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Image Analysis Methods for the Characterization of Mitochondrial Morphology and Dynamics

Research output: Book/ReportDoctoral thesisCollection of Articles

Details

Original languageEnglish
PublisherTampere University of Technology
Number of pages54
ISBN (Electronic)978-952-15-3810-0
ISBN (Print)978-952-15-3799-8
Publication statusPublished - 30 Sep 2016
Publication typeG5 Doctoral dissertation (article)

Publication series

NameTampere University of Technology. Publication
Volume1410
ISSN (Print)1459-2045

Abstract

Microscopy is the primary tool for analyzing dynamical processes in live cells. With modern fluorescence microscopy techniques, it is possible to image organelles and other subcellular structures at high frame rates in single cells, and even inside living animals. One organelle of particular interest is the mitochondrion, in which abnormalities in dynamics and morphology have been associated with many diseases. Because of this, imaging methods have been, and will continue to be, indispensable for developing an understanding of the morphology and dynamics of mitochondria, and how deficiencies in them can contribute to diseases.

In microscopy studies of mitochondria, it is still common for researchers to rely on visual inspection, as opposed to thorough computational image analysis, for drawing conclusions from image data. This not only limits the amount of data that can be analyzed in a reasonable time, but also introduces human error to the study due to subjective judgement. In the case of mitochondria, the present lack of automatic analysis methods is partly explained by the complex dynamics and morphology of this organelle, which can cause mitochondria to appear vastly different in different environments. Due to this variation in appearance, methods for segmenting and tracking small intracellular particles are often not directly applicable to analyzing mitochondrial images, and instead, special methods may need to be crafted for each application. This thesis is an attempt to facilitate studies on mitochondria by presenting new tools and methods specifically developed for the quantitative analysis of mitochondrial morphology and dynamics from fluorescence microscope images.

This thesis has three main outcomes. First, we developed a software tool, Mytoe, for quantifying morphological features of mitochondria and estimating their motion from time-lapse fluorescence microscopy. Second, we developed a method for detecting the tips of mitochondria, and demonstrated how these tips can be tracked using a general particle tracking framework. Finally, we propose a novel method for quantifying mitochondrial fragmentation from two-photon microscope images of brain tissue where mitochondria have been fluorescently labeled. We expect these contributions to help provide insights about mitochondrial dynamics and structure in both single-cell imaging and animal disease models.

Field of science, Statistics Finland

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