached cells?'. For 50 years reflection interference contrast has been used but this method actually reports the distribution of mass within the cell near to the membrane rather than the position of the membrane.We have recently reported a standing wave method of fluorescence imaging to map the surface of the cell membrane with super-resolution in depth, using a method that is almost cost-free to implement in a biomedical sciences laboratory with standard resource and infrastructure. In our standing-wave work, we placed fluorescently-stained red blood cells atop a simple mirror instead of a microscope slide and using a standing wave (SW) to create sub-diffraction limited planes of illumination. We observed an axial resolution of around 90 nm, which is comparable to other the super-resolution techniques described, but because we generate multi-planar images, we can readily obtain 3D information on the specimen at this resolution. The essence of this proposal is to add to this standing-wave work a new method which we call TartanSW (because of the similarity of the coloured fringe patterns to textile patterns). A contour map without heights marked on the lines is of little value, but we have discovered that by using multiple wavelength narrowband detection we can recognize the order of the standing wave antinodes by their colours and so tell the difference between hills and valleys. We propose to first develop a simple imaging microscope system, capable of recording multiple wavelengths simultaneously at speeds of up to 100 images per second, to provide super-resolved 3D information on cell structure. We will first characterise the microscope with dye monolayers and model specimens, and then extend the TartanSW imaging to individual red cells prepared with a fluorescent label that stains the cell membrane. Based on our preliminary work we expect to be able to detect very tiny but high-speed changes in the structure of the red cell membrane. We will also apply the method to study the highly dynamic skeletal structure of neurones and follow the growth of the cell edge over time.We also propose to perform TartanSW imaging with the Mesolens, a new giant objective lens that is capable of imaging large tissue specimens with sub-cellular resolution and which is at present unique to our laboratory. By applying TartanSW with the Mesolens, it will be possible to image hundreds of cells at even higher 3D resolution than the Mesolens can manage at present. We will apply TartanSW mesoscopy to study the same red cell and neurone specimens described previously, and in imaging hundreds of cells with high resolution simultaneously we expect it will be easier to detect rare events or abnormal cells that may indicate onset of disease, as in the malaria infected red cells which we have already studied.We will aid and encourage other laboratories to take up super-resolution TartanSW microscopy, which could be implemented at low cost in any lab already equipped with a fluorescence microscope, and although the Mesolens is presently unique to Strathclyde, the existing Mesolab facility will support wide access to the proposed technology.

重要的生物过程，如细胞运动，取决于细胞表面形状的动态变化。除了在运动和细菌病原体的摄入中，细胞膜在神经细胞之间突触的形成和免疫系统细胞对抗原的处理中主动改变形状。神经生长锥显示突起发生在秒的时间尺度上，并且在许多运动细胞中观察到更快的运动。不幸的是，传统的显微镜方法无法提供一个基本问题的确切答案：“细胞膜的形状是什么？'. 50年来，反射干涉对比度一直被使用，但这种方法实际上报告的是细胞内靠近膜的质量分布，而不是膜的位置。我们最近报道了一种荧光成像的驻波方法，可以在深度上以超分辨率绘制细胞膜的表面，使用在具有标准资源和基础设施的生物医学科学实验室中几乎免费实施的方法。在我们的驻波工作中，我们将荧光染色的红细胞放置在一个简单的镜子而不是显微镜载玻片上，并使用驻波（SW）来创建照明的子衍射限制平面。我们观察到约90 nm的轴向分辨率，这与所描述的其他超分辨率技术相当，但是因为我们生成多平面图像，所以我们可以很容易地在该分辨率下获得关于样本的3D信息。 这项建议的实质是在驻波工作中增加一种新的方法，我们称之为TartanSW（因为彩色条纹图案与纺织品图案相似）。一个等高线图上没有标出高度是没有什么价值的，但我们发现，通过使用多波长窄带检测，我们可以通过颜色识别驻波波腹的顺序，从而区分山丘和山谷。我们建议首先开发一种简单的成像显微镜系统，能够以每秒100幅图像的速度同时记录多个波长，以提供细胞结构的超分辨率3D信息。我们将首先用染料单层和模型标本对显微镜进行染色，然后将TartanSW成像扩展到用荧光标记染色细胞膜的单个红细胞。基于我们的初步工作，我们希望能够检测到红细胞膜结构中非常微小但高速的变化。我们还将应用该方法来研究神经元的高度动态的骨骼结构，并随着时间的推移跟踪细胞边缘的生长。我们还建议使用Mesolens进行TartanSW成像，Mesolens是一种新的巨型物镜透镜，能够以亚细胞分辨率对大型组织标本进行成像，目前是我们实验室独有的。通过将TartanSW应用于Mesolens，可以以比Mesolens目前所能管理的更高的3D分辨率对数百个细胞进行成像。我们将应用TartanSW介观镜来研究之前描述的相同的红细胞和神经元标本，并且在同时对数百个细胞进行高分辨率成像时，我们预计将更容易检测到可能指示疾病发作的罕见事件或异常细胞，例如我们已经研究过的疟疾感染红细胞。我们将帮助和鼓励其他实验室采用超分辨率TartanSW显微镜，这可以在任何已经配备了荧光显微镜的实验室中以低成本实施，尽管Mesolens目前是斯特拉斯克莱德独有的，但现有的Mesolab设施将支持广泛使用所提出的技术。

项目成果

Application of Light-Sheet Mesoscopy to Image Host-Pathogen Interactions in Intact Organs.

• DOI: 10.3389/fcimb.2022.903957
• 发表时间: 2022
• 期刊: Frontiers in cellular and infection microbiology
• 影响因子: 5.7

Intra-colony channel morphology in Escherichia coli biofilms is governed by nutrient availability and substrate stiffness.

• DOI: 10.1016/j.bioflm.2022.100084
• 发表时间: 2022-12
• 期刊: Biofilm
• 影响因子: 6.8

Multimodal optical mesoscopy reveals the quantity and spatial distribution of gram-positive biofilms in ex vivo tonsils

多模态光学介观镜揭示离体扁桃体革兰氏阳性生物膜的数量和空间分布

• DOI: 10.1101/2023.07.03.547470
• 发表时间: 2023
• 作者: Clapperton M

Light-sheet mesoscopy with the Mesolens provides fast sub-cellular resolution imaging throughout large tissue volumes.

• DOI: 10.1016/j.isci.2022.104797
• 发表时间: 2022-09-16
• 期刊: ISCIENCE
• 影响因子: 5.8
• 作者: Battistella, Eliana;Schniete, Jan;Wesencraft, Katrina;Quintana, Juan F.;McConnell, Gail
• 通讯作者: McConnell, Gail

Label2label: training a neural network to selectively restore cellular structures in fluorescence microscopy.

• DOI: 10.1242/jcs.258994
• 发表时间: 2022-02-01
• 期刊: Journal of cell science
• 影响因子: 4
• 作者: Kölln LS;Salem O;Valli J;Hansen CG;McConnell G
• 通讯作者: McConnell G