OF FUNDED PROJECT Accumulation of misfolded protein aggregates in the CNS is a common feature of many neurodegenerative diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Huntington's disease (HD) and Parkinson's disease (PD). A unifying mechanism of neurodegeneration in these diseases is impaired protein clearance via the autophagy-lysosome pathway (ALP) which results in the buildup of toxic proteins that cause neuronal dysfunction and ultimately neuronal death. Our hypothesis to be tested here is that while ALP may be impaired in each disease, subtle differences in the dysfunction of the ALP contribute to unique variations in neuropathology and clinical symptoms of each disease. We will investigate ALP across different neurodegenerative diseases using robotic microscopy (RM), a time- lapse imaging technology, which is an unbiased, sensitive and quantitative method that enables us to identify perturbations in ALP and determine how those perturbations relate to neurodegeneration. We used RM to monitor degeneration of single neurons in human models of ALS, FTD, HD and PD in which iPSCs from patients with familial or sporadic forms of these diseases are differentiated to neurons (i-neurons). In the case of ALS, HD and PD, neurons most vulnerable in each disease (motor neurons- ALS; striatal neurons- HD; dopaminergic neurons- PD) have a greater risk of dying than similar neurons from control volunteers. Because the human models express endogenous levels of the mutant disease-causing proteins at physiological levels and display spontaneous disease phenotypes, we can use RM to investigate the cellular mechanisms that impair ALP and protein clearance that are most directly relevant to neurodegeneration in each disease. We integrated a new technology into RM called optical pulse-labeling (OPL) that combines photoswitchable proteins with longitudinal single-cell analysis, enabling us to directly measure the flux of disease-causing proteins and clearance pathways in single neurons in high-throughput. We made OPL assays to monitor the metabolism of huntingtin, TDP43, ?-synuclein, LRRK2 and tau, and of the proteasomal and autophagic clearance pathways, including mitophagy. We have also adapted RM to high-throughput video and Z- projection imaging, enabling us to capture dynamic changes in intracellular morphology and trafficking of organelles such as mitochondria and lysosomes. Combining these ALP assays with RM, enables us to predict how disturbances in the ALP may affect cellular fate, predetermine which cell populations are more likely to degenerate in each disease and better understand how neuronal populations that are resistant to degeneration compensate for impaired ALP to survive. Our ultimate aim combines RM/OPL, human neuron disease models along with our proprietary compounds that increase turnover of misfolded proteins and common molecular targets that we found with family based whole genome sequencing, to identify new therapeutic strategies to treat these neurodegenerative disorders.
We aim to determine how neurons that are most vulnerable in common neurological diseases, become ineffective at removing disease causing misfolded proteins, leading to impaired neuron function and ultimately cell death. Predictive mechanisms of degeneration will be interrogated by an integrated approach that leverages human neuron models derived from amyotrophic lateral sclerosis, frontal temporal lobe dementia, Huntington's disease, and Parkinson's disease patients, robotic microscopy an automated longitudinal imaging system and optical pulse labeling, an innovative technology that monitors protein and organelle clearance pathways in single neurons. Proprietary compounds that increase turnover of misfolded proteins and common molecular targets identified using family based whole genome sequencing data, will be used to formulate new therapeutic strategies to treat these neurodegenerative disorders.
| Christiansen, Eric M; Yang, Samuel J; Ando, D Michael et al. (2018) In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images. Cell 173:792-803.e19 |
| Conlon, Erin G; Fagegaltier, Delphine; Agius, Phaedra et al. (2018) Unexpected similarities between C9ORF72 and sporadic forms of ALS/FTD suggest a common disease mechanism. Elife 7: |
| Yang, Samuel J; Berndl, Marc; Michael Ando, D et al. (2018) Assessing microscope image focus quality with deep learning. BMC Bioinformatics 19:77 |
| Epstein, Irina; Finkbeiner, Steven (2018) The Arc of cognition: Signaling cascades regulating Arc and implications for cognitive function and disease. Semin Cell Dev Biol 77:63-72 |
