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Collapsin response mediator protein-2 (CRMP2) in humans, UNC-33 in C. elegans , is a molecule that mediates axonal outgrowth and stability. UNC-33/CRMP2 has been hypothesized as a potential drug target for treating Alzheimer’s and other neurodegenerative diseases, which can often be attributed in part to aging. In aging, CRMP2 becomes hyperphosphorylated, which decreases the protein’s functionality, destabilizes the cellular skeleton, and contributes to neurodegeneration. In C. elegans, aging can be slowed by entering dauer diapause; a non-aging developmental stage turned on when the DAF-7/TGFβ signaling pathway is silenced in response to environmental stressors. In our laboratory, we discovered that unc-33 mutants are unable to form dauers in response to environmental stressors, but the mechanism behind this is still unknown. Here, we present a study that investigates whether a mutation in the daf-7 gene which leads to a temperature sensitive constitutive dauer phenotype can rescue phenotypes characteristic of unc-33 mutants. To this end, we created unc-33 ; daf-7 double mutants and quantified proper dauer formation after exposure to unfavorable environmental conditions. In addition, we tested how the introduction of the daf-7 mutation would affect the locomotion of the double mutants on an agar plate and a liquid medium. Furthermore, we examined axonal elongation of the double mutants using a transgene, juIs76, which expresses GFP in GABAergic motor neurons. Our analysis of unc-33; daf-7 double mutants showed that introducing the daf-7 mutation into an unc-33 mutant rescued dauer formation. However, further studies revealed that the unc-33; daf-7 double mutants had defects in axonal outgrowth of their D-type motor neuron which had been previously seen in unc-33 single mutants and impaired locomotion. Based on these results, we concluded that unc-33 mutants might have a problem suppressing DAF-7 signaling under unfavorable environmental conditions, leading to the activation of reproductive programs and the development of adults instead of dauers.
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Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock
Abstract Background Access to quantitative information is crucial to obtain a deeper understanding of biological systems. In addition to being low-throughput, traditional image-based analysis is mostly limited to error-prone qualitative or semi-quantitative assessment of phenotypes, particularly for complex subcellular morphologies. The PVD neuron in Caenorhabditis elegans , which is responsible for harsh touch and thermosensation, undergoes structural degeneration as nematodes age characterized by the appearance of dendritic protrusions. Analysis of these neurodegenerative patterns is labor-intensive and limited to qualitative assessment. Results In this work, we apply deep learning to perform quantitative image-based analysis of complex neurodegeneration patterns exhibited by the PVD neuron in C. elegans . We apply a convolutional neural network algorithm (Mask R-CNN) to identify neurodegenerative subcellular protrusions that appear after cold-shock or as a result of aging. A multiparametric phenotypic profile captures the unique morphological changes induced by each perturbation. We identify that acute cold-shock-induced neurodegeneration is reversible and depends on rearing temperature and, importantly, that aging and cold-shock induce distinct neuronal beading patterns. Conclusion The results of this work indicate that implementing deep learning for challenging image segmentation of PVD neurodegeneration enables quantitatively tracking subtle morphological changes in an unbiased manner. This analysis revealed that distinct patterns of morphological alteration are induced by aging and cold-shock, suggesting different mechanisms at play. This approach can be used to identify the molecular components involved in orchestrating neurodegeneration and to characterize the effect of other stressors on PVD degeneration.
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- Award ID(s):
- 1838314
- PAR ID:
- 10302689
- Date Published:
- Journal Name:
- BMC Biology
- Volume:
- 18
- Issue:
- 1
- ISSN:
- 1741-7007
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1186/s12915-020-00861-w
