Subcellular Euclidean distance measurements with multicolor fluorescence localization imaging in cultured cells.
Subcellular Euclidean distance measurements with multicolor fluorescence localization imaging in cultured cells.
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DOI：
10.1016/j.xpro.2021.100774
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发表时间：
2021-12-17
期刊：
影响因子：
--
通讯作者：
Burroughs NJ
中科院分区：
文献类型：
--
作者：
Germanova TE;Roscioli E;Harrison JU;McAinsh AD;Burroughs NJ
该方案使用Kinetochore Delta软件（KiDv1.0.1，基于MATLAB）测量固定样品中两个/三个荧光标记的动粒组分之间的3D欧几里得距离（Δ3D）。平均Δ3D的高估通过贝叶斯算法校正，ΔEC距离反映动粒群体内荧光团的总体平均位置。该软件包还支持着丝粒分类，可用于对着丝粒进行子采样并测量ΔEC。总之，这允许研究人类动粒的动态结构（在hTERT-RPE 1细胞中测试）。有关本方案使用和执行的完整详细信息，请参阅。从多色图像堆栈中测量动粒内距离以亚像素精度自动检测荧光点中心基于GUI的流水线实现点分类和数据质量控制贝叶斯算法校正欧几里德距离的高估该协议使用动粒Delta软件测量固定样品中两个/三个荧光标记的动粒组分之间的3D欧几里德距离（Δ3D）（KiDv1.0.1，基于MATLAB®）。平均Δ3D的高估通过贝叶斯算法校正，ΔEC距离反映动粒群体内荧光团的总体平均位置。该软件包还支持着丝粒分类，可用于对着丝粒进行子采样并测量ΔEC。总之，这允许研究人类动粒的动态结构（在hTERT-RPE 1细胞中测试）。
This protocol measures the 3D Euclidean distance (Δ3D) between two/three fluorescently labeled kinetochore components in fixed samples using Kinetochore Delta software (KiDv1.0.1, MATLAB based). Overestimation of mean Δ3D is corrected through a Bayesian algorithm, with ΔEC distances reflecting the ensemble average positions of fluorophores within a kinetochore population. This package also enables kinetochore categorization, which can be used to sub-sample kinetochores and measure ΔEC. Together, this allows the dynamic architecture of human kinetochores to be investigated (tested in hTERT-RPE1 cells). For complete details on the use and execution of this protocol, please refer to. Measurements of intra-kinetochore distances from multi-color image stacks Automated detection of fluorescent spot centers with sub-pixel accuracy GUI-based pipeline to enable spot classification and data quality control Bayesian algorithm to correct for over-estimation of Euclidian distances This protocol measures the 3D Euclidean distance (Δ3D) between two/three fluorescently labeled kinetochore components in fixed samples using Kinetochore Delta software (KiDv1.0.1, MATLAB® based). Overestimation of mean Δ3D is corrected through a Bayesian algorithm, with ΔEC distances reflecting the ensemble average positions of fluorophores within a kinetochore population. This package also enables kinetochore categorization, which can be used to sub-sample kinetochores and measure ΔEC. Together, this allows the dynamic architecture of human kinetochores to be investigated (tested in hTERT-RPE1 cells).
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