一种基于图像分析的细胞微管定量分析方法

兰晓东; 黄智勇; 谭子明; 汤慧英; 李凌霏; 王德怀

doi:10.16016/j.1000-5404.201906168

您当前的位置：

首页 >

文章列表页 >

一种基于图像分析的细胞微管定量分析方法

基础医学 | 更新时间：2026-01-09

- 一种基于图像分析的细胞微管定量分析方法
- A method for quantitative analysis of cell microtubules based on image analysis
- 第三军医大学学报 2019年41卷第22期页码：2190-2194
- 作者机构：
  
  1.610017 成都，成都市第二人民医院烧伤整形科
  2.400038 重庆，陆军军医大学第一附属医院全军烧伤研究所，创伤、烧伤与复合伤国家重点实验室
- 作者简介：
  
  [王德怀，E-mail:398174019@qq.comWANG Dehuai, E-mail: 398174019@qq.com
- 基金信息：
- DOI：10.16016/j.1000-5404.201906168
  中图分类号： R341; R730.23; R735.35
- 收稿：2019-06-21，
  
  修回：2019-08-04，
  
  纸质出版：2019-11-30
- 稿件说明：
移动端阅览
兰晓东, 黄智勇, 谭子明, 等. 一种基于图像分析的细胞微管定量分析方法[J]. 第三军医大学学报, 2019,41(22):2190-2194.

Xiaodong LAN, Zhiyong HUANG, Ziming TAN, et al. A method for quantitative analysis of cell microtubules based on image analysis[J]. Journal of Third Military Medical University, 2019, 41(22): 2190-2194.
兰晓东, 黄智勇, 谭子明, 等. 一种基于图像分析的细胞微管定量分析方法[J]. 第三军医大学学报, 2019,41(22):2190-2194. DOI： 10.16016/j.1000-5404.201906168.

Xiaodong LAN, Zhiyong HUANG, Ziming TAN, et al. A method for quantitative analysis of cell microtubules based on image analysis[J]. Journal of Third Military Medical University, 2019, 41(22): 2190-2194. DOI： 10.16016/j.1000-5404.201906168.

摘要

目的

基于像素比和粒度分析理论，通过图像处理和分析方法探究客观量化微管结构的方法。

方法

将常规培养的3 d人脐静脉内皮细胞(HUVEC)按随机数字表法分为正常对照组、微管解聚组和微管聚合组。采用Western blot检测乙酰化α微管蛋白的含量变化。免疫荧光染色后，激光共聚焦显微镜下观察微管形态变化并获取图像。Matlab 7.0编程进行图像分割、增强等处理并提取特征参数。对数据行单因素方差分析、多重比较以及多元判别分析。

结果

① 微管解聚组细胞乙酰化α微管蛋白含量明显低于正常对照组(

0.05)；微管聚合组细胞乙酰化α微管蛋白含量明显高于正常对照组(

0.05)。②正常对照组细胞微管结构完整，围绕核周束状分布，胞质中少量细小荧光斑；微管解聚组细胞微管纤维断裂，胞质中出现大量点样小荧光斑，呈现弥散性分布；微管聚合组细胞微管纤维数量多且粗大，呈多分支且杂乱的放射样分布，胞质中出现较大荧光斑。③正常对照组、微管解聚组和微管聚合组细胞微管荧光图像中像素比和粒度分析参数(平均粒度、分选度、偏度、峰度)组间差异具有统计学意义(

0.05)。④根据上述微管量化特征参数，Fisher多元判别分析的准确率达80.0%。

结论

微管荧光图像像素比和粒度分析的特征参数可作为微管量化分析的客观指标。

Abstract

Objective

To develop a method for objective quantitative analysis of microtubule structure based on image processing and analysis of the pixel ratio and particle size.

Methods

Human umbilical vein endothelial cells (HUVECs) cultured for 3 d were divided into control group

depolymerization group and polymerization group. Western blotting was performed to detect the changes in the content of acetylated α-tubulin in the cells. Immunofluorescence staining was used to observe the microtubule morphology under a laser confocal microscope

and the acquired images were analyzed using Matlab 7.0 for image segmentation

enhancement

and extraction of the feature parameters.

Results

① The content of acetylated α-tubulin was significantly lower in cells with depolymerization and significantly higher in cells with polymerization than in the control cells (both

0.05). ②The control cells showed bundles of intact microtubules around the cell nuclei

with a few small fluorescent spots in the cytoplasm. In depolymerization group

the cells presented with broken microtubule fibers with numerous small fluorescent spots distributed diffusely in the cytoplasm. In the polymerization group

a large number of thick microtubule fibers were observed

showing multiple branches with an irregular and roughly radial alignment

and many large fluorescent spots were seen in the cytoplasm. ③The parameters for pixel ratio and particle size analysis

including the average particle size

sorting degree

skewness and kurtosis

all differed significantly among the 3 groups (

0.05). ④Based on quantification of these characteristic parameters of the microtubules

the accuracy of Fisher's multivariate discriminant analysis could reach 80.0%.

Conclusion

The pixel ratio and the characteristic parameters for particle size analysis can be used as objective indicators for quantitative analysis of the microtubes in fluorescence images of cells.

关键词

Keywords

references

ROBERTS K. Cytoplasmic microtubules and their functions[J]. Prog Biophys Mol Biol, 1974, 28: 371-420.

LAN X D, LI L F, HU J Y, et al . A quantitative method for microtubule analysisin fluorescence images[J ] . Microsc Microanal, 2015, 21(6): 1582-1590. DOI: 10.1017/S1431927615015202.

APPLEGATE K T, BESSON S, MATOV A, et al . Plus Tip-Tracker: Quantitative image analysis software for the measurement of microtubule dynamics[J ] . J Struct Biol, 2011, 176(2): 168-184. DOI: 10.1016/j.jsb.2011.07.009.

BUÑO I, JUARRANZ A, CAÑETE M, et al . Image processing and analysis of fluorescent labelled cytoskeleton[J ] . Micron, 1998, 29(6): 445-449.

DANG Y M, LAN X D, ZHANG Q, et al . Analysis of grayscale characteristics in images of labeled microtubules from cultured cardiac myocytes[J ] . Microsc Microanal, 2015, 21(2): 334-342. DOI: 10.1017/S1431927615000185.

LU Y, HUANG C Y, WANG J, et al . An improved quantitative analysis method for plant cortical microtubules[J ] . Sci World J, 2014, 2014: 637183. DOI: 10.1155/2014/637183.

VASSY J, BEIL M, IRINOPOULOU T, et al . Quantitative image analysis of cytokeratin filament distribution during fetal rat liver development[J ] . Hepatology, 1996, 23(3): 630-638. DOI: 10.1002/hep.510230331.

XU X, ZHANG Q, HU J Y, et al . Phosphorylation of DYNLT1 at serine 82 regulates microtubule stability and mitochondrial permeabilization in hypoxia[J ] . Mol Cells, 2013, 36(4): 322-332. DOI: 10.1007/s10059-013-0114-x.

UCHIDA S. Image processing and recognition for biological images[J]. Dev Growth Differ, 2013, 55(4): 523-549. DOI: 10.1111/dgd.12054.

CHEEZUM M K, WALKER W F, GUILFORD W H. Quantitative comparison of algorithms for tracking single fluorescentparticles[J]. Biophys J, 2001, 81(4): 2378-2388. DOI: 10.1016/S0006-3495(01)75884-5.

LI K, SCHNEIDER M. Quantitative evaluation and visualization of size effect on cellular uptake of gold nanoparticles by multiphoton imaging-UV/Vis spectroscopic analysis[J]. J Biomed Opt, 2014, 19(10): 101505. DOI: 10.1117/1.JBO.19.10.101505.

BAGHERI-KHOULENJANI S, MIRZADEH H, ETRATI-KHOSROSHAHI M, et al . Particle size modeling and morphology study of chitosan/gelatin/nanohydroxyapatite nanocomposite microspheres for bone tissue engineering[J ] . J Biomed Mater Res A, 2013, 101(6): 1758-1767. DOI: 10.1002/jbm.a.34481.

MCALINDEN N, GLASS D G, MILLINGTON O R, et al . Accurate position tracking of optically trapped live cells[J ] . Biomed Opt Express, 2014, 5(4): 1026-1037. DOI: 10.1364/BOE.5.001026.

FOLK R L, WARD W C. Brazos River bar: a study in the significance of grain size parameters[J]. J Sediment Res, 1957, 27(1): 3-26. DOI: 10.1306/74d70646-2b21-11d7-8648000102c1865d.

JORDAN M A, KAMATH K. How do microtubule-targeted drugs work? An overview[J]. Curr Cancer Drug Targets, 2007, 7(8): 730-742.

JANKE C, BULINSKI J C. Post-translational regulation of the microtubule cytoskeleton: mechanisms and functions[J]. Nat Rev Mol Cell Biol, 2011, 12(12): 773-786. DOI: 10.1038/nrm3227.

TENG M, DANG Y M, ZHANG J P, et al . Microtubular stability affects cardiomyocyte glycolysis by HIF-1alpha expression and endonuclear aggregation during early stages of hypoxia[J ] . Am J Physiol Heart Circ Physiol, 2010, 298(6): H1919-H1931. DOI: 10.1152/ajpheart.01039.2009.

FANG Y D, XU X, DANG Y M, et al . MAP4 mechanism that stabilizes mitochondrial permeability transition in hypoxia: microtubule enhancement and DYNLT1 interaction with VDAC1[J ] . PLoS ONE, 2011, 6(12): e28052. DOI: 10.1371/journal.pone.0028052

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据