臺灣博碩士論文加值系統

粒線體作為與細胞代謝、能量及生命週期均息息相關的胞器，在細胞中會不斷地透過融合、分裂、再生、自噬、移動等動態行為來調整其型態及維持生理功能，以因應不同的環境條件及外在壓力。在本篇論文中，我們透過共軛焦螢光顯微鏡觀察INS-1以及PANC-1細胞的粒線體在不同的葡萄糖濃度環境以及藥物環境下的型態變化，並透過調整自參考論文中的影像分析方法來分析2D及3D的粒線體螢光影像以取得量化的指標，進而判斷粒線體在不同條件下的網路型態及動態平衡。

接著，為了進一步利用影像分析的結果以取得粒線體融合以及分裂速率的相關參數，我們採用並調整文獻中的粒線體網路模型，利用基因演算法搜尋「尖端對尖端」、「尖端對側邊」這兩種粒線體融合分裂模式的速率參數，並比較這些參數在細胞環境改變下呈現的趨勢。同時，我們也針對固有的粒線體網路模型進行改良，使之成為擁有再生、自噬及相對位置等反應及資訊的代理人模型，以模擬並視覺化粒線體的動態網路。

結果顯示，INS-1細胞在藥物FCCP作用、葡萄糖缺乏以及過高的情況下，於顯微影像中呈現較為破碎的粒線體型態，並在粒線體網路模型中擁有較低的融合速率。綜觀而言，這篇論文提供了包含細胞實驗、影像分析以及電腦模型的整合流程方法，使粒線體動態行為的研究更為有效率及便利。

Being an essential role in energetic and metabolic systems, mitochondria constantly regulate their morphology and functionality in response to cellular environments, biological stressors and energy demand by experiencing dynamic events such as fusion, fission, biogenesis, mitophagy and movement. In this thesis, we observed such dynamics of labeled mitochondria under several glucose concentrations and toxicity conditions with confocal fluorescent microscope. We adapted the methods from literature and designed 2D and 3D image analysis pipelines to extract quantitative morphological indicators from fluorescent images of several cell lines such as INS-1, PANC-1 and AC16, and elucidated the complexity and fragmentation status of mitochondrial networks.

Furthermore, we referred to the schemes of the published model and constructed a fitting model utilizing genetic algorithm to implement parameter search for two types of fusion and fission events (tip-to-tip and tip-to-side). We constructed an agent-based network model for simulation and visualization of mitochondrial dynamics as well.

The results showed that the propensities of tip-to-tip fusion events were statistically significantly lower in mitochondrial network of INS-1 cells treated with FCCP, glucose starvation and high glucose stimulation, which were consistent with the observation from fluorescent images and results of image analysis. All in all, this thesis provided an integrated pipeline including image analysis and computational simulation model as practical and analytical tools for further researches of mitochondrial dynamics.

摘要 ii
Abstract iii
Table of Contents v
List of Figures vii
List of Tables xi
Chapter 1: Introduction 1
Section 1.1 Mitochondria Dynamics and Functions 1
Section 1.2: Analyses for Mitochondria Fluorescent Images 12
Section 1.3: Computational Network Model of Mitochondria Dynamics 25
Section 1.4: Motivation and Objectives 36
Chapter 2: Methods and Materials 39
Section 2.1 Cell Culture 39
Section 2.2 Cell Imaging 42
Section 2.3 Image Analysis Pipelines 45
Section 2.4 Agent-Based Network Model for Mitochondria Simulation 73
Section 2.5 Genetic Algorithm for Parameters Fitting 89
Section 2.6 Statistical Analysis 96
Chapter 3: Results 97
Section 3.1 Image Analysis for INS-1 97
Section 3.2 Image Analysis for PANC-1 127
Section 3.3 Other Examples for Image Analysis 139
Section 3.4 Genetic Algorithm Fitting for parameters searching 142
Section 3.5 Agent-based Network Model for Visualization 150
Chapter 4: Discussion 156
Section 4.1 Experimental Design and Difficulties 156
Section 4.2 Validation and Limitation of Image Analysis Pipelines 159
Section 4.3 Remark and Limitation of Network Model and GA Fitting 163
Chapter 5: Conclusion and Future Works 169
Section 5.1 Conclusion and Summary of this study 169
Section 5.2 Future Works 173
References 176

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