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Rapid morphological characterization of isolated mitochondria using Brownian motion.

ABSTRACT: Mitochondrial morphology has been associated with numerous pathologies including cancer, diabetes, obesity and heart disease. However, the connection is poorly understood-in part due to the difficulty of characterizing the morphology. This impedes the use of morphology as a tool for disease detection/monitoring. Here, we use the Brownian motion of isolated mitochondria to characterize their size and shape in a high throughput fashion. By using treadmill exercise training, mitochondria from heart and gastrocnemius of Balb/c mice were modulated in size and used to investigate the protocol. Consistent with previous reports, the heart mitochondria of untrained mice increased 5% in diameter immediately after a single bout of moderate exercise (1.091 ± 0.004 ?m) as compared to completely sedentary controls (1.040 ± 0.022 ?m). In addition, no change was observed in the size of gastrocnemius mitochondria (1.025 ± 0.018 ?m), which was also in agreement with previous studies. The method was also successfully applied to smaller Saccharomyces cerevisiae mitochondria.

SUBMITTER: Palanisami A

PROVIDER: S-EPMC4590767 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Rapid morphological characterization of isolated mitochondria using Brownian motion.

Palanisami Akilan A Fang Jie J Lowder Thomas W TW Kunz Hawley H Miller John H JH

Analytical methods : advancing methods and applications 20120126 2

Mitochondrial morphology has been associated with numerous pathologies including cancer, diabetes, obesity and heart disease. However, the connection is poorly understood-in part due to the difficulty of characterizing the morphology. This impedes the use of morphology as a tool for disease detection/monitoring. Here, we use the Brownian motion of isolated mitochondria to characterize their size and shape in a high throughput fashion. By using treadmill exercise training, mitochondria from heart ...[more]

PMID: 26435755

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Project description:Precise spatiotemporal regulation is the foundation for the healthy development and maintenance of living organisms. All cells must correctly execute their function in the right place at the right time. Cellular motion is thus an important dynamic readout of signaling in key disease-relevant molecular pathways. However despite the rapid advancement of imaging technology, a comprehensive quantitative description of motion imaged under different imaging modalities at all spatiotemporal scales; molecular, cellular and tissue-level is still lacking. Generally, cells move either 'individually' or 'collectively' as a group with nearby cells. Current computational tools specifically focus on one or the other regime, limiting their general applicability. To address this, we recently developed and reported a new computational framework, Motion Sensing Superpixels (MOSES). Incorporating the individual advantages of single cell trackers for individual cell and particle image velocimetry (PIV) for collective cell motion analyses, MOSES enables 'mesoscale' analysis of both single-cell and collective motion over arbitrarily long times. At the same time, MOSES readily complements existing single-cell tracking workflows with additional characterization of global motion patterns and interaction analysis between cells and also operates directly on PIV extracted motion fields to yield rich motion trajectories analogous for single-cell tracks suitable for high-throughput motion phenotyping. This protocol provides a step-by-step practical guide for those interested in applying MOSES to their own datasets. The protocol highlights the salient features of a MOSES analysis and demonstrates the ease-of-use and wide applicability of MOSES to biological imaging through demo experimental analyses with ready-to-use code snippets of four datasets from different microscope modalities; phase-contrast, fluorescent, lightsheet and intra-vital microscopy. In addition we discuss critical points of consideration in the analysis.

Dataset Information

Rapid morphological characterization of isolated mitochondria using Brownian motion.

Publications

Rapid morphological characterization of isolated mitochondria using Brownian motion.

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