Morphological dynamics of mitochondria is associated with key cellular processes related to aging and neuronal degenerative diseases, but the lack of standard quantification of mitochondrial morphology impedes systematic investigation. This paper presents an automated system for the quantification and classification of mitochondrial morphology. We discovered six morphological subtypes of mitochondria for objective quantification of mitochondrial morphology. These six subtypes are small globules, swollen globules, straight tubules, twisted tubules, branched tubules and loops. The subtyping was derived by applying consensus clustering to a huge collection of more than 200 thousand mitochondrial images extracted from 1422 micrographs of Chinese hamster ovary (CHO) cells treated with different drugs, and was validated by evidence of functional similarity reported in the literature. Quantitative statistics of subtype compositions in cells is useful for correlating drug response and mitochondrial dynamics. Combining the quantitative results with our biochemical studies about the effects of squamocin on CHO cells reveals new roles of Caspases in the regulatory mechanisms of mitochondrial dynamics. This system is not only of value to the mitochondrial field, but also applicable to the investigation of other subcellular organelle morphology.
Mitochondria are “cellular power plants” that synthesize adenosine triphosphate (ATP) from degradation of nutrients, providing chemical energy for cellular activities. In addition, mitochondria are involved in a range of other cellular processes, such as signaling, cell differentiation, cell death, cell cycle and cell growth. Dysfunctional mitochondrial dynamics have been linked to several neurodegenerative diseases, and may play a role in the aging process. Previous studies on the correlation between mitochondrial morphological changes and pathological processes involve mostly manual or semi-automated classification and quantification of morphological features, which introduces biases and inconsistency, and are labor intensive. In this work we have developed an automated quantification system for mitochondrial morphology, which is able to extract and distinguish six representative morphological subtypes within cells. Using this system, we have analyzed 1422 cells and extracted more than 200 thousand individual mitochondrion, and calculated morphological statistics for each cell. From the numerical results we were able to derive new biological conclusions about mitochondrial morphological dynamics. With this new system, investigations of mitochondrial morphology can be scaled up and objectively quantified, allowing standardization of morphological distinctions and replicability between experiments. This system will facilitate future research on the relation between subcellular morphology and various physiological processes.