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Mitochondrial motility and distribution play a vital role in fulfilling variable and specialized energetic demands in polarized neurons. Neurons can extend extremely long axons to connect with targets through the formation of synapses, which demand high levels of energy for Ca2+ buffering and ion currents. Transport of mitochondria from soma to axon is critical for supporting axonal and synaptic function of neurons. Spatially and temporally dynamic mitochondrial movement is conducted by fast axonal transport at rates of several micrometers per second1.
Specifically, motor or adaptor proteins, such as kinesin and dynein, participate in the fast organelle transport along microtubules to control the movement of mitochondria2,3. Normal neuronal activity requires proper transport of newly assembled mitochondria from neuronal soma to distal axon (anterograde axonal transport) and reverse transport of mitochondria from the distal axon back to the cell body (retrograde transport). Recent studies have indicated that improper mitochondrial allocation is strongly associated with neuronal defects and motor neuron degenerative diseases4,5. Therefore, to dissect the role of mitochondria in neurodegeneration, it is important to establish methods for examining mitochondrial movement along axons in live cultures.
There are two main challenges in examining and analyzing the tracking of mitochondria: (1) identifying mitochondria from the background in every frame, and (2) analyzing and generating the connections between every frame. In resolving the first challenge, a fluorescence labeling approach is used widely to distinguish mitochondria from the background, such as MitoTracker dye or transfection of fluorescence-fused mitochondrial targeting protein (e.g., mito-GFP)6,7,8. To analyze the association between frames, several algorithms and software tools have been described in previous studies9. In a recent paper, researchers compared four different automated tools (e.g., Volocity, Imaris, wrMTrck, and Difference Tracker) to quantify mitochondrial transport. The results showed that despite discrepancies in track length, mitochondrial displacement, movement duration, and velocity, these automated tools are suitable for evaluating transport difference after treatment10. In addition to these tools, an integrated plugin "Macros" for ImageJ (written by Rietdorf and Seitz) has been widely used for analyzing mitochondrial transport11. This method generates kymographs that can be used to analyze mitochondrial movement, including velocity in both anterograde and retrograde directions.
Mitochondria are highly dynamic organelles that constantly change in number and morphology in response to both physiological and pathological conditions. Mitochondrial fission and fusion tightly regulate mitochondrial morphology and homeostasis. The imbalance between mitochondrial fission and fusion can induce extremely short or long mitochondrial networks, which can impair mitochondrial function and result in abnormal neuronal activities and neurodegeneration. Impaired mitochondrial transport and morphology are involved in various neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and hereditary spastic paraplegia (HSP)12,13,14,15. HSP is a heterogeneous group of inherited neurological disorders characterized by the degeneration of the corticospinal tract and subsequent failure to control lower limb muscles16,17. In this study, iPSC-derived forebrain neurons are used to assess mitochondrial transport and morphology in HSP. This method provides a unique paradigm for examining mitochondrial dynamics of neuronal axons in live cultures.