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A Quantitative Method for Microtubule Analysis in Fluorescence Images

Published online by Cambridge University Press:  29 September 2015

Xiaodong Lan ,
Lingfei Li ,
Jiongyu Hu ,
Qiong Zhang ,
Yongming Dang  and
Yuesheng Huang
Xiaodong Lan
Affiliation:
State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, Southwest Hospital, The Third Military Medical University, Chongqing 400038, China
Lingfei Li
Affiliation:
State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, Southwest Hospital, The Third Military Medical University, Chongqing 400038, China
Jiongyu Hu
Affiliation:
State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, Southwest Hospital, The Third Military Medical University, Chongqing 400038, China
Qiong Zhang
Affiliation:
State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, Southwest Hospital, The Third Military Medical University, Chongqing 400038, China
Yongming Dang*
Affiliation:
State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, Southwest Hospital, The Third Military Medical University, Chongqing 400038, China
Yuesheng Huang*
Affiliation:
State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, Southwest Hospital, The Third Military Medical University, Chongqing 400038, China
*
*Corresponding authors. yshuangtmmu@163.com; dymzy@qq.com
*Corresponding authors. yshuangtmmu@163.com; dymzy@qq.com
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Abstract

Microtubule analysis is of significant value for a better understanding of normal and pathological cellular processes. Although immunofluorescence microscopic techniques have proven useful in the study of microtubules, comparative results commonly rely on a descriptive and subjective visual analysis. We developed an objective and quantitative method based on image processing and analysis of fluorescently labeled microtubular patterns in cultured cells. We used a multi-parameter approach by analyzing four quantifiable characteristics to compose our quantitative feature set. Then we interpreted specific changes in the parameters and revealed the contribution of each feature set using principal component analysis. In addition, we verified that different treatment groups could be clearly discriminated using principal components of the multi-parameter model. High predictive accuracy of four commonly used multi-classification methods confirmed our method. These results demonstrated the effectiveness and efficiency of our method in the analysis of microtubules in fluorescence images. Application of the analytical methods presented here provides information concerning the organization and modification of microtubules, and could aid in the further understanding of structural and functional aspects of microtubules under normal and pathological conditions.

Keywords

microtubulequantitative analysisprincipal components analysiscell cultureconfocal imaging
Type
Equipment and Techniques Development
Information
Microscopy and Microanalysis , Volume 21 , Issue 6 , December 2015 , pp. 1582 - 1590
Copyright
© Microscopy Society of America 2015 

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