For decades, components of the mammalian nuclear envelope (NE), such as the nuclear lamina and nuclear pore complexes (NPCs), have been largely resistant to quantitative cell biological analysis using conventional fluorescence microscopy. This is in part due to their sub diffraction limit dimensions. Super-resolution microscopy, a major advancement in cell biology research, has now made possible the acquisition of images in which nuclear lamin networks and single NPCs can be resolved in intact mammalian somatic cells. In particular, single molecule localization microscopy is able to generate data sets that are accurate enough to allow detailed quantitative analysis. Here we describe an algorithm that will identify the centroid of single NPCs and will determine their localization relative to the distribution of lamin protein filaments. Using this algorithm, a percentage of NPCs localized within the nuclear lamin network was accurately calculated, that could be compared between cells expressing different lamin complements. With modifications tweaked according to user specified sample images, this algorithm serves as a semi-automatic and fast computational tool to quantify and compare the localization and distribution of two or more cellular components at the nanometre scale.

中文翻译：

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在单分子定位显微图像中量化核层网络内核孔复合分布的用户交互算法

几十年来，哺乳动物核膜 (NE) 的组成部分，例如核层和核孔复合物 (NPC)，在很大程度上对使用传统荧光显微镜进行的定量细胞生物学分析具有抗性。这部分是由于它们的亚衍射极限尺寸。超分辨率显微镜是细胞生物学研究的一项重大进步，现在可以获取图像，其中可以在完整的哺乳动物体细胞中解析核纤层网络和单个 NPC。特别是，单分子定位显微镜能够生成足够准确的数据集，以进行详细的定量分析。在这里，我们描述了一种算法，该算法将识别单个 NPC 的质心，并将确定它们相对于 lamin 蛋白丝分布的定位。使用该算法，可以准确计算出位于核 lamin 网络内的 NPC 百分比，可以在表达不同 lamin 互补物的细胞之间进行比较。通过根据用户指定的样本图像进行修改，该算法作为一种半自动和快速计算工具，在纳米尺度上量化和比较两个或多个细胞成分的定位和分布。