A novel algorithm identifies stress-induced alterations in mitochondrial connectivity and inner membrane structure from confocal images

作者：Ouellet Mathieu; Guillebaud Gerald; Gervais Valerie; St Pierre David Lupien; Germain Marc^*

来源：PLoS Computational Biology, 2017, 13(6): e1005612.

DOI：10.1371/journal.pcbi.1005612

Mitochondria exist as a highly interconnected network that is exquisitely sensitive to variations in nutrient availability, as well as a large array of cellular stresses. Changes in length and connectivity of this network, as well as alterations in the mitochondrial inner membrane (cristae), regulate cell fate by controlling metabolism, proliferation, differentiation, and cell death. Given the key roles of mitochondrial dynamics, the process by which mitochondria constantly fuse and fragment, the measure of mitochondrial length and connectivity provides crucial information on the health and activity of various cell populations. However, despite the importance of accurately measuring mitochondrial networks, the tools required to rapidly and accurately provide this information are lacking. Here, we developed a novel probabilistic approach to automatically measure mitochondrial length distribution and connectivity from confocal images. This method accurately identified mitochondrial changes caused by starvation or the inhibition of mitochondrial function. In addition, we successfully used the algorithm to measure changes in mitochondrial inner membrane/matrix occurring in response to Complex III inhibitors. As cristae rearrangements play a critical role in metabolic regulation and cell survival, this provides a rapid method to screen for proteins or compounds affecting this process. The algorithm will thus provide a robust tool to dissect the molecular mechanisms underlying the key roles of mitochondria in the regulation of cell fate.

• 出版日期2017-6