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Imaging and Quantifying Mitochondrial Morphology: a Focus on the 3D Freeware MitoGraph
Author(s) -
Harwig Megan Cleland,
Viana Matheus P,
Egner John M,
Harwig Jason,
Widlansky Michael E,
Rafelski Susanne M,
Hill R. Blake
Publication year - 2018
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2018.32.1_supplement.lb185
Subject(s) - consistency (knowledge bases) , morphology (biology) , computational biology , biology , variety (cybernetics) , saccharomyces cerevisiae , mitochondrion , computer science , microbiology and biotechnology , artificial intelligence , genetics , gene
Mitochondria are found in a variety of shapes, from small round punctate structures to a highly‐interconnected web. This morphological diversity is important for function, but complicates quantification. Consequently, early quantification efforts relied on various qualitative descriptors that understandably reduce the complexity of the network leading to challenges in consistency across the field. Recent application of state‐of‐the‐art computational tools have resulted in more quantitative approaches. This work focuses on MitoGraph, an open‐source image analysis platform for measuring mitochondrial morphology initially optimized for use with Saccharomyces cerevisiae. MitoGraph was used to assess mitochondrial morphology of five different mammalian cells types, all of which were accurately segmented by MitoGraph analysis. MitoGraph also successfully differentiated between distinct mitochondrial morphologies that ranged from entirely fragmented to hyper‐elongated. Support or Funding Information This was work was supported by the National Institutes of Health grants: R01‐GM067180, R01‐ HL128240 and R41‐AG056253. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .