Autophagy is an essential quality control process in which proteins and organelles are degraded. In this work, we first extended our understanding of autophagic degradation in disease by investigating the use of acidic nanoparticles to restore autophagic flux in a neurotoxic model of Parkinson Disease (PD). Normal autophagic degradation follows two key steps. First, material is engulfed to form a double-membraned autophagosome. Next, autophagosomes fuse with an acidic lysosome to degrade the inner membrane contents. Insufficient lysosomal acidity results in autophagic flux arrest, and in PC-12 cells, we characterized the use of polymeric nanoparticles as a tool to restore lysosomal acidity and rescue autophagic flux in PC-12 cells. Specifically, in an MPP+ model of neurotoxicity, we demonstrated that formulations of poly(lactic-co-glycolic acid) nanoparticles (PLGA) improved lysosomal acidity, autophagic flux, and cell health significantly, but is likely limited in efficacy by polymer degradation rate. To improve upon this, we developed a new acidic nanoparticle formulated with a novel polymer backbone (termed acNPs), engineered to degrade within lysosomes and release tetrafluorosuccinic acid, a highly potent acid (pKa ~1.6). On the benchtop, these engineered nanoparticles demonstrated both colloidal instability and acid release within a weakly acidic environment (pH 6.0) similar to a diseased lysosome but not at a neutral pH of 7.4. In cells, acNPs effectively decreased lysosomal pH within disease lysosomes, thereby restoring autophagic flux and mitochondrial activity in PC-12 cells. Encouragingly, we also were able to show efficacy of acNPs in 2D and 3D models of the human midbrain. acNPs readily trafficked within the lysosomes of cells in 2D midbrain cultures and 3D midbrain organoids. Similar to PC-12 cells, when we challenged these cells in a model of neurotoxicity, we observed restoration of viability in human organoids following acNP treatment.
Next, we addressed some current challenges regarding the quantification of autophagy within cells. We repurposed measures of economic income inequality to quantify the spatial dispersion of LC3 signal intensity in a starvation model of autophagy, and then compared these measures to other image-based measurements based on their ability to represent LC3-II levels, a robust protein marker of the autophagosome. Our analysis showed these indices outperformed all other generated measurements, including the current standard of autophagy research, LC3 puncta counting. Additionally, we also explored the linear decomposition properties of the generalized entropy index and found it a facile way to evaluate autophagic flux within 3D imaging datasets of multicellular systems. Specifically, we revealed a differential response to nutrient depravation between neurons and astrocytes. Finally, we translated this paradigm to a high throughput cell assay where we demonstrated EC50 and IC50 curves, produced from datasets acquired through both confocal and automated widefield fluorescence microscopy. Our results agree with standard cell assays.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/47509 |
| Date | 10 November 2023 |
| Creators | Martin, Andrew J. |
| Contributors | Grinstaff, Mark W., Han, Xue |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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