A microfluidic neuronal platform for neuron axotomy and controlled regenerative studies
2015
Understanding the basic mechanisms of neural regeneration after injury is a pre-requisite for developing appropriate treatments. Traditional approaches to model axonal lesions, such as high intensity power laser ablation or sharp metal scratching, are complex to implement, have low throughputs, and generate cuts that are difficult to modulate. We present here a novel reproducible microfluidic approach to model in vitro mechanical lesion of tens to hundreds of axons simultaneously in a controlled manner. The dimensions of the induced axonal injury and its distance from the neuronal cell body are precisely controlled while preserving both the proximal and distal portions of axons. We have observed that distal axons undergo Wallerian-like anterograde degeneration after axotomy; in contrast, proximal portions of the axons remain un-degenerated, possessing the potential to re-grow. More importantly, surpassing the previous axotomy methods performed in Petridishes in which local microenvironments cannot be tailored, our platform holds the capability to implement fine-tuned treatments to lesioned axon stumps in a local, controlled manner. Specifically, molecules such as chondroitin sulphate proteoglycans and its degrading enzyme chondroitinase ABC, hydrogels, and supporting cells have been shown to be deliverable to the lesioned site of injured axons. In addition, this system also permits double interventions at the level of the lesioned axons and the perikaryon. This proves the potential of our model by demonstrating how axonal regrowth can be evaluated under circumstances that are better mimics of biological problems. We believe that this novel mechanical microfluidic axotomy approach is easy to perform, yields high throughput axon lesions, is physiologically relevant, and offers a simplified platform for screening of potential new neurological drugs.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
42
References
15
Citations
NaN
KQI