Annals of Biomedical Engineering

, Volume 40, Issue 9, pp 1903–1916 | Cite as

Mitochondrial Dynamics and Motility Inside Living Vascular Endothelial Cells: Role of Bioenergetics

  • Randy J. Giedt
  • Douglas R. Pfeiffer
  • Anastasios Matzavinos
  • Chiu-Yen Kao
  • B. Rita AlevriadouEmail author


The mitochondrial network is dynamic with conformations that vary between a tubular continuum and a fragmented state. The equilibrium between mitochondrial fusion/fission, as well as the organelle motility, determine network morphology and ultimately mitochondrial/cell function. Network morphology has been linked with the energy state in different cell types. In this study, we examined how bioenergetic factors affect mitochondrial dynamics/motility in cultured vascular endothelial cells (ECs). ECs were transduced with mitochondria-targeted green fluorescent protein (mito-GFP) and exposed to inhibitors of oxidative phosphorylation (OXPHOS) or ATP synthesis. Time-lapse fluorescence videos were acquired and a mathematical program that calculates size and speed of each mitochondrial object at each time frame was developed. Our data showed that inner mitochondrial membrane potential (ΔΨm), ATP produced by glycolysis, and, to a lesser degree, ATP produced by mitochondria are critical for maintaining the mitochondrial network, and different metabolic stresses induce distinct morphological patterns (e.g., mitochondrial depolarization is necessary for “donut” formation). Mitochondrial movement, characterized by Brownian diffusion with occasional bursts in displacement magnitude, was inhibited under the same conditions that resulted in increased fission. Hence, imaging/mathematical analysis shed light on the relationship between bioenergetics and mitochondrial network morphology; the latter may determine EC survival under metabolic stress.


Mitochondrial fusion/fission Mitochondrial motility Endothelial function Fluorescence microscopy Digital image processing Mathematical analysis Object tracking 



The authors would like to thank Mr. C. J. Lloyd, undergraduate researcher, for his assistance with data analysis. This work was supported by National Institutes of Health (NIH) grant HL106392 to B. R. Alevriadou and an American Heart (AHA) predoctoral fellowship to R. J. Giedt. D. R. Pfeiffer was supported by the Ellie Kovalck Charitable Trust. A. Matzavinos was supported in part by the Mathematical Biosciences Institute at the Ohio State University and National Science Foundation (NSF) grant DMS-093164. C.-Y. Kao was supported in part by NSF grant DMS-0811003 and an Alfred P. Sloan Fellowship.

Supplementary material

10439_2012_568_MOESM1_ESM.tif (18.5 mb)
Supplementary material 1 (TIFF 18981 kb)

Supplementary material 2 (MPG 982 kb)


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Copyright information

© Biomedical Engineering Society 2012

Authors and Affiliations

  • Randy J. Giedt
    • 1
    • 2
  • Douglas R. Pfeiffer
    • 3
  • Anastasios Matzavinos
    • 4
  • Chiu-Yen Kao
    • 5
    • 6
  • B. Rita Alevriadou
    • 1
    • 2
    Email author
  1. 1.Department of Biomedical EngineeringThe Ohio State UniversityColumbusUSA
  2. 2.Division of Cardiovascular Medicine, Department of Internal Medicine, 607 Davis Heart & Lung Research InstituteThe Ohio State UniversityColumbusUSA
  3. 3.Department of Molecular and Cellular BiochemistryThe Ohio State UniversityColumbusUSA
  4. 4.Department of MathematicsIowa State UniversityAmesUSA
  5. 5.Department of MathematicsThe Ohio State UniversityColumbusUSA
  6. 6.Department of Mathematics and Computer ScienceClaremont McKenna CollegeClaremontUSA

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