Automatic fluorescent tag detection in 3D with super-resolution: application to the analysis of chromosome movement
Automatic fluorescent tag detection in 3D with super-resolution: application to the analysis of chromosome movement
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DOI：
10.1046/j.1365-2818.2002.01066.x
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发表时间：
2002-10-01
期刊：
影响因子：
--
通讯作者：
Danuser, G
中科院分区：
文献类型：
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作者：
Thomann, D;Rines, DR;Danuser, G
在本文中，我们描述了一种算法框架，用于在低于瑞利极限的分离下自动检测3D光学图像中的衍射极限荧光点，即具有超分辨率。我们展示了超分辨率检测的潜力，通过跟踪荧光标记的染色体在芽殖酵母有丝分裂。我们的生物学目标是鉴定和分析染色体分离过程中产生张力的蛋白质。通过绿色荧光蛋白（GFP）标记染色体和纺锤体极体以产生携带四个荧光斑点的细胞，并使用3D荧光显微镜观察斑点随时间的运动，可以在活细胞中进行动态测量。当标记的物体被低于光学分辨率的距离分开时，斑点检测中的中心问题与斑点的部分或完全重叠有关。为了在这些条件下检测多个点，建立了一组候选混合模型，并基于模型与图像数据的最小二乘拟合中残差的chi（2）-统计量从该组中选择最佳候选者。即使图像的信噪比（SNR）低至5-10，我们也能够将分辨率提高到瑞利极限以下的两倍。在SNR为5-10的图像中，可以定位孤立标签的精度小于5 nm。对于两个标签分离小于瑞利极限，定位精度被发现是在10和20 nm之间，这取决于有效的点到点的距离。这表明分辨率和定位精度之间的密切关系。
In this paper, we describe an algorithmic framework for the automatic detection of diffraction-limited fluorescent spots in 3D optical images at a separation below the Rayleigh limit, i.e. with super-resolution. We demonstrate the potential of super-resolution detection by tracking fluorescently tagged chromosomes during mitosis in budding yeast. Our biological objective is to identify and analyse the proteins responsible for the generation of tensile force during chromosome segregation. Dynamic measurements in living cells are made possible by green fluroescent protein (GFP)-tagging chromosomes and spindle pole bodies to generate cells carrying four fluorescent spots, and observe the motion of the spots over time using 3D-fluorescence microscopy. The central problem in spot detection arises with the partial or complete overlap of spots when tagged objects are separated by distances below the resolution of the optics. To detect multiple spots under these conditions, a set of candidate mixture models is built, and the best candidate is selected from the set based on chi(2)-statistics of the residuals in least-square fits of the models to the image data.Even with images having a signal-to-noise ratio (SNR) as low as 5-10, we are able to increase the resolution two-fold below the Rayleigh limit. In images with a SNR of 5-10, the accuracy with which isolated tags can be localized is less than 5 nm. For two tags separated by less than the Rayleigh limit, the localization accuracy is found to be between 10 and 20 nm, depending on the effective point-to-point distance. This indicates the intimate relationship between resolution and localization accuracy.