Direct evaluation of neuroaxonal degeneration with the causative genes of neurodegenerative diseases in drosophila using the automated axon quantification system, MeDUsA.
Yohei NittaHiroki KawaiRyuto MakiJiro OsakaSatoko Hakeda-SuzukiYoshitaka NagaiKarolína DoubkováTomoko UeharaKenji WatanabeKenjiro KosakiTakashi SuzukiGaia TavosanisAtsushi SugiePublished in: Human molecular genetics (2023)
Drosophila is an excellent model organism for studying human neurodegenerative diseases (NDs). However, there is still almost no experimental system which could directly observe the degeneration of neurons and automatically quantify axonal degeneration. In this study, we created MeDUsA (a 'method for the quantification of degeneration using fly axons'), a standalone executable computer program based on Python that combines a pre-trained deep-learning masking tool with an axon terminal counting tool. This software automatically quantifies the number of retinal R7 axons in Drosophila from a confocal z-stack image series. Using this software, we were able to directly demonstrate that axons were degenerated by the representative causative genes of NDs for the first time in Drosophila. The fly retinal axon is an excellent experimental system that is capable of mimicking the pathology of axonal degeneration in human NDs. MeDUsA rapidly and accurately quantifies axons in Drosophila photoreceptor neurons. It enables large-scale research into axonal degeneration, including screening to identify genes or drugs that mediate axonal toxicity caused by ND proteins and diagnose the pathological significance of novel variants of human genes in axons.
Keyphrases
- optic nerve
- deep learning
- endothelial cells
- spinal cord injury
- genome wide
- optical coherence tomography
- induced pluripotent stem cells
- bioinformatics analysis
- pluripotent stem cells
- genome wide identification
- diabetic retinopathy
- oxidative stress
- machine learning
- high throughput
- artificial intelligence
- gene expression
- convolutional neural network
- genome wide analysis
- high intensity
- data analysis
- single cell
- peripheral nerve
- drug induced